The Best Forex Trading Strategy Ever - Trend Following System

THROW YOUR FD's in FDS

Factset: How You can Invest in Hedge Funds’ Biggest Investment
Tl;dr FactSet is the most undervalued widespread SaaS/IT solution stock that exists
If any of you have relevant experience or are friends with people in Investment Banking/other high finance, you know that Factset is the lifeblood of their financial analysis toolkit if and when it’s not Bloomberg, which isn’t even publicly traded. Factset has been around since 1978 and it’s considered a staple like Bloomberg in many wealth management firms, and it offers some of the easiest to access and understandable financial data so many newer firms focused less on trading are switching to Factset because it has a lot of the same data Bloomberg offers for half the cost. When it comes to modern financial data, Factset outcompetes Reuters and arguably Bloomberg as well due to their API services which makes Factset much more preferable for quantitative divisions of banks/hedge funds as API integration with Python/R is the most important factor for vast data lakes of financial data, this suggests Factset will be much more prepared for programming making its way into traditional finance fields. According to Factset, their mission for data delivery is to: “Integrate the data you need with your applications, web portals, and statistical packages. Whether you need market, company, or alternative data, FactSet flexible data delivery services give you normalized data through APIs and a direct delivery of local copies of standard data feeds. Our unique symbology links and aggregates a variety of content sources to ensure consistency, transparency, and data integrity across your business. Build financial models and power customized applications with FactSet APIs in our developer portal”. Their technical focus for their data delivery system alone should make it stand out compared to Bloomberg, whose UI is far more outdated and complex on top of not being as technically developed as Factset’s. Factset is the key provider of buy-side portfolio analysis for IBs, Hedge funds, and Private Equity firms, and it’s making its way into non-quantitative hedge funds as well because quantitative portfolio management makes automation of risk management and the application of portfolio theory so much easier, and to top it off, Factset’s scenario analysis and simulation is unique in its class. Factset also is able to automate trades based on individual manager risk tolerance and ML optimization for Forex trading as well. Not only does Factset provide solutions for financial companies, they are branching out to all corporations now and providing quantitative analytics for them in the areas of “corporate development, M&A, strategy, treasury, financial planning and analysis, and investor relations workflows”. Factset will eventually in my opinion reach out to Insurance Risk Management a lot more in the future as that’s a huge industry which has yet to see much automation of risk management yet, and with the field wide open, Factset will be the first to take advantage without a shadow of a doubt. So let’s dig into the company’s financials now:
Their latest 8k filing reported the following:
Revenue increased 2.6%, or $9.6 million, to $374.1 million compared with $364.5 million for the same period in fiscal 2019. The increase is primarily due to higher sales of analytics, content and technology solutions (CTS) and wealth management solutions.
Annual Subscription Value (ASV) plus professional services was $1.52 billion at May 31, 2020, compared with $1.45 billion at May 31, 2019. The organic growth rate, which excludes the effects of acquisitions, dispositions, and foreign currency movements, was 5.0%. The primary contributors to this growth rate were higher sales in FactSet's wealth and research workflow solutions and a price increase in the Company's international region
Adjusted operating margin improved to 35.5% compared with 34.0% in the prior year period primarily as a result of reduced employee-related operating expenses due to the coronavirus pandemic.
Diluted earnings per share (EPS) increased 11.0% to $2.63 compared with $2.37 for the same period in fiscal 2019.
Adjusted diluted EPS rose 9.2% to $2.86 compared with $2.62 in the prior year period primarily driven by an improvement in operating results.
The Company’s effective tax rate for the third quarter decreased to 15.0% compared with 18.6% a year ago, primarily due to an income tax expense in the prior year related to finalizing the Company's tax returns with no similar event for the three months ended May 31, 2020.
FactSet increased its quarterly dividend by $0.05 per share or 7% to $0.77 marking the fifteenth consecutive year the Company has increased dividends, highlighting its continued commitment to returning value to shareholders.
As you can see, there’s not much of a negative sign in sight here.
It makes sense considering how FactSet’s FCF has never slowed down:
https://preview.redd.it/frmtdk8e9hk51.png?width=276&format=png&auto=webp&s=1c0ff12539e0b2f9dbfda13d0565c5ce2b6f8f1a

https://preview.redd.it/6axdb6lh9hk51.png?width=593&format=png&auto=webp&s=9af1673272a5a2d8df28f60f4707e948a00e5ff1
FactSet’s annual subscriptions and professional services have made its way to foreign and developing markets, and many of them are opting for FactSet’s cheaper services to reduce costs and still get copious amounts of data and models to work with.
Here’s what FactSet had to say regarding its competitive position within the market of providing financial data in its last 10k: “Despite competing products and services, we enjoy high barriers to entry and believe it would be difficult for another vendor to quickly replicate the extensive databases we currently offer. Through our in-depth analytics and client service, we believe we can offer clients a more comprehensive solution with one of the broadest sets of functionalities, through a desktop or mobile user interface or through a standardized or bespoke data feed.” And FactSet is confident that their ML services cannot be replaced by anybody else in the industry either: “In addition, our applications, including our client support and service offerings, are entrenched in the workflow of many financial professionals given the downloading functions and portfolio analysis/screening capabilities offered. We are entrusted with significant amounts of our clients' own proprietary data, including portfolio holdings. As a result, our products have become central to our clients’ investment analysis and decision-making.” (https://last10k.com/sec-filings/fds#link_fullReport), if you read the full report and compare it to the most recent 8K, you’ll find that the real expenses this quarter were far lower than expected by the last 10k as there was a lower than expected tax rate and a 3% increase in expected operating margin from the expected figure as well. The company also reports a 90% customer retention rate over 15 years, so you know that they’re not lying when they say the clients need them for all sorts of financial data whether it’s for M&A or wealth management and Equity analysis:
https://www.investopedia.com/terms/f/factset.asp
https://preview.redd.it/yo71y6qj9hk51.png?width=355&format=png&auto=webp&s=a9414bdaa03c06114ca052304a26fae2773c3e45

FactSet also has remarkably good cash conversion considering it’s a subscription based company, a company structure which usually takes on too much leverage. Speaking of leverage, FDS had taken on a lot of leverage in 2015:

https://preview.redd.it/oxaa1wel9hk51.png?width=443&format=png&auto=webp&s=13d60d2518980360c403364f7150392ab83d07d7
So what’s that about? Why were FactSet’s long term debts at 0 and all of a sudden why’d the spike up? Well usually for a company that’s non-cyclical and has a well-established product (like FactSet) leverage can actually be good at amplifying returns, so FDS used this to their advantage and this was able to help the share’s price during 2015. Also, as you can see debt/ebitda is beginning a rapid decline anyway. This only adds to my theory that FactSet is trying to expand into new playing fields. FactSet obviously didn’t need the leverage to cover their normal costs, because they have always had consistently growing margins and revenue so the debt financing was only for the sake of financing growth. And this debt can be considered covered and paid off, considering the net income growth of 32% between 2018 and 2019 alone and the EPS growth of 33%
https://preview.redd.it/e4trju3p9hk51.png?width=387&format=png&auto=webp&s=6f6bee15f836c47e73121054ec60459f147d353e

EBITDA has virtually been exponential for FactSet for a while because of the bang-for-buck for their well-known product, but now as FactSet ventures into algorithmic trading and corporate development the scope for growth is broadly expanded.
https://preview.redd.it/yl7f58tr9hk51.png?width=489&format=png&auto=webp&s=68906b9ecbcf6d886393c4ff40f81bdecab9e9fd

P/E has declined in the past 2 years, making it a great time to buy.

https://preview.redd.it/4mqw3t4t9hk51.png?width=445&format=png&auto=webp&s=e8d719f4913883b044c4150f11b8732e14797b6d
Increasing ROE despite lowering of leverage post 2016
https://preview.redd.it/lt34avzu9hk51.png?width=441&format=png&auto=webp&s=f3742ed87cd1c2ccb7a3d3ee71ae8c7007313b2b

Mountains of cash have been piling up in the coffers increasing chances of increased dividends for shareholders (imo dividend is too low right now, but increasing it will tempt more investors into it), and on top of that in the last 10k a large buyback expansion program was implemented for $210m worth of shares, which shows how confident they are in the company itself.
https://preview.redd.it/fliirmpx9hk51.png?width=370&format=png&auto=webp&s=1216eddeadb4f84c8f4f48692a2f962ba2f1e848

SGA expense/Gross profit has been declining despite expansion of offices
I’m a bit concerned about the skin in the game leadership has in this company, since very few executives/board members have significant holdings in the company, but the CEO himself is a FactSet veteran, and knows his way around the company. On top of that, Bloomberg remains king for trading and the fixed income security market, and Reuters beats out FactSet here as well. If FactSet really wants to increase cash flow sources, the expansion into insurance and corp dev has to be successful.
Summary: FactSet has a lot of growth still left in its industry which is already fast-growing in and of itself, and it only has more potential at its current valuation. Earnings September 24th should be a massive beat due to investment banking demand and growth plus Hedge fund requirements for data and portfolio management hasn’t gone anywhere and has likely increased due to more market opportunities to buy-in.
Calls have shitty greeks, but if you're ballsy October 450s LOL, I'm holding shares
I’d say it’s a great long term investment, and it should at least be on your watchlist.
submitted by WannabeStonks69 to wallstreetbets [link] [comments]

Factset DD

Factset: How You can Invest in Hedge Funds’ Biggest Investment
Tl;dr FactSet is the most undervalued widespread SaaS/IT solution stock that exists
If any of you have relevant experience or are friends with people in Investment Banking/other high finance, you know that Factset is the lifeblood of their financial analysis toolkit if and when it’s not Bloomberg, which isn’t even publicly traded. Factset has been around since 1978 and it’s considered a staple like Bloomberg in many wealth management firms, and it offers some of the easiest to access and understandable financial data so many newer firms focused less on trading are switching to Factset because it has a lot of the same data Bloomberg offers for half the cost. When it comes to modern financial data, Factset outcompetes Reuters and arguably Bloomberg as well due to their API services which makes Factset much more preferable for quantitative divisions of banks/hedge funds as API integration with Python/R is the most important factor for vast data lakes of financial data, this suggests Factset will be much more prepared for programming making its way into traditional finance fields. According to Factset, their mission for data delivery is to: “Integrate the data you need with your applications, web portals, and statistical packages. Whether you need market, company, or alternative data, FactSet flexible data delivery services give you normalized data through APIs and a direct delivery of local copies of standard data feeds. Our unique symbology links and aggregates a variety of content sources to ensure consistency, transparency, and data integrity across your business. Build financial models and power customized applications with FactSet APIs in our developer portal”. Their technical focus for their data delivery system alone should make it stand out compared to Bloomberg, whose UI is far more outdated and complex on top of not being as technically developed as Factset’s. Factset is the key provider of buy-side portfolio analysis for IBs, Hedge funds, and Private Equity firms, and it’s making its way into non-quantitative hedge funds as well because quantitative portfolio management makes automation of risk management and the application of portfolio theory so much easier, and to top it off, Factset’s scenario analysis and simulation is unique in its class. Factset also is able to automate trades based on individual manager risk tolerance and ML optimization for Forex trading as well. Not only does Factset provide solutions for financial companies, they are branching out to all corporations now and providing quantitative analytics for them in the areas of “corporate development, M&A, strategy, treasury, financial planning and analysis, and investor relations workflows”. Factset will eventually in my opinion reach out to Insurance Risk Management a lot more in the future as that’s a huge industry which has yet to see much automation of risk management yet, and with the field wide open, Factset will be the first to take advantage without a shadow of a doubt. So let’s dig into the company’s financials now:
Their latest 8k filing reported the following:
Revenue increased 2.6%, or $9.6 million, to $374.1 million compared with $364.5 million for the same period in fiscal 2019. The increase is primarily due to higher sales of analytics, content and technology solutions (CTS) and wealth management solutions.
Annual Subscription Value (ASV) plus professional services was $1.52 billion at May 31, 2020, compared with $1.45 billion at May 31, 2019. The organic growth rate, which excludes the effects of acquisitions, dispositions, and foreign currency movements, was 5.0%. The primary contributors to this growth rate were higher sales in FactSet's wealth and research workflow solutions and a price increase in the Company's international region
Adjusted operating margin improved to 35.5% compared with 34.0% in the prior year period primarily as a result of reduced employee-related operating expenses due to the coronavirus pandemic.
Diluted earnings per share (EPS) increased 11.0% to $2.63 compared with $2.37 for the same period in fiscal 2019.
Adjusted diluted EPS rose 9.2% to $2.86 compared with $2.62 in the prior year period primarily driven by an improvement in operating results.
The Company’s effective tax rate for the third quarter decreased to 15.0% compared with 18.6% a year ago, primarily due to an income tax expense in the prior year related to finalizing the Company's tax returns with no similar event for the three months ended May 31, 2020.
FactSet increased its quarterly dividend by $0.05 per share or 7% to $0.77 marking the fifteenth consecutive year the Company has increased dividends, highlighting its continued commitment to returning value to shareholders.
As you can see, there’s not much of a negative sign in sight here.
It makes sense considering how FactSet’s FCF has never slowed down
FactSet’s annual subscriptions and professional services have made its way to foreign and developing markets, and many of them are opting for FactSet’s cheaper services to reduce costs and still get copious amounts of data and models to work with.
Here’s what FactSet had to say regarding its competitive position within the market of providing financial data in its last 10k: “Despite competing products and services, we enjoy high barriers to entry and believe it would be difficult for another vendor to quickly replicate the extensive databases we currently offer. Through our in-depth analytics and client service, we believe we can offer clients a more comprehensive solution with one of the broadest sets of functionalities, through a desktop or mobile user interface or through a standardized or bespoke data feed.” And FactSet is confident that their ML services cannot be replaced by anybody else in the industry either: “In addition, our applications, including our client support and service offerings, are entrenched in the workflow of many financial professionals given the downloading functions and portfolio analysis/screening capabilities offered. We are entrusted with significant amounts of our clients' own proprietary data, including portfolio holdings. As a result, our products have become central to our clients’ investment analysis and decision-making.” (https://last10k.com/sec-filings/fds#link_fullReport), if you read the full report and compare it to the most recent 8K, you’ll find that the real expenses this quarter were far lower than expected by the last 10k as there was a lower than expected tax rate and a 3% increase in expected operating margin from the expected figure as well. The company also reports a 90% customer retention rate over 15 years, so you know that they’re not lying when they say the clients need them for all sorts of financial data whether it’s for M&A or wealth management and Equity analysis:
https://www.investopedia.com/terms/f/factset.asp

FactSet also has remarkably good cash conversion considering it’s a subscription based company, a company structure which usually takes on too much leverage. Speaking of leverage, FDS had taken on a lot of leverage in 2015:

So what’s that about? Why were FactSet’s long term debts at 0 and all of a sudden why’d the spike up? Well usually for a company that’s non-cyclical and has a well-established product (like FactSet) leverage can actually be good at amplifying returns, so FDS used this to their advantage and this was able to help the share’s price during 2015. Also, as you can see debt/ebitda is beginning a rapid decline anyway. This only adds to my theory that FactSet is trying to expand into new playing fields. FactSet obviously didn’t need the leverage to cover their normal costs, because they have always had consistently growing margins and revenue so the debt financing was only for the sake of financing growth. And this debt can be considered covered and paid off, considering the net income growth of 32% between 2018 and 2019 alone and the EPS growth of 33%

EBITDA has virtually been exponential for FactSet for a while because of the bang-for-buck for their well-known product, but now as FactSet ventures into algorithmic trading and corporate development the scope for growth is broadly expanded.

P/E has declined in the past 2 years, making it a great time to buy.

Increasing ROE despite lowering of leverage post 2016

Mountains of cash have been piling up in the coffers increasing chances of increased dividends for shareholders (imo dividend is too low right now, but increasing it will tempt more investors into it), and on top of that in the last 10k a large buyback expansion program was implemented for $210m worth of shares, which shows how confident they are in the company itself.

SGA expense/Gross profit has been declining despite expansion of offices
I’m a bit concerned about the skin in the game leadership has in this company, since very few executives/board members have significant holdings in the company, but the CEO himself is a FactSet veteran, and knows his way around the company. On top of that, Bloomberg remains king for trading and the fixed income security market, and Reuters beats out FactSet here as well. If FactSet really wants to increase cash flow sources, the expansion into insurance and corp dev has to be successful.
Summary: FactSet has a lot of growth still left in its industry which is already fast-growing in and of itself, and it only has more potential at its current valuation. Earnings September 24th should be a massive beat due to investment banking demand and growth plus Hedge fund requirements for data and portfolio management hasn’t gone anywhere and has likely increased due to more market opportunities to buy-in.
submitted by WannabeStonks69 to investing [link] [comments]

3.3 How to implement strategies in M language

3.3 How to implement strategies in M language

Summary

In the previous article, we explained the premise of realizing the trading strategy from the aspects of the introduction of the M language , the basic grammar, the model execution method, and the model classification. In this article, we will continue the previous part, from the commonly used strategy modules and technologies. Indicators, step by step to help you achieve a viable intraday quantitative trading strategy.

Strategy Module


https://preview.redd.it/a4l7ofpuwxs41.png?width=1517&format=png&auto=webp&s=3f97ea5a7316edd434a47067d9b76c894577d01d

Stage Increase

Stage increase is calculating the percentage of current K line's closing price compare with previous N periods of closing price's difference. For example: Computing the latest 10 K-lines stage increases, can be written:
1234
CLOSE_0:=CLOSE; //get the current K-line's closing price, and save the results to variable CLOSE_0. CLOSE_10:=REF(CLOSE,10); //get the pervious 10 K-lines' closing price, and save the results to variable CLOSE_10 (CLOSE_0-CLOSE_10)/CLOSE_10*100;//calculating the percentage of current K line's closing price compare with previous N periods of closing price's difference. 

New high price

The new high price is calculated by whether the current K line is greater than N cycles' highest price. For example: calculating whether the current K line is greater than the latest 10 K-lines' highest price, can be written:
12
HHV_10:=HHV(HIGH,10); //Get the highest price of latest 10 K-lines, which includes the current K-line. HIGH>REF(HHV_10,1); //Judge whether the current K-line's highest price is greater than pervious K-lines' HHV_10 value. 

Price raise with massive trading volume increase

For example: If the current K line's closing price is 1.5 times of the closing price of the previous 10 K-lines, which means in 10 days, the price has risen 50%; and the trading volume also increased more than 5 times of the pervious 10 K-lines. can be written:
1234567
CLOSE_10:=REF(CLOSE,10); //get the 10th K-line closing price IS_CLOSE:=CLOSE/CLOSE_10>1.5; //Judging whether the current K Line closing price is 1.5 times greater than the value of CLOSE_10 VOL_MA_10:=MA(VOL,10); //get the latest 10 K-lines' average trading volume IS_VOL:=VOL>VOL_MA_10*5; //Judging whether the current K-line's trading volume is 5 times greater than the value of VOL_MA_10 IS_CLOSE AND IS_VOL; //Judging whether the condition of IS_CLOSE and IS_VOL are both true. 

Price narrow-shock market

Narrow-shock market means that the price is maintained within a certain range in the recent period. For example: If the highest price in 10 cycles minus the lowest price in 10 cycles, the result divided by the current K-line's closing price is less than 0.05. can be written:
1234
HHV_10:=HHV(CLOSE,10); //Get the highest price in 10 cycles(including current K-line) LLV_10:=LLV(CLOSE,10); //Get the lowest price in 10 cycles(including current K-line) (HHV_10-LLV_10)/CLOSE<0.05; //Judging whether the difference between HHV_10 and LLV_10 divided by current k-line's closing price is less than 0.05. 

Moving average indicates bull market

Moving Average indicates long and short direction, K line supported by or resisted by 5,10,20,30,60 moving average line, Moving average indicates bull market or bear market. can be written:
123456
MA_5:=MA(CLOSE,5); //get the moving average of 5 cycle closing price. MA_10:=MA(CLOSE,10);//get the moving average of 10 cycle closing price. MA_20:=MA(CLOSE,20);//get the moving average of 20 cycle closing price. MA_30:=MA(CLOSE,30);//get the moving average of 30 cycle closing price. MA_5>MA_10 AND MA_10>MA_20 AND MA_20>MA_30; //determine wether the MA_5 is greater than MA_10, and MA_10 is greater than MA_20, and MA_20 is greater than MA_30. 

Previous high price and its locations

To obtain the location of the previous high price and its location, you can use FMZ Quant API directly. can be written:
123
HHV_20:=HHV(HIGH,20); //get the highest price of 20 cycle(including current K line) HHVBARS_20:=HHVBARS(HIGH,20); //get the number of cycles from the highest price in 20 cycles to current K line HHV_60_40:REF(HHV_20,40); //get the highest price between 60 cycles and 40 cycles. 

Price gap jumping

The price gap is the case where the highest and lowest prices of the two K lines are not connected. It consists of two K lines, and the price gap is the reference price of the support and pressure points in the future price movement. When a price gap occurs, it can be assumed that an acceleration along the trend with original direction has begun. can be written:
12345678
HHV_1:=REF(H,1); //get the pervious K line's highest price LLV_1:=REF(L,1); //get the pervious K line's lowest price HH:=L>HHV_1; //judging wether the current K line's lowest price is greater than pervious K line's highest price (jump up) LL:=H1.001; //adding additional condition, the bigger of the price gap, the stronger the signal (jump up) LLL:=H/REF(L.1)<0.999; //adding additional condition, the bigger of the price gap, the stronger the signal (jump down) JUMP_UP:HH AND HHH; //judging the overall condition, whether it is a jump up JUMP_DOWN:LL AND LLL; //judging the overall condition, whether it is a jump down 

Common technical indicators

Moving average

https://preview.redd.it/np9qgn3ywxs41.png?width=811&format=png&auto=webp&s=39a401b5c9498a13d953678c0c452b3b8f6cbe2c
From a statistical point of view, the moving average is the arithmetic average of the daily price, which is a trending price trajectory. The moving average system is a common technical tool used by most analysts. From a technical point of view, it is a factor that affects the psychological price of technical analysts. The decision-making factor of thinking trading is a good reference tool for technical analysts. The FMZ Quant tool supports many different types of moving averages, as shown below:
1234567
MA_DEMO:MA(CLOSE,5); // get the moving average of 5 cycle MA_DEMO:EMA(CLOSE,15); // get the smooth moving average of 15 cycle MA_DEMO:EMA2(CLOSE,10);// get the linear weighted moving average of 10 cycle MA_DEMO:EMAWH(CLOSE,50); // get the exponentially weighted moving average of 50 cycle MA_DEMO:DMA(CLOSE,100); // get the dynamic moving average of 100 cycle MA_DEMO:SMA(CLOSE,10,3); // get the fixed weight of 3 moving average of closing price in 10 cycle MA_DEMO:ADMA(CLOSE,9,2,30); // get the fast-line 2 and slow-line 30 Kaufman moving average of closing price in 9 cycle. 

Bollinger Bands


https://preview.redd.it/mm0lkv00xxs41.png?width=1543&format=png&auto=webp&s=a87bdb4feecf97cbeef423b935860bfea85ffe6d
Bollinger bands is also based on the statistical principle. The middle rail is calculated according to the N-day moving average, and the upper and lower rails are calculated according to the standard deviation. When the BOLL channel starts changing from wide to narrow, which means the price will gradually returns to the mean. When the BOLL channel is changing from narrow to wide, it means that the market will start to change. If the price is up cross the upper rail, it means that the buying power is enhanced. If the price down cross the lower rail, it indicates that the selling power is enhanced.
Among all the technical indicators, Bollinger Bands calculation method is one of the most complicated, which introduces the concept of standard deviation in statistics, involving the middle trajectory ( MB ), the upper trajectory ( UP ) and the lower trajectory ( DN ). luckily, you don't have to know the calculation details, you can use it directly on FMZ Quant platform as follows:
1234
MID:MA(CLOSE,100); //calculating moving average of 100 cycle, call it Bollinger Bands middle trajectory TMP2:=STD(CLOSE,100); //calculating standard deviation of closing price of 100 cycle. TOP:MID+2*TMP2; //calculating middle trajectory plus 2 times of standard deviation, call it upper trajectory BOTTOM:MID-2*TMP2; //calculating middle trajectory plus 2 times of standard deviation, call it lower trajectory 

MACD Indicator


https://preview.redd.it/9p3k7y42xxs41.png?width=630&format=png&auto=webp&s=b1b8078325fc142c1563a1cf1cc0f222a13e0bde
The MACD indicator is a double smoothing operation using fast (short-term) and slow (long-term) moving averages and their aggregation and separation. The MACD developed according to the principle of moving averages removes the defect that the moving average frequently emits false signals, and also retains the effect of the other good aspect. Therefore, the MACD indicator has the trend and stability of the moving average. It was used to study the timing of buying and selling stocks and predicts stock price change. You can use it as follows:

DIFF:EMA(CLOSE,10)-EMA(CLOSE,50); //First calculating the difference between short-term moving average and long-term moving average. DEA:EMA(DIFF,10); //Then calculating average of the difference. 
The above is the commonly used strategy module in the development of quantitative trading strategies. In addition, there are far more than that. Through the above module examples, you can also implement several trading modules that you use most frequently in subjective trading. The methods are the same. Next, we began to write a viable intraday trading strategy.

Strategy Writing

In the Forex spot market, there is a wellknown strategy called HANS123. Its logic are basically judging wether the price breaks through the highest or lowest price of the number of K lines after the market opening

Strategy logic

  • Ready to enter the market after 30 minutes of opening;
  • Upper rail = 30 minutes high after opening ;
  • Lower rail = 30 minutes low after opening ;
  • When the price breaks above the upper limit, buy and open the position;
  • When the price falls below the lower rail, the seller opens the position.
  • Intraday trading strategy, closing before closing;

Strategy code

12345678910111213
// Data Calculation Q:=BARSLAST(DATA<>REF(DATA,1))+1; //Calculating the number of period from the first K line of the current trading day to current k line, and assign the results to N HH:=VALUEWHEN(TIME=0930,HHV(H,Q)); //when time is 9:30, get the highest price of N cycles, and assign the results to HH LL:=VALUEWHEN(TIME=0930,LLV(L,Q)); //When time is 9:30, get the lowest price of N cycles, and assign the results to LL //Placing Orders TIME>0930 AND TIME<1445 AND C>HH,BK; //If the time is greater than 9:30 and lesser than 14:45, and the closing price is greater than HH, opening long position. TIME>0930 AND TIME<1445 AND C=1445,CLOSEOUT; //If the time is greater or equal to 14:45, close all position. //Filtering the signals AUTOFILTER; //opening the filtering the signals mechanism 

To sum up

Above we have learned the concept of the strategy module. Through several commonly used strategy module cases, we had a general idea of the FMZ Quant programming tools, it can be said that learning to write strategy modules and improve programming logic thinking is a key step in advanced quantitative trading. Finally, we used the FMZ Quant tool to implement the trading strategy according a classical Forex trading strategy.

Next section notice

Maybe there are still some confusion for some people, mainly because of the coding part. Don't worry, we have already thought of that for you. On the FMZ Quant platform, there is another even easier programming tool for beginners. It is the visual programming, let's learn it soon!
submitted by FmzQuant to CryptoCurrencyTrading [link] [comments]

Stock Market Week Ahead for the trading week beginning February 4th, 2019 (News, Earnings, etc.)

Hey what's up stocks! Good morning and happy Sunday to all of you on this subreddit. I hope everyone made out pretty decent last week in the market, and are ready for the new trading week ahead! :)
Here is everything you need to know to get you ready for the trading week beginning February 4th, 2019.

Jobs report removes some fear, but market still in 'tug of war' over how much growth is slowing - (Source)

After January's strong jobs report calmed some recession fears, investors will be picking through the next wave of earnings reports and economic data for clues on just how much the U.S. economy could be slowing.
Dozens of earnings, from companies like Alphabet, Disney and Eli Lily, report in the week ahead, and there are just a few economic reports like trade data and ISM services on Tuesday. Investors will also be watching the outcome of Treasury auctions for $84 billion in Treasury notes and bonds Tuesday through Thursday, after the Fed's dovish tone helped put a lid on interest rates in the past week.
Nearly half the S&P 500 companies had reported for the fourth quarter by Friday morning, and 71 percent beat earnings estimates, while 62 percent have beaten revenue estimates. But earnings growth forecasts for the first quarter continue to decline as more companies report, and they are currently barely breaking even at under 1 percent growth, versus the 15 percent growth in the fourth quarter, according to Refinitiv.
"Granted the more we hear from companies, and particularly in terms of their guidance and projections on revenues, things can slowly change. The first thing companies do is they stop spending money. Cap spending slows down, and if revenue growth does not pick up, they let people go. This is still wait and see," said Quincy Krosby, chief market strategist at Prudential Financial.
Krosby said the 304,000 jobs added in January did ease some concerns about a slowing economy, as did a stronger than expected ISM manufacturing report Friday. But the view of the first quarter is still unclear, as many economic reports were missed during the government shutdown. Economists expect growth in the first quarter of just above 2 percent, after growth of about 2.9 percent in the fourth quarter.
Stocks closed out January with a sharp gain on Thursday, and started February on Friday on a flattish note. The S&P 500 has rebounded about 15 percent from its Dec. 24 closing low. Last month's 7.9 percent gain was the best performance for January in more than 30 years. The old Wall Street adage says 'so goes January, so goes the year.' If that holds, stocks could finish 2019 higher. But February is another story, and on average, it is a flat month for the S&P 500.
"The tug of war that you saw in the market, that was going on in the last half of last year is playing out in the data. Some of the data is a bit lower, but some of the economic surprises are picking up to the upside rather than downside," said Krosby.
Peter Boockvar, chief investment strategist at Bleakley Advisory Group, said the ISM may have improved but it reflected very low exports and flat backlogs, even though there was a snap back in new orders.
"I would fade the jobs report," said Boockvar, noting the level of growth may have been inflated by government workers taking on part-time jobs during the government shutdown.
Boocvkar said the jobs report also looked strong on the surface, but he's concerned the unemployment rate ticked up to 4 percent from 3.9 percent.
"The question of whether we go into a recession or not is how does the stock market affect confidence?" Boockvar said. Confidence readings in the past week were low, and consumer sentiment Friday was its lowest since before President Donald Trump took office.
Krosby said stocks could test recent lows or put in a higher low. If there's a big selloff, "That would not necessarily mean it was a clue a recession is coming. It's just a normal testing mechanism," she said.
The Fed removed a big concern from the markets in the past week, when its post-meeting statement and Fed Chairman Jerome Powell's briefing tilted dovish, assuring markets the Fed would pause in its interest rate hiking. Investors had feared the Fed would hurt the softening economy with its rate hikes. Now, the biggest fears are about the trade war between the U.S. and China and slowing Chinese growth.
The jobs report, and the ISM manufacturing data were also important because the lack of data during the government's 35 day shutdown has left gaps in the economic picture.
"This is really a sign the Fed stole the thunder from the economic data. By saying they're patient plasters over any kind of economic data in the near term, and I suspect the near term lasts through the first quarter because of the government shutdown, the weather, weak GDP," said Marc Chandler, chief market strategist at Bannockburn Global Forex.
Chandler said the markets will be hanging on any news on the trade talks with China. "Even if it's not the all encompassing trade deal we were promised, it's a return to where we were before with China promising to buy energy and farm products. We'll continue to have some kind of talks with the China, like we had under Obama and Bush," said Chandler.

This past week saw the following moves in the S&P:

(CLICK HERE FOR THE FULL S&P TREE MAP FOR THE PAST WEEK!)

Major Indices for this past week:

(CLICK HERE FOR THE MAJOR INDICES FOR THE PAST WEEK!)

Major Futures Markets as of Friday's close:

(CLICK HERE FOR THE MAJOR FUTURES INDICES AS OF FRIDAY!)

Economic Calendar for the Week Ahead:

(CLICK HERE FOR THE FULL ECONOMIC CALENDAR FOR THE WEEK AHEAD!)

Sector Performance WTD, MTD, YTD:

(CLICK HERE FOR FRIDAY'S PERFORMANCE!)
(CLICK HERE FOR THE WEEK-TO-DATE PERFORMANCE!)
(CLICK HERE FOR THE MONTH-TO-DATE PERFORMANCE!)
(CLICK HERE FOR THE 3-MONTH PERFORMANCE!)
(CLICK HERE FOR THE YEAR-TO-DATE PERFORMANCE!)
(CLICK HERE FOR THE 52-WEEK PERFORMANCE!)

Percentage Changes for the Major Indices, WTD, MTD, QTD, YTD as of Friday's close:

(CLICK HERE FOR THE CHART!)

S&P Sectors for the Past Week:

(CLICK HERE FOR THE CHART!)

Major Indices Pullback/Correction Levels as of Friday's close:

(CLICK HERE FOR THE CHART!)

Major Indices Rally Levels as of Friday's close:

(CLICK HERE FOR THE CHART!)

Most Anticipated Earnings Releases for this week:

(CLICK HERE FOR THE CHART!)

Here are the upcoming IPO's for this week:

(CLICK HERE FOR THE CHART!)

Friday's Stock Analyst Upgrades & Downgrades:

(CLICK HERE FOR CHART LINK #1!)
(CLICK HERE FOR CHART LINK #2!)

Now What?

What a year it has been. After the worst December for stocks in 87 years that contributed to the worst fourth quarter since the 2008–09 financial crisis, stocks have bounced back in spectacular fashion. In fact, with a day to go, stocks are looking at their best first month of the year in 30 years.
What could happen next? “We like to say that the easy 10% has been made off the lows and the next 10% will be much tougher,” explained LPL Senior Market Strategist Ryan Detrick. “Things like Fed policy, China uncertainty, and overall global growth concerns all will play a part in where equity markets go from here.”
With the S&P 500 Index about 10% away from new highs, we do think new highs are quite possible at some point this year. Positive news from the Federal Reserve (Fed) and China trade talks, as well as the realization by investors that the odds of a recession in 2019 are quite low could spark potential new highs. Remember, fiscal spending as a percentage of overall gross domestic product (GDP) is higher this year than it was last year. Many think the tax cut and fiscal policies in play last year were a one-time sugar high. We don’t see it that way and expect the benefits from fiscal policy to help extend this economic cycle at least another year—likely more.
As we head into February, note that it hasn’t been one of the best months for stocks. In fact, as our LPL Chart of the Day shows, since 1950, February has been virtually flat, and over the past 20 years only June and September have shown worse returns. Overall, the market gains have been quite impressive since the December 24 lows, but we wouldn’t be surprised at all to see a near-term consolidation or pullback.
(CLICK HERE FOR THE CHART!)

A Fed Pause and the Flattening Yield Curve

Investors have increasingly positioned for a Federal Reserve (Fed) pause, which could portend a shift in fixed income markets. Fed fund futures are pricing in about a 70% probability that the Fed will keep rates unchanged for the rest of 2019, and the market’s dovish tilt has weighed on short-term rates.
As shown in the LPL Chart of the Day, the 2-year yield has typically followed the fed funds rate since policymakers began raising rates in December 2015. While we expect one or two more hikes this cycle, there is a possibility that the Fed’s December hike was its last, which will likely cap short-term rates.
(CLICK HERE FOR THE CHART!)
Short-term yields have outpaced longer-term yields over the past few years, flattening the yield curve and raising concerns that U.S. economic progress may not be able to keep up with the Fed’s tightening. The spread between the 2-year and 10-year yield has fallen negative before every single U.S. recession since 1970.
If the Fed pauses, the curve will likely reverse course and steepen as solid economic growth and quickening (but manageable) inflation drives longer-term yields higher. As mentioned in our Outlook 2019, FUNDAMENTAL: How to Focus on What Really Matters in the Markets, we’re forecasting the 10-year Treasury yield will increase significantly from current levels and trade within a range of 3.25–3.75% in 2019.
“We remain optimistic about U.S. economic growth prospects, and recent data show inflation remains at manageable levels,” said LPL Research Chief Investment Strategist John Lynch. “Because of this, we expect the data-dependent Fed to be less aggressive than initially feared, as policymakers juggle these factors with the impacts of trade tensions and tepid global growth.”
To be clear, investors shouldn’t fear a flattening yield curve given the backdrop of solid economic growth and modest inflation. Historically, the yield curve has remained relatively flat or inverted for years before some recessions started. Since 1970, the United States has entered a recession an average of 21 months after the yield curve inverted.

Jobless Claims’ Historic Significance

Jobless claims have dropped to a 49-year low. Based on historical trends, this could signal that a U.S. economic recession is further off than many expect.
Data released January 24 showed jobless claims fell to 199K in the week ending January 18, the lowest number since 1969 and far below consensus estimates of 218K. As shown in the LPL Chart of the Day, current jobless claims have been significantly lower than those in the 12-month periods preceding each recession since the early 1970s.
(CLICK HERE FOR THE CHART!)
Jobless claims have fallen out of the spotlight as the economic cycle has matured, but they could prove important again as investors’ recessionary fears increase. While most labor-market data serve as lagging indicators of U.S. economic health, jobless claims are a leading indicator. Historically, a 75–100K increase in claims over a 26-week period has been associated with a recession.
“Last week’s jobless claims print was particularly impressive given the partial government shutdown and weakening corporate sentiment,” said LPL Research Chief Investment Strategist John Lynch. “The U.S. labor market remains strong and will help buoy consumer health and output growth this year.”
Other predictive data sets have signaled U.S. recessionary odds are low. Data last week showed the Conference Board’s Leading Economic Index (LEI), based on 10 leading economic indicators (like jobless claims, manufacturers’ new orders, and stock prices), grew 4.3% year over year in December. In contrast, the LEI has turned negative year over year before all economic recessions since 1970. Because of its solid predictive ability, the LEI is a component of our Recession Watch Dashboard.

Best S&P January Since 1987

Most major U.S. stock indexes rallied to new recovery and year-to-date highs today shrugging off some misses and weakness from Microsoft, DuPont and Visa. S&P 500 finished the month strong with a 7.9% gain. This is the best S&P January since 1987. This is also the third January Trifecta in a row.
Last year the S&P 500 crumbled in the fourth quarter under the weight of triple threats from a hawkish and confusing Fed, a newly divided Congress and the U.S. trade battle with China, finishing in the red. 2017’s Trifecta was followed by a full-year gain of 19.4%, including a February-December gain of 17.3%. As you can see in the table below, the long term track record of the Trifecta is rather impressive, posting full-year gains in 27 of the 30 prior years with an average gain for the S&P 500 of 17.1%.
Devised by Yale Hirsch in 1972, the January Barometer has registered ten major errors since 1950 for an 85.5% accuracy ratio. This indicator adheres to propensity that as the S&P 500 goes in January, so goes the year. Of the ten major errors Vietnam affected 1966 and 1968. 1982 saw the start of a major bull market in August. Two January rate cuts and 9/11 affected 2001.The market in January 2003 was held down by the anticipation of military action in Iraq. The second worst bear market since 1900 ended in March of 2009 and Federal Reserve intervention influenced 2010 and 2014. In 2016, DJIA slipped into an official Ned Davis bear market in January. Including the eight flat years yields a .739 batting average.
Our January Indicator Trifecta combines the Santa Claus Rally, the First Five Days Early Warning System and our full-month January Barometer. The predicative power of the three is considerably greater than any of them alone; we have been rather impressed by its forecasting prowess. This is the 31st time since 1949 that all three January Indicators have been positive and the twelfth time (previous eleven times highlighted in grey in table below) this has occurred in a pre-election year.
(CLICK HERE FOR THE CHART!)
With the Fed turning more dovish and President Trump tacking to the center and meeting with China and market internals improving along with the gains, the market is tracking Base Case and Best Case scenarios outlined in our 2019 Annual Forecast. Next eleven month and full-year 2019 performance is expected to be more in line with typical Pre-Election returns.

February Almanac: Small-Caps Tend to Outperform

Even though February is right in the middle of the Best Six Months, its long-term track record, since 1950, is not all that stellar. February ranks no better than seventh and has posted paltry average gains except for the Russell 2000. Small cap stocks, benefiting from “January Effect” carry over; tend to outpace large cap stocks in February. The Russell 2000 index of small cap stocks turns in an average gain of 1.1% in February since 1979—just the seventh best month for that benchmark.
In pre-election years, February’s performance generally improves with average returns all positive. NASDAQ performs best, gaining an average 2.8% in pre-election-year Februarys since 1971. Russell 2000 is second best, averaging gains of 2.5% since 1979. DJIA, S&P 500 and Russell 1000, the large-cap indices, tend to lag with average advances of around 1.0%.
(CLICK HERE FOR THE CHART!)

5% Months

7%? Bulls will take it! After an abysmal December, the S&P 500 is currently set to finish the month with its best January return since 1987. This month’s gain will mark the 16th time since the lows of the Financial Crisis in March 2009 that the S&P 500 has rallied more than 5% in a given month. The table below highlights each of the 15 prior months where the S&P 500 rallied more than 5% and shows how much the S&P 500 gained on the month as well as its performance on the last trading day of the month and the first trading day of the subsequent month.
When looking at the table, a few things stand out. First, the first trading day of a month that follows a month where the S&P 500 rallied more than 5% has been extremely positive as the S&P 500 averages a gain of 0.84% (median: 1.01%) with positive returns 13 out of 15 times! In addition to the positive tendency of markets on the first day of the new month, there has also been a clear tendency for the S&P 500 to decline on the last trading day of the strong month. The average decline on the last trading day of a strong month has been 0.09% with positive returns less than half of the time. This is no doubt related to the fact that funds are forced to rebalance out of equities to get back inline with their benchmark weights. However, on those five prior months where the S&P 500 bucked the trend and was positive on the last trading day of a 5%+ month, the average gain on the first trading day of the next month was even stronger at 1.52% with gains five out of six times.
(CLICK HERE FOR THE CHART!)

STOCK MARKET VIDEO: Stock Market Analysis Video for February 1st, 2019

([CLICK HERE FOR THE YOUTUBE VIDEO!]())
(VIDEO NOT YET UP!)

STOCK MARKET VIDEO: ShadowTrader Video Weekly 2.3.19

([CLICK HERE FOR THE YOUTUBE VIDEO!]())
(VIDEO NOT YET UP!)
Here are the most notable companies reporting earnings in this upcoming trading month ahead-
  • $GOOGL
  • $TWTR
  • $SNAP
  • $CLF
  • $TTWO
  • $ALXN
  • $DIS
  • $BP
  • $CLX
  • $SYY
  • $GM
  • $GILD
  • $CMG
  • $GRUB
  • $EA
  • $STX
  • $SPOT
  • $AMG
  • $SAIA
  • $RL
  • $CNC
  • $EL
  • $UFI
  • $GLUU
  • $MTSC
  • $JOUT
  • $PM
  • $GPRO
  • $LITE
  • $FEYE
  • $SWKS
  • $LLY
  • $MPC
  • $BDX
  • $REGN
  • $VIAB
  • $ONVO
  • $HUM
  • $ARRY
  • $PBI
  • $ADM
  • $BSAC
(CLICK HERE FOR NEXT WEEK'S MOST NOTABLE EARNINGS RELEASES!)
(CLICK HERE FOR NEXT WEEK'S HIGHEST VOLATILITY EARNINGS RELEASES!)
(CLICK HERE FOR NEXT WEEK'S BIGGEST DECLINE IN EARNINGS EXPECTATIONS!)
(CLICK HERE FOR NEXT WEEK'S HIGHEST INCREASE IN EARNINGS EXPECTATIONS!)
Below are some of the notable companies coming out with earnings releases this upcoming trading week ahead which includes the date/time of release & consensus estimates courtesy of Earnings Whispers:

Monday 2.4.19 Before Market Open:

(CLICK HERE FOR MONDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES!)

Monday 2.4.19 After Market Close:

(CLICK HERE FOR MONDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES!)

Tuesday 2.5.19 Before Market Open:

(CLICK HERE FOR TUESDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES LINK #1!)
(CLICK HERE FOR TUESDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES LINK #2!)

Tuesday 2.5.19 After Market Close:

(CLICK HERE FOR TUESDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES LINK #1!)
(CLICK HERE FOR TUESDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES LINK #2!)

Wednesday 2.6.19 Before Market Open:

(CLICK HERE FOR WEDNESDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES!)

Wednesday 2.6.19 After Market Close:

(CLICK HERE FOR WEDNESDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES LINK #1!)
(CLICK HERE FOR WEDNESDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES LINK #2!)

Thursday 2.7.19 Before Market Open:

(CLICK HERE FOR THURSDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES LINK #1!)
(CLICK HERE FOR THURSDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES LINK #1!)

Thursday 2.7.19 After Market Close:

(CLICK HERE FOR THURSDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES LINK #1!)
(CLICK HERE FOR THURSDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES LINK #2!)

Friday 2.8.19 Before Market Open:

(CLICK HERE FOR FRIDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES!)

Friday 2.8.19 After Market Close:

([CLICK HERE FOR FRIDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES!]())
NONE.

Alphabet, Inc. -

Alphabet, Inc. (GOOGL) is confirmed to report earnings at approximately 4:05 PM ET on Monday, February 4, 2019. The consensus earnings estimate is $11.08 per share on revenue of $31.28 billion and the Earnings Whisper ® number is $11.03 per share. Investor sentiment going into the company's earnings release has 71% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 14.23% with revenue decreasing by 3.23%. Short interest has decreased by 6.6% since the company's last earnings release while the stock has drifted higher by 6.7% from its open following the earnings release to be 0.7% below its 200 day moving average of $1,127.05. Overall earnings estimates have been revised lower since the company's last earnings release. On Thursday, January 24, 2019 there was some notable buying of 1,493 contracts of the $1,200.00 call expiring on Friday, February 15, 2019. Option traders are pricing in a 5.2% move on earnings and the stock has averaged a 3.8% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Twitter, Inc. $33.19

Twitter, Inc. (TWTR) is confirmed to report earnings at approximately 7:00 AM ET on Thursday, February 7, 2019. The consensus earnings estimate is $0.25 per share on revenue of $871.59 million and the Earnings Whisper ® number is $0.29 per share. Investor sentiment going into the company's earnings release has 73% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 38.89% with revenue increasing by 19.14%. Short interest has decreased by 54.7% since the company's last earnings release while the stock has drifted higher by 6.0% from its open following the earnings release to be 3.1% below its 200 day moving average of $34.24. Overall earnings estimates have been revised higher since the company's last earnings release. On Monday, December 31, 2018 there was some notable buying of 45,575 contracts of the $34.00 call expiring on Friday, March 15, 2019. Option traders are pricing in a 13.4% move on earnings and the stock has averaged a 13.9% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Snap Inc. $6.91

Snap Inc. (SNAP) is confirmed to report earnings at approximately 4:10 PM ET on Tuesday, February 5, 2019. The consensus estimate is for a loss of $0.08 per share on revenue of $376.64 million and the Earnings Whisper ® number is ($0.04) per share. Investor sentiment going into the company's earnings release has 31% expecting an earnings beat The company's guidance was for revenue of $355.00 million to $380.00 million. Consensus estimates are for year-over-year earnings growth of 27.27% with revenue increasing by 31.83%. Short interest has decreased by 1.8% since the company's last earnings release while the stock has drifted higher by 12.7% from its open following the earnings release to be 33.6% below its 200 day moving average of $10.40. Overall earnings estimates have been revised higher since the company's last earnings release. On Thursday, January 3, 2019 there was some notable buying of 29,739 contracts of the $7.00 call expiring on Friday, February 15, 2019. Option traders are pricing in a 15.7% move on earnings and the stock has averaged a 19.2% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Cleveland-Cliffs Inc $10.53

Cleveland-Cliffs Inc (CLF) is confirmed to report earnings at approximately 8:00 AM ET on Friday, February 8, 2019. The consensus earnings estimate is $0.57 per share on revenue of $713.61 million and the Earnings Whisper ® number is $0.63 per share. Investor sentiment going into the company's earnings release has 87% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 119.23% with revenue increasing by 18.76%. Short interest has increased by 4.6% since the company's last earnings release while the stock has drifted lower by 9.8% from its open following the earnings release to be 11.2% above its 200 day moving average of $9.47. Overall earnings estimates have been revised lower since the company's last earnings release. On Monday, January 7, 2019 there was some notable buying of 10,030 contracts of the $8.00 call expiring on Thursday, April 18, 2019. Option traders are pricing in a 9.4% move on earnings and the stock has averaged a 7.0% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Take-Two Interactive Software, Inc. $104.95

Take-Two Interactive Software, Inc. (TTWO) is confirmed to report earnings at approximately 7:00 AM ET on Wednesday, February 6, 2019. The consensus earnings estimate is $2.72 per share on revenue of $1.46 billion and the Earnings Whisper ® number is $2.82 per share. Investor sentiment going into the company's earnings release has 84% expecting an earnings beat The company's guidance was for earnings of $0.31 to $0.41 per share. Consensus estimates are for year-over-year earnings growth of 106.06% with revenue increasing by 203.64%. Short interest has increased by 37.1% since the company's last earnings release while the stock has drifted lower by 18.7% from its open following the earnings release to be 9.9% below its 200 day moving average of $116.52. Overall earnings estimates have been revised higher since the company's last earnings release. On Wednesday, January 23, 2019 there was some notable buying of 2,067 contracts of the $120.00 call expiring on Friday, February 15, 2019. Option traders are pricing in a 9.2% move on earnings and the stock has averaged a 8.3% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Alexion Pharmaceuticals, Inc. $126.28

Alexion Pharmaceuticals, Inc. (ALXN) is confirmed to report earnings at approximately 6:35 AM ET on Monday, February 4, 2019. The consensus earnings estimate is $1.82 per share on revenue of $1.06 billion and the Earnings Whisper ® number is $1.95 per share. Investor sentiment going into the company's earnings release has 67% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 23.81% with revenue increasing by 16.52%. Short interest has decreased by 16.7% since the company's last earnings release while the stock has drifted higher by 0.4% from its open following the earnings release to be 5.8% above its 200 day moving average of $119.40. On Friday, February 1, 2019 there was some notable buying of 1,235 contracts of the $130.00 call expiring on Friday, February 15, 2019. Option traders are pricing in a 7.8% move on earnings and the stock has averaged a 6.5% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Walt Disney Co $111.30

Walt Disney Co (DIS) is confirmed to report earnings at approximately 4:05 PM ET on Tuesday, February 5, 2019. The consensus earnings estimate is $1.57 per share on revenue of $15.18 billion and the Earnings Whisper ® number is $1.62 per share. Investor sentiment going into the company's earnings release has 71% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 16.93% with revenue decreasing by 1.11%. Short interest has increased by 7.2% since the company's last earnings release while the stock has drifted lower by 5.8% from its open following the earnings release to be 1.9% above its 200 day moving average of $109.22. Overall earnings estimates have been revised lower since the company's last earnings release. On Friday, February 1, 2019 there was some notable buying of 8,822 contracts of the $110.00 put expiring on Friday, February 8, 2019. Option traders are pricing in a 3.1% move on earnings and the stock has averaged a 2.2% move in recent quarters.

(CLICK HERE FOR THE CHART!)

BP p.l.c $41.34

BP p.l.c (BP) is confirmed to report earnings at approximately 5:25 AM ET on Tuesday, February 5, 2019. The consensus earnings estimate is $0.77 per share on revenue of $60.72 billion and the Earnings Whisper ® number is $0.75 per share. Investor sentiment going into the company's earnings release has 65% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 20.31% with revenue decreasing by 13.28%. Short interest has increased by 6.5% since the company's last earnings release while the stock has drifted lower by 1.6% from its open following the earnings release to be 3.9% below its 200 day moving average of $43.01. Overall earnings estimates have been revised lower since the company's last earnings release. On Thursday, January 17, 2019 there was some notable buying of 2,010 contracts of the $33.00 put expiring on Friday, January 17, 2020. Option traders are pricing in a 3.3% move on earnings and the stock has averaged a 2.1% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Clorox Co. $149.86

Clorox Co. (CLX) is confirmed to report earnings at approximately 6:30 AM ET on Monday, February 4, 2019. The consensus earnings estimate is $1.32 per share on revenue of $1.48 billion and the Earnings Whisper ® number is $1.34 per share. Investor sentiment going into the company's earnings release has 63% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 7.32% with revenue increasing by 4.52%. Short interest has decreased by 9.8% since the company's last earnings release while the stock has drifted higher by 3.5% from its open following the earnings release to be 5.9% above its 200 day moving average of $141.57. Overall earnings estimates have been revised lower since the company's last earnings release. On Friday, January 18, 2019 there was some notable buying of 1,025 contracts of the $152.50 put expiring on Friday, February 8, 2019. Option traders are pricing in a 4.7% move on earnings and the stock has averaged a 3.3% move in recent quarters.

(CLICK HERE FOR THE CHART!)

SYSCO Corp. $63.57

SYSCO Corp. (SYY) is confirmed to report earnings at approximately 8:00 AM ET on Monday, February 4, 2019. The consensus earnings estimate is $0.72 per share on revenue of $14.85 billion and the Earnings Whisper ® number is $0.73 per share. Investor sentiment going into the company's earnings release has 63% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 9.09% with revenue increasing by 3.04%. Short interest has decreased by 1.0% since the company's last earnings release while the stock has drifted lower by 2.0% from its open following the earnings release to be 5.6% below its 200 day moving average of $67.34. Overall earnings estimates have been revised lower since the company's last earnings release. On Friday, February 1, 2019 there was some notable buying of 1,691 contracts of the $66.00 call expiring on Friday, February 8, 2019. Option traders are pricing in a 4.5% move on earnings and the stock has averaged a 4.8% move in recent quarters.

(CLICK HERE FOR THE CHART!)

DISCUSS!

What are you all watching for in this upcoming trading week ahead?
Have a fantastic Sunday and a great trading week ahead to all here on stocks! ;)
submitted by bigbear0083 to stocks [link] [comments]

90 Day Update / Beginner's Post

Hey all, First time poster, long time lurker. Just learning until I think of useful/interesting post. I just finished Babypips school. No this isn’t another, “What do I do next?!” eager to consume posts. More just introducing myself and share methods as I progress and chat more in this sub. It’s been a super helpful research tool with just the sidebar alone, but the interactions are also generally positive and research engaged. Forex was on my list of active/sidehobby/internet ideas to try. (Along with selling on Ebay and learning/teaching languages) I’ve always been into stocks/finance and I’m open still open to continuing learning past forex into futures and/or cryptocurrency. Forex to me is kind of an intro to price action and charts for me. Also the physics of it all that I’m hoping to apply more as time goes on. Anyways , started forex 2 years ago. Saw I needed disposable income you could lose (which I didnt have at the time) and put it off. Now I’m about 3 months in with my rediscovery of it with a lot more financial cushion/discipline.I finished the babypips school and try to practice 25-45 mins a day of something forex related the last 90 days or so. Here is my routine and some things I”ve learned since starting.
Demo Trading is overrated. And then it becomes the best thing ever. I’m gunna just go out and say it. IF you’re trading for 9 months on demo you should’ve stopped 8 months ago. I mean don’t get me wrong 9 months, that shows alot of persistence in your habits, but you’re spending time on a variable that doesn’t exchange certainty in the real system. I only even say this because you could be like me. Trade demo all this time then find out the leverage you wanted isn’t even available in your country. (U.S here) So I felt like a dummy from the jump, but that’s part of the learning curve you should be doing sooner rather than later. This does not mean fund your account fully. No, put just $200. I trade with my initial capitol @ $200 and I won’t add a penny more until I’ve developed a profitable system with what’s already in there. A good investment is a good investment and throwing more money doesn’t actually add value to the growth return on your investment.(In most cases) So what’s the big deal with Demo? Well for one you want to work with a system that’s tangible in your country. U.S is capped at 1:50 leverage. I don’t know other countries regulations but it’s something I wish someone told me to look out for before I started testing financial strategies. Another thing is the spreads are often very different from what you find in demo (attention scalpers out there) sometimes dramatically. (After NY close of the day /Weekends ) You have to implement all of these factors to your strategy. Now what is demo good for? Starting out! Learning how to set indicators, trades, stop losses and so on. I’d say 60 days max if you can’t donate much time. Even less than 60 days if you have more free time but then after that it’s time to get your feet wet. One other good thing about demo accounts is that it allows you to practice fundamentally different trading ideas out before trying them out on your actual account. An example would be a scalper trying a new position strategy he learned in demo to set some long term positions next year. I enjoy trading because it’s a discipline on your anxiety. When you deposit your first amount, any amount that's more than a new video game or dvd collection, your brain is going to fire off “Hey you bought something new that can make money let’s test it out! It could be making you money” You have to calm this voice first. IF you even can. This voice makes you check the charts 3x more than you did in demo and caused at least me to trade just so the money’s not going to waste. I lost 40% of my account the first week. I would’ve called myself mentally stable before this too. But that voice broke me and you have to confront it because it’s the impatience in all of us and causes you to force your view of the markets to fit your system. Demo is a great tool but shouldnt be held on longer than it’s purpose.
Immersion This is going to be a little shorter than my last topic because this is more something everyone has to find and listen to. Don’t just study the same website or forum for forex everyday. Try to get a wide view of the financial markets as a whole and various media input. Subscribe to a couple good youtube channels maybe a visual representation of what you’ve been learning could help solidify it. Maybe a podcasts personality makes your brain react differently to topics where a bland textbook reading didnt excite you the same. Watch a documentary on trading one week and hell maybe even Wolf of Wall Street another week, whatever it is that gets your whole body involved in the feeling of trading so 1) you don’t get burned out on the topic and 2) you find more ways to connect with the information you find. Whether emotional or visually. Here are two recommendations of channels that help me break the norm of my study routine:
“Two Blokes Trading” Podcast I discovered these guys a while back in a comment thread. I would recommend this podcast to beginners because you can start from the very beginning of their series and learn with them. They’re young, enthusiastic and open to exploring alot of areas to trading and different philosophies. So sometimes you can find gems in subjects you didn’t expect to encounter. They also bring in advisors and brokerage managers to feature on their subjects. And it’s not all forex focused. Check them out: http://twoblokestrading.com/podcast-episodes/
Barry Burns “Top Dog Trading” Barry Burns I like because you have him walking you through the charts on youtube. One of the few videos I watched on Price action were by him where the lightbulb went off. He offers a great free resource and sometimes I even feel guilty getting it on youtube for free before sharing it because it feels like the things he touches on and how he explains them, even paid classes probably couldn’t get right. He has so many videos on different markets and how to read them just apply them to the type of trader you are. https://www.youtube.com/channel/UCcjyImdSWDTCGCa7G24faIQ
Routine ( final topic on this post) So every week I try to keep a basic routine of forex and ways to practice. I try to wake up early as I’m on the Pacific Coast so I get up 2 hours early before I have to head to work. 20-30 mins of this time I do something related to forex education. The rest of the time I gather my foundation for the week and arrange goals / meditate/ journal. I’ll look at the charts, when I still had Babypips to finish I’d set a time and study through what I could of the course through that time. Now that I’m finished I’ll either check this sub, watch a video/podcast or try to read something related fundamentally to trading or finance. (I’d like to get some more book ideas about trading and it’s psychology) So that’s one habit. You’ve got to be able to at least schedule 20-45 minutes a day to consistent study + practice time to acquire new skills. 20 minutes uninterrupted is enough. Wake up early if you have to. Then throughout the day you’ll find time to reflect or research more and soon the time will start to add up. This also works on the other extreme too. If you have alot of free time I’d say starting out 1 hour to 2 hours max is what you should dedicate to studying. Forex is a very mentally fatiguing process skill. You’ve got to let your brain recharge (need those MP potions it seems) the whole currency system is heavy and complex enough that starting from scratch you couldn’t learn everything in 24 hours straight. I’d say even a week straight wouldn’t work. It takes time and a habitual familiarity. It’s not dissimilar to learning a language. Where concepts become stacked on a foundation of understanding to be acted upon through your day to day. Even if you can name all the working parts, experience build with how much time you think in that language per day. There’s a reason I chose the word “Immersion” for my second topic. Moving along. Another part of my routine is backtesting 40-50 trades a week of my strongest system. This equates to a little under 10 trades a day. I completely journal and track profits like they were live. Some suggest using a simulator, while that is a great practice for timing entries, I’ve found just using the Metatrader 4 Desktop and using the F12 key to progress forward one tick at a time has been sufficient for my backtesting needs. Backtesting gives you an opportunity to practice way more trades in a week than live session will be able to provide. I’m using M15 - H1 intraday strategies and maybe pull off 5-6 trades a week. BUT I practice 10x that amount per week. Soon you’ll find your live performance is really only a display of how your last week backtesting went. It’s like football practice for the gameday. Now which system I test varies, like I said I’ll try my strongest, but that changes. Just grab any system you think you can pull off and backtest it. Babypips gave me my first few, then I created some ridiculous ones, but over time your experience of a system and how to get them to work for you grows by running test trades. Systems I’ve found and backtested that are online are: the “So Easy It’s Ridiculous” system and the Cowabunga System, both found on babypips and a simple google search. Easy. I know, and really a system is just supposed to make having trading decisions easier for you. But your participation and exit are equally important. Can you follow easy rules you or others make? No questions asked?
So that concludes my post. I hope in the future when I’ve backtested 1,000 trades I can post some of my personal systems I’ve followed, right now they feel to amateur to even share. I am the humble fool, so any ideas on my style or feedback on where I should head are greatly appreciated. I’m open to questions and dialogue so feel free to send a PM or comment. Hearing from other traders is the reason I even started this account to post and interact. This post and future ones I have planned are kind of a new element I wanted to try of journaling that allows me some social accountability and feedback from a community rather than all my entries being hoarded in my notebooks, so my apologies if it’s more wordy than usual on here. Thanks everyone and have fun!
-AP
TL:DR Just browse over the bold sections
submitted by AzathothsPips to Forex [link] [comments]

Subreddit Stats: cs7646_fall2017 top posts from 2017-08-23 to 2017-12-10 22:43 PDT

Period: 108.98 days
Submissions Comments
Total 999 10425
Rate (per day) 9.17 95.73
Unique Redditors 361 695
Combined Score 4162 17424

Top Submitters' Top Submissions

  1. 296 points, 24 submissions: tuckerbalch
    1. Project 2 Megathread (optimize_something) (33 points, 475 comments)
    2. project 3 megathread (assess_learners) (27 points, 1130 comments)
    3. For online students: Participation check #2 (23 points, 47 comments)
    4. ML / Data Scientist internship and full time job opportunities (20 points, 36 comments)
    5. Advance information on Project 3 (19 points, 22 comments)
    6. participation check #3 (19 points, 29 comments)
    7. manual_strategy project megathread (17 points, 825 comments)
    8. project 4 megathread (defeat_learners) (15 points, 209 comments)
    9. project 5 megathread (marketsim) (15 points, 484 comments)
    10. QLearning Robot project megathread (12 points, 691 comments)
  2. 278 points, 17 submissions: davebyrd
    1. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes (37 points, 10 comments)
    2. Project 1 Megathread (assess_portfolio) (34 points, 466 comments)
    3. marketsim grades are up (25 points, 28 comments)
    4. Midterm stats (24 points, 32 comments)
    5. Welcome to CS 7646 MLT! (23 points, 132 comments)
    6. How to interact with TAs, discuss grades, performance, request exceptions... (18 points, 31 comments)
    7. assess_portfolio grades have been released (18 points, 34 comments)
    8. Midterm grades posted to T-Square (15 points, 30 comments)
    9. Removed posts (15 points, 2 comments)
    10. assess_portfolio IMPORTANT README: about sample frequency (13 points, 26 comments)
  3. 118 points, 17 submissions: yokh_cs7646
    1. Exam 2 Information (39 points, 40 comments)
    2. Reformat Assignment Pages? (14 points, 2 comments)
    3. What did the real-life Michael Burry have to say? (13 points, 2 comments)
    4. PSA: Read the Rubric carefully and ahead-of-time (8 points, 15 comments)
    5. How do I know that I'm correct and not just lucky? (7 points, 31 comments)
    6. ML Papers and News (7 points, 5 comments)
    7. What are "question pools"? (6 points, 4 comments)
    8. Explanation of "Regression" (5 points, 5 comments)
    9. GT Github taking FOREVER to push to..? (4 points, 14 comments)
    10. Dead links on the course wiki (3 points, 2 comments)
  4. 67 points, 13 submissions: harshsikka123
    1. To all those struggling, some words of courage! (20 points, 18 comments)
    2. Just got locked out of my apartment, am submitting from a stairwell (19 points, 12 comments)
    3. Thoroughly enjoying the lectures, some of the best I've seen! (13 points, 13 comments)
    4. Just for reference, how long did Assignment 1 take you all to implement? (3 points, 31 comments)
    5. Grade_Learners Taking about 7 seconds on Buffet vs 5 on Local, is this acceptable if all tests are passing? (2 points, 2 comments)
    6. Is anyone running into the Runtime Error, Invalid DISPLAY variable when trying to save the figures as pdfs to the Buffet servers? (2 points, 9 comments)
    7. Still not seeing an ML4T onboarding test on ProctorTrack (2 points, 10 comments)
    8. Any news on when Optimize_Something grades will be released? (1 point, 1 comment)
    9. Baglearner RMSE and leaf size? (1 point, 2 comments)
    10. My results are oh so slightly off, any thoughts? (1 point, 11 comments)
  5. 63 points, 10 submissions: htrajan
    1. Sample test case: missing data (22 points, 36 comments)
    2. Optimize_something test cases (13 points, 22 comments)
    3. Met Burt Malkiel today (6 points, 1 comment)
    4. Heads up: Dataframe.std != np.std (5 points, 5 comments)
    5. optimize_something: graph (5 points, 29 comments)
    6. Schedule still reflecting shortened summer timeframe? (4 points, 3 comments)
    7. Quick clarification about InsaneLearner (3 points, 8 comments)
    8. Test cases using rfr? (3 points, 5 comments)
    9. Input format of rfr (2 points, 1 comment)
    10. [Shameless recruiting post] Wealthfront is hiring! (0 points, 9 comments)
  6. 62 points, 7 submissions: swamijay
    1. defeat_learner test case (34 points, 38 comments)
    2. Project 3 test cases (15 points, 27 comments)
    3. Defeat_Learner - related questions (6 points, 9 comments)
    4. Options risk/reward (2 points, 0 comments)
    5. manual strategy - you must remain in the position for 21 trading days. (2 points, 9 comments)
    6. standardizing values (2 points, 0 comments)
    7. technical indicators - period for moving averages, or anything that looks past n days (1 point, 3 comments)
  7. 61 points, 9 submissions: gatech-raleighite
    1. Protip: Better reddit search (22 points, 9 comments)
    2. Helpful numpy array cheat sheet (16 points, 10 comments)
    3. In your experience Professor, Mr. Byrd, which strategy is "best" for trading ? (12 points, 10 comments)
    4. Industrial strength or mature versions of the assignments ? (4 points, 2 comments)
    5. What is the correct (faster) way of doing this bit of pandas code (updating multiple slice values) (2 points, 10 comments)
    6. What is the correct (pythonesque?) way to select 60% of rows ? (2 points, 11 comments)
    7. How to get adjusted close price for funds not publicly traded (TSP) ? (1 point, 2 comments)
    8. Is there a way to only test one or 2 of the learners using grade_learners.py ? (1 point, 10 comments)
    9. OMS CS Digital Career Seminar Series - Scott Leitstein recording available online? (1 point, 4 comments)
  8. 60 points, 2 submissions: reyallan
    1. [Project Questions] Unit Tests for assess_portfolio assignment (58 points, 52 comments)
    2. Financial data, technical indicators and live trading (2 points, 8 comments)
  9. 59 points, 12 submissions: dyllll
    1. Please upvote helpful posts and other advice. (26 points, 1 comment)
    2. Books to further study in trading with machine learning? (14 points, 9 comments)
    3. Is Q-Learning the best reinforcement learning method for stock trading? (4 points, 4 comments)
    4. Any way to download the lessons? (3 points, 4 comments)
    5. Can a TA please contact me? (2 points, 7 comments)
    6. Is the vectorization code from the youtube video available to us? (2 points, 2 comments)
    7. Position of webcam (2 points, 15 comments)
    8. Question about assignment one (2 points, 5 comments)
    9. Are udacity quizzes recorded? (1 point, 2 comments)
    10. Does normalization of indicators matter in a Q-Learner? (1 point, 7 comments)
  10. 56 points, 2 submissions: jan-laszlo
    1. Proper git workflow (43 points, 19 comments)
    2. Adding you SSH key for password-less access to remote hosts (13 points, 7 comments)
  11. 53 points, 1 submission: agifft3_omscs
    1. [Project Questions] Unit Tests for optimize_something assignment (53 points, 94 comments)
  12. 50 points, 16 submissions: BNielson
    1. Regression Trees (7 points, 9 comments)
    2. Two Interpretations of RFR are leading to two different possible Sharpe Ratios -- Need Instructor clarification ASAP (5 points, 3 comments)
    3. PYTHONPATH=../:. python grade_analysis.py (4 points, 7 comments)
    4. Running on Windows and PyCharm (4 points, 4 comments)
    5. Studying for the midterm: python questions (4 points, 0 comments)
    6. Assess Learners Grader (3 points, 2 comments)
    7. Manual Strategy Grade (3 points, 2 comments)
    8. Rewards in Q Learning (3 points, 3 comments)
    9. SSH/Putty on Windows (3 points, 4 comments)
    10. Slight contradiction on ProctorTrack Exam (3 points, 4 comments)
  13. 49 points, 7 submissions: j0shj0nes
    1. QLearning Robot - Finalized and Released Soon? (18 points, 4 comments)
    2. Flash Boys, HFT, frontrunning... (10 points, 3 comments)
    3. Deprecations / errata (7 points, 5 comments)
    4. Udacity lectures via GT account, versus personal account (6 points, 2 comments)
    5. Python: console-driven development (5 points, 5 comments)
    6. Buffet pandas / numpy versions (2 points, 2 comments)
    7. Quant research on earnings calls (1 point, 0 comments)
  14. 45 points, 11 submissions: Zapurza
    1. Suggestion for Strategy learner mega thread. (14 points, 1 comment)
    2. Which lectures to watch for upcoming project q learning robot? (7 points, 5 comments)
    3. In schedule file, there is no link against 'voting ensemble strategy'? Scheduled for Nov 13-20 week (6 points, 3 comments)
    4. How to add questions to the question bank? I can see there is 2% credit for that. (4 points, 5 comments)
    5. Scratch paper use (3 points, 6 comments)
    6. The big short movie link on you tube says the video is not available in your country. (3 points, 9 comments)
    7. Distance between training data date and future forecast date (2 points, 2 comments)
    8. News affecting stock market and machine learning algorithms (2 points, 4 comments)
    9. pandas import in pydev (2 points, 0 comments)
    10. Assess learner server error (1 point, 2 comments)
  15. 43 points, 23 submissions: chvbs2000
    1. Is the Strategy Learner finalized? (10 points, 3 comments)
    2. Test extra 15 test cases for marketsim (3 points, 12 comments)
    3. Confusion between the term computing "back-in time" and "going forward" (2 points, 1 comment)
    4. How to define "each transaction"? (2 points, 4 comments)
    5. How to filling the assignment into Jupyter Notebook? (2 points, 4 comments)
    6. IOError: File ../data/SPY.csv does not exist (2 points, 4 comments)
    7. Issue in Access to machines at Georgia Tech via MacOS terminal (2 points, 5 comments)
    8. Reading data from Jupyter Notebook (2 points, 3 comments)
    9. benchmark vs manual strategy vs best possible strategy (2 points, 2 comments)
    10. global name 'pd' is not defined (2 points, 4 comments)
  16. 43 points, 15 submissions: shuang379
    1. How to test my code on buffet machine? (10 points, 15 comments)
    2. Can we get the ppt for "Decision Trees"? (8 points, 2 comments)
    3. python question pool question (5 points, 6 comments)
    4. set up problems (3 points, 4 comments)
    5. Do I need another camera for scanning? (2 points, 9 comments)
    6. Is chapter 9 covered by the midterm? (2 points, 2 comments)
    7. Why grade_analysis.py could run even if I rm analysis.py? (2 points, 5 comments)
    8. python question pool No.48 (2 points, 6 comments)
    9. where could we find old versions of the rest projects? (2 points, 2 comments)
    10. where to put ml4t-libraries to install those libraries? (2 points, 1 comment)
  17. 42 points, 14 submissions: larrva
    1. is there a mistake in How-to-learn-a-decision-tree.pdf (7 points, 7 comments)
    2. maximum recursion depth problem (6 points, 10 comments)
    3. [Urgent]Unable to use proctortrack in China (4 points, 21 comments)
    4. manual_strategynumber of indicators to use (3 points, 10 comments)
    5. Assignment 2: Got 63 points. (3 points, 3 comments)
    6. Software installation workshop (3 points, 7 comments)
    7. question regarding functools32 version (3 points, 3 comments)
    8. workshop on Aug 31 (3 points, 8 comments)
    9. Mount remote server to local machine (2 points, 2 comments)
    10. any suggestion on objective function (2 points, 3 comments)
  18. 41 points, 8 submissions: Ran__Ran
    1. Any resource will be available for final exam? (19 points, 6 comments)
    2. Need clarification on size of X, Y in defeat_learners (7 points, 10 comments)
    3. Get the same date format as in example chart (4 points, 3 comments)
    4. Cannot log in GitHub Desktop using GT account? (3 points, 3 comments)
    5. Do we have notes or ppt for Time Series Data? (3 points, 5 comments)
    6. Can we know the commission & market impact for short example? (2 points, 7 comments)
    7. Course schedule export issue (2 points, 15 comments)
    8. Buying/seeking beta v.s. buying/seeking alpha (1 point, 6 comments)
  19. 38 points, 4 submissions: ProudRamblinWreck
    1. Exam 2 Study topics (21 points, 5 comments)
    2. Reddit participation as part of grade? (13 points, 32 comments)
    3. Will birds chirping in the background flag me on Proctortrack? (3 points, 5 comments)
    4. Midterm Study Guide question pools (1 point, 2 comments)
  20. 37 points, 6 submissions: gatechben
    1. Submission page for strategy learner? (14 points, 10 comments)
    2. PSA: The grading script for strategy_learner changed on the 26th (10 points, 9 comments)
    3. Where is util.py supposed to be located? (8 points, 8 comments)
    4. PSA:. The default dates in the assignment 1 template are not the same as the examples on the assignment page. (2 points, 1 comment)
    5. Schedule: Discussion of upcoming trading projects? (2 points, 3 comments)
    6. [defeat_learners] More than one column for X? (1 point, 1 comment)
  21. 37 points, 3 submissions: jgeiger
    1. Please send/announce when changes are made to the project code (23 points, 7 comments)
    2. The Big Short on Netflix for OMSCS students (week of 10/16) (11 points, 6 comments)
    3. Typo(?) for Assess_portfolio wiki page (3 points, 2 comments)
  22. 35 points, 10 submissions: ltian35
    1. selecting row using .ix (8 points, 9 comments)
    2. Will the following 2 topics be included in the final exam(online student)? (7 points, 4 comments)
    3. udacity quiz (7 points, 4 comments)
    4. pdf of lecture (3 points, 4 comments)
    5. print friendly version of the course schedule (3 points, 9 comments)
    6. about learner regression vs classificaiton (2 points, 2 comments)
    7. is there a simple way to verify the correctness of our decision tree (2 points, 4 comments)
    8. about Building an ML-based forex strategy (1 point, 2 comments)
    9. about technical analysis (1 point, 6 comments)
    10. final exam online time period (1 point, 2 comments)
  23. 33 points, 2 submissions: bhrolenok
    1. Assess learners template and grading script is now available in the public repository (24 points, 0 comments)
    2. Tutorial for software setup on Windows (9 points, 35 comments)
  24. 31 points, 4 submissions: johannes_92
    1. Deadline extension? (26 points, 40 comments)
    2. Pandas date indexing issues (2 points, 5 comments)
    3. Why do we subtract 1 from SMA calculation? (2 points, 3 comments)
    4. Unexpected number of calls to query, sum=20 (should be 20), max=20 (should be 1), min=20 (should be 1) -bash: syntax error near unexpected token `(' (1 point, 3 comments)
  25. 30 points, 5 submissions: log_base_pi
    1. The Massive Hedge Fund Betting on AI [Article] (9 points, 1 comment)
    2. Useful Python tips and tricks (8 points, 10 comments)
    3. Video of overview of remaining projects with Tucker Balch (7 points, 1 comment)
    4. Will any material from the lecture by Goldman Sachs be covered on the exam? (5 points, 1 comment)
    5. What will the 2nd half of the course be like? (1 point, 8 comments)
  26. 30 points, 4 submissions: acschwabe
    1. Assignment and Exam Calendar (ICS File) (17 points, 6 comments)
    2. Please OMG give us any options for extra credit (8 points, 12 comments)
    3. Strategy learner question (3 points, 1 comment)
    4. Proctortrack: Do we need to schedule our test time? (2 points, 10 comments)
  27. 29 points, 9 submissions: _ant0n_
    1. Next assignment? (9 points, 6 comments)
    2. Proctortrack Onboarding test? (6 points, 11 comments)
    3. Manual strategy: Allowable positions (3 points, 7 comments)
    4. Anyone watched Black Scholes documentary? (2 points, 16 comments)
    5. Buffet machines hardware (2 points, 6 comments)
    6. Defeat learners: clarification (2 points, 4 comments)
    7. Is 'optimize_something' on the way to class GitHub repo? (2 points, 6 comments)
    8. assess_portfolio(... gen_plot=True) (2 points, 8 comments)
    9. remote job != remote + international? (1 point, 15 comments)
  28. 26 points, 10 submissions: umersaalis
    1. comments.txt (7 points, 6 comments)
    2. Assignment 2: report.pdf (6 points, 30 comments)
    3. Assignment 2: report.pdf sharing & plagiarism (3 points, 12 comments)
    4. Max Recursion Limit (3 points, 10 comments)
    5. Parametric vs Non-Parametric Model (3 points, 13 comments)
    6. Bag Learner Training (1 point, 2 comments)
    7. Decision Tree Issue: (1 point, 2 comments)
    8. Error in Running DTLearner and RTLearner (1 point, 12 comments)
    9. My Results for the four learners. Please check if you guys are getting values somewhat near to these. Exact match may not be there due to randomization. (1 point, 4 comments)
    10. Can we add the assignments and solutions to our public github profile? (0 points, 7 comments)
  29. 26 points, 6 submissions: abiele
    1. Recommended Reading? (13 points, 1 comment)
    2. Number of Indicators Used by Actual Trading Systems (7 points, 6 comments)
    3. Software Install Instructions From TA's Video Not Working (2 points, 2 comments)
    4. Suggest that TA/Instructor Contact Info Should be Added to the Syllabus (2 points, 2 comments)
    5. ML4T Software Setup (1 point, 3 comments)
    6. Where can I find the grading folder? (1 point, 4 comments)
  30. 26 points, 6 submissions: tomatonight
    1. Do we have all the information needed to finish the last project Strategy learner? (15 points, 3 comments)
    2. Does anyone interested in cryptocurrency trading/investing/others? (3 points, 6 comments)
    3. length of portfolio daily return (3 points, 2 comments)
    4. Did Michael Burry, Jamie&Charlie enter the short position too early? (2 points, 4 comments)
    5. where to check participation score (2 points, 1 comment)
    6. Where to collect the midterm exam? (forgot to take it last week) (1 point, 3 comments)
  31. 26 points, 3 submissions: hilo260
    1. Is there a template for optimize_something on GitHub? (14 points, 3 comments)
    2. Marketism project? (8 points, 6 comments)
    3. "Do not change the API" (4 points, 7 comments)
  32. 26 points, 3 submissions: niufen
    1. Windows Server Setup Guide (23 points, 16 comments)
    2. Strategy Learner Adding UserID as Comment (2 points, 2 comments)
    3. Connect to server via Python Error (1 point, 6 comments)
  33. 26 points, 3 submissions: whoyoung99
    1. How much time you spend on Assess Learner? (13 points, 47 comments)
    2. Git clone repository without fork (8 points, 2 comments)
    3. Just for fun (5 points, 1 comment)
  34. 25 points, 8 submissions: SharjeelHanif
    1. When can we discuss defeat learners methods? (10 points, 1 comment)
    2. Are the buffet servers really down? (3 points, 2 comments)
    3. Are the midterm results in proctortrack gone? (3 points, 3 comments)
    4. Will these finance topics be covered on the final? (3 points, 9 comments)
    5. Anyone get set up with Proctortrack? (2 points, 10 comments)
    6. Incentives Quiz Discussion (2-01, Lesson 11.8) (2 points, 3 comments)
    7. Anyone from Houston, TX (1 point, 1 comment)
    8. How can I trace my error back to a line of code? (assess learners) (1 point, 3 comments)
  35. 25 points, 5 submissions: jlamberts3
    1. Conda vs VirtualEnv (7 points, 8 comments)
    2. Cool Portfolio Backtesting Tool (6 points, 6 comments)
    3. Warren Buffett wins $1M bet made a decade ago that the S&P 500 stock index would outperform hedge funds (6 points, 12 comments)
    4. Windows Ubuntu Subsystem Putty Alternative (4 points, 0 comments)
    5. Algorithmic Trading Of Digital Assets (2 points, 0 comments)
  36. 25 points, 4 submissions: suman_paul
    1. Grade statistics (9 points, 3 comments)
    2. Machine Learning book by Mitchell (6 points, 11 comments)
    3. Thank You (6 points, 6 comments)
    4. Assignment1 ready to be cloned? (4 points, 4 comments)
  37. 25 points, 3 submissions: Spareo
    1. Submit Assignments Function (OS X/Linux) (15 points, 6 comments)
    2. Quantsoftware Site down? (8 points, 38 comments)
    3. ML4T_2017Spring folder on Buffet server?? (2 points, 5 comments)
  38. 24 points, 14 submissions: nelsongcg
    1. Is it realistic for us to try to build our own trading bot and profit? (6 points, 21 comments)
    2. Is the risk free rate zero for any country? (3 points, 7 comments)
    3. Models and black swans - discussion (3 points, 0 comments)
    4. Normal distribution assumption for options pricing (2 points, 3 comments)
    5. Technical analysis for cryptocurrency market? (2 points, 4 comments)
    6. A counter argument to models by Nassim Taleb (1 point, 0 comments)
    7. Are we demandas to use the sample for part 1? (1 point, 1 comment)
    8. Benchmark for "trusting" your trading algorithm (1 point, 5 comments)
    9. Don't these two statements on the project description contradict each other? (1 point, 2 comments)
    10. Forgot my TA (1 point, 6 comments)
  39. 24 points, 11 submissions: nurobezede
    1. Best way to obtain survivor bias free stock data (8 points, 1 comment)
    2. Please confirm Midterm is from October 13-16 online with proctortrack. (5 points, 2 comments)
    3. Are these DTlearner Corr values good? (2 points, 6 comments)
    4. Testing gen_data.py (2 points, 3 comments)
    5. BagLearner of Baglearners says 'Object is not callable' (1 point, 8 comments)
    6. DTlearner training RMSE none zero but almost there (1 point, 2 comments)
    7. How to submit analysis using git and confirm it? (1 point, 2 comments)
    8. Passing kwargs to learners in a BagLearner (1 point, 5 comments)
    9. Sampling for bagging tree (1 point, 8 comments)
    10. code failing the 18th test with grade_learners.py (1 point, 6 comments)
  40. 24 points, 4 submissions: AeroZach
    1. questions about how to build a machine learning system that's going to work well in a real market (12 points, 6 comments)
    2. Survivor Bias Free Data (7 points, 5 comments)
    3. Genetic Algorithms for Feature selection (3 points, 5 comments)
    4. How far back can you train? (2 points, 2 comments)
  41. 23 points, 9 submissions: vsrinath6
    1. Participation check #3 - Haven't seen it yet (5 points, 5 comments)
    2. What are the tasks for this week? (5 points, 12 comments)
    3. No projects until after the mid-term? (4 points, 5 comments)
    4. Format / Syllabus for the exams (2 points, 3 comments)
    5. Has there been a Participation check #4? (2 points, 8 comments)
    6. Project 3 not visible on T-Square (2 points, 3 comments)
    7. Assess learners - do we need to check is method implemented for BagLearner? (1 point, 4 comments)
    8. Correct number of days reported in the dataframe (should be the number of trading days between the start date and end date, inclusive). (1 point, 0 comments)
    9. RuntimeError: Invalid DISPLAY variable (1 point, 2 comments)
  42. 23 points, 8 submissions: nick_algorithm
    1. Help with getting Average Daily Return Right (6 points, 7 comments)
    2. Hint for args argument in scipy minimize (5 points, 2 comments)
    3. How do you make money off of highly volatile (high SDDR) stocks? (4 points, 5 comments)
    4. Can We Use Code Obtained from Class To Make Money without Fear of Being Sued (3 points, 6 comments)
    5. Is the Std for Bollinger Bands calculated over the same timespan of the Moving Average? (2 points, 2 comments)
    6. Can't run grade_learners.py but I'm not doing anything different from the last assignment (?) (1 point, 5 comments)
    7. How to determine value at terminal node of tree? (1 point, 1 comment)
    8. Is there a way to get Reddit announcements piped to email (or have a subsequent T-Square announcement published simultaneously) (1 point, 2 comments)
  43. 23 points, 1 submission: gong6
    1. Is manual strategy ready? (23 points, 6 comments)
  44. 21 points, 6 submissions: amchang87
    1. Reason for public reddit? (6 points, 4 comments)
    2. Manual Strategy - 21 day holding Period (4 points, 12 comments)
    3. Sharpe Ratio (4 points, 6 comments)
    4. Manual Strategy - No Position? (3 points, 3 comments)
    5. ML / Manual Trader Performance (2 points, 0 comments)
    6. T-Square Submission Missing? (2 points, 3 comments)
  45. 21 points, 6 submissions: fall2017_ml4t_cs_god
    1. PSA: When typing in code, please use 'formatting help' to see how to make the code read cleaner. (8 points, 2 comments)
    2. Why do Bollinger Bands use 2 standard deviations? (5 points, 20 comments)
    3. How do I log into the [email protected]? (3 points, 1 comment)
    4. Is midterm 2 cumulative? (2 points, 3 comments)
    5. Where can we learn about options? (2 points, 2 comments)
    6. How do you calculate the analysis statistics for bps and manual strategy? (1 point, 1 comment)
  46. 21 points, 5 submissions: Jmitchell83
    1. Manual Strategy Grades (12 points, 9 comments)
    2. two-factor (3 points, 6 comments)
    3. Free to use volume? (2 points, 1 comment)
    4. Is MC1-Project-1 different than assess_portfolio? (2 points, 2 comments)
    5. Online Participation Checks (2 points, 4 comments)
  47. 21 points, 5 submissions: Sergei_B
    1. Do we need to worry about missing data for Asset Portfolio? (14 points, 13 comments)
    2. How do you get data from yahoo in panda? the sample old code is below: (2 points, 3 comments)
    3. How to fix import pandas as pd ImportError: No module named pandas? (2 points, 4 comments)
    4. Python Practice exam Question 48 (2 points, 2 comments)
    5. Mac: "virtualenv : command not found" (1 point, 2 comments)
  48. 21 points, 3 submissions: mharrow3
    1. First time reddit user .. (17 points, 37 comments)
    2. Course errors/types (2 points, 2 comments)
    3. Install course software on macOS using Vagrant .. (2 points, 0 comments)
  49. 20 points, 9 submissions: iceguyvn
    1. Manual strategy implementation for future projects (4 points, 15 comments)
    2. Help with correlation calculation (3 points, 15 comments)
    3. Help! maximum recursion depth exceeded (3 points, 10 comments)
    4. Help: how to index by date? (2 points, 4 comments)
    5. How to attach a 1D array to a 2D array? (2 points, 2 comments)
    6. How to set a single cell in a 2D DataFrame? (2 points, 4 comments)
    7. Next assignment after marketsim? (2 points, 4 comments)
    8. Pythonic way to detect the first row? (1 point, 6 comments)
    9. Questions regarding seed (1 point, 1 comment)
  50. 20 points, 3 submissions: JetsonDavis
    1. Push back assignment 3? (10 points, 14 comments)
    2. Final project (9 points, 3 comments)
    3. Numpy versions (1 point, 2 comments)
  51. 20 points, 2 submissions: pharmerino
    1. assess_portfolio test cases (16 points, 88 comments)
    2. ML4T Assignments (4 points, 6 comments)

Top Commenters

  1. tuckerbalch (2296 points, 1185 comments)
  2. davebyrd (1033 points, 466 comments)
  3. yokh_cs7646 (320 points, 177 comments)
  4. rgraziano3 (266 points, 147 comments)
  5. j0shj0nes (264 points, 148 comments)
  6. i__want__piazza (236 points, 127 comments)
  7. swamijay (227 points, 116 comments)
  8. _ant0n_ (205 points, 149 comments)
  9. ml4tstudent (204 points, 117 comments)
  10. gatechben (179 points, 107 comments)
  11. BNielson (176 points, 108 comments)
  12. jameschanx (176 points, 94 comments)
  13. Artmageddon (167 points, 83 comments)
  14. htrajan (162 points, 81 comments)
  15. boyko11 (154 points, 99 comments)
  16. alyssa_p_hacker (146 points, 80 comments)
  17. log_base_pi (141 points, 80 comments)
  18. Ran__Ran (139 points, 99 comments)
  19. johnsmarion (136 points, 86 comments)
  20. jgorman30_gatech (135 points, 102 comments)
  21. dyllll (125 points, 91 comments)
  22. MikeLachmayr (123 points, 95 comments)
  23. awhoof (113 points, 72 comments)
  24. SharjeelHanif (106 points, 59 comments)
  25. larrva (101 points, 69 comments)
  26. augustinius (100 points, 52 comments)
  27. oimesbcs (99 points, 67 comments)
  28. vansh21k (98 points, 62 comments)
  29. W1redgh0st (97 points, 70 comments)
  30. ybai67 (96 points, 41 comments)
  31. JuanCarlosKuriPinto (95 points, 54 comments)
  32. acschwabe (93 points, 58 comments)
  33. pharmerino (92 points, 47 comments)
  34. jgeiger (91 points, 28 comments)
  35. Zapurza (88 points, 70 comments)
  36. jyoms (87 points, 55 comments)
  37. omscs_zenan (87 points, 44 comments)
  38. nurobezede (85 points, 64 comments)
  39. BelaZhu (83 points, 50 comments)
  40. jason_gt (82 points, 36 comments)
  41. shuang379 (81 points, 64 comments)
  42. ggatech (81 points, 51 comments)
  43. nitinkodial_gatech (78 points, 59 comments)
  44. harshsikka123 (77 points, 55 comments)
  45. bkeenan7 (76 points, 49 comments)
  46. moxyll (76 points, 32 comments)
  47. nelsongcg (75 points, 53 comments)
  48. nickzelei (75 points, 41 comments)
  49. hunter2omscs (74 points, 29 comments)
  50. pointblank41 (73 points, 36 comments)
  51. zheweisun (66 points, 48 comments)
  52. bs_123 (66 points, 36 comments)
  53. storytimeuva (66 points, 36 comments)
  54. sva6 (66 points, 31 comments)
  55. bhrolenok (66 points, 27 comments)
  56. lingkaizuo (63 points, 46 comments)
  57. Marvel_this (62 points, 36 comments)
  58. agifft3_omscs (62 points, 35 comments)
  59. ssung40 (61 points, 47 comments)
  60. amchang87 (61 points, 32 comments)
  61. joshuak_gatech (61 points, 30 comments)
  62. fall2017_ml4t_cs_god (60 points, 50 comments)
  63. ccrouch8 (60 points, 45 comments)
  64. nick_algorithm (60 points, 29 comments)
  65. JetsonDavis (59 points, 35 comments)
  66. yjacket103 (58 points, 36 comments)
  67. hilo260 (58 points, 29 comments)
  68. coolwhip1234 (58 points, 15 comments)
  69. chvbs2000 (57 points, 49 comments)
  70. suman_paul (57 points, 29 comments)
  71. masterm (57 points, 23 comments)
  72. RolfKwakkelaar (55 points, 32 comments)
  73. rpb3 (55 points, 23 comments)
  74. venkatesh8 (54 points, 30 comments)
  75. omscs_avik (53 points, 37 comments)
  76. bman8810 (52 points, 31 comments)
  77. snladak (51 points, 31 comments)
  78. dfihn3 (50 points, 43 comments)
  79. mlcrypto (50 points, 32 comments)
  80. omscs-student (49 points, 26 comments)
  81. NellVega (48 points, 32 comments)
  82. booglespace (48 points, 23 comments)
  83. ccortner3 (48 points, 23 comments)
  84. caa5042 (47 points, 34 comments)
  85. gcalma3 (47 points, 25 comments)
  86. krushnatmore (44 points, 32 comments)
  87. sn_48 (43 points, 22 comments)
  88. thenewprofessional (43 points, 16 comments)
  89. urider (42 points, 33 comments)
  90. gatech-raleighite (42 points, 30 comments)
  91. chrisong2017 (41 points, 26 comments)
  92. ProudRamblinWreck (41 points, 24 comments)
  93. kramey8 (41 points, 24 comments)
  94. coderafk (40 points, 28 comments)
  95. niufen (40 points, 23 comments)
  96. tholladay3 (40 points, 23 comments)
  97. SaberCrunch (40 points, 22 comments)
  98. gnr11 (40 points, 21 comments)
  99. nadav3 (40 points, 18 comments)
  100. gt7431a (40 points, 16 comments)

Top Submissions

  1. [Project Questions] Unit Tests for assess_portfolio assignment by reyallan (58 points, 52 comments)
  2. [Project Questions] Unit Tests for optimize_something assignment by agifft3_omscs (53 points, 94 comments)
  3. Proper git workflow by jan-laszlo (43 points, 19 comments)
  4. Exam 2 Information by yokh_cs7646 (39 points, 40 comments)
  5. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes by davebyrd (37 points, 10 comments)
  6. Project 1 Megathread (assess_portfolio) by davebyrd (34 points, 466 comments)
  7. defeat_learner test case by swamijay (34 points, 38 comments)
  8. Project 2 Megathread (optimize_something) by tuckerbalch (33 points, 475 comments)
  9. project 3 megathread (assess_learners) by tuckerbalch (27 points, 1130 comments)
  10. Deadline extension? by johannes_92 (26 points, 40 comments)

Top Comments

  1. 34 points: jgeiger's comment in QLearning Robot project megathread
  2. 31 points: coolwhip1234's comment in QLearning Robot project megathread
  3. 30 points: tuckerbalch's comment in Why Professor is usually late for class?
  4. 23 points: davebyrd's comment in Deadline extension?
  5. 20 points: jason_gt's comment in What would be a good quiz question regarding The Big Short?
  6. 19 points: yokh_cs7646's comment in For online students: Participation check #2
  7. 17 points: i__want__piazza's comment in project 3 megathread (assess_learners)
  8. 17 points: nathakhanh2's comment in Project 2 Megathread (optimize_something)
  9. 17 points: pharmerino's comment in Midterm study Megathread
  10. 17 points: tuckerbalch's comment in Midterm grades posted to T-Square
Generated with BBoe's Subreddit Stats (Donate)
submitted by subreddit_stats to subreddit_stats [link] [comments]

Subreddit Stats: AskEconomics posts from 2018-08-22 to 2018-11-12 07:20 PDT

Period: 82.02 days
Submissions Comments
Total 979 6319
Rate (per day) 11.94 76.69
Unique Redditors 688 1060
Combined Score 5907 19076

Top Submitters' Top Submissions

  1. 322 points, 37 submissions: benjaminikuta
    1. So, what's the difference between this new trade deal with Mexico and Canada and the old one, and what are the implications? (71 points, 12 comments)
    2. The EU is considering making product life expectancy a mandatory piece of info for consumer electronics. What would the economic implications of that be? (64 points, 24 comments)
    3. Do powerful unions increase wages above the optimal level, or do firms with market power cause imperfect competition in the labor market, causing sub optimal wages? (Or both?) (27 points, 3 comments)
    4. How do economists measure unpaid work? (24 points, 8 comments)
    5. When it is said that someone in a third world country lives on a dollar a day, what does that actually mean? (22 points, 19 comments)
    6. What are some common misconceptions about economics? (14 points, 19 comments)
    7. What would be a better alternative to Bernie's proposal to tax employers of welfare recipients? (14 points, 65 comments)
    8. How effectively can negative externalities be quantified? (10 points, 7 comments)
    9. To what degree has the internet increased the liquidity of the labor market? (7 points, 3 comments)
    10. What happened with the Greek economic crisis? (7 points, 5 comments)
  2. 146 points, 30 submissions: Whynvme
    1. When economists refer to industrialization, does it mean a move from agricultural to manufacturing economy? Is the growth in services a different term? (22 points, 6 comments)
    2. Do economists actually calculate consumer surplus empirically, or is it more of s theoretical concept? (20 points, 5 comments)
    3. If we have cobb douglas preferences, my demand for x is not a function of the price of y. How do substitution effects arise then? (11 points, 6 comments)
    4. Is me making more money than I would necessarily require to work( so more than my 'opportunity wage') for a job an economic inefficiency? or is ineffiency in labor markets a wedge between my marginal revenue product and my wage? (11 points, 3 comments)
    5. why is ceteris paribus important for analyzing/thinking about the world? (11 points, 7 comments)
    6. Why does inflation necessarily mean wages will be increasing too? (6 points, 3 comments)
    7. some basic macro questions (6 points, 2 comments)
    8. what is meant by value added? (6 points, 3 comments)
    9. Trying to understand economies of scale, e.g. costco (5 points, 5 comments)
    10. Why would an economy implode long term if there are decreasing returns to scale? (5 points, 15 comments)
  3. 95 points, 2 submissions: MrDannyOcean
    1. Announcing a new policy direction for /AskEconomics (75 points, 135 comments)
    2. The new rules for AskEconomics are now in place. Please see the details within. (20 points, 20 comments)
  4. 79 points, 7 submissions: Fart_Gas
    1. Is free public transport a good idea? (41 points, 20 comments)
    2. Will Venezuela's plummeting economy make it a good choice for low-wage industries? (17 points, 8 comments)
    3. What might cause sudden inflation? (8 points, 2 comments)
    4. Why do some countries without hyperinflation use a foreign currency in everyday life? (8 points, 3 comments)
    5. Has any country tried reducing the minimum wage, and ended up with a good result from it? (3 points, 8 comments)
    6. Do boycotts really work? (1 point, 3 comments)
    7. Why do some businesses sponsor sporting teams in countries they don't operate in, and that they don't plan to expand to in the foreseeable future? (1 point, 1 comment)
  5. 66 points, 7 submissions: FrankVillain
    1. Can the Euro become the global currency for trade? (17 points, 3 comments)
    2. Is China still considered a centrally planned economy? (16 points, 4 comments)
    3. Ressources on the Soviet industrial failures due to poor economics? (14 points, 2 comments)
    4. What is the reason behind France's high unemployment rate? (9 points, 14 comments)
    5. About Land Value Tax & Single Tax: how would it affect farmers and those of them who own their land? (7 points, 3 comments)
    6. Does welfare policies contribute to inflation? (2 points, 1 comment)
    7. If a Bitcoin is worth $1 000 000 and some persons like Satoshi have one or more millions of it... what power do they have? Can they disrupt the financial system with the huge amount of dollars that they have? (1 point, 8 comments)
  6. 66 points, 1 submission: imadeadinside
    1. If Bruce Wayne was revealed as Batman, would stock prices and sales skyrocket or plummet for Wayne Enterprises (66 points, 16 comments)
  7. 64 points, 6 submissions: Serpenthrope
    1. Have there been any serious proposals for economic systems that don't use money? (23 points, 67 comments)
    2. Could a company ever become quality-control for a market in which they're competing, assuming no government interference? (16 points, 4 comments)
    3. Is there a formal name for this? (15 points, 6 comments)
    4. Why are second-hand clothing donations fundamentally different from other types of imports? (5 points, 1 comment)
    5. I saw this article on a UN report calling for the dismantling of Capitalism to stop Global Warming, and was wondering what most economists think of the claims? (3 points, 4 comments)
    6. Peter Navarro and Lyndon Larouche? (2 points, 1 comment)
  8. 62 points, 2 submissions: JeffGotSwags
    1. What are the most commonly held misconceptions about economics among people with at least some background? (36 points, 38 comments)
    2. How did the financial crisis affect the demand for economists? (26 points, 5 comments)
  9. 61 points, 11 submissions: Chumbaka
    1. Can someone explain M0 , M1 and M2 to me? (13 points, 2 comments)
    2. Can anyone explain why this happens and what it means? (11 points, 3 comments)
    3. Can a monopoly also be a monopsony? (10 points, 13 comments)
    4. Why is inflation and deflation bad? (10 points, 8 comments)
    5. Stupid question but : Why does printing lots of money lead to inflation? (5 points, 14 comments)
    6. Why aren't all banks Full Reserve Banking? (5 points, 3 comments)
    7. What does this stock market fall mean to the economy as a whole? (4 points, 4 comments)
    8. How would an universal free market deal with situations like NK? (3 points, 21 comments)
    9. How do I pick an economist ideology to support? (0 points, 3 comments)
    10. Is investing in Forex worth it? (0 points, 15 comments)
  10. 60 points, 6 submissions: Jollygood156
    1. Why didn't quantitative easing + low interest rates raise inflation high? (20 points, 36 comments)
    2. How do we actually refute MMT? (14 points, 68 comments)
    3. Tax Cuts boost Consumption, but the growth is short term while investments are long term. Why? (12 points, 7 comments)
    4. How exactly are land value taxes calculated? (6 points, 3 comments)
    5. What is Nominal GDP targeting and why do so many people advocate for it? (5 points, 16 comments)
    6. What even is Austerity? (3 points, 3 comments)
  11. 49 points, 1 submission: Akehc99
    1. Those who went into the job market after an Econ Undergrad, what do you do and briefly what does it entail? (49 points, 27 comments)
  12. 48 points, 1 submission: Traveledfarwestward
    1. What do most Economists think about The Economist? (48 points, 26 comments)
  13. 48 points, 1 submission: piltonpfizerwallace
    1. What would happen if the US printed $12.3 trillion tomorrow and paid off all of its debt? (48 points, 31 comments)
  14. 47 points, 6 submissions: lalze123
    1. Will Bernie's "STOP BEZOS" plan lower the opportunity cost of hiring non-poor workers, thereby harming poor workers? (19 points, 15 comments)
    2. What does the current economic literature say about the effects of net neutrality? (14 points, 0 comments)
    3. What government programs have been empirically proven to help displaced workers from import competition? (8 points, 0 comments)
    4. By how much does lowering the budget deficit lower the trade deficit? (5 points, 4 comments)
    5. What are some good studies analyzing the difference in efficiency between markets and central planning? (1 point, 1 comment)
    6. Is the study below reliable? (0 points, 3 comments)
  15. 45 points, 1 submission: gh0bs
    1. Why does the economy have to be a series of bubbles and bursts/corrections, rather than a sustained gradual growth? (45 points, 32 comments)
  16. 42 points, 1 submission: Turnt_Up_For_What
    1. You've just been declared supreme potentate of Venezuela. Now how do you fix the economy? (42 points, 24 comments)
  17. 41 points, 1 submission: Crane_Train
    1. How could Venezuela fix its economy? (41 points, 19 comments)
  18. 41 points, 1 submission: TheHoleInMoi
    1. Are there any papers/solid arguments about the benefits of having more local business as opposed to corporate consolidation? (41 points, 2 comments)
  19. 39 points, 5 submissions: UyhAEqbnp
    1. Does income inequality really matter? (19 points, 39 comments)
    2. What happens when there's a surplus of labour? Can there ever be a point where the wages earned are less than the cost of living? (10 points, 2 comments)
    3. Several questions (4 points, 4 comments)
    4. "Keeping seniors from retiring does not boost wages via aggregate demand" (3 points, 5 comments)
    5. Is Okun's Law valid? (3 points, 3 comments)
  20. 39 points, 4 submissions: justinVOLuntary
    1. Best resource on the financial crisis of 2008 (17 points, 7 comments)
    2. Blogs? (11 points, 5 comments)
    3. Econ Internship (7 points, 5 comments)
    4. Not sure if this is the kind of question I should be asking here. I’m an Undergrad Econ major and I’m looking for reading recommendations. Anything from economic theory, history, current research, etc. Main interest is Macro. Thanks (4 points, 5 comments)
  21. 39 points, 2 submissions: ConditionalDew
    1. How much would the iPhone be if it was made in the US? (37 points, 15 comments)
    2. Who are some famous people/celebrities that were economics majors? (2 points, 2 comments)
  22. 39 points, 1 submission: rangerlinks
    1. Who are the best economist to follow on Twitter? (39 points, 16 comments)
  23. 36 points, 5 submissions: CanadianAsshole1
    1. If free trade is so good, then why do countries insist on making trade deals? Why can't we just abolish all tariffs? (18 points, 11 comments)
    2. If climate change is such a huge problem, then why aren't countries utilizing nuclear energy more? (8 points, 17 comments)
    3. Do I understand the problem with"trickle-down" economics correctly? (6 points, 38 comments)
    4. How much of the Reagan administration's deficits could be attributed to increased defense spending? (3 points, 3 comments)
    5. If automation will result in less jobs, then shouldn't the government stop incentivizing childbirth through tax credits and stop immigration? (1 point, 12 comments)
  24. 35 points, 7 submissions: MedStudent-96
    1. Is my textbook wrong? (11 points, 8 comments)
    2. Quasi-convexity of the Indirect Utility Function? (9 points, 14 comments)
    3. Consumer Demand Interpretation for Cobb Douglas-Non Convex to Origin. (4 points, 6 comments)
    4. Do monopolies produce the same as a competitive firm in the long run? (4 points, 8 comments)
    5. Interpretation of Lagrange Multipliers for Consumer (4 points, 4 comments)
    6. Optimisation when MRTS > price ratio (2 points, 7 comments)
    7. Help with the Partial Derivative of the Marginal Cost Function. (1 point, 10 comments)
  25. 35 points, 1 submission: grate1438
    1. Why do Croatians receieve so much more through their pension than their working wage? (35 points, 8 comments)

Top Commenters

  1. BainCapitalist (2626 points, 648 comments)
  2. Calvo_fairy (947 points, 232 comments)
  3. smalleconomist (885 points, 255 comments)
  4. RobThorpe (776 points, 259 comments)
  5. zzzzz94 (577 points, 111 comments)
  6. Cross_Keynesian (520 points, 108 comments)
  7. Integralds (418 points, 68 comments)
  8. penguin_rider222 (395 points, 116 comments)
  9. whyrat (362 points, 69 comments)
  10. bbqroast (319 points, 74 comments)
  11. MrDannyOcean (314 points, 54 comments)
  12. isntanywhere (207 points, 63 comments)
  13. RedditUser91805 (189 points, 28 comments)
  14. CapitalismAndFreedom (176 points, 68 comments)
  15. benjaminikuta (171 points, 112 comments)
  16. LucasCritique (162 points, 33 comments)
  17. raptorman556 (157 points, 44 comments)
  18. lawrencekhoo (156 points, 22 comments)
  19. daokedao4 (131 points, 16 comments)
  20. Yankee9204 (121 points, 15 comments)
  21. roboczar (112 points, 20 comments)
  22. RegulatoryCapture (109 points, 23 comments)
  23. ecolonomist (105 points, 45 comments)
  24. TheoryOfSomething (102 points, 9 comments)
  25. Forgot_the_Jacobian (97 points, 31 comments)

Top Submissions

  1. Announcing a new policy direction for /AskEconomics by MrDannyOcean (75 points, 135 comments)
  2. So, what's the difference between this new trade deal with Mexico and Canada and the old one, and what are the implications? by benjaminikuta (71 points, 12 comments)
  3. If Bruce Wayne was revealed as Batman, would stock prices and sales skyrocket or plummet for Wayne Enterprises by imadeadinside (66 points, 16 comments)
  4. The EU is considering making product life expectancy a mandatory piece of info for consumer electronics. What would the economic implications of that be? by benjaminikuta (64 points, 24 comments)
  5. Those who went into the job market after an Econ Undergrad, what do you do and briefly what does it entail? by Akehc99 (49 points, 27 comments)
  6. What would happen if the US printed $12.3 trillion tomorrow and paid off all of its debt? by piltonpfizerwallace (48 points, 31 comments)
  7. What do most Economists think about The Economist? by Traveledfarwestward (48 points, 26 comments)
  8. Why does the economy have to be a series of bubbles and bursts/corrections, rather than a sustained gradual growth? by gh0bs (45 points, 32 comments)
  9. What is the difference in knowledge between academic economists(Krugman, Acemoglu, Mankiw etc) and hedge fund managers and the like(Soros, James Simons)? by deleted (43 points, 5 comments)
  10. You've just been declared supreme potentate of Venezuela. Now how do you fix the economy? by Turnt_Up_For_What (42 points, 24 comments)

Top Comments

  1. 62 points: Calvo_fairy's comment in Milton Friedman is well respected by many economists, why aren't there more Libertarians?
  2. 62 points: Calvo_fairy's comment in Milton Friedman is well respected by many economists, why aren't there more Libertarians?
  3. 59 points: RedditUser91805's comment in The EU is considering making product life expectancy a mandatory piece of info for consumer electronics. What would the economic implications of that be?
  4. 58 points: arctigos's comment in What do most Economists think about The Economist?
  5. 55 points: hbtn's comment in Why are Little Caesar's cheese pizzas the same price as its pepperoni pizzas?
  6. 54 points: Calvo_fairy's comment in Could someone explain the wage gap and whether it's a myth or not.
  7. 51 points: Calvo_fairy's comment in If Bruce Wayne was revealed as Batman, would stock prices and sales skyrocket or plummet for Wayne Enterprises
  8. 51 points: RedditUser91805's comment in You've just been declared supreme potentate of Venezuela. Now how do you fix the economy?
  9. 51 points: smalleconomist's comment in What are the most commonly held misconceptions about economics among people with at least some background?
  10. 49 points: TheoryOfSomething's comment in Which parts of Marxism are theoretically dependent on the labor theory of value and which are not?
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