[…]3 Final Rank Value (FRV) for each ETF is Step2A * 40% + Step2B * 40% + Step2C * 20% The downloadable spreadsheet contains an example of how to do this ranking. Universe The tricky part about any ETF strategy like this is the selection of the trading universe. This has a huge impact on the results. I will test 2 universes for this post but if you have your own idea of a universe to test, add it to the comments below. If I get enough good universes, I will do another post with those results. US Sector Universe: […]
[…]strategy from beginning to end Minimum prerequisite: AmiBroker installed and connected to a daily data source. Help me shape the class by filling the survey below. Enter your email and I will send an AFL back test code template that I often use. Also included are custom metrics of the yearly returns and the best/worst […]
[…]of the 10 period ATR. The stop is evaluated at the close and exited the next day at the open. Again we see the same general results. Adding the ATR max loss hurts with CAR or MDD. Again we see big improvements in the worst 50 trades and worst 5 drawdowns. I like the ATR factor between 1 and 2 they seem to strike a good balance. Profit Targets The second most voted on research idea was profit targets. Unfortunately I was not clear on how to add these. I tested intraday based targets. If you voted for this and […]
[…]articles that I found interesting and made me think. Learn Math or Get Left Behind Every now and again, events occur that cause me to shake my head in dismay at people’s math skills. When the weather forecast is a 90 percent chance of a sunshine, and it rains, that doesn’t mean the forecast was wrong; rather, it was one of those cases where the low probability event occurred. Some people seem to believe that 90 percent and 100 percent are the same. Obviously, they are not. Recall model assumptions before jumping to conclusions I have written numerous times […]
A mean reversion strategy I trade was developed with another researcher. This strategy enters on a further intraday weakness with a limit order and typically exits a few days later when the stock bounces. Recently this researcher sent me and email saying “Try the strategy as a day trade. Enter at the open and exit at the close. Surprisingly good results.” Of course, this piqued my interest and I went off and changed the code and ran it. The new strategy lost money. Hum. Why the difference? Step 1: The Rules Well, I know that we are not trading the […]
[…]survivorship bias. I am optimizing over the period of 2010-2012 inclusive, and our out-of sample data is 2013-2015 inclusive (well, almost to the end of the year). I also take a look at a wider period of 2000-2015 to see if the system holds up. We calculate diffusion as before: dif30qtr = total_up_30 / ( total_up_30 + total_down_30 ) * 100 I’m multiplying by 100 to give it a percent-y feel, but that part isn’t strictly necessary. As always the first step is to replicate the results from the site. Matt was very helpful in answering questions and I was […]
[…]see and use. Different ways of measuring strength of a sell-off and volatility expansion. Along with a different type of exit being used on a mean reversion strategy. Not simply waiting for the bounce. Rules Test date range 2007 to 8/31/2020. Buy Stock is a member of the S&P500 index 4-period RSI is less than 30 The highest High in the last 21 days divided by the lowest Low of the last 21 days is greater than 1.04 The r-squared value of the last 4 days is greater than .6 The 4-day standard deviation of closes is greater than the […]
[…]For detailed information on correlation you can read Correlation and dependence or for simpler explanation read Correlation at Math is Fun. For steps on how to do this in Excel, which is where of course I did it, read Correlation at Excel Easy. I will cover here how one can use correlation analysis between equity curves. Correlation Coefficient Size of Correlation Interpretation .90 to 1.00 (−.90 to −1.00) Very high positive (negative) correlation .70 to .90 (−.70 to −.90) High positive (negative) correlation .50 to .70 (−.50 to −.70) Moderate positive (negative) correlation .30 to .50 (−.30 to −.50) Low […]
I am frequently asked what data provider I use and recommend for stocks. I have been using Norgate Data for four years and recommend them to anyone looking for data. This review will focus on US Stocks and AmiBroker integration which is what I use daily. Norgate Data has data for the Australian and US markets, forex and futures data. They integrate with AmiBroker and RightEdge. Disclosures: I have paid for my data. The links to Norgate Data on this page are affiliate links. Features I want I focused on these features: Data back to at least 1995 Delisted stock […]
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