[…]AmiBroker questions or projects. Matt Radtke is a trader, researcher, software engineer, and freelance consultant with a focus on helping clients build and test quantified trading strategies using AmiBroker. After earning a pre-internet Computer Science degree from Michigan State University, he spent more than two decades writing software for a variety of companies from small startups to multinational conglomerates like Hewlett-Packard. Mr. Radtke started trading stocks and options in 2007, and later added futures to the mix. In 2010 he was introduced to the concept of quantified trading by Larry Connors, and between 2012 and 2019 held various roles including researcher, […]
[…]with doing this when trading a portfolio of symbols is that trades are often correlated together. For example a mean reversion strategy during a market has a sell off. Typically most of trades are losers during this time. Monte Carlo analysis does not account for this behavior. Doing this type of testing in AmiBroker is not straightforward. Adding noise to the rules (Method 1) For method 2, one varies the rule values by a small percentage. Take the RSI(2) < 7.5 rule. What we do is vary 7.5 by a little. Instead of 7.5, we use 6.82 or 9.84. One […]
[…]this method. Now, this sounded like an idea with good potential. And even better it should be easy to test since I had the code written already. Or Not What I thought would be a few minutes to test this turned out to be a couple of hours. It turns out dealing with the 100 or 500 positions and making sure you don’t run out of money to get into them all was a little more work than expected. The joys of coding. Nothing is as simple as you think it will be. The Rules Test date range 1/1/2007 to […]
[…]Should one trade high or low volatility stocks?, we placed stocks into three volatility buckets and compared their performance. Several readers pointed out that using a fixed percentage stop made it more likely for high volatility stocks to hit the stop thus not performing as well. Readers suggested using an Average True Range stop or a time stop. We will explore those two stops and see how the volatility buckets compare. Individual Trade Quality Before we get to the tests, I need to explain a new metric I will be using. At Connors Research we use Individual Trade Quality, ITQ, […]
[…]seen something like this and conceptually it is simple. I also liked that it was not “easy” to test or optimize on. Therefore hopefully not many people would be using this indicator and I could potentially find better values. Trust but Verify From the site This next market breadth indicator counts all the stocks in the Russell 3000 that are up at least 30% over the last quarter (60 trading days), as well as all the stocks that are down at least 30% for the last 60 days. I’m using historical constituents of the Russell 3000 including delisted stocks to […]
[…]Finding to a Portfolio I have a mean reversion strategy I trade that I want to add these results to. To my set-up rules, I will add PercentRank(Volume, 20) < 20 as another filter. As expected, the exposure dropped dramatically from 25% to 5%. The avg. % p/l takes a large jump from 1.87% to 2.58% with % winners increasing slightly. Instead of adding PercentRank as a filter, what happens if we rank signals with a PercentRank < 20, higher than those without? This should give us about the same number of trades. We see a small improvement in CAR, […]
[…]similar. The problem is how does one say which data source is correct without a third data source to compare against. I could compare about a dozen symbols with Bloomberg’s data. Eight symbols agreed between CSI and Bloomberg. Four symbols agreed with Premium Data. Of the eight symbols were Premium Data did not agree there were a couple of obvious data errors, which I reported to Norgate Investor Services. Grade: A The data can be adjusted for dividends and one time capital gains There seems to be some misconception that Premium Data Services cannot do this. I have had several […]
[…]bad luck in the trades. Now I try to avoid the really smooth curves. For fit, I want the strategy to complement my other strategies. I look at rolling 1-3 month correlation of the equity curve. I want values all over the place. I don’t want the strategy to always be strongly correlated with another strategy I am trading. When I combine the strategies, I want the overall drawdown and drawlengths to go down. These are what I focus on. Each person needs to decide what stats they will focus on and the values they are looking for. These can […]
[…]is. One Variable When the strategy only has a few variables it is possible simply to test them all out. Take this simple strategy on the SPY. Buy when the close is greater than 220 day moving average. Sell when it is below it. Say we originally came to this number by doing an optimization in steps of 20 from 140 to 300. Here are the results all lengths of the moving average from 50 to 100. You can see peaks at 200, 220 and 240. The original test in steps of 20 would lead one to think all was […]
[…]is working on both the long and short side, one would be expect the order of the lines from top to bottom to be green, blue and red. In most years this is the case. From this point of view mean reversion is OK. Spreadsheet Fill the form below to get the spreadsheet with the yearly numbers used to generate this data. Final Thoughts These were good tests to run but none gave any solid proof that mean reversion is dying. Have the edges shrunk yes. Are they to where it is not worth trading, not in my opinion. Tell […]
