Volatility Based Position Sizing

I just finished coding a volatility based position sizing algorithm and the results are pretty dramatic. My hypothesis was that it would transform my system's equity curve into more of a straight line and that's exactly what it did, smoothing the results over time. When conditions are more volatile a wider stop is used and less shares are purchased. Less volatile means a tighter stop and more shares, so smaller moves are capitalized on.

If anybody is interested in seeing the code I can post it with the disclaimer that it hasn't been tested in live trading.

Before Position Sizing with Static Stops

After Position Sizing with Dynamic Stops

New direction for this blog

For those who may have been following this blog for a while, I want to let you know that this blog will be taking a different direction. If you are mainly interested in seeing examples of discretionary trading, than there are several excellent traders that I link to over at the left column. I was discretionary trading for the last year and a half to get familiar with the markets. I am now embarking on the second phase of my trading career. Discretionary trading taught me a lot about myself. If you don't think you are emotional, try trading for a while. I had some good months, but I realize that the biggest obstacle to my success is myself. I believe that to really become a good trader you must enjoy the challenge of trading and have extreme mental toughness. Watch Tiger Woods play golf and you will see that he is intensely competitive and always believes that he is able to win, even after some bad shots. As a trader you have to be able to shake off some bad trades and not get into a negative feedback loop. It is difficult to "keep the faith" after a drawdown period no matter how many psychology books you have read. My advice to those looking to discretionary trade is make sure you love what you're doing.

If you're still reading than you probably have an interest in automated trading. I've been using Tradestation for about a week and have already developed some simple algorithms that outperform my own trading record, so the results are encouraging. I don't think I will be sharing the specifics of my strategies out of fear that Golman Sachs reads my blog and starts frontrunning my orders :) My approach to developing automated strategies is to keep it simple and general. I think if you get too specific, you end up with something that works great for a short period of time and then stops working. If I look at the trades my systems make, I can see examples of how people trade, like that's a narrow range bar at the ORH, or that's a pullback to a 50% fibonacci retracement. But I'm not searching for those setups specifically. If you keep your strategies general, you cast a wider net. There is always the temptation to overoptimize. If my algorithms start performing at an 80% win rate, I get suspicious. I look for a profit factor around 2.0 and a win rate around 60-70%. Anything higher seems suspect. I backtest over several years but weigh the last two more highly. I test on SPY mainly, but I may be getting into currency trading as a backup market. Right now there is too much correlation though, so the benefit of diversification really isn't there.