Model Decisions for the Year So Far

The chart shows each short and long decision the model has made in the NASDAQ 100 index since the beginning of the year. The letter S or L is placed on the first day the model was long or short in each trade. So in theory you should get long or short at the previous close. Most trades were winners, though in late February, for example, the model got short on a big up day and then switched back to long the next day, which turned out to be the top. That long trade was also a loser. There were also stop outs along the way, which aren't marked here as new trades. Some times the model picks the exact top or bottom, at other times it misses it by a couple of days.

So, all I need to do is trade exactly like the model :) I put a new long trade on this morning.

New Investment: BlueSky Alternatives Fund

I had read back in April about BlueSky's battle with activist hedge fund Glaucus. As a result, the share price of the management company (BLA.AX) collapsed and they undertook a thorough review and independent valuation of all their investments. Listed investment company (closed-end fund) BAF.AX, is a fund of funds, investing in BLA managed investments in real estate, private equity, agriculture, and water rights. The price of this fund also fell, though not as dramatically. The valuation of all but one of its investments is now complete and the net asset value is AUD 1.13 per share. On Friday the stock was trading around AUD 0.80. The company is buying back a lot of stock which is supporting the price. I made an initial investment today and could add more if my thesis that it should rise, plays out.

Position Size

One of the main ideas in traditional momentum trading wisdom is that as volatility increases your position size should decrease. This is one of the key ideas in the Turtle Trading System, for example. If you have no idea what will happen, then higher volatility likely will result in higher losses as well as higher gains.

But if you do have some ability to predict the future, that trading signal might be stronger when volatility is higher and weaker when volatility is lower. Then you will have more losing trades when volatility is low and a higher proportion of winning trades when volatility is high. This seems to be the case with my system. Higher volatility means higher risk but also a higher probability of being right. In this case, position size maybe should be constant regardless of volatility.

P.S. 22 July

I calculated the Sharpe ratio for constant position size and for strategies that reduce position size as volatility increases and and increase position size as volatility increases. The constant position size strategy has the highest Sharpe ratio confirming my intuition. The strategy with a negative correlation between position size and volatility has the lowest Sharpe ratio. The strategy with a positive correlation is in between. So, for the moment I will stick with constant position sizing.

Turtle Trading

I have been reading the Complete Turtle Trader, trying to get some inspiration. Back in the early 1980s, futures trader Richard Dennis hired a bunch of relative novices (some actually had trading experience) and taught them a trend-following method of trading. He then got them to trade some of his assets using the methods. The idea was to see if trading could be taught. During the next few years, many of them generated extraordinary returns, as documented in the book. Then the experiment ended after Dennis suffered major losses and shut his fund.

Some of the "turtles" went on to run their own investment firms. The star pupil seems to be Jerry Parker who founded Chesapeake Capital. However, subsequent performance has not really been that good.* The fund has underperformed the S&P 500 and has had about twice as much volatility. Taxes would be much higher on Chesapeake's strategy than on buying and holding the index. Why does voltatility matter? Because I could have used leverage to invest in the S&P 500, increasing volatility to the level of the Chesapeake Capital fund, but increasing returns far beyond its returns.

This doesn't encourage me to adopt a long-term trend following strategy. The assumption of this kind of model is that the future is entirely unpredictable... Eckhardt is cited in the book as saying that random entry into a trade is just as good as long as you follow exit rules. That's true about most momentum trading strategies I think.

It's notable that none of these turtle related firms are very big in terms of assets under management.

* The "LV" fund performed better but still underperformed the S&P 500 on a risk adjusted basis. Salem Abraham's – described as a "second-generation turtle" in the book – fund has gone nowhere in the last ten years.