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.

The Index Gives Better Trading Signals than Futures Prices Do

It turns out that the NASDAQ 100 Index gives better trading signals than the NQ futures prices themselves do. I think the reason for this is that most trading takes place when the stock market is open and that is usually when big moves happen. The "out of hours" trading is mostly noise then reflecting what is happening in other stock markets and after hours earnings reports etc. The futures prices still provide signals that "beat the market" but not as well.

I did find again, that stops mostly detract from performance and I am introducing a new stops policy. When we change direction we set the stop loss at the the second pivot support for a long or the second pivot resistance for a short. We then keep that stop until either the direction of trade changes or we are stopped out. This results in far fewer stop outs.

It's likely that in commodity markets such as oil or gold the futures prices do provide good trading signals. Well, there isn't anything else to use anyway.

Futures Prices vs. Index Values

I didn't trade while I was in Japan because my mobile phone wasn't receiving the text messages I needed to log in to my trading account. When I got back to Australia I dithered about getting back in for a couple of days, missing a nice rally. Then this morning I decided to make the plunge (on the long side) and 2 hours later I was stopped out. Apparently there is negative news on US tariffs on trade with China.

After the cash market closes at 4pm New York time, the stock index futures trade for another hour before closing for one hour. The futures closing price can, therefore, be quite different to the index closing price. This was the case today where the futures plunged around 30 points in the last ten minutes of the futures trading session. Using the index data for the 4pm close, my model said to stay long. However, if we had knocked 30 NASDAQ points off to reflect the futures closing price, it would have switched to short. So, I think I need to get historical futures data and re-estimate my model with these. I should be able to get these from Quandl. An additional advantage of using futures prices is that I can do the analysis one hour later -  currently from 7am Australian Eastern time rather than 6am Australian Eastern time. The futures market then shuts for an hour and reopens at 6pm New York time or 8am Australian time.

However, on Saturday morning the futures market closes at Friday 5pm New York time and then doesn't reopen till Monday morning at 8am in Australia. So, I will need to do the analysis with index closing data before 7am on Saturdays unless I want to get stuck in possibly the wrong direction over the weekend.