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.

June 2018 Report

This month was the third month of the futures trading experiment. The first month was the model development phase, while last month was about ironing out the glitches and training myself to trade the model properly (and not give in to gut instinct etc). It turned out that this month was more of the same and I am still on the second stage of the experiment, which is learning to consistently trade the model and iron out the glitches. The third stage is to reach a level of profits equal to my salary, while the fourth stage would be to maximize returns beyond that. I had planned to move to trading two contracts this month, but mostly traded one contract still.

June is the month when our Australian managed funds pay out their main distributions at the end of the Australian financial year. These usually have large tax credits associated with them. In this report, I have estimated the likely tax credits, which won't be known till later in July.

The Australian Dollar fell from USD 0.7571 to USD 0.7391. The MSCI World Index fell 0.50% and the S&P 500 rose 0.62%. The ASX 200 rose 3.63%. All these are total returns including dividends. We gained 3.16% in Australian Dollar terms and 0.71% in US Dollar terms. So, we  underperformed the Australian market and outperformed international markets.

The best performing investment in dollar terms  was CFS Geared Share Fund gaining AUD 23k. The next best in dollar terms was IPE, gaining AUD 19k. The best performing asset class was "private equity", gaining 7.79%. The second best performer was Australian large cap stocks, gaining 3.21%. The worst performing asset class was hedge funds, losing 0.46%, the only asset class that lost money.

The following is table of investment performance statistics computed over the last 36 months of data:

The first two rows gives the annual rate of return and Sharpe ratio for our investment performance in US dollars and Australian dollars. The other statistics are in comparison to the two indices. Beta expresses the change in investment returns for a 1% change in the market. Compared to the MSCI World Index we seem to be slightly geared, while compared to the Australian index we are less sensitive to market movements. Alpha shows the risk adjusted excess annual return. This is how much we are beating the market (or not) adjusted for risk expressed as beta. We have a slightly positive alpha compared to the Australian and world markets. Finally, up capture and down capture breaks beta into the response to positive and negative months in the stockmarket. A greater up capture than down capture ratio is desirable. We now capture more of the up movements in the international and less in the Australian market and suffer less of the down movements in both the Australian and international markets. A hedge fund like return would show this positive skew and a positive alpha. We show some hedge fund like properties across the markets.

This month I only made a small amount of money trading futures: USD 1.2k. The table compares my performance to the markets and the models:

The US markets went up and then down, ending quite flat. The models did outperform the market.* Through a series of missteps I performed worse than the models given that I was using leverage. This is mostly because I picked the wrong contract to trade with for some of the time. I think one way to trade in strongly trending markets is to act more tactically, trading in the direction of the model when other short term indicators (using a chart with 3 hour candles) show it is advantageous and then closing the position when the odds move the other way. More than once I was up USD 2k and then gave it all back... On 21 June I did exactly the wrong thing, throwing in the towel for the day and closing my short just as the market was about to reverse and go down... Seeing that happen did increase my faith in the model a little bit more. Gut instinct is not as good as the model. But then the same thing, kind of, happened on the last day of the month. The models were short, the market went up, but I capitulated at almost the worst point, because at the market close the indices were way down from the highs.

The best I can say is that I didn't lose money for the month as a whole. So it looks like more of the same for next month. I'll try to trade one contract exactly according to the model and one tactically.

We made a little more progress towards the new long-run asset allocation:

Total leverage includes borrowing inside leveraged (geared) mutual (managed) funds. The allocation is according to total assets including the true exposure in leveraged mutual funds.

The improvement in allocation, came partly due to market movements and partly due to investment activity. We invest AUD 2k monthly in a set of managed funds, and there are also retirement contributions. Then there are distributions from funds and dividends. During the month, I also:

• I shifted money out of trading when I shifted the account I am trading with. This decreased the allocation to commodities.
• Added another AUD 10k to the Winton Global Alpha fund, increasing the allocation to commodities.
• I sold 500,000 shares in IPE and bought a small amount of OCP.AX, reducing the allocation to private equity.
• I sold some Platinum Capital (PMC.AX) and bought a lot of PIXX.AX, which is the equivalent ETF, because PMC was particularly overvalued. This increased the allocation to hedge funds.

* The statistics at the bottom of the table are based on only 3 months of data and so are not at all reliable yet.

Trading Update: Tokyo Edition

So far it looks like the "old" more systematic model won today. US stocks are down. I'm not trading as I was flying to Japan and now my phone's connectivity is dodgy and I need it as a security device. Anyway, Wednesday is US Independence Day and Tuesday is already a short trading day so, I'll wait till Thursday or when I am back in Australia next week,

My hotel is the blue tower in the background.

P.S.
The stockmarket turned and went up. So, the "new" model was vindicated in the end. Still, I don't like trading rules that don't make logical sense.

Changing the Model Back and Researching the Model

I'm not happy with this model rule that I added on 27th April. It's not very systematic. So, I dropped it, while keeping rules added more recently. The stock market switches between two states - trending and cycling - and the model uses different indicators in each state. Deciding what state we are in is a little problematic. So, I am going to have another look at the rules for that and also possibly smoothing out very small moves, which are noise. The rule I just dropped was ad hoc - it switched to the indicator for the cycling state when we are in a trending state based on one period lagged positive performance.

Monday is a good test of the two algorithms - the simpler model is short and the model with the "ad hoc" rule is long. Let's see which wins.

I also thought of using the volatility indices, VIX and VXN, as indicators. The basic idea is that volatility is highest at bottoms in the market. But I couldn't see a way to do this. This graph shows why:

VXN (and VIX) rose throughout January while the stock market rose too. This was a warning sign that a correction was coming. But a model that shorts the market when VXN is expected to increase would have lost money all January. Also, my existing forecasting model is no good here...

Gold 2048: The Future of Gold

This report seems bullish for the price of gold over the next 30 years. Continued growth in India and limited gold discoveries recently seem bullish. On the other hand, some regions haven't been explored much and technology could enhance extraction, though the latter likely balanced by increased environmental restrictions.

Mercantile Makes Offer to Take Over IPE

Mercantile Capital (MVT.AX) has made an offer to take over IPE.AX at AUD 0.0775 per share. I've discussed Mercantile's interest in IPE before and bought shares as a result. I had 1.5 million shares. My only regret is I didn't buy more. People selling even below 6 cents discouraged me from buying more.

I had 500,000 on offer for sale and they sold just now at 0.075 up from 0.063 yesterday. I will wait and see with the remaining million. I should at least hold it into the next tax year, next month. If I sell now, it will wipe out my existing tax losses and more. So better to defer tax for another year.

Tax Optimization for Trading

I still have some capital losses left over from the financial crisis. I will probably use them up for this tax year ending 30 June. After that, trading profits would be taxed at my marginal rate of 47% (and even higher if Labor get back into power and implement their tax policy). So, I am opening an account at Interactive Brokers for Moominmama (formerly Snork Maiden). Trading in her account will only attract a marginal rate of 34.5% initially and then higher if we make lots of profits. This will reduce our overall tax bill and is totally legitimate in Australia.

Actually, given that franking credits are fully refundable, even if they exceed your tax bill (but Labor wants to change that too), it also would make sense to have other investments in Moominmama's name. The reason we don't, is that up to a couple of years ago, when my income went over AUD 180k per year and she went part-time we were in the same marginal tax bracket. But perhaps I should direct new investments to her account?

In somewhat related news, the minimum wage in Australia has just been raised, so that someone working full time at the minimum wage earns just over AUD 37k a year (about USD 14.25 per hour). This means that the marginal rate for such workers is now also 34.5%! That really seems crazy to me.

May 2018 Report

Another very active month financially. The Australian stock market rebounded quite strongly but then turned over as other markets did. This month was the second month of the futures trading experiment. The first month was the model development phase, while this month was about ironing out the glitches and training myself to trade the model properly (and not give in to gut instinct etc).

The Australian Dollar rose from USD 0.7540 to USD 0.7571. The MSCI World Index rose 0.21%, and the S&P 500 2.41%. The ASX 200 rose 1.09%. All these are total returns including dividends. We gained 1.84% in Australian Dollar terms and 2.26% in US Dollar terms. So, we outperformed both the Australian market and the international markets and slightly underperformed the US market.

The best performing investment in dollar terms was NASDAQ futures gaining AUD 9.5k (this is going to be a theme :)). The second best was CFS Geared Share Fund gaining AUD 8.9k. The worst performer in dollar terms was IPE, losing AUD 1.5k. The best performing asset class was "commodities", which includes futures trading, gaining 6.24%. Hopefully, this will become a near permanent feature. The second best performer was Australian small cap stocks, gaining 2.92%. The worst performing asset class was private equity, losing 0.78%, the only asset class that lost money.

A new feature starting this month is the following table of investment performance statistics. The statistics are computed with the last 36 months of data:

The first row gives the Sharpe ratio for our investment performance in US dollars and Australian dollars. The other statistics are in comparison to the two indices. Beta expresses the change in investment returns for a 1% change in the market. Compared to the MSCI World Index we seem to be slightly geared, while compared to the Australian index we are less sensitive to market movements. Alpha shows the risk adjusted excess annual return. This is how much we are beating the market (or not) adjusted for risk expressed as beta. We have a slightly positive alpha compared to the Australian market and a close to zero alpha compared to the world market. Finally, up capture and down capture breaks beta into the response to positive and negative months in the stockmarket. A greater up capture than down capture ratio is desirable. We do capture more of the up movements in the Australian market and suffer less of the down movements. A hedge fund like return would show this positive skew and a positive alpha. Compared to the Australian market we show some hedge fund like properties.

This month I made money trading futures: USD 7.2k. The table compares my performance to the markets and the models:

I also bought and sold investments in this account and added AUD 25k in cash towards the end of May, so don't expect the starting cash to change with just income earned. My rate of return in May far exceeds the models or markets because of leverage. I mostly traded one contract at a time and so was using a bit over 3 times leverage. I could also select the market where I thought the model signal was most reliable. In the early part of the month I mostly traded NQ (NASDAQ) and in the later part of the month ES (S&P 500). I also traded CL (oil). Most of the gains were made early in the month when the market rose. After that the market mostly went sideways.

I more or less successfully followed the plan for the month, which was to consistently trade one futures contract according to the trades that the model provides, while learning about entering trades more optimally and setting stops. There were some hiccups, particularly on 14 May when I lost much more than the model due to bad trading. I can say that the second of my goals in the experiment - to consistently trade the model - was a qualified success. I was much more disciplined than when I previously traded futures, but still not disciplined enough. The third goal - to earn as much as my salary from trading fell short though I was in the ballpark. I would need to make USD 12.5k to reach the goal. For the next month I plan to work on the same goals and maybe increase the position size when I am particularly certain about the market direction. This is why I added more cash to the account. After adding the money and doing some bad daytrading, which I shouldn't be doing, I had second thoughts about taking a larger position. But I maybe should be trading both stocks and oil simultaneously. Horizontal rather than vertical expansion.

We made more progress towards the new long-run asset allocation:

Total leverage includes borrowing inside leveraged (geared) mutual (managed) funds. The allocation is according to total assets including the true exposure in leveraged mutual funds.

The improvement in allocation, came partly due to market movements and partly due to investment activity. We invest AUD 2k monthly in a set of managed funds, and there are also retirement contributions. Then there are distributions from funds and dividends. During the month, I also:

• Traded futures successfully, increasing the allocation to "commodities" as a result. As mentioned above, I also added cash to the trading account. Just over 4% of net worth is now allocated to trading.
• Added another AUD 10k to the Winton Global Alpha fund, also increasing the allocation to commodities.
• Closed my investment in GMOM, due to poor performance over many years.
• Increased investments in the China Fund (CHN), Boulder Income Fund (BIF), and 3i (III.L).
• Sold my trade in Woolworths (WOW.AX) and made a quick trade in Platinum Capital (PMC.AX).
• Switched from Colonial First State Geared Share Fund to CFS Conservative Fund in a small account I have, which I am planning to close soon (after the end of June distribution). Then I switched back again. Originally, I had this account as a trading account!

Flipped Back to Short

The model was long NQ for one day and lost a little (it remained short ES, surprisingly). Now it has flipped back to short. Given yesterday's post, I'm still thinking this is a limited correction. Here is a possible interpretation based on Elliott Wave Theory:

We are now in wave C of 4. Based on Elliott Wave Theory that wave should stop before price falls below the maximum point of Wave 1, as shown on the graph. I find Elliott Wave very useful in understanding the different things that might happen, but I don't think it is an exact fit to what the market does, especially on very long and very short time scales. Over the time scale shown on this chart, it is particularly useful. On the other hand, Eliott Wave is notorious for continually morphing and following what the market does, rather than predicting it.

Of course, my model has nothing to do with Elliott Wave Theory it is just nice to have some other approach that does not conflict with the model or confirms it.

If you look closely you'll see I'm short from 6911.5 and up quite nicely, but I was up $500 when long yesterday evening too and that reversed...

P.S.
The downside didn't last long! Market turned around in the morning US time and went up, eventually reaching above the top of the triangle in the chart above. At one point I was up USD 1500, but unfortunately I didn't take profits as I was sticking to what the model said to do. Now I am considering doubling my position during the Australian daytime - the US overnight and then closing half in the US morning. If I had done that yesterday I would have ended up on the day. I am going to backtest the strategy of course. 10 years back when I previously was trading futures, I did look at "overnight trading" as a strategy, and now it has come up again.

Model has now flipped back to long. S&P model was short till today, and now has also gone long.