Trading the SPI

The graph compares idealized trading of the ASX200 futures contract, known as the "SPI" (share price index) vs. buy and hold. The trading uses my new day-trading approach. I actually transcribed by hand all the opening, high, low, and close values off a chart of the past month with 8 hour bars to get the data. The ticks are each of the five daily 8 hour bars. Yes, they're not all actually 8 hours long. 9:50-10:00am is one of them! Each index point is worth AUD 25 per contract and this tracks trading one contract.

The good news is that trading would have made money over the past month. On the other hand, buy and hold would have done just as well. But trading is less volatile. Hopefully, trading also does better in down markets. As I started near the end of this chart, so far I have lost money. But I have been making money in daytrading the Australian Dollar and the S&P 500 index in the last week. I also did a rough backtest on the NASDAQ 100 Index. But as I don't have access to bulk hourly data I can't do very extensive backtesting. Either I need to get that data or I need to just trade at a small scale until the results are statistically significant.

Worst Loss on Bitcoin

Just got stopped out for a 7.06% loss on Bitcoin trading. That is the worst loss that the Bitcoin model has suffered so far. So, most losses won't be as bad as that. Back to short...

This position was never in the money. The position was entered on a spike in price, which just triggered the stop. But I exactly followed my approach. 

This is our equity curve (USD) so far in trading Bitcoin futures:

We also had some profits trading Bitcoin CFDs.

New Macro Trade

I've started another long-term macro trade by buying a treasury note futures spread. The spread is short one ten year treasury note futures contract and long two two year treasury futures contracts. You can execute this with one trade using the TUT ticker. The face value of a two year contract is $200,000 and for a ten year contract, $100,000, so actually the trade is long four times as many two year notes as it is short ten year notes. The idea is that this spread will gain value as the yield curve steepens, which following a yield curve inversion, it already seems to be doing. The curve would steepen mainly because the Federal Reserve would cut short term interest rates. So, if they don't cut much the trade will lose. The more they cut the more likely it is to make money.

My other macro trade is gold. Though that is also a bit more like an investment as we plan to allocate to gold in the long term and I am using the IAU ETF for tax and psychological reasons. I've increased my position at this point to 4.89% of assets. The net treasuries position is nominally $302k, which is much bigger than that.

I've also been thinking about how to improve my new day-trading strategy. I think that I will add exit stops to each order I place. This means, for example, if we go long initially in a "headfake"and then the market falls and the sell stop order is triggered, rather than getting out of the market it will initiate a short position. That would have been a profitable trade in the S&P 500 futures on 16th and 19th of July. The resulting short gained more than the stopped out long lost. Also, I am thinking to keep half of the position as a turtle style trend following position rather than an actual daytrade. The difference to the medium term turtle trading is that the stop is moved each day based on action in the first part of the day rather than action over the last few days.

So I now have three time frames of trades. I am hoping that this diversification, while requiring entering more orders, actually results in me being less anxious about the trades and so actually spending less time looking at the market. We will see.

Systematic Day Trading

I figured out a way to adapt the turtle trading method to systematic day-trading. I plan to apply it to markets which tend to move strongly after the release of US economic news at 8:30am Eastern Time on many days and which have elevated volume when US cash markets are open. The idea is to put buy and sell orders in for these markets at around 8:00am (currently 10pm here in Australia) based on the movement of the futures markets over the day up to that point. If there is a breakout of that range you go long or short automatically. Then you close the positions at the end of the trading day. This is a day trading method where you don't look at the market all day.

I don't have access to historic hourly data at the moment but I have backtested the idea for a couple of months by looking at charts for the NASDAQ 100 futures. It seems that the approach wins more times than it loses, though average wins and losses are about equal in size. Once the market starts moving in a given direction intraday it tends to keep moving in that direction. It looks like it would work well for stocks, bonds, gold, Australian Dollars... It doesn't look like it would work for oil, soybeans etc. These commodities typically expand their trading range in both directions when the market gets more active. As a result trades would tend to get stopped out.

I'll start trading it using the new micro-futures that are a 10th of the size of the e-mini NASDAQ and S&P contracts as well as with CFDs for gold (trading 10 ounces say) and Australian Dollars (starting with AUD 10k) and see how we go.

Trading Bitcoin Futures over the Weekend or Not

Because recently Bitcoin rallied strongly over weekends, I decided to close any Bitcoin futures short position at the end of trading on Friday. That means that this weekend I closed my short on Friday at the worst possible point and missed a more than 1000 points decline over the weekend. However, I've resolved not to get into this trade now and just wait for the next long trade.

Not including this weekend's action the average return over the weekend in the last 15 months when my model was short was -0.2%, i.e. a loss. But this is a small loss and is statistically insignificant. The t-statistic to test that this mean is different to zero is -0.31 (p = 0.74). On the other hand, the average return over the weekend when long was 1.5%. And this return is highly statistically significant. The t-statistic is 2.33 (p = 0.026).

This explains why I was reluctant to be short over the weekend but not to be long over the weekend. On the other hand, the expected loss isn't much, so avoiding trading over the weekend when short is due to risk aversion. Especially as I can place an effective stop in our Plus 500 CFD account. If we go long there and are short futures we are effectively out of the market. But it's expensive to do so due to their spread and overnight financing charges, and they only allow me to trade a maximum of 6 Bitcoin. On the other hand, I am only shorting one futures contract (5 Bitcoin) at a time at the moment.

So, how did this weekend affect these results? The gain to being short over the weekend was 9.5%. The mean weekend short return is now 0.07% with a t-statistic of 0.11 (p = 0.91). So, that is even closer to zero. Someone who is risk averse would still stay out of the market as the expected return is insignificantly different to zero.

To deal with the frustration, I am just telling myself that there will be a better opportunity to go long the further the price falls :) In the longer term, I think I would be less concerned about this if I diversify trading to multiple markets.

Individual Investment Returns for June 2019

I finally got around to doing this analysis for June:

It's not as straightforward as my other reporting and probably takes 20 minutes or so to prepare. International stocks, gold, and Australian real estate did really well. Australian small cap did really badly. The Unisuper superannuation fund also performed very well. Bitcoin trading was the real star though. It's not looking good this month so far... USD corporate bond performance continues to improve as the portfolio matures.

Distribution of Income and Wealth in Australia in 2017-18

The latest survey results have been released by ABS. To be in the top 1% in Australia you need to have a household net worth of about AUD 7.5 million (USD 5.25 million). We're in the top 4% according to the data. The mean household has a net worth of AUD 1.022 million and the median AUD 559k.

We're also in roughly the top 4% by household income if we'd earned 2018-19 income in 2017-18... Median household earns AUD 1,700 per week (AUD 88k per year) and mean 2,242 (AUD 117k). Of course, households with children average a lot more than this as the data include pensioners, students, singles etc. These data don't let you compute the income of the top 1% directly.

June 2019 Report

Because the financial year has just ended in Australia, this report has more estimated figures than normal. June was another positive month with big wins in Bitcoin and gold. In June the Australian Dollar rose from USD 0.6930 to USD 0.7012. The MSCI World Index rose 6.59% and the S&P 500 7.05%. The ASX 200 rose 3.80%. All these are total returns including dividends. We gained 1.39% in Australian Dollar terms and 2.59% in US Dollar terms. The target portfolio gained 2.36% in Australian Dollar terms and the HFRI hedge fund index gained 2.60% in US Dollar terms. So, we under-performed all benchmarks apart from HFRI. On the other hand, all months since the end of November have had positive returns in Australian Dollar terms:


Here is a report on the performance of investments by asset class (futures includes managed futures and trading):

Gold was the best performing asset class gaining 12%. The worst asset class was Australian small cap, losing 4%. The largest contributions to the rate of return came from futures followed by bonds. The Australian Dollar return is lower than the 2.02% reported here because of foreign currency losses due to the rise in the Australian Dollar over the month.

Things that worked very well this month:

• Trading Bitcoin. Trading profits for this month were greater than for all of 2018. 
• Gold.

What really didn't work:

• Tribeca Global Resources and Cadence Capital. These are now two of my three worst investments in dollar terms. Both of these are trading a lot below NAV. Tribeca is actually doing fine but investors have sold it perhaps because of a misleading report from Morningstar.

Trading income was USD 21,451 for the month, which is three times larger than any previous monthly total. The rate of return on cash in trading accounts was 13.88%.

We moved towards our new long-run asset allocation * as we began to shift out of bonds and moved the first money that orginally came from Chocolateland into our Australian bank account. Gold futures, and cash all increased. As predicted, last month was "peak bonds".

On a regular basis, we also invest AUD 2k monthly in a set of managed funds, and there are also retirement contributions. Then there are distributions from funds and dividends. Other moves this month:

• USD 130k of corporate bonds matured (Cigna) or we sold them after early redemptions were announced (CNO, HCA) and we bought USD 103k of USD bonds (Genworth, Goodyear, Xerox, and Avon Products). We also sold 2,000 CBAPH Commonwealth Bank hybrid securities.
• We traded successfully, as discussed above.
• I bought 5,000 shares of the IAU gold ETF. 
• We bought 66,126 shares in Domacom (DCL.AX), a startup company that is enabling fractional ownership of residential property.
• I bought another 4,734 shares in Oceania Capital.

* Total leverage includes borrowing inside leveraged (geared) mutual (managed) funds. The allocation is according to total assets including the true exposure in leveraged funds. We currently don't have any leveraged funds.

Adding Individual Stock Trading

My last post looked at my trading profit and loss from futures, ETFs, CFDs etc. But it didn't include individual stocks, which I traded a lot in the early years. So, I went into my data and tried to identify, which individual stocks were trades and which investments. It's not so easy to tell in some cases. However, anything I was generally short was clearly a trade as well as stocks I held for less than a month typically. So, the result is quite rough.

But the picture is clear. Adding individual stocks makes my trading history look much worse up to 2006:

I have now almost recouped all my previous trading losses in the last two years of trading. There are still a few days left to go and anything can happen, but this month is looking to be a record trading gain.

Trading History

I was wondering how my trading performance looked over the long haul and put together this chart which is cumulative profits from trading futures, ETFs, options etc. Mostly, I haven't included individual company stocks. Up to 2002 I just lost money really. Then from 2006 to 2008 I started systematic trading and had ups and downs and mainly went sideways. But then as the financial crisis deepened things went off a cliff. After that, I didn't trade for a decade until last year. After and initial dip, I made money every month till October last year and then took a break from trading. This year, I came back with a new approach and so far are doing even better. I am now better than breakeven in the long run from trading. I would say that I am optimistic now rather than confident that this can be a long-run source of profits.

Only 40 Active Accounts Trading Bitcoin Futures?

According to this article, there are only 40 active accounts trading CME bitcoin futures. I can't read the whole article without paying for an expensive subscription, so I don't know their methodology. I am surprised by this as I have two accounts regularly trading bitcoin futures. I wonder if all accounts at a broker like Interactive Brokers are bundled into a single virtual account?