The Australian Dollar rose from USD 0.7201 to USD 0.7228. The MSCI World Index rose 0.48% and the S&P 500 rose 0.57%. The ASX 200 fell 1.04%. All these are total returns including dividends. We lost 0.63% in Australian Dollar terms and 0.26% in US Dollar terms. So, we outperformed the Australian market and underperformed international markets.
The best performing investment in dollar terms was NASDAQ futures gaining AUD 2.6k – and the worst the CFS Geared Share Fund losing AUD 10.7k. The best performing asset class was private equity, gaining 1.28% followed by commodities (this includes trading), gaining 1.22%. The worst performing asset class was Australian large cap, losing 1.57%.
The following is table of investment performance statistics computed over the last 60 months (extended from 36 months previously) 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. Based on beta, 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. We have a positive alpha compared to the Australian and a negative alpha compared to world markets. We capture more of the up movements and less of the down movements in the Australian market and the reverse in the international markets. The fall in the Australian Dollar over this period explains the poor performance compared to international benchmarks.
This month I made USD 2.5k trading futures. This is the second best result to date and ocurred as the NDX declined for the month. The table * compares my performance to the market and the model:
This month was the sixth month of the futures trading experiment. The first month was the model development phase, and since then I have been trying to get disciplined at trading and further incrementally improving the model. I didn't trade in the first half of the month as I was traveling to Europe and Singapore and the model was short and based on relatively low volatility I thought the profit potential was low. This was a mistake as the model did very well. Then when I got back into trading we were in a corrective phase with the market trading sideways. I traded long NQ short ES for the last few days of the month. The model outperformed the market this month, though its return was not that high. The model is bearish and under-performs when the market is strong and outperforms when the market is weak. It got stopped out a couple of times, which is unusual. As a result the model made 4 trades in 4 days. The second time the model was stopped out, the market ended up on the day and so the stop was too tight. The first time, the stop reduced losses.
What I want to do next on the trading front is write the model's decision algorithm in computer code. At the moment I estimate the indicators I use with an econometric model but I then make decisions manually and record the details in an Excel spreadsheet. It is quite quick to do to make daily decisions in a single market but it is quite hard to do backtesting of different ideas. This will be much easier once we have the decision algorithm coded in the same program as the estimation model. Also, in the long run I plan to automate trading or at least automate data acquisition and decision making for multiple markets. Coding the model in the language of my econometrics program is a first step towards that. Once the model is written in one computer language, converting it to another shouldn't be hard.
I did our tax returns this month. I should get a big refund and Moominmama had to pay a little under AUD 1,000 in extra tax. Otherwise, I am waiting for the probate process to play out before undergoing a big round of financial restructuring.
We made a little bit of 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 funds.
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. Major moves tbis month:
The best performing investment in dollar terms was NASDAQ futures gaining AUD 2.6k – and the worst the CFS Geared Share Fund losing AUD 10.7k. The best performing asset class was private equity, gaining 1.28% followed by commodities (this includes trading), gaining 1.22%. The worst performing asset class was Australian large cap, losing 1.57%.
The following is table of investment performance statistics computed over the last 60 months (extended from 36 months previously) of data:
This month I made USD 2.5k trading futures. This is the second best result to date and ocurred as the NDX declined for the month. The table * compares my performance to the market and the model:
What I want to do next on the trading front is write the model's decision algorithm in computer code. At the moment I estimate the indicators I use with an econometric model but I then make decisions manually and record the details in an Excel spreadsheet. It is quite quick to do to make daily decisions in a single market but it is quite hard to do backtesting of different ideas. This will be much easier once we have the decision algorithm coded in the same program as the estimation model. Also, in the long run I plan to automate trading or at least automate data acquisition and decision making for multiple markets. Coding the model in the language of my econometrics program is a first step towards that. Once the model is written in one computer language, converting it to another shouldn't be hard.
I did our tax returns this month. I should get a big refund and Moominmama had to pay a little under AUD 1,000 in extra tax. Otherwise, I am waiting for the probate process to play out before undergoing a big round of financial restructuring.
We made a little bit of progress towards the new long-run asset allocation:
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. Major moves tbis month:
- I redeemed the Janus-Henderson Global Resources Fund, which reduced exposure to ROW stocks.
- I reduced cash and the margin loan in preparation for investing in the Tribeca IPO. As a result our allocation to hedge funds will increase substantially next month.
- I added to the Yellow Brick Road position which is now about 1% of net worth.
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