If you are an investor and being honest to yourself, this is likely a question on your mind. This is no different from any endeavor you may have embarked on. For example, if you are on a weight-loss campaign, you would want to know if the program is effective and meeting your expectation. So how can we have an honest assessment of this? It boils down to three stages.
Set expectations based on past results. What are the experiences of people who have undergone the same weight-loss campaign? What did their progress look like along the way?
Collect live data at regular intervals. Measure your weight at regular intervals or significant milestones as you go through the weight-loss journey.
Compare against past results. At each regular interval or milestone, check that your progress is not too far from the past results attained by people with similar profiles as you.
Let's now use the AQ Multi-Strategy Model Portfolio to illustrate how the same three stages can be applied to monitoring and assessing investment performance. You can refer to our latest May update here.
Set Expectations Based On Past Results
For discretionary investors, this stage is not so straightforward because there is no clear past result to refer to. No two discretionary investors are alike, so looking at other past discretionary investors is not helpful. The best is to look at your own past results and set a realistic expected performance target. Quantitative investors have a distinct advantage here because they just need to look at the past performance of their quantitative models. Below is the past performance of the AQ Multi-Strategy Model up to the end of May 2023.
Based on the above, a realistic compound annual growth rate of 12.5% can be expected. A long-term Sharpe ratio of 1.3 can also be used as a target. Finally, peak-to-trough losses should not exceed 15%, after allowing for some buffer from the maximum drawdown of about 11% ever experienced by the model.
Collect Live Data At Regular Intervals
To know how your investment portfolio is doing, you need to collect performance data regularly. The interval depends on the granularity you wish to observe. You can collect monthly data, but that means you will not know what happens intra-month. To do that, you need daily data. This can be onerous but all you need is the daily return data which is something your broker should be able to provide.
If you are running a quantitative strategy and you know that your trades follow closely to the model, you can rely on the daily return of the model as a proxy for live performance. You just need to make sure that the monthly return of the portfolio does not deviate much from the model.
With the daily return data, we can calculate some performance statistics like compound annual growth rate, Sharpe ratio, and maximum drawdown.
Compare Against Past Results
This is the interesting part where you figure out whether your investment strategy is still delivering what it delivered in the past. We have already set realistic performance expectations in Stage 1 above. All that's left is to create effective charts to see how the performance metrics match up to expectations across time. We do not expect the performance metrics to match expectations all the time but it should not deviate too much as well. Let's look at each metric in turn.
Compound Annual Growth Rate (CAGR)
Imagine a dream investment that grows at a fixed rate of 12.5% CAGR every day. This will result in a smooth upward sloping NAV chart. If we superimpose our portfolio NAV chart with this line, sometimes it will be above and sometimes it will be below this smooth line. The chart above is showing the deviation between the portfolio NAV and the smooth line over time. The horizontal orange line that cuts the y-axis at 1 represents the portfolio NAV giving 12.5% at all times. When the blue line is above in the green zone, it means the portfolio is doing better than 12.5% CAGR. When it is below in the red zone, it is giving less than 12.5% CAGR. The blue line is expected to fluctuate around the orange line but a stable portfolio should stay close to the orange line. As of the end of May 2023, the portfolio is close to the 12.5% CAGR target.
We know the Sharpe ratio of the strategy is 1.30 over the entire model history. However, in any given 1 year period, the Sharpe ratio over that period can be rather different. This is mainly due to the variation in return over any 1 year. Some years can even be losing years which gives rise to a negative Sharpe ratio. So if we plot a rolling 1-year Sharpe ratio over time, we can expect the chart to look something like the one above. The blue line should fluctuate around the horizontal orange line which is the long-term Sharpe ratio. Again, a stable portfolio should have a blue line that finds itself constantly mean-reverting towards the orange line. If the blue line keeps deviating to the downside, it might indicate that the strategy has lost its edge. You can also use a longer window period, for example, 5 years, to calculate the rolling Sharpe ratio which should give a more stable blue line but the same principle applies.
Last but not least, we have a drawdown chart that shows the peak-to-trough losses of the portfolio. This is straightforward. If the portfolio has never experienced a drawdown greater than 11% in the past, then we should not expect it to exceed that in the future as well. However, we do want to cater for possible market conditions that the model has not experienced before. So we add a discretionary buffer to the historical maximum drawdown to make it 15%. This is what we call the hard-stop level where once breached, hard risk management measures must be put into place. Depending on the qualitative assessment, it means full liquidation into cash or at the minimum, 50% risk to be taken off. Thankfully, as it stands now, the AQ Multi-Strategy Model is far from the hard-stop level.
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