It is important to write down clear goals about what I expect from my investments and the different outcomes that are possible. This will help me to stay the course during rough times.
This will always be just a general estimate as it´s impossible to know what the future will bring. I try to look at the problem from different angles to get a feel for what might happen in my portfolio and from that I generate practical rules to achieve a high rate of capital growth while keeping downside risks in check.
I concentrate a lot of my efforts in portfolio management in determining the right level of leverage for my risk / return goals in prevailing market conditions as I think a lot of value can be found in this area – especially in combination with the diversification benefits of asset allocation and strategy selection.
The Outside View
Rather than trying to calculate expected risk and return from all the individual portfolio elements and their correlation, I like to take the opposite approach first and take the outside view, looking at the examples of other investors and market studies to find a realistic benchmark. From that I estimate what results my approach might bring. I try to analyze my own risk tolerance visualizing my past investing experiences, especially the large drawdowns. I then build in a margin of error to be more realistic and decide on my portfolio exposure from there.
I concentrate on the Sharpe ratio as a measure of risk-adjusted return even though it has some limitations. It is the most widely used measure, which allows comparison of a variety of different studies to each other. Absolute return numbers alone are quite useless, as they don´t give any indication of the risk taken to achieve them.
The Sharpe ratio is the excess return (above the risk free rate) divided by the volatility of returns (as a proxy for risk).
As a rule of thumb the higher the ratio is, the better. For example a Sharpe ratio of 1 implies excess return and volatility of the same magnitude; e.g. 10% excess return with a standard deviation of 10%. You should expect maximum drawdowns between 2 and 3 times your annual return, depending on the skew of your return distribution, with a Sharpe ratio of 1 at some point in the future.
Long term US equity returns have been about 10% (excess returns about 6%) with a standard deviation of 19% and a Sharpe ratio of 0,32. Drawdowns of -40% to -50% have happened quite frequently, but have reached more than -80% at a maximum.
When looking at the risk-adjusted returns of different asset classes over a long period of time their Sharpe ratios cluster around 0,3 – they all basically have the same risk-adjusted return expectation over time.
Financial markets are fairly risk efficient overall, because investors constantly seek to find pockets of excess return for a given level of risk and thereby bring it back down to a common mean.
The Sharpe ratio has two major drawbacks to be aware of: It treats upside and downside deviation the same way and it uses the return´s standard deviation, implying an independent, normal distribution of returns, which ignores the reality of negatively skewed, correlated returns with abnormaly fat tails (large extreme returns, especially losses). This is the reason why long term equity returns have had higher volatility and larger drawdowns than the standard deviation might lead us to expect. Negative skew causes the Sharpe ratio to overestimate the risk-adjusted return – this, for example, is visible in short options strategies, which tend to have overestimated Sharpe ratios.
Sharpe ratios fluctuate a lot over time. US large cap stocks have had Sharpe ratios per decade ranging from -0,08 (the 1970s) to 1,4 (the 1950s). That means the historical Sharpe ratio of strategies will show great variation depending on the backtested time frame.
For realistic estimates the historical time frame should be across whole market cycles including several good and bad times, for example 1990-2010. Including data from the Great Depression will give a good worst case scenario of the possible magnitude of losses.
The upper ceiling of possible returns
Looking at the all time best investors, one has to be aware that they are absolute outliers and simply define an upper ceiling of returns that are possible at all. This gives a reality check when encountering return claims that are way above that. If that were consistently possible, compounding would lead to the investor owning the entire world´s assets after some decades. As it is super investors already own a fair chunk of it.*
- Star investors like Warren Buffet, George Soros, Paul Icahn and others have managed to earn 20% – 30% yearly returns over a span of decades boasting Sharpe ratios between 0,7 and 1. This implies a very high risk tolerance, as drawdowns frequently top -50% for such return distributions.
- The best long term hedge fund returns I came across are James Simons´s Renaissance Technology´s Medallion fund at 35% annual return over decades and Edward Thorp´s Princeton Newport Partners averaging 20% annually with a minute 6% standard deviation and an incredible Sharpe Ratio of 2,33 (the highest I ever came across spanning decades) – this was achieved using leverage around 8 times in a completely hedged statistical arbitrage portfolio.
- A very interesting example of concentrated value investing during very bad times is John Maynard Keynes investment management of the Chest Fund, King’s College, Cambridge, during the great depression, 1927-1945. Beating the market considerably, he made 9% per year with a Sharpe ratio of 0,4.
The realistic average of the market including timing and strategies
- The classic portfolio mix of 60/40 stocks and bonds historically had an annual return of 8,5% and a Sharpe ratio of 0,4-0,5.
- Different buy and hold Global Asset Allocation methodologies including smart beta factors had 9,5% to 12% annual return and historical Sharpe ratios around 0,8. The return dispersion of different allocations over long time frames has been astonishingly small.
- Global Asset Allocation including market timing (moving average trend following) boosts Sharpe ratios to 1-1,1 by reducing drawdowns.
- Trend-following Managed Futures strategies have achieved long-term Sharpe ratios between 0,6 and 1 and are able to target specific volatility levels very well.
- Historical Sharpe ratios for Volatility Selling vary more widely because strategies differ considerably. Examples are PUT index 0,7; S&P systematic strangle portfolio 1,53 or Vix strategies 0,85 – 1,3 (biased towards overestimation because of negative skew).
- A reality check back with the actual historical return of professional money managers shows that a Sharpe ratio of 1 has been a long term ceiling for virtually all of them.
If the future rhymes with the past, judging from these outside sources, combining different strategies could land a portfolio´s long-term Sharpe ratio at 0,7 – 1 at a maximum. That is the goal I set for my portfolio.
Adding up the historical returns of the different strategies I use and accounting for correlation benefits, I actually arrive at a 1-1,5 Sharpe ratio. There seems to be a reduction in portfolio performance, when moving from theory to practice. Maybe in general, Sharpe ratios in backtests are better than Sharpe ratios measured on actual returns, because we are seeing the effect of costs, fees and taxes? In practice mistakes in execution or simply ignoring well established rules cause a strong drag on returns. I will definitely keep a close eye on the distribution of actual returns that my portfolio generates in real time and adjust my strategies accordingly.
An intriguing opposing position is that, during a shareholders meeting in 1999, Warren Buffett lamented that he could generate 50% average annual returns, if only he had less money to invest. Maybe with a smaller portfolio we can more easily generate relatively high returns?
Setting benchmark expectations
Averaging statistics from a wide range of studies, historically a fully invested diversified portfolio (mixing the strategies above) would have returned between 11% to 15% annually with a standard deviation between 8% and 12% depending on weighting and exact rules. The Sharpe ratio historically had a fairly stable value around 1, as higher returns coincide with higher volatility. The maximum drawdown since 1973 was approximately -20% to -25%. The reality check above leads me to pull these estimates down a bit and anticipate higher volatility and drawdowns.
Let´s set a basic benchmark and expect 10% annual return with 12% volatility (a Sharpe ratio of 0,8) for our unleveraged portfolio of global asset classes and strategies. Current 10-year estimates from virtually all market experts are quite a bit lower than historic averages for the major asset classes, due to the high valuation of stocks and bonds. To realize our benchmark going forward, we may have to rely heavily on global diversification, real assets and alternative strategies, looking very different from a traditional 60/40 portfolio.
As option selling strategies and futures allow the efficient use of low-cost leverage for individual investors in a margin account, I look at optimizing the benchmark exposure for my personal goals and risk tolerance. This is a very personal process and it would not be a good idea to simply copy it.
To me the portfolio statistics feel very benign, I have seen a -25% to -30% drawdown in my portfolio many times and I wouldn’t mind it to be higher, provided this leads to better overall returns. To someone else that may feel quite different – it is easy to simply invest a fraction of the available capital in such a portfolio to target a fraction of the risk and average return.
My goal is to build my investment portfolio to be a primary source of my current income as well as a growing retirement account.
As I am self-employed and run my own business, I don´t depend on the investment income and – in contrast to someone in a full-time job – am very flexible in scaling my business activities up or down to fit my financial needs and the time demands of doing investment research. Although I have a long time until retirement, I would be quite interested in increasing my financial independence in the near future.
As I currently am in a phase where I aim primarily at growing my wealth, I think targeting a high level of risk is justified. Later on in my investing career, when wealth preservation becomes my focus, I will dial down the risk.
Being comfortable with a higher level of risk than the portfolio statistics suggest (always adding a margin of safety in case the future turns out to be very different from the past), my next question is: What would my optimal leveraged exposure be, to reach my financial goals as soon as possible while minimizing risk of ruin?
The Kelly Criterion
There is a method to calculate the level of portfolio leverage, that will lead to the highest equity growth over time while avoiding ruin (assuming the portfolio statistics accurately describe the future) called the Kelly Criterion.** Using the annual excess return and its standard deviation (careful – a normal distribution of return is assumed), Kelly´s formula calculates the optimal amount of leverage to use for the highest compound growth of our portfolio over time. Investing at full Kelly leverage will result in an extremely geared up and volatile portfolio. Drawdowns of more than -90% can easily happen (a drawdown has a 10% chance to reach -90% and a 50% chance to reach -50% using full Kelly). That is not suitable for real life investing with all its uncertainties.
But using a fraction of Kelly leverage reduces volatility dramatically, returns less so and it becomes a powerful tool.
My rule of thumb is to use conservative estimates of my portfolio statistics and then employ roughly one quarter Kelly leverage.
Running the benchmark numbers from above leads to a quarter Kelly leverage of 1,75x times available investment capital (incidentally this is just about the level of leverage Warren Buffett used to build his fortune according to several studies).
To leverage the portfolio in practice, we could allocate all available capital to global asset classes via ETF. We could then sell options using a systematically diversified strategy, until the exposure to the underlying ETF adds up to the portfolio´s short volatility allocation, capping overall exposure at the desired portfolio leverage. With more strategies added (eg. trend-following managed futures) the process gets trickier and close supervision in real time is required.
We can use 1,75x as our average portfolio leverage and take the current market environment into account. Return and volatility look drastically different across market regimes and a time-varying level of leverage applied through our adaptive portfolio allocation concept is the best answer to that variance. In good times (when the actual Sharpe ratios are above average), I apply up to 3,4 times leverage – which equals half Kelly exposure for our benchmark portfolio. When the market heats up (volatility is on the rise and fundamentals point to strong overvaluation) I reduce leverage to 1,75x – 1x and finally go to a large proportion of cash in bad times. On average this should cause the portfolio to be leveraged at the right time, reducing the risk of overbetting and large drawdowns in adverse conditions.
The main problem could be a flash crash or 1987 type of event, when higher drawdowns are to be expected. The leverage should still prove to be low enough to avoid ruin – the margin of error until we reach full Kelly leverage (about 7 times) is high enough.
This levered portfolio could yield 17% to 22% annually with 15% to 25% volatility and I expect to experience drawdowns around -30% to -50%. These are much better prospects than a pure equity portfolio, which experiences similar drawdowns with much lower return expectations. Compounded over time this would definitely make you financially independent no matter where you start. Your money would double roughly every four to five years (divide 72 by the annual return to estimate the years it takes to double your capital).
I would consider this a highly aggressive risk level – it will definitely feel very uncomfortable at times.
Using optimal Kelly leverage, the exposure level still has some room to be pushed without suicidal overbetting, if you don´t mind an extreme rollercoaster ride. This could be done on a small speculative portion of one´s wealth – e.g. a barbell approach of combining a very conservative and a very risky portfolio.
Aggressive risk taking could also be justified, when the invested amount of capital is quite small and the savings rate to grow that capital is comparatively high. This would often be the case in the beginning of an investment career.
I would counsel against taking such high risks, because the level of skill and experience required to successfully run a combination of strategies is very easily underestimated. At the beginning active investing is much more likely to lead to reduced performance compared to market averages.
I don´t think I´m straying into fantasy land with these expectations, as there are many real life examples that boast a similar Sharpe ratio. Most of the time these yield an average annual return between 10% and 15% like our unleveraged portfolio benchmark, which is a much more tolerable approach with lower volatility and smaller drawdowns than traditional portfolios would experience.
On the other hand higher return numbers than the framework above, imply very high risk taking (likely drawdowns are far beyond -60% there might even be a high probability to reach -100% and blow-up your account), or the presence of serious alpha which is exceedingly rare and could not be systematized for very long as the superior returns would soon be arbitraged away by the competition.
Analyzing the robustness of our investment approach – will it likely hold up in the future?
All strategies in the portfolio should have a positive return expectation over a very wide range of variations (the wider the better) for parameters, time frames and asset classes.
For example momentum and trend strategies work over virtually all asset classes with lookback periods ranging between 2 and 15 months.
For a value strategy you can employ any of dozens of value metrics successfully.
Volatility strategies, even though they target a narrower field, work with all kinds of different instruments and different signals to produce positive returns.
I use strategy parameters that fall in the middle of the range that has worked historically and do not optimize these parameters – I put my trust in the strength of the underlying concept. Optimization would lead to curve fitting and future underperformance as your parameter set will most likely regress back to the mean performance of all parameters. It is also possible to diversify across different parameters – e.g. strategies implemented across different time frames often behave quite differently.
Simplicity (few inputs and parameters) equals robustness and enhances consistency and trust in our portfolio. Future performance of simple strategies is more likely to be similar to the past than with complex strategies with lots of moving parts – higher degrees of freedom will make a strategy more fragile.
Focusing on building a solid investment process is more important than looking too closely at return numbers – Good outcomes follow good process.<
*an article on common sense return limitations is “MISSION IMPOSSIBLE: BEATING THE MARKET OVER LONG PERIODS OF TIME“ by Alpha Architects
**„Fortune´s formula“ by William Poundstone goes deep into the subject of bet sizing.
continue with part 8: Avoiding mistakes