6 Adaptive portfolio allocation

As we have already moved well into the realm of active investing, we might as well tackle the next big no-no in the world of finance: market timing. Many studies claim it doesn’t work, but in recent years more studies have appeared suggesting that it might work after all.* A commonly used argument against market timing is, that missing the 10 best days in the market will drastically reduce returns. It usually fails to analyze the distribution of the best and worst days – an overwhelming majority of both the best and the worst days are clustered in a high volatility environment, when the market is already down. Missing both the best and worst days will actually boost your risk-adjusted returns considerably, if it can be achieved.
In practice market timing is used in many forms – from technical indicators to the use of valuations or other fundamentals to shift the allocation between different assets. There are even some robo- advisors, that integrate a tactical allocation to protect the downside.
Maybe a good question to ask is: how can market timing be useful to my portfolio and my consistency in managing it?


Reducing downside extremes may offer the best chance to achieve less volatility and lower drawdowns. This is my main focus: loss avoidance to beat the market in bad years and reduce the drawdowns of individual strategies. Reduction in volatility is very valuable, even if the overall return stays the same – returns can always be adjusted through leverage. It will make it easier to stay the course during bad times – which is incredibly hard to do when facing drawdowns of -40%, -50% or more. Be aware, that your risk tolerance will change with the size of drawdowns. At new equity highs risk appetite seems unlimited, with growing drawdowns risk tolerance shrinks rapidly, causing investors to throw in the towel.


Let´s try to build a roadmap that tells us: “When the world looks like this, do that.”
It should allow us to allocate to strategies, factors and asset classes tactically by adapting exposure to different market conditions.
We want to utilize our strategies to their full potential in a favorable market environment and batten down the hatches when storm clouds appear and the wind starts blowing.


There are two basic methods available for use: technical and fundamental indicators.
I use a mix of both.
Fundamental data hints at which point in a market cycle we are in. It works well to build a long term expectation of the future size of different risk premia, but not so well to identify the actual turning points in the market. Markets can stay in a fundamentally extreme state for a long time before reverting to the mean.
Technical indicators, on the other hand, work well to tell us which state the market is in at the moment, without making a prognosis about the future. We simply assume it stays in its present state, e.g. up- or down-trending, – hopefully for a profitable amount of time – until the next inflection point, after which we get an indication of the new state the market is in.
Fundamental data allows us to be prepared for what might happen (I don´t think prognosticating the future shows much promise), while technical indicators provide the timing, by showing that the market has changed its regime.


Different market regimes have certain properties that suit different strategies, or, more importantly, are unsuited to being invested in the market at all. To me the key states markets can be in are: going up, sideways or going down and being calm or being volatile.
Fundamental indications of which area of the market might be changing at some point in the future are valuation, economic development and investor sentiment.


For a birds-eye overview of the fundamental state of the market cycle useful ideas are:
  • Cape ratio for valuation: high or low compared to historic averages
  • Yield as another valuation measurement, especially useful for bonds
  • rising or falling GDP and earnings growth
  • Lending activity: easy or tight credit
  • Investor sentiment: excessive optimism or pessimism in extrapolating recent returns into the future works as a contra indicator, trusting that regression to the mean will happen eventually
  • Increasing strategy popularity leads to momentum then to overcrowding
  • Overcrowding (or ignorance) of ideas and market areas: no one is left to buy (or sell)
  • Inflation and interest rates
These indicators can be used to shift exposure from expensive and loved areas in the market towards cheap and hated and to scale overall leverage up or down. But mainly they create an awareness of what is going on, which leads to being prepared to act when change actually starts to happen. The market can get even more expensive or cheap for an extended period of time, which will cause unnecessary losses or missed opportunities, if one acts to early. It´s better to be a little late to the party (or the exit) and to wait for confirmation through very simple technical indicators before changing strategies more radically.


The basic technical measurements are price and volatility:
  • The simplest and most effective measurement of the up or down state of a market is whether price trades above or below its long term moving average. I prefer to shift away from the very commonly used 200 day moving average a little bit to avoid the crowd. For evaluating the allocation of equities overall I use the world market ETF VT.
  • Rules for asset classes, countries, sectors and factors are very simple: Reduce to a basic allocation (which may be 0 or some fraction that you are prepared to hold through a prolonged downturn) when the ETF trades below the moving average. Go back to your defined allocation when the ETF trades above the moving average. When you are out of several market areas you have to think about whether to stay in cash or to shift allocations to strategies that are still performing well.
  • You can apply the same concept to the equity curve or real time performance measures of individual strategies.
  • The moving average acts as a trailing stop loss, but for some volatile strategies it makes sense to define a maximum loss through a set percentage stop loss. Large gaps or sudden crashes, similar to the October 1987 crash, can possibly lead to much larger losses than your stops suggest.
  • When assets have been down more than three years in a row, regression to the mean is likely to kick in in the near future.
  • To measure, when the market changes volatility regimes, gets more complex, but it yields some valuable information – indispensable when actually trading volatility: the key data comes from VIX levels and the VIX Futures Term Structure – research in this area has provided me with a lot of valuable insights. For example the propensity of volatility to cluster, implying that market regimes tend to stick around for a while before changing again. I use this indicator mainly to determine whether to trade volatility strategies or put them on hold, but combined with price indications it adds additional depth. The market falling below its long term moving average, while the VIX Term Structure inverts is a doubly strong warning sign.
  • Rising volatility in a rising market is another good indication that trouble may lie ahead. It can be used to reduce exposure before prices actually turn. A good example is 2007 when volatility started to rise steadily from very low levels, while the market still looked very benign. Underneath the surface a lot of quantitative strategies suffered meltdowns long before the advent of the financial crisis.
A good rule of thumb is to drastically reduce exposure to a fraction of your capital and move to more cash, when volatility spikes and more and more ETF break their long term uptrend. A crisis occurs when unexpected events meet risky, levered structures and we want to avoid being part of that. Going into hibernation may be more effective than trying to trade the short side with bear market strategies. Try to lose as little as possible in volatile bad times by radically reducing exposure. Downturns are usually violent and short and provide great opportunities on the long side when they pass and you have preserved enough cash to be able to use these opportunities. It pays to be patient as the market spends about 75% of the time going up. This implies that going short goes against basic probability distributions (i.e. the equity risk premium) and therefore is a losing game on average, unless done with exceptional skill. I prefer to assume my skill is average and make that work – it is quite a high bar already.
Crank up exposure again in good times to achieve great returns and take great care not to compromise the ability to survive under adverse circumstances.


Adapting option strategies might be the best way to actively trade downturns of the market. The strategy of selling a portfolio of diversified index options could be implemented with a directional tilt: sell puts on index ETF above their moving average, sell calls on index ETF below their moving average, creating a weighted option strangle over different underlying securities. This tactic will overweight your short option exposure towards the direction the majority of markets has and change that weight gradually when markets break their trends at different times.
Higher volatility in downturns will cause option premiums to rise and give the portfolio good returns even when scaling down overall exposure considerably.
Long put hedging positions could also be filtered by moving average trends and increased as more opportunities appear, rather than putting them on in a rising market, when the right timing will be hard to accomplish.


Technical indications will flash when the market has already started turning – giving back some book profits by definition. The major drawback are whipsaws, when the market changes its state back and forth so quickly, that you are giving back more than the accumulated book profits each time, causing net losses. Keep in mind that the purpose of an adaptive allocation is to keep us out of the market when major downturns eventually materialize, as they inevitably do.


Lastly, a portfolio is not a fixed entity. Even if it adopts to market cycles, constant research and the development of new ideas are necessary to react to changes in the market environment and to improve your process. I monitor my live strategies´ real time performance statistics regularly, so that I have a chance to detect when something goes completely off the reservation. The adaptive allocation will help to avoid the worst and preserve the ability to restructure after things have gone haywire. A good concept is to probe for weaknesses and try to figure out what could be wrong in your process to make the whole construct more robust.


When you have defined an adaptive allocation framework write down its exact rules and resulting allocation sizes in your portfolio. Run some what-if scenarios as this can be quite complex.




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