But how do I figure out which strategies to concentrate on?
Drawing from high-quality outside sources of other people´s previous experiences, gives my own ideas a solid foundation and often a healthy reality check.
Before implementing strategy rules with real money, I often backtest by hand going trade by trade. Although this low tech approach is cumbersome and it is hard to be exact, it has some distinct advantages: you can visualize the strategy unfolding and begin to get a feeling for the emotional rollercoaster of drawdowns and profits it brings with it. It boils down a selection of possible strategies to the most promising ones, as only those will be worthwhile testing like that. It keeps curve fitting in check, as it is not possible to run through countless variations of a strategy. And it is possible to do right away, without having to clear high technological hurdles first.
How to do that in practice?
Collect information on the long-term historical risk-adjusted return of different investment approaches: asset classes, return factors, trading strategies etc.. Radically narrow your investment universe to strategies that show favorable basic probabilities across long periods of time. These are opportunities with a natural edge – you can select the ones with the best historical results and combine them into a portfolio using additional criteria.
A purely discretionary approach won´t be able to generate these guidelines before we actually implement the strategy or at least paper-trade it.
Randomness and uncertainty are the major factor in investing and we always want to have basic probabilities on our side.
For me this has proven to be an extremely powerful filter, it has completely transformed my approach to investing and my success. I don´t aim to generate alpha (through unique sources of return), but instead concentrate on combining many diverse sources of beta (different market returns), including alternative beta (through well known return factors and trading strategies).
Statistically about 65% of stocks underperform their index. The best performing stocks in a broad index perform much better than the other stocks in the index. That means average index returns depend heavily on a relatively small set of winners. No wonder that studies keep telling us, that almost no active fund manager consistently outperforms his benchmark over time – not even speaking of non-professional individual investors: Your stock picking skills must be in the top 35% to even match index returns, therefore you are going against basic probabilities and are likely to underperform.
The statistic implies that using low cost index ETF to capture the market´s equity risk premium will be superior (with a probability of about 65%) to trying to pick the best stocks – that´s what I concentrate on.
With very specific expertise and skill value can be found in individual equities, but it is a very efficient environment as many of the most highly skilled market players compete here. It would make most sense to me, to concentrate on the most inefficient areas of the market (e.g. micro cap, deep value or emerging markets).
But more pronounced inefficiencies are likely to be found on the asset class level.
Most deviations from a market cap index, that have shown long-term outperformance, can be explained by different return factors (e.g. value, momentum etc.) and can be accessed through a wide range of securities targeted by ETF that screen for these specific factors.
This particular filter has the valuable advantage of blocking out a lot of the confusing media noise and to bypass an incredible amount of intricate information about individual companies which is unlikely to lead to outperformance – it allows us to concentrate on more useful ideas.
As I can´t answer any of these questions positively for myself, any short-term strategies, I look at, have to derive their edge from a basic risk premium or from consistent human behavior, that can be shown to have existed for decades and is likely to continue to do so. I want to see quantifiable rules and long term strategy statistics from different sources and those are hardest to find in the short term trading space – that in itself is a red flag.
We want to be where the money flows to.
But strategic, active investing has the potential to further tilt probabilities in our favor.
Overview of long-term positive risk premia, that can potentially be harvested:****
The data is averaged from different resources and these are rough numbers only – which is good, because the past can only provide an uncertain approximation of what the future may bring: