Selecting equities out of the Stoxx Europe 600 universe based on the finebalance® F1 factor leads to outperformance in 86% of all yearly periods between 1993 and now. So, the outperformance of the F1 strategy is highly persistent. The yearly cumulative excess return is 9,28% and alpha is 12,06% on a yearly basis. Alpha is highly significant with a t-stat of 6,23 for a 95% confidence interval. With such a high t-stat, there’s no reason to doubt the significance of the F1 factor.
finebalance® F1 Market Hedged
Yearly cumulative excess return 9,04%. Alpha 15,66% (t-stat 6,72, 95% confidence interval). Beta 11,77%.
Yearly cumulative excess return 6,97%. Alpha 8,58% (t-stat 3,08, 95% confidence interval). Beta 73,94%.
finebalance® F2 Market Hedged
Yearly cumulative excess return 7,70%. Alpha 12,92% (t-stat 4,22, 95% confidence interval). Beta 26,31%.
Yearly cumulative excess return 12,17%. Alpha 14,80% (t-stat 2,63, 95% confidence interval). Beta 98,15%.
finebalance® F3 Constrained
Yearly cumulative excess return 15,50%. Alpha 15,21% (t-stat 2,70, 95% confidence interval). Beta 98,50%.
Predicting future (out)performance
Unfortunately, there’s no one who can predict the future. So what can we do? The only thing we can do is learn from the past, applying investment methods that have shown the best performance over long periods up to date. True, historical performance is no guarantee for the future. But what is more logical? To invest applying robust strategies with proven and persistent outperformance or to apply strategies that are lacking in performance, persistence and/or robustness? Of course it’s the former. That’s why finebalance analyses known strategies and develops new strategies so we can select the strategies that give the best chances for long term investment growth.
Market efficiency and outperformance
Of course you’ve heard of the Nobel prize winning idea called ‘market efficiency hypothesis’ taking the position market prizes reflect the value of investments efficiently. The implication of this idea is that if market prizes are correct, there’s no way of outperforming the market. Although the extent wherein the market is or is not efficient remains open to academic discussion, it is scientifically irrefutable there are not many investment strategies that have significantly outperformed the market on the long term. For sure, most strategies haven’t.
To a trained eye, graphics can tell a lot about a strategy. That’s why finebalance shows you a graph of the simulated NAV (Nett Asset Value) development for every strategy shown.
True professionals will never select a strategy without applying sound statistical methods. To help you select the best strategies in a professional way, finebalance states excess returns, alpha’s and the according level of statistical significance for all the strategies shown. finebalance is aware there are many more measures applicable. Please notify us if you’re interested in additional measures. We have them ready for you.
An ‘at first glance’ measure of outperformance is ‘excess return’. Excess return is the difference of the cumulative return of a strategy minus the cumulative return for the applicable benchmark for a given period. Because short calculating periods suffer highly from statistical noise, making test results highly prone to luck or coincidence, only testing strategies over sufficiently long periods will do. In science, testing is typically done over decennia instead of years, months, weeks or days. finebalance® strategies are tested for a period of almost 30 years. And finebalance keeps testing..
Analysing two sets of contemporaneous return data, alpha states the cumulative strategy return independent of market risk. In other words, it shows us the strategy return attained without bearing market risk. Since market risk is the biggest source of investment risk, alpha is the single most important measure of outperformance. Again, if the testing period is long enough.
Together with alpha it’s normal to state the level of statistical significance of the found alpha. If significance is low, alpha is not dependable and vice versa. In other words, if significance is low, chances are the found alpha is due to coincidence.
The scientific literature has shown time and time again that many strategies that seem to beat the market before calculating investment costs, won’t be able to do the same after calculating investment costs. Of course, it’s also painful for us to see a nice idea translated in a logical strategy showing high outperformance before costs missing the real world test after applying investment costs. However, only strategies with outperformance after calculating costs will do. Therefore, all strategies shown present investment returns after calculating investment costs.