In 2013 Eugene Fama along with Robert Shiller and Lars Peter Hansen received the Nobel Memorial Prize in Economic Sciences for their work on the efficient-market hypothesis. Simply put it claims that nobody can outperform highly liquid markets because they are efficient, meaning any information available is already priced into the respective asset(s). So the price you see at any given moment is the fairest and best you can get, nobody can predict what happens next. Thus beating the market could only be done
a) with leveraging (including higher risks)
b) by randomness
c) by illegal practices like insider dealing and price rigging etc.
So there shouldn’t be any better strategy than “buy and hold”. However when considering overall oscillating prices as in the forex market even said method wouldn’t bring any profits in the long run. Regarding hedge funds this would mean that averaged over them long-ranging, we should see a very bad performance. And the latter would have to be dramatically poorer than the growth of the broad market because of said funds’ high fees. The HFRX Global Hedge Fund Index (also available as EFT) includes about 2000 legally regulated hedge funds. Here’s said index' performance:
It seems that Fama is not wrong. Of course there are hedge funds that have beaten the market for several years and some funds also performed even worse than the red line shown above. However this can simply be explained with the standard normal distribution:
In other words: If you have thousands of dicer, some of them may dice an average number of spots for a while that is bigger than the mathematical expectation (3.5), and some of them may dice an average number of spots for a while that is smaller than said expectation. The first type of dicer is the “super trader” then .
Well, is there any proof or at least circumstantial evidence that could counter said hypothesis? Let’s have a look at two of the most recognized and successful investors of all time that have proven track records over decades (to minimize the danger of randomness) – Ray Dalio and Warren Buffett:
1.) Ray Dalio’s performance of “Pure Alpha” (Bridgewater Fund) from 11/1/1991 to 3/1/2015 vs S&P500:
What we can see is that Ray didn’t beat the index but had a significantly better performance in terms of reward to risk over many years. That’s actually great however doesn’t really contradict the efficient-market hypothesis respectively Fama.
2.) Warren Buffett’s performance of “Berkshire Hathaway” (stock) from 1964 to 2017 vs S&P500:
Ok, there can’t be any doubt that Warren outperformed the index over decades. However when looking especially at the last 10 years we see something different:
Warren’s company Berkshire Hathaway meanwhile has big problems to outperform the index. But the explanation is simple: If you own the whole world, you can’t grow faster than it. Sure, there is still a lot to be purchased on earth for Buffett but the bigger you get the harder it is to find enough small firms etc. with huge potential where you can put all your money into.
Conclusion so far: Even the best investors in the world have issues to disprove Fama’s awarded efficient-market hypothesis. But Warren Buffett showed that basically it seems to be possible to really beat the market not only by chance.
Now what does this mean for us DARWIN owners, what can we learn from Fama, Buffett and Dalio?
1.) Beating the market in the long run is extremely difficult, much more than most of us might think.
2.) Most performances that look great are based on coincidence (good dicer, see above). When choosing track records from millions of accounts by rankings on social media platforms etc. you mostly only find the surviving ones and will always discover a “super trader by chance” even if he/she is not cheating with grid or martingale strategies etc.
However the probability that said “filtered” trader or EA etc. really has an edge increases dramatically with every quarter he/she can sustain the profitability AFTER the “discovery” by you via rankings. This is a statistical issue / phenomenon and could be discussed separately.
3.) Whenever you develop a trading strategy you must ensure that it potentially has a very strong robustness, especially when considering that the market permanently changes. If you don’t know anything about
- in sample / out of sample backtest (BT)
- consideration of real variable spread, slippage, swaps and commission in BT
- profit factor, real relative drawdown
- Monte Carlo Simulation
- portfolio correlation
- avoidance of curve fitting within optimization processes
- circumventing BT distortion by compound interest effects
- leverage and asset weighted expectancies in Pips
- multi currency / timeframe backtesting in MT5
- high quality price data over minimum 10 years
- top of the book, depth of market, partial entries & exits
- etc. etc.
then go and learn all this stuff if you’re serious about trading. Otherwise you’ll waste your time and your investors’ money – that’s the bitter truth.
So do the best you can to develop trading systems that have a real chance to survive the next decades and you may be the next Warren Buffett :-)!