|Chennai||Rs. 25020.00 (0.81%)|
|Mumbai||Rs. 25890.00 (0.98%)|
|Delhi||Rs. 25200.00 (-0.2%)|
|Kolkata||Rs. 25480.00 (1.03%)|
|Kerala||Rs. 24800.00 (0.61%)|
|Bangalore||Rs. 25000.00 (0.81%)|
|Hyderabad||Rs. 25080.00 (1.09%)|
In any given year, in any given market, some investors will beat the benchmark index by a large margin. Others will under-perform. How much of this performance difference is due to luck, rather than skill?
Quite a lot could be due to luck. Even if two investors use very similar methods of analysis, and buy and sell the same stocks, they could still have widely different results. This might happen even if they buy and sell the same stocks on the same day.
To take a theoretical example, a stock might swing in price between a low of 99 and a high of 101 on a given day, when two investors buy it. One buys it at 99, the other buys at 101.
A month later, the share has gone up and they both book profits. They sell on a day when the stock swings between 119 and 121. The investor who bought at 99 sells at 121, while the investor who bought at 101 sells at 119. The same trades on the same day lead to a difference of over five per cent in absolute returns.
Nobody can guarantee the "best price" in a given trade and the price movements cited above are not extraordinary. Thousands of investors trade lakhs of shares in every liquid counter at each price-point on any given day. Simply due to the large number of players and volumes, some investors who make similar trades will register large return differentials.
When one looks at active mutual funds with similar mandates and similar portfolios, this random luck factor could well account for what seems to be large differences in returns. Say, two funds are benchmarked to the same index and both managers use similar methods to build portfolios. They may hold very similar portfolios.
However, one fund might generate considerably higher returns in a given period. The winning manager is entitled to claim superior insight. But he might have been plain lucky compared to the other manager because they made the same decisions. In the next time-period, the luck might change.
Smart traders back-test their methods to develop optimal parameters but luck is a difficult variable to isolate. For example, a trader might want to use a moving average-based system to generate buy and sell signals. He can back-test using historical data to compare results from various moving average time-periods. But how does he account for possible luck factors when judging the results?
It's often difficult to tell if an investment system or trading method has just been very lucky or really provides excess returns across different types of markets. If the sample size of historical data is large, it is also likely to be more representative and there is more chance the luck will even out.
But given the sheer number of trades and market participants, some system could get lucky over a long period. The more statistically competent will use Monte Carlo simulations and run regressions, etc, but even after such efforts, it might not be possible to isolate the influence of luck.
My sense is that you have to assume a pretty large error factor in estimating the possible returns from any investment idea or any trading method. The error could be in your favour, of course, if you get lucky! But it's better to be conservative and assume you'll miss the best entry and exit points.
Most traders and investors don't realise the enormous role luck plays. In fact, most don't even think in these terms, and simply assume their methods are good when they get lucky.
Active long-term investors often have very little sense of the possible returns and many don't weigh the potential risks at all before they take a position. Traders are forced to be a little more aware of the risk-reward equation but most are too lazy to really run stress tests and discount the role of luck.