In logic, some conditions are defined as “necessary but insufficient”. When it comes to business, one such condition is immersion. People who launch start-ups have to be on the job 24x7x365. That passion and commitment is common to all successful CEO-promoters. Without it, qualities such as high IQ, competence, knowledge, and so on will generally not be enough.
Very successful entrepreneurs retain that focus. Nine of the 10 richest persons in the world - Carlos Slim, Bill Gates, Mukesh Ambani, Lakshmi Mittal, Larry Ellison, Bernard Arnault, Elke Batista, Amancio Ortega and Karl Albrecht - have their fortunes completely tied to the businesses they run. If their respective businesses failed, about 90 per cent of their personal net worth would be wiped out.
The exception in the top 10 list is Warren Buffett, who is the only professional investor. But even Buffett prefers concentrated bets in a few businesses in a few specific industries. He is not a widely-diversified investor.
Does this mean that the theory of diversification is wrong? Well, there is an overwhelming selection bias above - we are only examining the lives of the successful and ignoring the lives of failures. It's possible, even likely, that for each success story, there are hundreds or thousands of counter-examples of people who failed despite having similar levels of focus.
Absolute focus carries the risk of absolute failure. If you don't have the required risk appetite, or you reckon that the odds don't favour you, diversification is the way to create a safety net. Another point is more subtle but important. It is one thing to be absolutely committed to a business that you run. It is another thing altogether to be emotionally invested in businesses run by other people.
This happens quite frequently when an investor falls in love with a stock. It is especially common with a certain kind of fundamental investor, who studies a business deeply and believes that he understands it really well. So, he invests.
But the share price drops and continues to drop. Even as he suffers capital losses, such an investor refuses to consider the possibility of a mistake in analysis. So he hangs on to the stock, maybe even increases his exposure, and suffers even more losses.
Why do experienced investors display this irrationality? After all, anybody who has been in the stock market for a while is aware that mistakes in judgement are inevitable. Sometimes the investor will overlook a key factor. Sometimes the market behaves irrationally and drives the share price of a good business down. The problem is that the stock market can remain irrational for longer than any given person can stay solvent.
There is a point beyond which it is silly to remain invested in a given stock if that is the major cause of deteriorating portfolio performance. Whether you use mechanical stop losses, or some other review system, if a stock is offering abnormally poor returns, consider getting rid of it.
Can this logic be extended to the broader stock market? That is, do investors fall in love with the stock market and stay invested through long bearish phases, where they suffer capital losses? Undoubtedly this happens.
But the logic in favour of staying invested when the entire market is bearish is much stronger. Individual businesses can go bankrupt at any given time. But stock markets as a whole tend to eventually recover (though they can stay depressed for long periods).
In the Indian context, there seem to be optimum periods for buy-and-hold investors in the broad stock market. Using a “rolling return” calculation for a passive Nifty investor (and neglecting dividend yields), we see that the highest returns seem to come in the timeframe of five to seven years.
Since 1990, if we take rolling returns over 1, 2, 3, 5, 7 and 10 years respectively, the respective compounded average returns are 11.6 per cent, 10.3 per cent, 10.7 per cent, 12.7 per cent, 12.3 per cent, and 10.8 per cent.
In shorter time frames, the risks are higher. On that ascending time-scale of 1, 2, 3, 5, 7, and 10 years, the percentage of losing returns is (all figures in per cent) 41, 41, 26, 14, 9, and 4 respectively. Clearly the chances of a loss drop as the time frame increases. In terms of standard deviation, volatility also drops. On that same ascending timescale, the standard deviation is (all figures in per cent) 34, 14, 17, 14, 12, 9 respectively.
The statistics validate a commitment to buy and hold over the long term since the risk-adjusted returns rise. But it only works when holding a widely-diversified portfolio. In the case of single stocks, this sort of commitment can be a recipe for potential disaster.