My Road of Trials

In this chapter, Ray details how he resurrected from his failure.  In the last chapter, we saw that some of the estimation errors led Ray, loose his clients, employees and eventually  his firm (Bridgewater) was on the verge of closure. Now it was his determination that led to the success of the firm in its second term. 

In the second term, Ray was not left with enough money, however, still he understood the importance of data (computers) and hence kept investing on research. It was only a matter of time when his upswings were higher than downswings. Getting insights from computers through algorithms was not a straight forward one day task. It  improved slowly over a period of time. Ray had a habit of doing research side by side with the computer and then tallying the final result as to how to allocate the portfolio. Majority of the time, as Ray quotes, it was the computer which gave him better insights, however, it also happened that Ray (or team) had some more criteria which gave better insights than the computer. These in turn are systematized in order to make the algorithm better.

Ray had tested his algo across markets going back in centuries. This gave him an understanding of how the economic machinery works. The system was made so efficient that they had to override the system’s decision just 2% of the time. These as well, were times that were unprecedented like the 9/11.

In this chapter, Ray introduced us to two important terms, Alpha and Beta which are used vividly in the investment field. Beta is the sensitivity of the stock to the market. For example, suppose the beta of Reliance Industries is 2x, it means that if Sensex (the market) goes up by 100 points, Reliance should go up by 200 points. The same is the rule on the downside as well. The lower the beta, the lower the volatility (risk) of the stock.

Alpha is the difference between the market (Sensex) and the return of the stock (Reliance). So, if Sensex has given a return of 10% in a period of one-year, and Reliance has given a return of 15% over the same period, it is said to have generated positive alpha of 5% and the stock (Reliance) has outperformed the market (Sensex). Alpha can be negative if the stock underperforms the market.

Now, the focus of the chapter shifts to how Ray established his name in the hedge fund industry. One of his early clients, Alan Bond, was a famous entrepreneur, who bought an asset in Australia by taking a loan in the US in US Dollar currency. This was done because the US had a lower interest rate than Australia during that time. Ray advised them. In the case of Alan Bond, he carried the risk of US Dollar appreciating against Australian Dollar. Hence in order to hedge themselves, they needed to buy US Dollars. The strategy was explained to them by Ray, however, as hedging activity involves cost, Bond did not go for it and suffered huge losses.

Now, Ray was doing interest rate and currency trading and also consulting businesses in order to manage currency and interest rate risk. This was going well, but Ray did not stop at this. He was able to garner $5million from the World Bank’s pension fund and henceforth made a killing in managing that and growing to $180million in a matter of 10 years.

The trading strategies used by Ray proved to be successful even during the Black Monday on October 19, 1987, the day when the stock market declined 20%+. That same month, Ray’s fund was up by 22%. This got him a lot of coverage and they were being called, “Heroes of October” by the financial press.

However, this success did not let him forget the basics of investing. He was still cognizant of the fact that no matter how confident he was of a particular trade, it could still be wrong and hence proper diversification was a must. His study of diversification discovered that with fifteen to twenty good uncorrelated return streams, he could reduce the portfolio risk materially. He called it the “Holy Grail of Investing”. Look at the chart to see how increasing the number of uncorrelated assets to 20 provides the highest return to risk ratio and reduces the probability of losing money.