It's not that trend following didn't work, it was that thier system stopped working. It was a breakout system, higher highs type of thing.
Most liked posts in thread: Why did trend following work well in commodities in 1970s but not as good later?
From what I've read:
1. High inflation in the 70's spurred big trends in commodities.
2.Nearly everyone who was around in the 70s says that the markets were easier to trade back then because professionals made up a far smaller % of those trading in the markets.
As its name suggests, trend following requires a trend to develop and continue for a sufficient period of time to identify it, invest in it, and then profit from it. Trend following works just as well now as it has done in the past, it's just that one needs to be looking across a sufficiently large opportunity-set to find those trends. A good example is gold stocks. Trend followers have made 4-5 times their money over the past 12 months by following the trend in gold stocks. But the key to success in trend-following is also having an investment model that identifies trends early in their trend-cycle, and then also identifies the end-point of the trend thus allowing the investor to exit the investment before giving back too much of their profit.
I believe trend following has three definitions. This short three-point section is an excerpt from my latest book "Foundations of Trading."
The phrase "trend following" is used in several contexts.
1. An entry technique. The pattern being recognized is that the price has been in a trend according to some trendiness indicator. A signal to enter a position is generated. The reason a trading system would use this entry is the expectation that the trend will continue. Test this as you would any indicator and rule.
2. A trading philosophy. Trend following is a euphemism for holding positions for a long time anticipating large gains. This falls into the category of conventional wisdom. The technique was very successful through the 1980s and early 90s. As the markets have become more efficient, the profit per time period has decreased and intra-trade risk increased. Pay careful attention to risk. Select a set of trades that you feel are representative and work through the risk / safe-f / CAR25 calculations.
3. Every trade. Every trade is a trend following trade for the period it is held. To be profitable, the sell price must be higher than the buy price -- a trend.
A little explanation of some of the terminology.
The section in the book quoted above comes after a discussion of trading system development, where the focus of the model is identifying patterns in the price and volume data that precede profitable trades, and generating buy and sell signals and associated trades when those patterns are detected.
The book describes a technique for analyzing the risk of trading through use of a Monte Carlo technique applied to the set of trades. At the start of the risk analysis, the trader states his or her personal risk tolerance. The risk of the trading system as represented by the set of trades is compared with the personal risk tolerance and position size adjusted (safe-f) to hold risk of drawdown to the trader's tolerance. When traded at safe-f, CAR25 is an estimate of the profit potential. I call the process risk-normalization. CAR25 is the most universal objective function I have found.
I highly recommend that every trading system be analyzed using this technique. Given two or more potential uses for funds -- say two trading systems, or a trading system and a bank account -- analyze both, adjust each to its own safe-f, compute CAR25 for each, use the funds for the one that has the highest CAR25. If you have realistically stated your risk tolerance and chosen your best estimate of the trades that might occur in the future, and since risk is the same, the choice is easy -- pick the one with the higher profit potential as measured by CAR25.
I was working as a research analyst for an American Commodity Trading Advisor in the 1990s. The founders of the company were pioneers in turtle-like "break out" systems and had been very profitable for many years. All of our systems were algorithmic -- no subjective decisions. We traded long and short, day and night, in all markets, all around the world. We watched the effectiveness of trend following go from very profitable to marginal to break even. We tried very hard to resurrect trend following for both commodities and equities, but could not. I left around 1999. The performance never recovered. The company recently returned all customer funds and closed operations. None of the large money management firms that were in our peer group have been successful with long-term-holding trading systems since about year 2000. Compare with short-term-holding algorithmic firms such as Renaissance Technologies (James Simons) and Shaw Group (David Shaw) which have been exceptionally successful.