Relative Strength In A Long-Term Point & Figure Chart Format
Discover The Amazing Power Of Point & Figure Charting
How institutional portfolio managers use
Market Dynamics to generate better investment performance.
Most institutional portfolio managers base their activities on fundamental predictions of how they expect a stock to perform in the future. They buy the stock and "naively" hope for the best. All too frequently the predictions of future performance don't work out and the stock performs poorly. In fact, behavioral finance suggests that portfolio managers are prone to take profits quickly and to hold poorly performing stocks and to even buy more of these bad stocks. Why is this so?
Many, if not most, institutional investors do not measure the performance of the stocks in their portfolios. Therefore, they are unaware of how bad the stock is performing until the loss gets to be so large that it can no longer be ignored. I believe this is a direct result of the aggressive indoctrination that most institutional investors receive during their academic studies in Finance. This training teaches most Finance graduates to believe, totally without reservation, that stocks price movements are completely random and that the use of charts cannot predict how a stock will perform in the future.
It must be accepted that stock price movements are random and therefore unpredictable but to say that charts are completely worthless is wrong. Charts cannot be used to predict the future but they can be used to considerable advantage to record and measure the trend of performance generated by a stock.
It must be understood that good performance is random and bad performance is also random. The measurements of stock performance reveals that the behavior by a stock with good performance is very different from the behavior of a stock with bad performance, even though both are random. The following table shows the difference.
For the year ended June 30, 2008 using the Market Dynamics database averages of the percent of the days up versus the percent of the days down.
% Days up % Days Down
All 4062 stocks 46.8% 53.2% average loss of about -14%
Worst 500 stocks 58.3% 41.7% big losers
Best 500 stocks 51.2% 48.8% big winners
This table suggests that the average proportion of days up to days down was very close to flipping a coin at 50/50. Even the biggest winners were very close to flipping a coin. The big losers showed quite a few more days up than down and still they were the biggest losing stocks over that period of time. All three sets of stocks were very close to flipping a coin and that suggests randomness.
So how did the behavior of the big losers differ so much from the behavior of the big winners. It cannot be explained by one set of stocks being random and the other being non-random. Something else must have happened. Both groups were close to 50/50 in terms of the percent of up days versus down days.
The explanation lies in the fact that the magnitude of the percent changes on the up days were much smaller than the down days for the big losers. Likewise, the magnitude of the percent changes on the up days were much greater than the down days for the big winners. The differences in the magnitudes of the changes persisted throughout the year. This is a clear indication that strong trends existed in these two groups of stocks. These trends are readily observable on a chart of relative performance such as those used by Market Dynamics.
This also suggests that the "Random Walk Hypothesis" is wrong, at least for stocks on the far left and far right sides of the distribution of returns because the step sizes are different. The direction of each step is close to 50/50 or random but the size of the steps can differ and that suggests that the "drunk" can wander away from the lamp-post. In other words trends can and do develop among the performance of groups of stocks.
"You Cannot Manage What You Do Not Measure."
Market Dynamics was developed to allow institutional portfolio managers to record and measure these trends of performance. These trends of relative performance are not as rare as you might think. Strong up trends occur in about one third of all stocks and strong downtrends occur in about another third of all stocks. The stocks in the middle of the distribution of returns represent the remaining third of all stocks and they are classified as trading range stocks and they do not show trends of performance that are as persistent as the stocks on the far sides of the distribution of returns.
In order to manage the performance of a portfolio, the portfolio manager should measure the performance of every stock in the portfolio.
The institutional portfolio manager needs to be able to tell which third a stock falls into, up trend, down trend, or trading range. Market Dynamics makes it easy for a portfolio manager to answer that question and act accordingly. This is not about predicting the future performance for a stock. The best conclusion is that the trend of performance that is in place will probably continue and that rule has been proven over and over again in actual experience. It also follows that if the trend changes, the portfolio manager will see the trend change and be aware that the situation has changed. This allows the portfolio manager to adapt to trend changes while those changes are still in motion. Given the unpredictability of these trend changes, the only way to tell when the trend changes is to continuously observe the evolution of the trend of a stock's performance.
In conclusion, the decision an institutional portfolio manager must make is which stocks to participate in and which stocks to avoid. We all have expectations about how a stock will perform in the market but we need to verify that those expectations are actually being realized by the performance of the stock. The best way to verify a stock's performance is to measure its trend of performance.
"Trust but Verify"