Price acceleration, by itself, is a simple concept. The easiest way to grasp it is to measure, over time, the movement of a particular stock. If it is going up, you calculate how long it has taken to reach its present price. If it has gone up $10 in 10 days, then the average acceleration is $1. However, this is an exceptionally simple idea that is not very useful for following stocks. Regression analysis is the primary way to get the real acceleration figure, because in this method the dollar amounts are controlled for by independent variables.
1. Gather your data. Data is called the “n” in statistics. If you are following a single stock that has been going up consistently for the last 30 business days, for example, you want to program into the regression software program the hourly changes in price in this period. The larger your “n,” the better your model will be.
2. Clarify your dependent variable. Your dependent variable is the price movement of a specific stock. More significant is the question of what, specifically, is causing it to increase. In other words, price acceleration is a very specific figure that requires the rising price to be understood through other variables.
3. Gather and clarify your independent variables. These are those things you think are causing the price to rise. These variables include the movement of the market as a whole, the behavior of bonds and interest rates, gross national product growth that quarter, and the value of the dollar.
4. Interpret your findings. Stock price acceleration is far more than just seeing the average stock increase over a few days. Anyone can do that. Price acceleration must be measured relative to the independent variables in your model. If the stock you are following is seeing a large accelerated growth, your independent variables will be able to give the true acceleration figure rather than a mere average. This is because the increase of the stock price makes sense only when controlled for by other macroeconomic variables.
5. Weigh the independent variables. In a regression analysis, each independent variable will have a “p” score. This tells you how significant each variable is in explaining the increase in your stock price. Your stock might be accelerating in cost because the bond market is seeing record low rates. The stock market as a whole might be growing rapidly. If these two independent variables have a high “p” score, then they are what is creating the acceleration. The actual, real acceleration figure will then be reached, because the prices are controlled by these important variables. Acceleration, therefore, is the figure you get when the average price increase is controlled for by the other variables working on the market.
6. Apply your data. For example, you are measuring a stock that is going up quickly. an average of $3 per day. You are using fairly typical independent variables such as market volatility, bonds prices, exchange rates and private-sector debt. In this example, your highest “p” score is attached to the “dollar value” variable. This says that 70 percent of this $3 is coming from a weak dollar. If you then hear that the Chinese are going to dump some of their dollar holdings, buying more of that stock might be a good idea. In other words, since much of the price variation is based on the dollar's value, news on the dollar your main concern. Any news suggesting that the dollar would continue to fall would be your cue to buy more of that stock. Once that $3 average begins to fall, it is time to hold steady.
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