Statistical Analysis

• Stock investors often use complex statistical analysis to make stock price predictions. These traders analyze the trend, volatility and other factors to calculate prices. For example, traders often like to use volume to analyze and predict stock movements. When they see that the price has moved dramatically in one direction and that the volume --- number of orders --- has also increased, this is a strong sign that the trend will be in that direction. The theory is that each additional purchase or sale of a stock adds confirmation to the one before it.
  
  

Ratio Analysis

• Another quantitative method of analysis is based on corporate ratios. The most common are price divided by revenue and price divided by earnings. This analysis can be conducted for an individual company or for the market as a whole. For example, a company's share price is $50 and and next year's projected earnings are $5 per share. The company's price earnings forward, or next year's price-to-earnings ratio, is 10. If a comparable company has a forward price-to-earnings ratio of 12, then the original company's price would be expected to rise to $60 --- five times 12 --- to match the comparable company.
  
  

Fundamental Analysis

• Fundamental analysis is a method that uses the balance sheet, income statement and traditional company evaluation tools to determine whether a company's stock price will improve. Investors calculate important trends such as earnings per share, revenue and income growth, and free cash flow. If a company is in danger of bankruptcy, investors can calculate whether the cash flow can cover principal debt and interest payments. Healthier companies receive more attention from investors and are expected to see their stock prices rise.
  
  

Market Making

• A market maker is a type of investor who programs computers to do his analysis for him and execute orders in microseconds --- millionths of a second --- to exploit tiny price variations. Market makers use the highest-level math because they depend on the smallest price movements and the largest data set. One example is called comparative strength, which can be done with a large amount of data, such as all of the stocks in the S&P 500 --- the largest 500 companies. Traders can program software to constantly analyze the movements of these companies; if one is statistically volatile, the computer can bet that the stock will revert to the mean.