Quantitative behavioral finance

Quantitative behavioral finance is a new discipline that uses mathematical and statistical methodology to understand behavioral biases in conjunction with valuation. The research can be grouped into the following areas: Empirical studies that demonstrate significant deviations from classical theories. Modeling using the concepts of behavioral effects together with the non-classical assumption of the finiteness of assets. Forecasting based on these methods. Studies of experimental asset markets and use of models to forecast experiments. The prevalent theory of financial markets during the second half of the 20th century has been the efficient market hypothesis (EMH) which states that all public information is incorporated into asset prices. Any deviation from this true price is quickly exploited by informed traders who attempt to optimize their returns and it restores the true equilibrium price. For all practical purposes, then, market prices behave as though all traders were pursuing their self-interest with complete information and rationality. Toward the end of the 20th century, this theory was challenged in several ways. First, there were a number of large market events that cast doubt on the basic assumptions. On October 19, 1987 the Dow Jones average plunged over 20% in a single day, as many smaller stocks suffered deeper losses. The large oscillations on the ensuing days provided a graph that resembled the famous crash of 1929. The crash of 1987 provided a puzzle and challenge to most economists who had believed that such volatility should not exist in an age when information and capital flows are much more efficient than they were in the 1920s. As the decade continued, the Japanese market soared to heights that were far from any realistic assessment of the valuations. Price-earnings ratios soared to triple digits, as Nippon Telephone and Telegraph achieved a market valuation (stock market price times the number of shares) that exceeded the entire market capitalization of West Germany.