There are many economic models to utilize for predicting and describing markets, but we will explore two of them—the efficient market hypothesis model (EMHM) and the behavioral finance model. In EMHM the assumption is that investors are fully rational. This means in economic parlance that investors maximize their individual utility function. Another feature of EMHM is that information cannot be used to make above normal profits in the long term. In short, an investor cannot beat the market. In terms of stochastic variation, variances in returns mean to zero and are normally distributed. Lastly, EMHM proposes that the market should always be in steady state; therefore boom and bust cycles should not occur.
The problems with EMHM are many, but we will discuss four issues. Firstly, traders are greedy and not rational agents. This irrationality is due in part from the dopamine response mechanism during trading. Secondly, new information is not completely in the price, therefore EMHM over estimates how much the market price has incorporated current information. We can see this lagged diffusion of news when a central bank announces interest rates—the currency market increases in volatility for many time periods within an intraday chart. Information is not instantaneously incorporated in the price. Thirdly, profits can be statistically above average for certain investors or traders. Lastly, EMHM does not incorporate the reality that there are boom and bust cycles. e.g. crash of 1929, of the crash of 2008.
Behavior finance field has models to describe the behavior of economic agents. We will explore just one aspect of behavior finance—the concept of equilibrium in markets. There are two equilibriums: fundamental and speculative equilibriums. Fundamental equilibriums are when prices are close to economic value. The proxy for the fundamental value of an asset can be assumed to be the 200 period moving averages in a long duration chart, e.g. day or weekly chart. In a fundamental equilibrium the investors that use fundamental analysis rule the trading game. Fundamental analysis is varied, but a simple example is as follows. An investor can look at the discounted free cash flow of a company and apply a historical price-to-earnings multiple to determine fair value of the stock. If the market price is lower than this calculated fundamental value then the fundamental trader will buy the stock.
In speculative equilibrium, the price deviates from economic value, i.e. fundamental value. Speculative equilibrium can be above or below economic value. Chartists or quantitative finance researchers are rulers of this game. According to De Grauwe and Grimaldi (2006) most financial trading assets are in speculative equilibrium, especially currency pairs. Evidence of speculative equilibrium is shown with the 50 period moving averages, whereby the asset price vacillates around the 200 period moving averages. The dynamic of the price curve shows mean reverting characteristics, which is also represented in the volatility parameter in a Brownian motion function.
Cottrell (2014) has shown how to use the De Grauwe and Grimaldi model to simulate fundamental and speculative equilibriums. The De Grauwe and Grimaldi model is a useful tool to simulate the agent behavior of fundamental and technical traders. At present the De Grauwe and Grimaldi model seems useful in momentum and mean reversion trading. But the parameterization of their model is difficult and very sensitive at phase transitional points—which leads to the possible conclusion that parameterized models might not perform as well as non-parameterized valuation techniques.