A Historical Analysis Of Volatility In The Mexican Stock Market Index
Pedro Martínez López
National Autonomous University of Mexico (UNAM), Faculty of Economics, Mexico City, Mexico
Abstract
The predictability of stock price movements has long been a subject of debate in academia and the finance sector. This study delves into the age-old question: how can historical stock price data be leveraged to forecast future behavior? This question has spurred two competing theories: the chartist theory and the theory of random walks.
Chartists, who primarily follow Dow Theory and Technical analysis, share a common belief that historical asset price data holds valuable information for predicting future behavior. They posit that patterns observed in past prices tend to recur in the future, suggesting that history repeats itself. Consequently, analysts following this approach use historical patterns to forecast future price movements, aiming to boost their expected profits (Murphy, 2000).
In stark contrast, the theory of random walks contends that stock prices follow a random walk, making it impossible to predict future prices based on historical data (Fama, 1965). This theory asserts that price changes are random variables that are independent and identically distributed (Johnston & Dinardo, 1997). In essence, past prices do not offer any information that can be used to anticipate future prices. Fama (1970) introduced three levels of market efficiency, with the weak form suggesting that the history of stock prices does not contain information capable of generating yields beyond what a random portfolio would yield.