What is the Fractal Markets Hypothesis?

Fractal Markets Hypothesis (FMH) is an investment theory that serves as an alternative to the popular Efficient Market Hypothesis (EMH). FPH differs from EMH in the sense that it predicts and explains market behavior by factoring fractals, chaos, crises, and crashes in the market. Fractal Markets Hypothesis (FMH) is a new capital-market theory that was developed in 1991 by Edgal Peters. FMH takes into account the daily randomness experienced in the market and other turbulence such as crashes.

How Does the Fractal Markets Hypothesis Work?

Fractal Markets Hypothesis (FMH) uses traditional quantitative methods and other theories to explain the behaviors on investors and market participants when there are chaos and anomalies in the market. As a new capital-market theory, FMH also gives a vivid explanation of market behaviors prevalent in periods of booms and crises. The Fractal market hypothesis uses fractals and other chaos theories to explain the behaviors of the stock market given the daily randomness and turbulence. Due to the movement of stock prices in fractals (fragments), and the repeatable attributes of fractals, FMH analyzes and gives explanation to stock market trends.

How is the Fractal Market Hypothesis Used?

Generally, the stock market becomes largely unstable during bearish trends, due to the reaction of investors to price movements in this period, market inefficiency occurs. The Fractal Market Hypothesis seeks to explain the behaviors of investors in all market conditions, including when there is a boom or bust in the market. FMH analyzes investor behaviors both when the market is stable and unstable. This hypothesis also analyses the trend in which a pattern is repeated in the market, whether weekly, monthly or a longer period.