The Fractal Indicator — Detecting Tops & Bottoms in Markets.
Insights from Chaos Theory Applied to Trading. A Study in Python.
The efficient market hypothesis fails to account for the many anomalies and recurring exploitable patterns within financial assets. This is why active portfolio management is still the dominant party when compared to passive investing.
Financial markets are not perfectly random, they are random-like, i.e. they exhibit a low signal-to-noise ratio. In other words, it is hard to predict the markets and even harder to be consistently profitable. However, the word hard does not mean impossible. In this article we will learn about Chaos theory and how its definition is used in the financial markets. Then, we will develop an indicator that uses a formula close to the Rescaled Range calculation which is often related to fractal mathematics, albeit simpler in nature. After all, we do not need to overcomplicate things to understand how the market moves.
I have just published a new book after the success of New Technical Indicators in Python. It features a more complete description and addition of complex trading strategies with a Github page dedicated to the continuously updated code. If you feel that this interests you, feel free to visit the below link, or if you prefer to buy the PDF…
