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Fractal-Like Price Paths, Brownian Motion, and Market Predictability

Article Quant Q&A · Author: Jarro

Summary

The document responds to an observation that volatile Bitcoin prices seem to form a Weierstrass-like pattern across candlestick time scales. It explains that rough, fractal-like paths are not unique to cryptocurrency: Brownian motion and related stochastic models have long been used to describe asset prices, and their paths are continuous yet almost surely nowhere differentiable. The response also notes the connection between Brownian motion and fractal dimension, and points to broader work on financial-market fractals.

It attributes price fluctuations to uncertainty about future cash flows, while treating the question of market efficiency as open. The resemblance of a price chart to a fractal does not establish a trading opportunity. Whether momentum or mean reversion creates exploitable predictability depends on the broader evidence about market behavior; the response does not test a strategy or offer empirical results for Bitcoin.

Key ideas

  • Brownian motion sample paths are continuous and almost surely nowhere differentiable.
  • Fractal-like price behavior is a general stochastic-process concept, not specific to cryptocurrency.
  • Uncertainty about future cash flows is offered as a source of price fluctuations.
  • Chart patterns across time scales alone do not show that a trading strategy is exploitable.
  • Potential momentum or mean reversion depends on whether markets exhibit transient predictability.

Tags

Full text
# Weierstrass function as market movement's attractor


# Weierstrass function as market movement's attractor












I suddenly realized that BTC/USD index (while being unbounded to anything, yet liquid) in times of high volatility turns itself into something really beautiful and well-structured. Stochastic movements of unstable market spontaneously organize itself into highly structured fractal-like function filled with axes of symmetries, much similar to Weierstrass function. Such movements can be easily observed in the last week, as well as in many moments of whole 2017. Other way it can be proven is by changing candlesticks timescale and still observing same patterns over different scales, which all combined will form Weierstrass-like fractal function.

Here is an illustration for the most recent BTC/USD 'Weierstrass-like' movement:

So, I've come up with plenty of questions related:

- Is it really some kind of well-known market movement? If so, any articles/books/papers to read on this topic?

- What's the main cause of it?

- Can it be observed outside of cryptocurrency market?

- Is this tendency somehow exploitable by specific trading strategy?

## Answer by RRL (score 4, accepted)

https://quant.stackexchange.com/a/37938

This is not a new phenomenon indiginous to cryptocurrency.

As far back as 1900 when Bachelier wrote his thesis The Theory of Speculation, stochastic processes (Brownian motion or variants) have been used to model the random nature of stock prices and other financial assets. The assumption that stock prices follow a geometric Brownian motion lead to the original development of option-pricing models by Black, Scholes and Merton (and Thorp to be perfectly fair).

The sample paths of Brownian motion exhibit similar characteristics to the Weierstrass function in that they are continuous and nowhere differentiable almost surely.

The "fractal-like" behavior is also relevant. The fractal (Hausdorff) dimension of 1D Brownian motion is $\frac{3}{2}$ (which happens to fall in between the coastline of Great Britain and Norway). Much more on fractals in financial markets was developed and discussed by Mandelbrodt.

What is the main cause? If asset prices reflect expectations about future cash flows in an uncertain world then, obviously,they should undergo random fluctuations. Otherwise everything returns a risk-free rate.

Whether or not markets are so efficient that all price behavior is that of a martingale or there is some degree of (transient) predictability (momentum or mean reversion) is too broad a topic to go into here. It does have a bearing on the final question of whether the observed tendency is exploitable.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.