Market Efficiency is Dead - Overview over Chaos, Momentum, Hurst Exponents and Market Crashes
Channel: VoglData
Date: 2022-06-30

In this video I will demonstrate the total invalidity of the efficient market hypothesis and explicate several concepts and trading insights:

- Elaboration on empirical characteristics of financial instruments (i.e. stylized facts)
- Statment of chaotic evolutionary dynamics, strange attractor, multifractal spectrum and powerlaw distribution in the S&P500 cascadic wavelet filtered (denoised) return series
- Display of momentum effects and momentum crashes via rolling window Hurst exponents
- Possibility of market outperformance, beating the markets and generation of positive alpha returns
- Direct determination of market efficiency validity based on rolling window Hurst exponent series
- Behavioral biases in humans

It will be shown that one can elucidate the validity of the efficient market hypothesis directly by analysing rolling window Hurst exponents, which also show the existence of fractal persistent trends, which are responsible for the momentum effect. Thus, if no fractal trending is observable in the markets, momentum crashes occur. This is mostly the case during recessions, market meltdowns or financial crises.


Content Tags

Introduction 00:00 - 00:09
Content 00:10 - 01:20
Recapitulation of EMH 01:20 - 04:54
Total Invalidity of EMH (Overview) 04:55 - 07:55
Total Invalidity of EMH (Stylized Facts) 07:56 - 10:10
Total Invalidity of EMH (Chaotic Dynamics) 10:11 - 15:55
Total Invalidity of EMH (Momentum and Trending) 15:56 - 19:47
Total Invalidity of EMH (Hurst Exponents) 19:48 - 23:01
Total Invalidity of EMH (Behavioral Human Biases) 23:02 - 24:26
Overview of Video Series 24:27 - 25:12
Concluding Remarks 25:13 - End


Social Media

https://twitter.com/VoglData
https://vogl-datascience.de/


Scientific References

E. F. Fama, “The Behaviour of Stock-Market Prices,” The Journal of Business, 38(1), 34-105, 1965.

E. Fama and K. French, “Business conditions and expected returns on stocks and bonds,” Journal of Financial Economics, 25(1), 23-49, 1989. 

L. Bachelier, Théorie de la Spéculation Annales Scientifiques de LÉcole Normale Supérieure (1900) Reprinted in: P.H. Cootner, The Random Character of Stock Market Prices, Cambridge: MIT Press, 1964. 

Wilhelm Berghorn (2015) Trend momentum, Quantitative Finance, 15(2), 261-284, DOI: 10.1080/14697688.2014.941912
Berghorn, Wilhelm and Schulz, Martin and Otto, Sascha, Fractal Markets, Frontiers, and Factors (September 26, 2019). Available at SSRN: https://ssrn.com/abstract=3463151 or http://dx.doi.org/10.2139/ssrn.3463151

Berghorn, Wilhelm and Vogl, Markus and Schulz, Martin and Otto, Sascha, Trend Momentum II: Driving Forces of Low Volatility and Momentum (February 8, 2018). Available at SSRN: https://ssrn.com/abstract=3120232 or http://dx.doi.org/10.2139/ssrn.3120232

Vogl, Markus and Rötzel, Peter Gordon (2022). Chaoticity Versus Stochasticity in Financial Markets: Are Daily S&P 500 Return Dynamics Chaotic? In: Communications in Nonlinear Science and Numerical Simulation, 108, 106218
 Vogl, Markus, Hurst Exponent Dynamics of S&P 500 Returns: Implications for Market Efficiency, Long Memory, Multifractality and Financial Crises Predictability by Application of a Generalized Nonlinear Dynamics Analysis Framework (May 3, 2021). Available at SSRN: https://ssrn.com/abstract=3838850 or http://dx.doi.org/10.2139/ssrn.3838850


Audio Sources
Chasing Daylight by Scott Buckley | https://soundcloud.com/scottbuckleyMusic promoted by https://www.free-stock-music.comAttribution 4.0 International (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/


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