Work detail

Entropy as a Measure of Predictability in Financial Time Series

Author: Bc. Vladimír Nahodil
Year: 2017 - summer
Leaders: doc. PhDr. Ladislav Krištoufek Ph.D.
Work type: Bachelors
Language: English
Pages: 67
Awards and prizes: B.A. with distinction from the Director of IES FSV UK for an extraordinarily good bachelors diploma thesis.
Abstract: This work studies stock markets efficiency and predictability using the information-theoretic
concepts of approximate entropy (ApEn) and sample entropy (SampEn) and compares them
to the estimates of the Hurst exponent. This is assessed together with the property of
distinguishing between developing and developed markets. Moreover, an investment
strategy based on the value of the sample entropy is tested. ApEn shows very weak
relationship with other measures and performs poorly as a measure of efficiency. SampEn
and the Hurst exponent clearly confirm lower overall efficiency of developing markets. The
sample entropy also forms quite strong downward linear relationship with hit-rates of
forecasting models. ARMA shows highest hit-rates in periods with SampEn values around 1.6
- 1.7. This could be considered as an investment strategy with lower risk; however, also as one
with potentially lower accumulated returns due to smaller investing windows.


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