Work detail

Trading strategies based on estimates of conditional distribution of stock returns

Author: Mgr. Adam Sedlačík
Year: 2018 - summer
Leaders: doc. PhDr. Jozef Baruník Ph.D.
Consultants:
Work type: Economic Theory
Masters
Language: English
Pages: 70
Awards and prizes:
Link: https://is.cuni.cz/webapps/zzp/detail/190343/
Abstract: In this thesis, a new trading strategy is proposed. By the help of quantile regression, the
conditional distribution functions of stock market returns are estimated. Based on the
knowledge of the distribution the strategy produced buying and selling signals which
together with a weight function derived from exponential moving averages determines how
much and when to buy or sell. The strategy performs better than the market in terms of
absolute return and the Sharpe ratio in-sample, but it does not provide satisfactory results
out-of-sample.

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