Data-Snooping Biases in Backtesting

Thesis title: Data-Snooping Biases in Backtesting
Author: Krpálek, Jan
Thesis type: Diploma thesis
Supervisor: Bašta, Milan
Opponents: Malá, Ivana
Thesis language: English
Abstract:
In this paper, we utilize White's Reality Check, White (2000), and Hansen's SPA test, Hansen (2004), to evaluate technical trading rules while quantifying the data-snooping bias. Secondly, we discuss the result with Probability of Backtest Overfitting framework, introduced by Bailey et al. (2015). Hence, the study presents a comprehensive test of momentum trading across the US futures markets from 2004 to 2016. The evidence indicates that technical trading rules have not been pro?table in the US futures markets after correcting for the data snooping bias.
Keywords: Probability of Backtest Over?tting; Data Snooping; Backtesting; Reality Check; Algorithmic Trading
Thesis title: Data-Snooping Biases in Backtesting
Author: Krpálek, Jan
Thesis type: Diplomová práce
Supervisor: Bašta, Milan
Opponents: Malá, Ivana
Thesis language: English
Abstract:
C??ílem diplomov?é pr?áce je implementace Whitova Reality testu, White (2000), a Hansenova SPA testu, Hansen (2004), za ?účelem identi?kace tzv. "data snooping" vych?ýlen??í v algoritmick?ych obchodních strategi??ích. V?ýsledky t?ěchto testů budou konfrontov?ány s PBO statistikou, Bailey et al. (2015). Za vyu?žití t?ěchto test?ů n?ásledn?ě hodnotí??me obchodov?an??í momentum strategi??í na americk?ých futures trz??ích v letech 2004-2016. Z?áv?ěrem konstatujeme, ?že strategie po o?či?št?ění?? o data snooping vych?ýlení?? nedosahuj??í v?yznamn?é ziskovosti.
Keywords: Algoritmick?é obchodov?ání; Probability of Backtest Over?tting; Reality Check; Data Snooping; Backtesting

Information about study

Study programme: Kvantitativní metody v ekonomice/Statistika
Type of study programme: Magisterský studijní program
Assigned degree: Ing.
Institutions assigning academic degree: Vysoká škola ekonomická v Praze
Faculty: Faculty of Informatics and Statistics
Department: Department of Statistics and Probability

Information on submission and defense

Date of assignment: 2. 2. 2016
Date of submission: 5. 1. 2017
Date of defense: 1. 2. 2017
Identifier in the InSIS system: https://insis.vse.cz/zp/57029/podrobnosti

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