Can volatility based technical signals capture consistent abnormal equity index returns?

This thesis examines a combined technical signal approach (CSA) on four stock index implied volatility indices for the aim of day trading the underlying stock indices. The purpose is to determine whether excess returns derived from the use of a combined technical trading strategy are statistically significantly different than zero. The null hypothesis is that the average daily rate of excess return of the strategy, for every underlying stock index is zero; the alternative hypothesis is that the average daily rate of excess return of the strategy, per equity index, is different than zero, both before and after trading costs and dividends are considered. A two-tailed z test is utilized to test the statistical significance of the difference between the annualized mean daily rate of excess return of the day trading strategy and zero. For every implied volatility index, all available data is utilized to determine the persistence of excess returns over a robust timeframe, the total available sample period. White's Reality Check Test is applied to each excess return series, first by utilizing the moving blocks bootstrapping method, to determine whether mean excess returns are statistically significantly different than zero, regardless of the shapes of the original distributions of excess returns. This research also tests whether each distribution of excess returns for each of the four daily traded stock indices conforms to a normal distribution using the Jarque-Bera goodness of fit to normality test, before and after transaction costs and dividends are considered. Three different trading strategies are compared: a volatility based CSA that utilizes the momentum approach to day trading, an equity based CSA that utilizes the mean reversion approach to day trading, and a buy and hold approach. A final measure of performance, the Sharpe Ratio, is utilized in order to determine which strategy has the highest risk adjusted returns.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Agricultural & Applied Econ

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2016

Author dc:creator

• Falakos, Menas Constantine

Contributors dc:contributor

• Mallory, Mindy

• Volatility Technical Analaysis

Statement dc:rights

• Copyright 2016 Menas Falakos

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/92762

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/92762