This document studies the power of CBOE Volatility Index (VIX) to predict stock market returns of Standard & Poor’s 500 (S&P 500), a good proxy of the USA economy. VIX measures the market’s expectation of S&P 500 volatility, however many authors call it fear index because the value of the index spikes in moments of high selling in financial markets. Even though VIX is a common indicator in technical analysis and market sentiment (Baker & Wurgler, 2007), this study fits better to fundamental analysis of the USA economy as a whole.
Finance managers or investors may take advantage of the results of this work. Historical data provides strong evidences of positive and negative correlations. By order of significance, very strong negative relationship with TB3M, strong positive relationship with TS and moderate positive relationship with CS, SPYDY and VIX. However, if we assume a weak from of the efficient market hypothesis or random walk theory the historical data is not representative of future returns, consequently investors should be cautious taking decision from historical data.
This study suggests at least two new research lines. One is to explore the decomposition of VIX in variance risk premium and realized variance following methods such as GARCH, HAR, etc., and complement existing literature with periorized CC returns rather than annualized CC returns only. The second direction can be a microeconomic study using companies volatility indexes such as VXIBM or VXAPL representative of Apple and IBM respectively.
The download includes the complete master thesis in pdf. Additionally, it includes the complete project in R programming language, it is used to gather the data from internet, process the data, create all regression models and plot the images present in the management project.