scholarly journals Spot Market Volatility and Futures Trading: The Pitfalls of Using a Dummy Variable Approach

2015 ◽  
Vol 36 (1) ◽  
pp. 30-45 ◽  
Author(s):  
Martin T. Bohl ◽  
Jeanne Diesteldorf ◽  
Christian A. Salm ◽  
Bernd Wilfling
Keyword(s):  
Spot Market ◽  
Market Volatility ◽  
Futures Trading ◽  
Dummy Variable ◽  
Variable Approach ◽  
Dummy Variable Approach

scholarly journals The Volatility Effect of Single-Stock Futures Trading on the Pakistani Stock Market

2013 ◽  
Vol 2 (1) ◽  
pp. 65-93
Author(s):  
Adil Awan ◽  
Amir Rafique
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Spot Market ◽  
Market Volatility ◽  
Time Varying ◽  
Futures Trading ◽  
F Test ◽  
Single Stock Futures ◽  
The Impact ◽  
Econometric Technique

The impact of single-stock futures on spot market volatility is still debated in the finance literature. The aim of this study is to analyze the effect of the introduction of single-stock futures on the volatility of the Karachi Stock Exchange (KSE). We examine changes in the level of volatility and structure after the introduction of single-stock futures, evaluating 24 companies listed on the KSE. The study applies the F-test to determine differences in variance as a traditional measure for volatility and uses GARCH (1,1) as an econometric technique for detecting time-varying volatility. The results show that there is no effect on the volatility level but that changes occur in the structure of volatility after stock futures trading.

Abstract: A Note on Dummy Variables and the Chow Test: Their Equivalence and Uses in Testing

1977 ◽  
Vol 12 (4) ◽  
pp. 675-675
Author(s):  
Marcellus S. Snow
Keyword(s):  
Analysis Of Covariance ◽  
Variable Technique ◽  
Test Analysis ◽  
Dummy Variables ◽  
Dummy Variable ◽  
Chow Test ◽  
Variable Approach ◽  
Regression Parameters ◽  
Regression Framework ◽  
Dummy Variable Approach

A general proof using matrices is given proving the equivalence of the Chow test (analysis of covariance) and an appropriate adaptation of the dummy variable technique. Implications of hypothesis testing in the linear regression framework are reviewed for each method. The dummy variable approach is found to have the following advantages: (a) it is more convenient in testing hypotheses regarding the equality of subvectors of the parameter vectors from separate regressions, in particular not requiring the running of new regressions as the Chow test approach sometimes does; and (b) a more general form of hypothesis can be tested, namely that corresponding regression parameters differ by a constant other than zero.

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