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2015 | OriginalPaper | Buchkapitel

76. VAR Models: Estimation, Inferences, and Applications

verfasst von : Yangru Wu, Xing Zhou

Erschienen in: Handbook of Financial Econometrics and Statistics

Verlag: Springer New York

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Abstract

Vector autoregression (VAR) models have been used extensively in finance and economic analysis. This paper provides a brief overview of the basic VAR approach by focusing on model estimation and statistical inferences. Applications of VAR models in some finance areas are discussed, including asset pricing, international finance, and market microstructure. It is shown that such approach provides a powerful tool to study financial market efficiency, stock return predictability, exchange rate dynamics, and information content of stock trades and market quality.

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Fußnoten
1
For further discussions on VAR techniques, see Watson (1994); Lutkepohl (1991), and Stock and Watson (2001), among others.
 
2
For more estimation details, refer to Hasbrouck (1993).
 
3
Whether options lead stocks in the price discovery process is still a question open to debate. Early studies in this literature present strong evidence in favor of the option lead in prices. For example, Latane and Rendleman (1976) and Beckers (1981) show that the volatility implied in option prices predicts future stock-price volatility. Consistently, Manaster and Renleman (1982) find that the option-implied stock prices contain valuable information about the equilibrium prices of the underlying stocks that has not been revealed in the stock market. However, Vijh (1988) questions the results in Manaster and Rendleman (1982), since using daily closing prices introduces a bias associated with the bid-ask spread and nonsynchronous trading. After purging the effects of bid-ask spreads, Stephan and Whaley (1990) find that the stock market leads the option market. Nevertheless, Chan et al. (1993) argue that the stock lead is due to the relative smaller stock tick. If the average of the bid and ask is used instead of transaction prices, neither market leads the other. Latter studies on the stock option lead-lag analysis have been focused more on the trading volume. Easley et al. (1998) show that “positive news option volumes” and “negative news option volumes” have predictive power for future stock-price changes. See also Pan and Poteshman (2006) and Cao et al. (2003). By measuring the relative share of price discovery occurring in the stock and option markets, Chakravarty et al. (2004) conclude that informed trading takes place in both stock and option markets, suggesting an important role for option volume.
 
4
Zhou’s (2009) analysis incorporates the option market trades in addition to the stock and bond market transactions. Chava and Tookes (2005) also incorporate the option markets and examine the volatility reaction of stock, bond, and options to macroeconomic and firm specific information, finding significant effects near announcements. Overall, they find that corporate bond and option trades have information content for future stock price movements.
 
5
For convertible bonds, Downing et al. (2009) find that these results also hold, but only for those with conversion options deep in the money. Kwan (1996) first examines the relation between individual stocks and bonds using weekly quote data and also finds evidence in support of stock leads.
 
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Metadaten
Titel
VAR Models: Estimation, Inferences, and Applications
verfasst von
Yangru Wu
Xing Zhou
Copyright-Jahr
2015
Verlag
Springer New York
DOI
https://doi.org/10.1007/978-1-4614-7750-1_76