Corporate Finance

Analyzing Event Statistics in Corporate Finance: by Jau-Lian Jeng

By Jau-Lian Jeng

Studying occasion facts in company Finance offers new replacement methodologies to extend accuracy whilst appearing statistical assessments for occasion stories inside company finance. not like traditional surveys or literature experiences, Jeng makes a speciality of quite a few methodological defects or deficiencies that bring about faulty empirical effects, which eventually produce undesirable company guidelines. This paintings discusses the problems of information assortment and constitution, the recursive smoothing for systematic elements in extra returns, the alternatives of occasion home windows, diversified time horizons for the occasions, and the results of purposes of other methodologies. In supplying development for occasion experiences in company finance, and in line with the truth that adjustments in parameters for monetary time sequence are universal wisdom, a brand new replacement technique is constructed to increase the traditional research to extra strong arguments.

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Extra resources for Analyzing Event Statistics in Corporate Finance: Methodologies, Evidences, and Critiques

Example text

Chudik et al. (2011) consider the cross-sectional weak and strong dependence of large panels. Their framework defines the weak and strong cross-sectional dependence using weight sequences that satisfy the granularity condition where the vector norms of these weights are bounded by the growth rate N 1/2 , where N represents the number of cross-sectional items in panel data. In addition, the weak and strong cross-sectional dependence is defined as whether the conditional variance of the weighted sequence of panel data observations at a certain point in time will converge to zero or not.

In contrast to their work, a stronger condition for nondiversifiability (for factor(s)) is introduced. A formal proof is also shown that the nondiversifiability of the (hidden) factor will lead to the cross-sectional long dependence. In particular, the long memory tests such as cross-sectional KPSS test, cross-sectional rescaled variance test, and assessments on Hurst exponent are also introduced. 44 A N A LY Z I N G E V E N T S T A T I S T I C S I N C O R P O R A T E F I N A N C E While Chudik et al.

2. is to define the set of diversifying weights. 3. is for defining diversification. 1 shows the conditions of factors or pre-specified reference variables applied as factors. The assumption allows different choice sets of instrumental or reference variables applied to specify the risk premium. These choice sets may be evolving over time or different sample sizes. In particular, the reference variables may be generated by the innovations from the multivariate time series models of prespecified economic variables in a conditional expectation approach.

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