CMS physics technical design report : Addendum on high density QCD with heavy ions

Peer reviewe

The Physics of the B Factories

This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C

Is systematic downside beta risk really priced? evidence in emerging market data

Several studies advocating safety first as a major concern to investors propose downside beta risk as an alternative to the traditional systematic risk- beta. Downside measures are concerned with a subset of the data and therefore the results in the studies that consider the downside beta only may be biased. This study addresses this issue by including downside co-skewness risk in addition to the downside beta risk in the pricing model. In a sample of 27 emerging markets two-stage rolling regression analysis fail to support pricing models with downside risk measures. In a cross-sectional analysis inclusion of downside co-skewness improves model fit. When considered together, downside beta is potential and downside co-skewness is a risk to the rational investor. Even though our results are inconclusive the evidence strongly suggests a need for further investigation of co-skewness risk in pricing models that adopt a downside risk framework

Multivariate tests of asset pricing: simulation evidence from an emerging market

The finite sample performance of the Wald, GMM and Likelihood Ratio (LR) tests of multivariate asset pricing tests have been investigated in several studies on the US financial markets. This paper extends this analysis in two important ways. Firstly, considering the fact that the Wald test is not invariant to alternative non-linear formulation of the null hypothesis the paper investigates whether alternative forms of the Wald and GMM tests result in considerable difference in size and power. Secondly, the paper extends the analysis to the emerging market data. Emerging markets provide an interesting practical laboratory to test asset pricing models. The characteristics of emerging markets are different from the well developed markets of US, Japan and Europe. It is found that the asymptotic Wald and GMM tests based on Chi-Square critical values result in considerable size distortions. The bootstrap tests yield the correct sizes. Multiplicative from of bootstrap GMM test appears to outperform the LR test when the returns deviate from normality and when the deviations from the asset pricing model are smaller. Application of the bootstrap tests to the data from the Karachi Stock Exchange strongly supports the zero-beta CAPM. However the low power of the multivariate tests warrants a careful interpretation of the results

Is systematic downside beta risk really priced? evidence in emerging market data

Several studies advocating safety first as a major concern to investors propose downside beta risk as an alternative to the traditional systematic risk- beta. Downside measures are concerned with a subset of the data and therefore the results in the studies that consider the downside beta only may be biased. This study addresses this issue by including downside co-skewness risk in addition to the downside beta risk in the pricing model. In a sample of 27 emerging markets two-stage rolling regression analysis fail to support pricing models with downside risk measures. In a cross-sectional analysis inclusion of downside co-skewness improves model fit. When considered together, downside beta is potential and downside co-skewness is a risk to the rational investor. Even though our results are inconclusive the evidence strongly suggests a need for further investigation of co-skewness risk in pricing models that adopt a downside risk framework

Testing conditional asset pricing models: an emerging market perspective

The CAPM as the benchmark asset pricing model generally performs poorly in both developed and emerging markets. We investigate whether allowing the model parameters to vary improves the performance of the CAPM and the Fama-French model. Conditional asset pricing models scaled by conditional variables such as Trading Volume and Dividend Yield generally result in small pricing errors. However, a graphical analysis shows that the predictions of conditional models are generally upward biased. We demonstrate that the bias in prediction may be caused by not accommodating frequent large variation in asset pricing models. In emerging markets, volatile institutional, political and macroeconomic conditions results in thick tails in the return distribution. This is characterized by excess kurtosis. It is found that the unconditional Fama-French model augmented with a cubic market factor performs the best among the competing models. This model is also more parsimonious compared to the conditional Fama-French model in terms of number of parameters