Determinants of stock returns: Factors or systematic co-moments? Crisis versus non-crisis periods

In this paper we evaluate the intertemporal pricing performance of stock return determinants over the periods surrounding, and outside of, financial crises. The analysis focuses on the variables of size, book-to-market ratio, momentum, liquidity, and higher-order systematic co-moments. The evidence reveals that over non-crisis periods the market beta plays an important role in determining the cross-section of stock returns. Size, value, momentum, and liquidity also exhibit associations with the cross-section of stock returns. However, over crisis periods most of the variables we examined lose their explanatory power, suggesting that their usefulness is limited for investment purposes when financial markets experience crises. There is some evidence of coskewness pricing surrounding market crashes. Practitioners may consider coskewness over crisis periods.

Three essays on stock returns and inflation - Australian evidence

Results of this thesis suggest that a significant negative relation between stock returns and inflation identified in Australia during ‘inflation targeting’ is mainly due to an incidence of ‘flight to safety’. Furthermore, the impact of inflation news on stock returns is industry-sector dependent. Specifically, in Australia rising inflation seems to be good news for Financials, but bad news for Materials.

A hybrid approach to fuzzy risk analysis in stock market

The analysis and prediction of stock market has always been well recognized as a difficult problem due to the level of uncertainty and the factors that affect the price. To tackle this challenge problem, this paper proposed a hybrid approach which mines the useful information utilizing grey system and fuzzy risk analysis in stock prices prediction. In this approach, we firstly provide a model which contains the fuzzy function, k-mean algorithm and grey system (shorted for FKG), then provide the model of fuzzy risk analysis (FRA). A practical example to describe the development of FKG and FRA in stock market is given, and the analytical results provide an evaluation of the method which shows promote results. © 2013 IEEE.