Is liquidity the missing link?

Durand et al. (2006a ) argue that the Australian market is both internationally integrated and domestically segmented. They find that the US‐based three‐factor model captures returns of the largest stocks in Australia (evidence of international integration), but that it is unable to account for the returns of the smallest stocks (evidence of domestic segmentation). This study resolves the puzzle left by Durand et al. (2006a) . Incorporating a liquidity factor provides the missing link in their analysis: it results in a model that permits both the international integration of the largest stocks and the model can account for the returns of the smallest stocks. Our analysis highlights the important role of liquidity in Australian asset pricing.     

Estimating the time Varying Components of international stock markets' risk

In this study an alternative approach for assessing securities' risk is applied. Various authors have argued that security returns are not homoskedastic but exhibit variation over time. They have observed that large changes tend be followed by more large changes in either direction, and so volatility must be predictably high after large changes. This phenomenon of securities' volatility, referred to as clustering, has important implications for security pricing and risk management. Among the most popular techniques currently used to capture the clustering effect and to forecast future volatilityare those belonging to the family of Autoregressive Conditional Heteroskedastic (ARCH) models. The main aim of this paper is to investigate whether such volatility modelling can be used to capture the time variation not only in the total risk of a security return but also its systematic and unsystematic components. Using weekly local stock market data, the time varying beta with the World Index has been estimated via a bivariate GARCH-M model. The GARCH-M parameterization used here is a dynamic specification of the SIM. The hypothesis that this dynamic specification holds cannot be rejected for 11 out of 13 local portfolios. The results provide evidence that both the systematic and the non-systematic counterparts are also changing over time. However, in some markets those risk changes may take place with some delay. This suggests that some of the low correlation coefficients computed for certain stock market returns may not be due to differences in business cycles among those countries, but may be caused by the non-synchronous response to world market developments. This finding should have important implications in many investment decisions such as portfolio selection, market timing and risk hedging.     

Two Paradigms and Nobel Prizes in Economics: a Contradiction or Coexistence?

Abstract Markowitz and Sharpe won the Nobel Prize in Economics for the development of Mean‐Variance (M‐V) analysis and the Capital Asset Pricing Model (CAPM). Kahneman won the Nobel Prize in Economics for the development of Prospect Theory. In deriving the CAPM, Sharpe, Lintner and Mossin assume expected utility (EU) maximisation in the face of risk aversion. Kahneman and Tversky suggest Prospect Theory (PT) as an alternative paradigm to EU theory. They show that investors distort probabilities, make decisions based on change of wealth, exhibit loss aversion and maximise the expectation of an S‐shaped value function, which contains a risk‐seeking segment. Can these two apparently contradictory paradigms coexist? We show in this paper that although CPT (and PT) is in conflict to EUT, and violates some of the CAPM's underlying assumptions, the Security Market Line Theorem (SMLT) of the CAPM is intact in the CPT framework. Therefore, the CAPM is intact also in CPT framework.     

Modeling Conditional Skewness in Stock Returns

Abstract

In this paper, we propose a new GARCH-in-Mean (GARCH-M) model allowing for conditional skewness. The model is based on the so-called z distribution capable of modeling skewness and kurtosis of the size typically encountered in stock return series. The need to allow for skewness can also be readily tested. The model is consistent with the volatility feedback effect in that conditional skewness is dependent on conditional variance. Compared to previously presented GARCH models allowing for conditional skewness, the model is analytically tractable, parsimonious and facilitates straightforward interpretation.Our empirical results indicate the presence of conditional skewness in the monthly postwar US stock returns. Small positive news is also found to have a smaller impact on conditional variance than no news at all. Moreover, the symmetric GARCH-M model not allowing for conditional skewness is found to systematically overpredict conditional variance and average excess returns.     

The pricing of sentiment risk in European stock markets

This paper studies whether sentiment is rewarded with a significant risk premium in the European stock markets. We examine several sentiment proxies and identify the Economic Sentiment Indicator from the EU Commission as the most relevant sentiment proxy for our sample. The analysis is performed for the contemporaneous excess returns of EA-11 stock markets in the period from February 1999 to September 2015. We apply a conditional multi-beta pricing model in order to track the variation of the sentiment risk premium over time. The results demonstrate a positive significant relationship between sentiment and contemporaneous excess returns which is consistent with previous studies. The calculated sentiment risk premium is significant as well but negative implying that an investment in EA-11 countries over the examined time period – that is bearing sentiment risk – would have been unattractive to the investors on average.     

Is Financial Flexibility a Priced Factor in the Stock Market?

This paper develops a factor analysis–based measure for shifts in corporate financial flexibility (FFLEX) that can be observed from public accounting information. Companies that experience positive shifts in FFLEX are associated with higher future investment growth opportunities. We show that FFLEX is a robust determinant of future stock returns. Firms that have increased their financial flexibility are associated with lower stock returns in the subsequent period. A zero‐cost return portfolio produces a significant positive monthly premium of 0.69%, which is driven by covariance (risk). Risk inherent in the flexibility factor is not explained away by either prominent pricing characteristics or factors.     

Have European Stocks become More Volatile? An Empirical Investigation of Idiosyncratic and Market Risk in the Euro Area

We examine the dynamics of idiosyncratic risk, market risk and return correlations in European equity markets using weekly observations from 3515 stocks listed in the 12 euro area stock markets over the period 1974–2004. Similarly to Campbell et al. (2001) , we find a rise in idiosyncratic volatility, implying that it now takes more stocks to diversify away idiosyncratic risk. Contrary to the US, however, market risk is trended upwards in Europe and correlations are not trended downwards. Both the volatility and correlation measures are pro‐cyclical, and they rise during times of low market returns. Market and average idiosyncratic volatility jointly predict market wide returns, and the latter impact upon both market and idiosyncratic volatility. This has asset pricing and risk management implications.     

Time‐Varying Risk–Return Trade‐off in the Stock Market

We uncover a strong comovement of the stock market risk–return trade‐off with the consumption–wealth ratio (CAY). The finding reflects time‐varying investment opportunities rather than countercyclical aggregate relative risk aversion. Specifically, the partial risk–return trade‐off is positive and constant when we control for CAY as a proxy for investment opportunities. Moreover, conditional market variance scaled by CAY is negatively priced in the cross‐section of stock returns. Our results are consistent with a limited stock market participation model, in which shareholders require an illiquidity premium that increases with CAY, in addition to the risk premium that is proportional to conditional market variance.