The value premium and time-varying volatility

Numerous studies have documented the failure of the static and conditional capital asset pricing models to explain the difference in returns between value and growth stocks. This paper examines the post-1963 value premium by employing a model that captures the time-varying total risk of the value-minus-growth portfolios. Our results show that the time-series of value premia is strongly and positively correlated with its volatility. This conclusion is robust to the criterion used to sort stocks into value and growth portfolios and to the country under review (the US and the UK). Our paper is consistent with evidence on the possible role of idiosyncratic risk in explaining equity returns, and also with a separate strand of literature concerning the relative lack of reversibility of value firms' investment decisions.

The importance of the volatility risk premium for volatility forecasting

In this paper, we study the role of the volatility risk premium for the forecasting performance of implied volatility. We introduce a non-parametric and parsimonious approach to adjust the model-free implied volatility for the volatility risk premium and implement this methodology using more than 20 years of options and futures data on three major energy markets. Using regression models and statistical loss functions, we find compelling evidence to suggest that the risk premium adjusted implied volatility significantly outperforms other models, including its unadjusted counterpart. Our main finding holds for different choices of volatility estimators and competing time-series models, underlying the robustness of our results.

Idiosyncratic volatility and the pricing of poorly-diversified portfolios

This article examines the role of idiosyncratic volatility in explaining the cross-sectional variation of size- and value-sorted portfolio returns. We show that the premium for bearing idiosyncratic volatility varies inversely with the number of stocks included in the portfolios. This conclusion is robust within various multifactor models based on size, value, past performance, liquidity and total volatility and also holds within an ICAPM specification of the risk–return relationship. Our findings thus indicate that investors demand an additional return for bearing the idiosyncratic volatility of poorly-diversified portfolios.

New evidence on the green building rent and price premium

This paper investigates the effect of voluntary eco-certification on the rental and sale prices of US commercial office properties. Hedonic and logistic regressions are used to test whether there are rental and sale price premiums for LEED and Energy Star certified buildings. The results of the hedonic analysis suggest that there is a rental premium of approximately 6% for LEED and Energy Star certification. A sale price premium of approximately 35% was found for 127 price observations involving LEED rated buildings and 31% for 662 buildings involving Energy Star rated buildings. When compared to samples of similar buildings identified by a binomial logistic regression for LEED-certified buildings, the existence of a rent and sales price premium is confirmed albeit with differences regarding the magnitude of the premium. Overall, the results of this study confirm that LEED and Energy Star buildings exhibit higher rental rates and sales prices per square foot controlling for a large number of location- and property-specific factors.

International financial centres, office market rents and volatility

Despite continuing developments in information technology and the growing economic significance of the emerging Eastern European, South American and Asian economies, international financial activity remains strongly concentrated in a relatively small number of international financial centres. That concentration of financial activity requires a critical mass of office occupation and creates demand for high specification, high cost space. The demand for that space is increasingly linked to the fortunes of global capital markets. That linkage has been emphasised by developments in real estate markets, notably the development of global real estate investment, innovation in property investment vehicles and the growth of debt securitisation. The resultant interlinking of occupier, asset, debt and development markets within and across global financial centres is a source of potential volatility and risk. The paper sets out a broad conceptual model of the linkages and their implications for systemic market risk and presents preliminary empirical results that provide support for the model proposed.

Stochastic volatility jump-diffusions for European equity index dynamics

Major research on equity index dynamics has investigated only US indices (usually the S&P 500) and has provided contradictory results. In this paper a clarification and extension of that previous research is given. We find that European equity indices have quite different dynamics from the S&P 500. Each of the European indices considered may be satisfactorily modelled using either an affine model with price and volatility jumps or a GARCH volatility process without jumps. The S&P 500 dynamics are much more difficult to capture in a jump-diffusion framework.

Volatility forecasting for risk management

Recent research has suggested that forecast evaluation on the basis of standard statistical loss functions could prefer models which are sub-optimal when used in a practical setting. This paper explores a number of statistical models for predicting the daily volatility of several key UK financial time series. The out-of-sample forecasting performance of various linear and GARCH-type models of volatility are compared with forecasts derived from a multivariate approach. The forecasts are evaluated using traditional metrics, such as mean squared error, and also by how adequately they perform in a modern risk management setting. We find that the relative accuracies of the various methods are highly sensitive to the measure used to evaluate them. Such results have implications for any econometric time series forecasts which are subsequently employed in financial decisionmaking.