Oleksandr Zhylyevskyy

Impact of idiosyncratic volatility on stock returns: A cross-sectional study.

This paper proposes a new approach to estimate the idiosyncratic volatility premium. In contrast to the popular two-pass regression method, this approach relies on a novel GMM-type estimation procedure that uses only a single cross-section of return observations to obtain consistent estimates. Also, it enables a comparison of idiosyncratic volatility premia estimated using stock returns with different holding periods. The approach is empirically illustrated by applying it to daily, weekly, monthly, quarterly, and annual US stock return data over the course of 2000–2011. The results suggest that the idiosyncratic volatility premium tends to be positive on daily return data, but negative on monthly, quarterly, and annual data. They also indicate the presence of a January effect.

A Methodology to Support Product-Differentiation Decisions

Choosing the right set of new products to offer is a key driver of profitability. New products often share some design attributes with existing products, thus, firms need to decide which attributes to keep common and which to differentiate. We propose and empirically implement a new methodology that can help managers to navigate the complex decision of where to focus differentiation, using “looks-like” prototypes that typically become available in the later stages of the product-development process. Our methodology complements early stage product-positioning methods, such as conjoint analysis and perceptual mapping. It also offers a way to estimate the impact of context dependence on choice. Finally, our methodology provides a way to test empirically whether perceptual mapping based on pairwise similarity judgments is appropriate for a product category. Using data obtained from a major wristwatch manufacturer, we are able to suggest guidelines on how to differentiate the firms offerings and estimate the magnitude of context dependent effects. We also find that for wristwatches, attributes that drive perceptions differ from those that drive choice. Overall, our approach can help avoid falling into the trap of focusing variety on attributes that are costly to differentiate and have little impact on choice.