The final disposition of assets at the conclusion of joint venture arrangements is important to an understanding of the motivation to pursue a joint venture and the wealth created by these collaborations. A comparison between conventional asset sales and asset sales occurring within a joint venture structure shows that the total wealth created is larger if the assets have been under shared control in a joint venture. Our results support the contention that the establishment of a joint venture creates an opportunity for a relationship-based exchange of information that can serve as a mechanism to transfer assets in the presence of a high degree of asymmetric information.

We analyze joint ventures initiated by two publicly traded firms, and compare the results to asset sales and mergers. Combined returns are significantly greater for joint ventures than asset sales, and smaller than mergers. Gains are shared between joint venture parties, unlike asset sales and mergers where all gains accrue to sellers/targets. Ownership structure has no effect on joint venture returns. Combined gains from quasi-asset-sale joint ventures are significantly greater than for asset sales, and similar to mergers. Horizontal joint ventures generate greater gains than vertical or cross-industry ventures, and there is evidence that horizontal ventures capitalize expected monopoly rents.

This paper contributes to our understanding of the informational content of implied volatility. Here we examine whether the S&P 500 implied volatility index (VIX) contains any information relevant to future volatility beyond that available from model based volatility forecasts. It is argued that this approach differs from the traditional forecast encompassing approach used in earlier studies. The findings indicate that the VIX index does not contain any such additional information relevant for forecasting volatility.

This paper considers the estimation of the expected rate of return on a set of risky assets. The approach to estimation focuses on the covariance matrix for the returns. The structure in the covariance matrix determines shared information which is useful in estimating the mean return for each asset. An empirical Bayes estimator is developed using the covariance structure of the returns distribution. The estimator is an improvement on the maximum likelihood and Bayes–Stein estimators in terms of mean squared error. The effect of reduced estimation error on accumulated wealth is analyzed for the portfolio choice model with constant relative risk aversion utility.