STRATEGIC ASSET ALLOCATION FOR LONG‐TERM INVESTORS: PARAMETER UNCERTAINTY AND PRIOR INFORMATION

We study the effect of parameter uncertainty on the long‐run risk for three asset classes: stocks, bills and bonds. Using a Bayesian vector autoregression with an uninformative prior we find that parameter uncertainty raises the annualized long‐run volatilities of all three asset classes proportionally with the same factor relative to volatilities that are conditional on maximum likelihood parameter estimates. As a result, the horizon effect in optimal asset allocations is much weaker compared to models in which only equity returns are subject to parameter uncertainty. Results are sensitive to alternative informative priors, but generally the term structure of risk for stocks and bonds is relatively flat for investment horizons up to 15 years. Copyright © 2013 John Wiley & Sons, Ltd.     

Correlation dynamics and international diversification benefits

Forecasting the evolution of security co-movements is critical for asset pricing and portfolio allocation. Hence, we investigate patterns and trends in correlations over time using weekly returns for developed markets (DMs) and emerging markets (EMs) over the period 1973–2012. We show that it is possible to model co-movements for many countries simultaneously using BEKK, DCC, and DECO models. Empirically, we find that correlations have trended upward significantly for both DMs and EMs. Based on a time-varying measure of diversification benefits, we find that it is not possible to circumvent the increasing correlations in a long-only portfolio by adjusting the portfolio weights over time. However, we do find some evidence that adding EMs to a DM-only portfolio increases diversification benefits.     

A bivariate Poisson count data model using conditional probabilities

The applied econometrics of bivariate count data predominantly focus on a bivariate Poisson density with a correlation structure that is very restrictive. The main limitation is that this bivariate distribution excludes zero and negative correlation. This paper introduces a new model which allows for a more flexible correlation structure. To this end the joint density is decomposed by means of the multiplication rule in marginal and conditional densities. Simulation experiments and an application of the model to recreational data are presented.     

Non-parametric estimation of historical volatility

Evolving volatility is a dominant feature observed in most financial time series and a key parameter used in option pricing and many other financial risk analyses. A number of methods for non-parametric scale estimation are reviewed and assessed with regard to the stylized features of financial time series. A new non-parametric procedure for estimating historical volatility is proposed based on local maximum likelihood estimation for the t-distribution. The performance of this procedure is assessed using simulated and real price data and is found to be the best among estimators we consider. We propose that it replaces the moving variance historical volatility estimator.     

Effects of commitment on intentional loyalty at the person-to-person and person-to-firm levels

This study explores how customers’ affective commitment and calculative commitment to the personal adviser and bank, respectively, affect their intentional loyalty to the personal adviser and bank. Data were collected using a web survey of mass affluent customers of a major Swedish bank. Responses were measured and analysed using factor, correlation, and regression analyses. The results reveal that the person-to-person and person-to-firm loyalty categories are influenced by affective and calculative commitment to the personal advisor and by affective commitment to the bank, but not by calculative commitment to the bank. Moreover, there is a strong relationship between customer loyalty to the personal adviser and to the bank. It can be concluded that affective commitment has a stronger overall impact on customer loyalty than does calculative commitment, indicating the importance of creating affective ties with customers, and that personal advisers are central to bank – customer relationships. The importance of financial issues to mass affluent customers implies that both affective commitment and calculative commitment to the personal adviser are important in building customer loyalty to a bank or brand.     

Complementary technologies,knowledge relatedness,and invention outcomes in high technology mergers and acquisitions

Prior research on M&As and invention outcomes has not systematically examined the influence of two types of knowledge differences. Knowledge relatedness has typically been equated with knowledge similarity and the separate influence of knowledge complementarity has been overlooked. Similarly, studies examining innovation outcomes of M&As have typically focused on the role of technological knowledge and overlooked the influence of scientific knowledge. We develop a model of relatedness and invention performance of high‐technology M&As that considers science and technology similarity and complementarity as important drivers of invention. We test the model using a sample of M&As from the drug, chemical, and electronics industries and a fine‐grained measure of knowledge relatedness that distinguishes between science and technology relatedness. We find that complementary scientific knowledge and complementary technological knowledge both contribute to post‐merger invention performance by stimulating higher quality and more novel inventions. This suggests that high‐technology firms seeking acquisitions should search for, identify, and acquire businesses that have scientific and technological knowledge that is complementary to their own. Our results also suggest that similarities in knowledge facilitate incremental renewal, while complementarities would make discontinuous strategic transformations more likely, and that absorptive capacity research should be expanded to consider complementarities as well as similarities. Copyright © 2010 John Wiley & Sons, Ltd.     

Intradaily volatility and adjustment

Intradaily volatility is related to the speed of adjustment of prices towards their intrinsic values. The decomposition of volatility into intrinsic and noise related components is demonstrated to be impacted by speeds of adjustment. Intradaily speeds of adjustment are estimated for U.K. index data and some empirical evidence of overreaction at the open and underreaction at the close of the trading day found for the FTSE100 index. The major result that we report in this paper is that differential intradaily volatilities at the index level are related to differential speeds of adjustment, thus providing insights into the similar results reported in U.S. index studies, such as [Gerety, M., Mulherin, J., 1994. Price formation on stock exchanges: the evolution of trading within the day. The Review of Financial Studies 7, 609–629].     

Investor efficiency in the face of takings

Governmental entities at all levels are empowered to acquire private property for the public's benefit, provided that just compensation is paid. The level of compensation typically viewed by courts as just is market value, but questions arise as to whether market value compensation motivates the private owner of land, potentially subject to a taking, to improve the property to a degree that is socially efficient. Earlier works have found market value to be a compensation level too high to promote efficiency. The present paper offers an analysis, based on a simple model of investor profit maximization, that provides a unified view of models presented in some important earlier works. In a special application of the general case, it is shown that market value can be too low a level of compensation to promote efficient behavior by the land owner.