The impact of individual and institutional investor sentiment on the market price of risk

We examine the effect of individual and institutional investor sentiment on the market price of risk derived from DJIA and S&P500 index returns. Consistent with behavioral asset pricing models, we find significant positive response of rational sentiment suggesting greater incentive for rational investors to engage in arbitrage when the compensation for taking risk is greater. Further, an increase in irrational optimism leads to a significant downward movement, but an increase in rational sentiment does not lead to a significant change market price of risk. These results are robust for both market indexes, DJIA and S&P500 and for both individual and institutional investor sentiment.     

基于学习风格的高职教育课程体系构建的理论思考

高等职业教育应该贯彻的一个最基本的教育教学原则是因材施教 ,依据高职学生的智力因素和非智力因素 ,选择相应的教学内容 ,采取不同的教育教学策略 ,实现现代高等职业教育“合格”、“胜任”的培养目标。教学内容的选择实质是高职教育课程体系的构建过程 ,其主要依据是学科的发展现状、社会的需求以及学生的特点。其中 ,如何使教学内容更加适合高职学生的特点 ,已经成为高职教育课程体系构建的中心问题。     

The effect of operational slack,diversification, and vertical relatedness on the stock market reaction to supply chain disruptions

This paper empirically examines whether operational slack, business diversification, geographic diversification, and vertical relatedness influence the stock market reaction to supply chain disruptions. The results are based on a sample of 307 supply chain disruptions announced by publicly traded firms during 1987–1998. Our analysis shows that firms with more slack in their supply chain experience less negative stock market reaction. The extent of business diversification has no significant effect on the stock market reaction. Firms that are more geographically diversified experience a more negative stock market reaction. We find that firms with a high degree of vertical relatedness experience a less negative stock market reaction. These results have important implications on how firms design and operate their supply chains to mitigate the negative effect of supply chain disruptions.     

Rational plunging and the option value of sequential investment: The case of petroleum exploration

The potential to invest sequentially in related assets creates a tradeoff between diversification and concentration. Loading a portfolio with correlated assets has the potential to inflate variance, but also creates information spillovers and real options that may augment total return and mitigate variance. We examine this tradeoff in the context of petroleum exploration. Using a simple model of geological dependence, we show that the value of learning options creates incentives for investors to plunge into dependence; i.e., to assemble portfolios of highly correlated exploration prospects. Risk-neutral and risk-averse investors are distinguished not by the plunging phenomenon, but by the threshold level of dependence that triggers such behavior. Aversion to risk does not imply aversion to dependence. Indeed the potential to plunge should be larger for risk-averse investors than for risk-neutral investors. We test the empirical validity of our theory by examining bidding activity in petroleum lease sales. We find significant plunging behavior across a broad sample of oil companies. We also find that privately-held firms pursue even more concentrated (less diversified) prospect portfolios than publicly-held firms—which we attribute to risk aversion rather than size.     

Evaluating factor forecasts for the UK: The role of asset prices

This paper applies a large data set, consisting of 167 monthly time series for the UK, both economic and financial, to simulate out-of-sample predictions of industrial production, inflation, 3-month Treasury Bills, and other variables. Fifteen dynamic factor models that allow forecasting based on large panels of time series are considered. The performances of these factor models are then compared to the following competing models: a simple univariate autoregressive, a vector autoregressive, a leading indicator, and a Phillips curve models. The results show that the best dynamic factor models outperform the competing models in forecasting at 6-, 12-, and 24-month horizons. Thus, the financial markets may have predictive power for the economic activity. This can be a useful tool for central banks and financial institutions, which may use the factor models to construct leading indicators of the economic conditions. In addition, researchers can see a strategic application of factor models.     

The Measurement of Consumption Efficiency Considering the Discrete Choice of Consumers

In this study we propose a mathematical definition of the consumption efficiency of multi-attribute products in the price–quality space. A new model, the discrete Range Adjusted Measure (RAM) model, is suggested as an empirical tool to measure the level of consumption efficiency. We further discuss the effect of consumption efficiency on the innovation incentive. Empirical work is made for the mobile phone market. We expect that the consumption efficiency concept will contribute to the extension of the traditional framework of production efficiency analysis on the one hand and to the understanding of the nature of innovation in a technology-intensive market on the other hand.JEL Classification: C67, D11, D12, D21