住宅价格与经济基本面的实证研究——以上海市为例

近几年来,我国房地产市场发展迅速,个别区域性房地产市场出现了价格过高的现象.对此,国家采取了一系列宏观调控措施.对于房地产价格的合理与否,目前仍然存在着争议.影响住宅实际价格的因素主要是土地价格和住宅价格的历史信息.而可支配收入对价格的影响并不显著,因此应加强对不合理的房地产投机需求的调控.     

股票价格对物价水平的影响

股票价格作为最重要的金融资产价格，会通过“财富效应”、“替代效应”、“预期效应”、“新产品效应”和“工资效应”等途径影响投资和消费等宏观经济变量，进而影响包括商品劳务价格在内的一般物价水平。在发达国家和发展中国家，股票价格影响物价水平的方向和程度有着重大区别。     

浅议网络经济条件下的理财创新

网络经济是没有时空、地域限制的生产者和消费者直接见面的经济,它对传统的财务理论与实践既提出了挑战,又提供了创新的机会.本文就网络经济条件下,财务管理如何创新的问题作了探讨.     

Economic Risk Factors and Commercial Real Estate Returns

A great deal of research has focused on the links between stock and bond market returns and macroeconomic events such as fluctuations in interest rates, inflation rates, and industrial production. Although the comovements of real estate and other asset prices suggests that these same systematic risk factors are likely to be priced in real estate markets, no study has formally addressed this issue. This study identifies the growth rate in real per capita consumption, the real T-bill rate, the term structure of interest rates, and unexpected inflation as fundamental drivers or state variables that systematically affect real estate returns. The finding of a consistently significant risk premium on consumption has important ramifications for the vast literature that has examined the (risk-adjusted) performance of real estate, for it suggests that prior findings of significant abnormal returns (either positive or negative) that have ignored consumption are potentially biased by an omitted variables problem. The results also have important implications for dynamic asset allocation strategies that involve the predictability of real estate returns using economic data.     

动态资本资产定价理论评述

本文主要讨论了动态资产定价理论的产生和发展.默顿和布里登使用贝尔曼开创的动态规划方法和伊藤随机分析技术,重新考察在由随机过程驱动的不确定环境下,个人如何连续地做出消费/投资决策,使得终身效用最大化.无须单期框架中的严格假定,他们也获得了连续时间跨期资源配置的一般均衡模型--时际资产定价模型(ICAPM)以及消费资产定价模型(CCAPM).这些工作开启了连续时间金融方法论的新时代.     

The macroeconomic determinants of technology stock price volatility

Stock prices reflect the value of anticipated future profits of companies. Since business cycle conditions impact the future profitability of firms, expectations about the business cycle will affect the current value of firms. This paper uses daily and monthly data from July 1986 to December 2000 to investigate the macroeconomic determinants of US technology stock price conditional volatility. Technology share prices are measured using the Pacific Stock Exchange Technology 100 Index. One of the novel features of this paper is to incorporate a link between technology stock price movements and oil price movements. The empirical results indicate that the conditional volatilities of oil prices, the term premium, and the consumer price index each have a significant impact on the conditional volatility of technology stock prices. Conditional volatilities calculated using daily stock return data display more persistence than conditional volatilities calculated using monthly data. These results further our understanding of the interaction between oil prices and technology share prices and should be of use to investors, hedgers, managers, and policymakers.     

Mood and Judgment of Subjective Probabilities: Evidence from the U.S. Index Option Market

Numerous psychological studies show that weather conditions affect people'smood and that mood states are correlated with people's subjective evaluationof future probabilities. In this paper, a new approach is developed and assetmarket data are employed to test the mood-subjective probability relation. Cloudcover and precipitation volume serve as two mood proxies. Our statistical analysissuggests that bad mood states are characterized by investors placing higher probabilitieson adverse events.     

Characteristics of Earnings-Leading Versus Price-Leading Firms

This study attempts to identify firm characteristics that explain the disparity between the information content of accounting earnings and stock prices. Granger's causality concept was employed to classify sample firms into four groups: price-leading firms, feedback-system firms, earnings-leading firms, and no-causation firms. The feedback-system firms were either combined with the no-causation firms or eliminated entirely to form three sample groups. The entire sample firms then were divided into two classes. The first is for estimation, and the second is for prediction. Results indicate that firm size, capital structure, R-square of regressing prices at time t against earnings at time t – 1, R-square of regressing earnings at time t against prices at time t – 1, and percentage of shares held by institutions are the significant explaining variables. The application of the coefficient estimates to the hold-out sample indicates that 76.2% of the firms can be correctly classified into the corresponding groups. These results were consistent with those from canonical discrimination and other multivariate statistical methods.     

On the Distribution of CBOE Option Trade Prices Occurring Between Consecutive Stock Trades

This paper examines the volume distribution of option trade prices that occurs when the underlying stock price remains constant. The width of these option trade price bands provides direct evidence on the law of one price and the redundancy of options assumed in many option models. We find that index option bands are narrower than equity option bands. Furthermore, for both equity and index options, puts have narrower bandwidths than calls. In general, option price bandwidth is narrow and can be explained by the minimum price movement allowed by the Chicago Board Options Exchanges (CBOE). This supports the single price law and the redundancy assumption. The existence of bid/ask quotes on the option does not materially affect the above results although it does alter the frequency of multiple option trade prices for a given underlying stock price. We note that over 53% of option trading volume occurs without bid/ask quotes on the CBOE compared to less than 15% a decade ago. Our results suggest that the effective bid/ask spread on options is probably no larger than the minimum price movements allowed by the CBOE. Furthermore, the need for the liquidity services of market makers may be declining if the decline in quoting activity stems from cross trading (i.e. trades not involving market makers).     

The Announcement Effect of an Airport Expansion on Housing Prices

The purpose of this study is to examine the influence of the announcement of a new airport hub on housing prices near the airport. While numerous studies of airport noise have found that high noise levels reduce property values, few have been able to measure the announcement effect on values. The results indicate that after controlling to extraneous influences, housing property prices in a 2.5 mile band from the Greensboro/High Point/Winston Salem metropolitan airport declined approximately 9.2% in the post-announcement period. In the next 1.5-mile band, house prices declined approximately 5.7% in the post-announcement period.