Thesis (Ph.D.)--University of Delaware, 2007. / Principal faculty advisors: James L. Butkiewicz, Dept. of Economics; Jeffrey H. Harris, Dept. of Finance. Includes bibliographical references.

Thesis (Ph. D.)--College of William and Mary. / Vita. Includes bibliographical references.

This study examines whether short-sellers and financial analysts develop complementary information about future earnings and returns and assesses whether investors can improve predictions made by each of these intermediaries using information provided by the other. The first main result is that the relative short interest ratio (shares sold short divided by total shares outstanding) contains information that is useful for predicting future earnings, beyond (i.e., incremental to) the information in analyst forecasts. I also find that analysts do not fully incorporate short interest information into their forecasts and demonstrate that analyst forecasts can be improved (i.e., can be made to be less biased and more accurate) by adjusting for short interest information. The second main result is that analyst forecast revisions contain information that is useful for predicting future abnormal returns, beyond the information in the relative short interest ratio. I demonstrate that portfolios of stocks formed based on consistent signals from short-sellers and analysts produce abnormal return spreads that are significantly larger than spreads produced by portfolios formed using signals from short-sellers alone. Collectively, the evidence suggests that short-sellers and analyst provide complementary information about future firm performance that is useful to investors.

This paper studies the persistence of daily returns of 21 German stocks from 1960 to 2008. We apply a widely used test based upon the modified R/S-Method by Lo [1991]. As an extension to Lux [1996] and Carbone et al. [2004] and in analogy to moving average or moving volatility, the statistics is calculated for moving windows of length 4, 8, and 16 years for every time series. Periods of persistence or long memory in returns can be found in some but not all time series. Robustness of results is verified by investigating stationarity and short memory effects.

The main purpose of this thesis is to investigate what is the optimal futures-spot arbitrage strategy for China‘s stock index futures investment. Specifically, Index replication method and no-arbitrage pricing model are examined. We compare the different combinations of ETFs portfolio in mainland China with W.I.S.E-CSI 300 ETF in Hong Kong in three aspects including liquidity level, correlation of ETFs with underlying index, and tracking error of the replication methods. Then, we add several new parameters into interval pricing model to obtain a more accurate no-arbitrage band. As a result, we found that the portfolio of SSE 50 ETF, SZSE 100 ETF, and SSE Bonus ETF could provide the best tracking effect of CSI 300 Index, with different weight as 0.369, 0.403, and 0.19 in turn separately. Furthermore, the new modified pricing model could find out more arbitrage opportunities than interval pricing model especially for reverse cash-and-carry arbitrage. On the whole, the optimal arbitrage strategy for investment on CSI 300 Index futures consist of two steps, implement ETFs portfolio replicate CSI 300 Index and using new modified pricing model to discover and define arbitrage opportunities then to apply futures-spot arbitrage. At the end of thesis, we also give a small case study to illustrate how to exercise the arbitrage strategy in realistic situation.

Abstract Since the open of domestic financial market recent years, the financial products have become more and more various. In six years, there has been 2.7 funds issued every month on average. For investors, how to choose a good fund company and an appropriate fund from plenty of new offered funds is uneasy. Particularly new offered fund has no history data to examine the performance, and also lacks the regular benchmarks like £]and Sharp ratio. This thesis uses the data of the domestic stock funds which were offered over 1 year from 1997 January 1 to 2006 December 31.The data resources is from TEJ. The study will distinguish all data from whether the prospectuses regulate the funds¡¦ stock holding percentage over 70 ¢H or not. Then we want to investigate the behavior in the first year and to discuss if the fund managers¡¦ experiment will result in the abnormal performance. The study results shows that the stock holding percentage of the domestic stock funds have been over 70¢H on average since offered 3 months, but the percentage of the funds with free investment period of 3 months is less than 60¢H. However the percentage of the funds with free investment period of 6 months would rise to be 70¢H early in the second or third month. We try to use a statistic way and set a dummy variable to test whether there is different between the performance of the funds with free period and those with limited period. The result shows that there is no fund performance difference between these two period. From the second month after the fund is offered, turnover rare is close or even over the average of one year. The average level is about 30¢H and it shows the domestic stock funds have changed stocks frequently since it is offered . The tenure of Fund managers¡¦ after domestic stock funds raised is 20 months on average from 95 months to 1 month.13¢Mof fund managers will be taken place less than half year after the fund offered, 39¢Mwill be less than 1 year. 60¢Mof the fund managers have ever managed other funds before the newly one which he manage now, but 40¢Mhave no such experiment. The statistics shows that there is no significant different between fund managers¡¦ experiment and fund¡¦s abnormal returns.

This dissertation examines stock return predictability with aggregate credit conditions. The aggregate credit conditions are empirically measured by credit standards (Standards) derived from the Federal Reserve Board's Senior Loan Officer Opinion Survey on Bank Lending Practices. Using Standards, this study investigates whether the aggregate credit conditions predict the expected returns and volatility of the stock market. The first essay, "Credit Conditions and Expected Stock Returns," analyzes the predictability of U.S. aggregate stock returns using a measure of credit conditions, Standards. The analysis reveals that Standards is a strong predictor of stock returns at a business cycle frequency, especially in the post-1990 data period. Empirically the essay demonstrates that a tightening of Standards predicts lower future stock returns. Standards performs well both in-sample and out-of-sample and is robust to a host of consistency checks including a small sample analysis. The second essay, "Credit Conditions and Stock Return Volatility," examines the role played by credit conditions in predicting aggregate stock market return volatility. The essay employs a measure of credit conditions, Standards in the stock return volatility prediction. Using the level and the log of realized volatility as the estimator of the stock return volatility, this study finds that Standards is a strong predictor of U.S. stock return volatility. Overall, the forecasting power of Standards is strongest during tightening credit periods.

It is wide believed that the economic growth is good to stockholders, but there still exist some arguments about the positive relationship between the economic growth and stock market returns. We prove that the economic growth has positive effect on the stock market returns. As a result, the stockholders could use the economic index to choose their target market to earn return. We find that the stock market could only reflect the short term condition of the country and could not reflect the long term accumulation of a country. That is, the national competitiveness could not reflect on the stock market return for stockholders in the long term. Otherwise, we also find that the capital formation and productivity are significantly positive to the stock market returns. We use the real GDP growth rate as the economic growth proxy and the national competitiveness rank to measure the national competitiveness from IMD competitiveness center. The time period of data is from 1997~2010. Fifty countries included in our sample.

The volatility of share prices is an important variable in most asset pricing models and option pricing formulas.Valuation of volatility of share prices have become a major challenge with the development of the knowledge-driven economy as evidence suggest that not all elements of company wealth are physical in nature. The purpose of this project entitled “The intensity of the firm’s intangible asset on the volatility of their stock price” is to check if the intensity of intangible assets in a firm’s balance sheet affects the volatility of their stock price. A brief overview of intangible assets is also included in this study. An OLS regression was run and the results of the entire data set gives a negative correlation between intensity of intangible assets and volatility of stock prices probably due to the fact that the volatility of the firm share prices are driven by uncertainty and expectation of future growth. An industry-grouping regression was carried out, the results shows that for basic pharmaceuticals there is a positive correlation between the intensity of intangible assets and their price volatility while the other three industry groups produce a negative correlation. The study relies on secondary data of randomly selected fourty (40) publicly traded companies in Europe from four different industry groupings namely: manufacture of basic pharmaceuticals, manufacture of food products and beverages, information technology and manufacture of basic metals.

There have been countless empirical studies conducted to test the validity of the Capital Asset Pricing Model（CAPM）since its naissance. However, few have considered the Chinese Stock Market. The purpose of this paper is to test the CAPM to see if it holds true in the Shanghai Stock Exchange (SSE). We use weekly stock returns from 100 companies listed on the SSE during 2000.1.1 to 2005.12.31. Black, Jensen and Scholes (1972) (time-series test) and Fama and MacBeth (1973) (cross-sectional test) methods were used to test the CAPM. We found that the excepted returns and betas are linear related with each other during the entire period of 2000.1.1 to 2005.12.31, which implies a strong support of the CAPM hypothesis. On the other hand, as the CAPM hypothesizes for the intercept, is it should equal zero and the slope should equal to the average risk premium. However, the results from the test refute the above hypothesizes and offer evidence against the CAPM. According to the findings of the empirical test, we conclude that the Capital Asset Pricing Model does not give a valid description of the Chinese Stock Market during 2000.1.1 to 2005.12.31.