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本篇論文以滬深300 指數調整前後期的異常報酬、影子成本、流動性、資訊不稱性及套利風險的變動觀察中國投資者的行為。本研究發現在調整後的短期間中中國股票的報酬與國外文獻的變動方向一致,調入股將上漲而調出股則下跌，但於長期則有十分明顯的相反傾向。本文將影子成本等四個變數加入作前後期變動的觀察。發現調整期前後影子成本、流動性、套利風險和資訊不對稱性的變動都與與文獻變動方向假設一致。最後本文把異常報酬作應變數，其餘各項作自變數去觀察四個變數影響報酬的程度和方向。回歸後發現只有流動性的影響符合前人以S&P500 作指標的研究,其他則是有著不一致的影響。本文認為這個現象與文獻中不同的原因是滬 深300 指數偏向於納入高估的股票而剔除低估的股票。滬深300 指數是以股票前一年的交易量大小作標準，這使得81%交易量為個人投資者提供的滬深300 指數偏向納入高估股票。這可能使得中國市場的指數調整效應與文獻並不一致。 / This paper empirically examines the differences of abnormal return, shadow cost, liquidity effect, information asymmetry and arbitrage risk during the composition change of CSI300 index to observe the behavior of investors in China market. Although this paper examines the short term return of adjusted stock change in the same direction as recent studies, added stocks increase and deleted stocks decrease, the long term return reverse. This paper also computes those four variables to observe their changes during the adjustment. The results show that the movements of these four variables are similar to the previous studies. To observe how these variables affect the return of the stocks, this paper computes a regression analysis with the cumulative abnormal return as the dependent variable. The results show that only the affection of liquidity matches the recent studies of S&P 500, when the others are not. The reason of this phenomenon maybe because of the CSI 300 index intends to include the overestimated stocks and exclude the underestimated stocks. The adjustment is determined by the past one year trading volume, which means that the market, with individual investors provided 81 % of trading volume, may possibly overestimate the included stocks. That maybe the reason why the influence of composition change is not similar to recent studies.

This dissertation consists of three essays. The first essay focuses on idiosyncratic volatility as a primary arbitrage cost for short sellers. Previous studies document (i) negative abnormal returns for high relative short interest (RSI) stocks, and (ii) positive abnormal returns for low RSI stocks. We examine whether these market inefficiencies can be explained by arbitrage limitations, especially firms' idiosyncratic risk. Consistent with limits to arbitrage hypothesis, we document an abnormal return of -1.74% per month for high RSI stocks (>=95th percentile) with high idiosyncratic volatility. However, for similar level of high RSI, abnormal returns are economically and statistically insignificant for stocks with low idiosyncratic volatility. For stocks with low RSI, the returns are positively related to idiosyncratic volatility. These results imply that idiosyncratic risk is a potential reason for the inability of arbitrageurs to extract returns from high and low RSI portfolios. The second essay investigates market efficiency in the absence of limits to arbitrage on short selling. Theoretical predictions and empirical results are ambiguous about the effect of short sale constraints on security prices. Since these constraints cannot be eliminated in equity markets, we use trades from futures markets where there is no distinction between short and long positions. With no external constraints on short positions, we document a weekend effect in futures markets which is a result of asymmetric risk between long and short positions around weekends. The premium is higher in periods of high volatility when short sellers are unwilling to accept higher levels of risk. On the other hand, riskiness of long positions does not seem to have a similar impact on prices. The third essay studies investor behaviors that generate mispricing by examining relationship between stock price and future returns. Based on traditional finance theory, valuation should not depend on nominal stock prices. However, recent literature documents that preference of retail investors for low price stocks results in their overvaluation. Motivated by this preference, we re-examine the relationship between stock price and expected return for the entire U.S. stock market. We find that stock price and expected returns are positively related if price is not confounded with size. Results in this paper show that, controlled for size, high price stocks significantly outperform low price stocks by an abnormal 0.40% per month. This return premium is attributed to individual investors' preference for low price stocks. Consistent with costly arbitrage, the return differential between high and low price stocks is highest for the stocks which are difficulty to arbitrage. The results are robust to price cut-off of $5, and in different sub-periods. / Ph. D.

Der Milchsektor ist einer der bedeutendsten landwirtschaftlichen Sektoren in der Europäischen Union. Seit die Reformen der Gemeinsamen Agrarpolitik 2005 in Kraft traten, wurde der Markt stark liberalisiert und ist durch zunehmende Preisschwankungen gekennzeichnet. Für die Michviehbetriebe ist dies eine Herausforderung, denn Faktorpreisunsicherheit ist eng mit den betrieblichen Entscheidungsprozessen für die optimale langfristige Nutzung der Produktionsfaktoren verbunden. Ein weitreichender Teil der Literatur analysiert den Zusammenhang zwischen Betriebsgröße oder Betriebsführung und ökonomischer Effizienz. Die statische Effizienzmessung ist weitverbreitet, vernachlässigt jedoch die zeitliche Abhängigkeit und die Anpassungsprozesse der quasi-fixen Faktoren. Dies wird im Konzept der dynamischen Effizienzmessung aufgegriffen. Das verwendete Effizienzmodell berücksichtigt zudem Faktorpreisunsicherheit. Der Beitrag dieser Dissertation ist es, die dynamische Effizienz westdeutscher Milchviehbetriebe erstmals unter Unsicherheit zu analysieren. Es wird untersucht, ob die Produktionsfaktoren technisch und allokativ effizient einsetzen werden. Zudem wird die Rolle der Unsicherheit für die Faktornachfrage und die Effizienzmessung beleuchtet. Die Ergebnisse zeigen, dass die Milchviehbetriebe auf einem hohen technischen Effizienzniveau arbeiten im Vergleich zur allokativen Effizienz und dass die Futternachfrage negativ mit der Futterpreisvolatilität verbunden ist. Investitionen reagieren negativ auf die Volatilität des Milchpreises, wobei der Einfluss der Unsicherheit mit zunehmender Betriebsgröße steigt. Die Ergebnisse belegen, dass die Preisunsicherheit bei der (dynamischen) Effizienzmessung von entscheidender Bedeutung ist und die Vernachlässigung zu niedrigeren Effizienzwerten führt und die Betriebe ineffizient erscheinen. Diese Ergebnisse sind nicht nur für Milchviehbetriebe relevant, sondern auch für Sektoren, die durch volatile Marktbedingungen gekennzeichnet sind. / Dairy farming, the most important farming sector in the European Union, has been subject to considerable de-regulation since the 2005 EU Common Agricultural Policy came into effect and to increased commodity price volatility. This is a new challenge for dairy farms, since price volatility is related to farm-level decision-making with regard to the optimal factor allocation in the long run. A vast body of literature relates economic efficiency to dairy farm characteristics such as size or managerial ability. However, it is common for static approaches of efficiency which ignore the role of time and the adjustment processes of farms with respect to the quasi-fixed factors to be applied. The intertemporal linkages of production and investment decisions are emphasized by dynamic efficiency and an extended model incorporates factor price volatility. The contribution of this thesis is to analyze the dynamic efficiency of German dairy farms under uncertainty, which thus far has not been done. The application aims to investigate whether West German dairy farms use their production factors in a technically and allocative efficient way in the long run. Moreover, the application will explore the role of uncertainty for factor demand and efficiency measurement. The results show that the farms operate at high levels of technical efficiency in comparison to allocative efficiency and that feed demand is negatively related to the variance of the feed concentrate price. Investment is negatively related to the variance of the milk price and the effect increases with farm size. The results further show empirical evidence for considering uncertainty when deriving (dynamic) efficiency measures: neglecting uncertainty within the estimation procedure will underestimate the average efficiency score, and thus farms appear inefficient. This finding is not only interesting for dairy farms; it also applies to other sectors that operate in highly-volatile markets.