The essays empirically show the impact of investors speculation and disagreements on the returns and trading volume of securities. The results also shed light on the central issues of price formation and investors’ trading motives in security markets. The first essay investigates whether the trading activities of retail investors affect option prices through volatility speculation. This essay empirically shows that higher retail trading proportions are related to lower delta-hedged option returns. The phenomenon is more pronounced before earnings announcements and among stocks with more time-varying and positively skewed volatility. The results suggest that retail investors speculate and pay a lottery premium on the expected future volatility, resulting in more expensive options in terms of higher implied volatilities. This systematic deviation of option-implied volatility from realized volatility suggests retail investor clientele as a behavioral-based driving force of volatility risk premium. The second essay investigates the motive of option trading. It is shown that option trading is mostly driven by differences of opinion, a finding different from the current literature that attempts to attribute option trading to information asymmetry. First, option trading around earnings announcements is speculative in nature and mostly dominated by small, retail investors. Second, around earnings announcements, option turnovers do not predict stock returns, once prior stock returns are controlled for. Third, regression results reveal that option trading is also significantly explained by differences of opinion at ordinary times. While informed trading is present in stocks, it is not detected in options. The third essay provides strong evidence of reduction in informational efficiency when there are short-sale constraints and disagreements. Post earnings announcement returns are found to be significantly lower for stocks with more dispersed opinions and stocks that are exogenously short-sale prohibited by the Hong Kong Stock Exchange, supporting Miller’s (1977) overvaluation hypothesis. The results also suggest short-sale constraint as an explanation to negative post earnings announcement drift.

The essays empirically show the impact of investors speculation and disagreements on the returns and trading volume of securities. The results also shed light on the central issues of price formation and investors’ trading motives in security markets. The first essay investigates whether the trading activities of retail investors affect option prices through volatility speculation. This essay empirically shows that higher retail trading proportions are related to lower delta-hedged option returns. The phenomenon is more pronounced before earnings announcements and among stocks with more time-varying and positively skewed volatility. The results suggest that retail investors speculate and pay a lottery premium on the expected future volatility, resulting in more expensive options in terms of higher implied volatilities. This systematic deviation of option-implied volatility from realized volatility suggests retail investor clientele as a behavioral-based driving force of volatility risk premium. The second essay investigates the motive of option trading. It is shown that option trading is mostly driven by differences of opinion, a finding different from the current literature that attempts to attribute option trading to information asymmetry. First, option trading around earnings announcements is speculative in nature and mostly dominated by small, retail investors. Second, around earnings announcements, option turnovers do not predict stock returns, once prior stock returns are controlled for. Third, regression results reveal that option trading is also significantly explained by differences of opinion at ordinary times. While informed trading is present in stocks, it is not detected in options. The third essay provides strong evidence of reduction in informational efficiency when there are short-sale constraints and disagreements. Post earnings announcement returns are found to be significantly lower for stocks with more dispersed opinions and stocks that are exogenously short-sale prohibited by the Hong Kong Stock Exchange, supporting Miller’s (1977) overvaluation hypothesis. The results also suggest short-sale constraint as an explanation to negative post earnings announcement drift.

This paper investigates both the information contents of recommendations disseminated by foreign security firms and the interaction of foreign security firms’ trading activities with their recommendations in Taiwan’s stock market. Using event study, correlation test, and regression analysis, we find negative average abcdrmal returns(AARs) and average cumulative abcdrmal returns(CARs) for negative and neutral foreign analysts’ recommendations levels and recommendation changes in the pre-recommendation period. AARs and CARs for positive recommendations in pre-recommendation period are positive, but reverse to negative three days after the event day. Our results also show that correlation coefficients of recommendations (both in recommendation levels and recommendation changes) and holding period returns are significantly positive in the pre-recommendation period, but insignificantly negative in the post-recommendation period. In the regression analyses, we find that price momentum factor is significantly related to foreign analysts’ recommendation, but the incremental contribution of this factor to foreign analysts’ recommendations are marginal and not significant. We also find that foreign security firms respond more rigorously to stocks receiving recommendation above buy recommendations and stocks being downgraded. These results show that foreign security firms are more conservative toward trading stocks in Taiwan’s stock market. They only buy stocks above buy recommendations (in a delay pattern), but immediately sell downgraded stocks.

This thesis utilizes statistical physics concepts and mathematical modeling to study complex systems. I investigate the emergent complexities in two systems: (i) the stock volume volatility in the United States stock market system; (ii) the robustness of networks in an interdependent lattice network system. In Part I, I analyze the United States stock market data to identify how several financial factors significantly affect scaling properties of volume volatility time intervals. I study the daily trading volume volatility time intervals between two successive volume volatilities above a certain threshold q, and find a range of power law distributions. I also study the relations between the form of these distribution functions and several financial factors: stock lifetimes, market capitalization, volume, and trading value. I find that volume volatility time intervals are short-term correlated. I also find that the daily volume volatility shows a stronger long-term correlation for sequences of longer lifetimes. In Part II, I apply percolation theory to interacting complex networks. The dependency links between the two square lattice networks have a typical length r lattice units. For two nodes connecting by a dependency link, one node fails once the node on which it depends in the other network fails. I show that rich phase transition phenomena exist when the length of the dependency links r changes. The results suggest that percolation for small r is a second-order transition, and for larger r is a first-order transition. The study suggests that interdependent infrastructures embedded in two-dimensional space become most vulnerable when the interdependent distance is in the intermediate range, which is much smaller than the size of the system.

One basic assumption of the celebrated Black-Scholes-Merton PDE model for pricing derivatives is that the volatility is a constant. However, the implied volatility plot based on real data is not constant, but curved exhibiting patterns of volatility skews or smiles. Since the volatility is not observable, various stochastic volatility models have been proposed to overcome the problem of non-constant volatility. Although these methods are fairly successful in modeling volatilities, they still rely on the implied volatility approach for model implementation. To avoid such circular reasoning, we propose a new class of stochastic volatility models based on directly observable volatility proxies and derive the corresponding option pricing formulas. In addition, we propose a new GARCH (1,1) model, and show that this discrete-time stochastic volatility process converges weakly to Heston's continuous-time stochastic volatility model. Some Monte Carlo simulations and real data analysis are also conducted to demonstrate the performance of our methods.

This dissertation investigates the effects of changes in the accounting environment on the capital markets. Included are three manuscripts, each of which, make an important contribution to the accounting literature. The first two manuscripts investigate the impact and importance of analysts' forecasts. The third manuscript documents the impact of eliminating an important accounting disclosure. This dissertation makes the following contributions to the accounting literature. The first manuscript documents that investor skepticism towards meet/beat firms appears to have been a temporary phenomenon and investors have resumed rewarding firms that meet/beat analysts' earnings expectations. Further, the study provides evidence that changes in the analyst forecasting environment also contributed to this temporary decline implying that the scandals did not have as strong of an effect on investors' confidence in earnings as previously believed. The second manuscript contributes to the accounting literature by documenting the importance of meeting/beating cash flow forecasts to participants in the debt markets. Finally, the third manuscript contributes to the existing literature regarding the value relevance of the IFRS -- U.S.GAAP reconciliation by documenting a significant decrease in publicly available information to equity investors at the first reporting period following the SEC's decision to eliminate the reconciliation. All of these manuscripts extend what is currently known about the importance of public disclosures to capital market participants. / Ph. D.

According to theory, trading volume decreases in information asymmetries, i.e. when there are differences in information. This is due to the fact that uninformed investors delay their trades when they are facing adverse selection. When the asymmetry is resolved there should be a corresponding increase in trading volume. Around earnings announcements (scheduled an-nouncements) this asymmetry is greater than normal, hence one can expect a decrease in trading volume. Around unexpected announcements such as acquisition announcement (unscheduled announcements) a total increase is instead expected because of an increase in trading by informed investors. All these effects are likely to be greater for smaller stocks. The purpose of this thesis is to investigate the trading volume before- and after scheduled announcements and the trading volume before unscheduled announcements in order to investigate how informed- and uninformed investors behave in information asymmetries on Stockholmsbörsen. The method is quantitative with secondary data from the Stockholm Stock exchange from 1998-2004. The method is the same as Chae (2005) uses with paired-samples t-tests. It tests whether the change in trading volume is different from a benchmark consisting of an average of the trading volume 30 days before the announcement. We found a statistically significant decrease in trading volume in 6 of 10 days before a scheduled announcement and an increase also on 7 of 10 days after the announcement. For unscheduled announcements we found an increase before it was released but were not able to prove it statistically. We conclude that uninformed investors behave strategically before scheduled announcements in order to avoid adverse selection. We could not conclude that the effects are greater for smaller stocks.

Background: According to theory, trading volume decreases in information asymmetries, i.e. when there are differences in information. This is due to the fact that uninformed investors delay their trades when they are facing adverse selec-tion. When the asymmetry is resolved there should be a corresponding in-crease in trading volume. Around earnings announcements (scheduled an-nouncements) this asymmetry is greater than normal, hence one can expect a decrease in trading volume. Around unexpected announcements such as acquisition announcement (unscheduled announcements) a total increase is instead expected because of an increase in trading by informed investors. All these effects are likely to be greater for smaller stocks. Purpose: The purpose of this thesis is to investigate the trading volume before- and after scheduled announcements and the trading volume before unscheduled announcements in order to investigate how informed- and uninformed in-vestors behave in information asymmetries on Stockholmsbörsen. Method: The method is quantitative with secondary data from the Stockholm Stock exchange from 1998-2004. The method is the same as Chae (2005) uses with paired-samples t-tests. It tests whether the change in trading volume is different from a benchmark consisting of an average of the trading volume 30 days before the announcement. Conclusion: We found a statistically significant decrease in trading volume in 6 of 10 days before a scheduled announcement and an increase also on 7 of 10 days after the announcement. For unscheduled announcements we found an in-crease before it was released but were not able to prove it statistically. We conclude that uninformed investors behave strategically before scheduled announcements in order to avoid adverse selection. We could not conclude that the effects are greater for smaller stocks.

By the time of 2011, Taiwan Futures Exchange has issued 8 kinds of stock index futures. By taking a closer look at the transaction of the index futures, we found out that, in terms of trading volume, there is a significant difference among each others. Based on the observation, our research focuses on studying the existence value of the index futures in terms of hedging and speculating functions. The definition of futures¡¦ existence value is that the investors can use the futures to achieve the objectives of hedging and speculating in financial market. The research objects are TX, TE, TF, MTX, XIF, and GTF. The method to measure the hedging function is based on Portfolio and Hedging Theory of Johnson (1959). We estimate the hedging ratio with different data periods to calculate the hedging effectiveness. The method to measure the speculating function is based on the theory of Rutledge (1979) et al. We calculate the speculating trading volume to study the relationship with the basis by using OLS model. The empirical result shows that, in the hedging function, all of the index futures¡¦ hedging ratios are almost less than 1, and all have high hedging effectiveness. There is no significant influence on hedging effectiveness with different data periods and issuing time. In the speculating function, TX, MTX, and GTF will make speculating activities increase when the basis get bigger but TE, TF, and XIF will not. To sum up, TX, MTX, and GTF have higher existence value than TE, TF, and XIF. At last, based on the observation from this study, we propose several policy suggestions for enhancing the existence value of the index futures in financial market.

Using the intraday data on the Taiwan Stock Exchange (TWSE), we address the issue of the informativeness of the limit order book in the periodic call market. We find that the pre-call information variables, i.e., the market order and the radius of the order book, have significant impacts on the trade variables, i.e., trading volume, the post-call bid-ask spread, and the trader surplus. Furthermore, we are able to show that the radius, as well as the market order, contains two differential forces in impacting these trade variables.