The profitability and the sources of the returns on momentum strategy have always been a popular subject of study in the financial field. Nevertheless, there exist significant discrepancies between the conclusions of the papers due to the difference in time period and the emphasis on average results. Thus, the purpose of this paper is to investigate momentum strategy with information uncertainty in Taiwan stock market during the period 1990-2009 given the basis on the research method of Jegardeesh and Titman(1993). The result shows that momentum strategy cannot averagely obtain significantly positive returns in the long run in Taiwan stock market and moreover it presents an enormous short-term reversal. Besides, in terms of business cycle, there is still no significant return on momentum strategy either; there will be significantly negative return when implementing momentum strategy in the recession of business cycle. On the other hand, from the view of investor psychological biases, it should be seen greater psychological biases owing to greater information uncertainty. As a result, a stronger stock price continuation may be observed under high information uncertainty stocks. However, the effect of information uncertainty is only pronounced among loser portfolios. To summarize, compared with the profitability and the stability of contrarian strategy, the findings support that there is no significant momentum phenomena in Taiwan stock market at all.

This dissertation examines the effect of income smoothing on information uncertainty, stock returns, and cost of equity. Following existing literature, I construct two income smoothing measures - capturing income smoothing through both total accruals and discretionary accruals. I show that income smoothing tends to reduce firms' information uncertainty, as measured by stock return volatility, analyst forecast dispersion, and analyst forecast error. Further, I provide evidence that market prices income smoothing and rewards income smoothing firms with a premium. Controlling for unexpected earnings shocks and other firm characteristics, income smoothing firms have significantly higher abnormal returns around earnings announcement. Finally, I show that income smoothing, particularly through discretionary accruals, reduces firms' implied cost of equity.

Information uncertainty is inherent in many real-world problems and adds a layer of complexity to modeling and visualization tasks. This often causes users to ignore uncertainty, especially when it comes to visualization, thereby discarding valuable knowledge. A coherent framework for the modeling and visualization of information uncertainty is needed to address this issue In this work, we have identified four major barriers to the uptake of uncertainty modeling and visualization. Firstly, there are numerous uncertainty modeling tech- niques and users are required to anticipate their uncertainty needs before building their data model. Secondly, parameters of uncertainty tend to be treated at the same level as variables making it easy to introduce avoidable errors. This causes the uncertainty technique to dictate the structure of the data model. Thirdly, propagation of uncertainty information must be manually managed. This requires user expertise, is error prone, and can be tedious. Finally, uncertainty visualization techniques tend to be developed for particular uncertainty types, making them largely incompatible with other forms of uncertainty information. This narrows the choice of visualization techniques and results in a tendency for ad hoc uncertainty visualization. The aim of this thesis is to present an integrated information uncertainty modeling and visualization environment that has the following main features: information and its uncertainty are encapsulated into atomic variables, the propagation of uncertainty is automated, and visual mappings are abstracted from the uncertainty information data type. Spreadsheets have previously been shown to be well suited as an approach to visu- alization. In this thesis, we devise a new paradigm extending the traditional spreadsheet to intrinsically support information uncertainty.Our approach is to design a framework that integrates uncertainty modeling tech- niques into a hierarchical order based on levels of detail. The uncertainty information is encapsulated and treated as a unit allowing users to think of their data model in terms of the variables instead of the uncertainty details. The system is intrinsically aware of the encapsulated uncertainty and is therefore able to automatically select appropriate uncertainty propagation methods. A user-objectives based approach to uncertainty visualization is developed to guide the visual mapping of abstracted uncertainty information. Two main abstractions of uncertainty information are explored for the purpose of visual mapping: the Unified Uncertainty Model and the Dual Uncertainty Model. The Unified Uncertainty Model provides a single view of uncertainty for visual mapping, whereas the Dual Uncertainty Model distinguishes between possibilistic and probabilistic views. Such abstractions provide a buffer between the visual mappings and the uncertainty type of the underly- ing data, enabling the user to change the uncertainty detail without causing the visual- ization to fail. Two main case studies are presented. The first case study covers exploratory and forecasting tasks in a business planning context. The second case study inves- tigates sensitivity analysis for financial decision support. Two minor case studies are also included: one to investigate the relevancy visualization objective applied to busi- ness process specifications, and the second to explore the extensibility of the system through General Purpose Graphics Processor Unit (GPGPU) use. A quantitative anal- ysis compares our approach to traditional analytical and numerical spreadsheet-based approaches. Two surveys were conducted to gain feedback on the from potential users. The significance of this work is that we reduce barriers to uncertainty modeling and visualization in three ways. Users do not need a mathematical understanding of the uncertainty modeling technique to use it; uncertainty information is easily added, changed, or removed at any stage of the process; and uncertainty visualizations can be built independently of the uncertainty modeling technique.

This study examines the post-earnings announcement drift (PEAD) anomaly on the Swedish stock market. By constructing a corporate governance index based on share structure, board independence and board gender diversity, we test how the quality of firms’ corporate governance affects the drift – a link which is previously unexplored. We find no evidence of PEAD for firms with good corporate governance, while firms with bad corporate governance do experience a drift. Furthermore, a PEAD trading strategy based on bad governance firms yields significantly larger abnormal returns compared to the corresponding trading strategy for good governance firms. Our results are robust to controlling for the risk factors of the Fama-French 3-factor model. The findings support that investors tend to underreact to extreme earnings surprises reported by bad governance firms due to a higher degree of information uncertainty, while the stock price reactions are more complete for good governance firms.

Thesis "Economics and Information" advances a consistent theoretic concept of information as part of economic theory. In contrast of contemporary semantic confusions about information in economics this thesis tries to build a meaningful theory based on classical economic studies and conception of information in system theory. The first part is concerned with methodological foundation and contemporary methodological problems of information in economic theory. These issues are crucial for presenting methodological individualism and subjectivism as fundamental approach to understanding role of information in social sciences. This leads to human action as basic framework for studying information. Next part of the thesis describes few basic approaches to information in economics. In comparison with neoclassical views like information asymmetry this thesis propose own praxeology based concept of information. This concept shows information in its duality as a resource of human activities, but also as objective of human action. This duality as resource and objective connect information to concepts of interpretation, knowledge and dynamic processes. The final part of the thesis applies theoretical concepts to economic policy issues and institutional problems.

This thesis examines the response of a representative agent investor to sequences (streaks) of quarterly earnings surprises over a period of twelve quarters using the United States S&P500 constituent companies sample frame in the years 1991 to 2006. This examination follows the predictive performance of the representative agent model of Rabin (2002b) [Inference by believers in the law of small numbers. The Quarterly Journal of Economics. 117(3).p.775 816] and Barberis, Shleifer, and Vishny (1998) [A model of investor sentiment. Journal of Financial Economics. 49. p.307 343] for an investor who might be under the influence of the law of small numbers, or another closely related cognitive bias known as the gambler s fallacy. Chapters 4 and 5 present two related empirical studies on this broad theme. In chapter 4, for successive sequences of annualised quarterly earnings changes over a twelve-quarter horizon of quarterly earnings increases or falls, I ask whether the models can capture the likelihood of reversion. Secondly, I ask, what is the representative investor s response to observed sequences of quarterly earnings changes for my S&P500 constituent sample companies? I find a far greater frequency of extreme persistent quarterly earnings rises (of nine quarters and more) than falls and hence a more muted reaction to their occurrence from the market. Extreme cases of persistent quarterly earnings falls are far less common than extreme rises and are more salient in their impact on stock prices. I find evidence suggesting that information discreteness; that is the frequency with which small information about stock value filters into the market is one of the factors that foment earnings momentum in stocks. However, information discreteness does not subsume the impact of sequences of annualised quarterly earnings changes, or earnings streakiness as a strong candidate that drives earnings momentum in stock returns in my S&P500 constituent stock sample. Therefore, earnings streakiness and informational discreteness appear to have separate and additive effects in driving momentum in stock price. In chapter 5, the case for the informativeness of the streaks of earnings surprises is further strengthened. This is done by examining the explanatory power of streaks of earnings surprises in a shorter horizon of three days around the period when the effect of the nature of earnings news is most intense in the stock market. Even in shorter windows, investors in S&P500 companies seem to be influenced by the lengthening of negative and positive streaks of earnings surprises over the twelve quarters of quarterly earnings announcement I study here. This further supports my thesis that investors underreact to sequences of changes in their expectations about stock returns. This impact is further strengthened by high information uncertainties in streaks of positive earnings surprise. However, earnings streakiness is one discrete and separable element in the resolution of uncertainty around equity value for S&P 500 constituent companies. Most of the proxies for earnings surprise show this behaviour especially when market capitalisation, age and cash flow act as proxies of information uncertainty. The influence of the gambler s fallacy on the representative investor in the presence of information uncertainty becomes more pronounced when I examine increasing lengths of streaks of earnings surprises. The presence of post earnings announcement drift in my large capitalised S&P500 constituents sample firms confirms earnings momentum to be a pervasive phenomenon which cuts across different tiers of the stock markets including highly liquid stocks, followed by many analysts, which most large funds would hold.

This dissertation is concerned with the relationship between accounting earnings and stock prices. It consists of three empirical papers, all using a sample of firms listed on the Stockholm Stock Exchange (1990-2008). The first paper documents the existence of a drift in stock prices subsequent to quarterly earnings announcements. Two interesting empirical observations are that the drift is only significant for longer holding periods and that the drift on the short position, i.e. after bad earnings news, is negligible. The lack of downward drift on the short position is interpreted as an indication of the post-earnings announcement drift, at least partly, being explained by investors demanding a compensation for a risk factor that is omitted in the test design. The second paper illustrates under what conditions information risk in the earnings signal might explain a low announcement reaction and a price drift in the post-announcement period. It is hypothesized that two earnings signals – based either on GAAP earnings or core earnings – have different levels of information uncertainty with respect to how they depict the value creation of the firm. In the empirical sections, it is concluded that the low immediate announcement reaction and high post-announcement drift for the GAAP earnings signal is due to this signal being perceived by investors as containing more uncertainty than the core earnings signal. It is argued that this uncertainty might be due to GAAP earnings encompassing items that prior research has shown more likely to be manipulated and/or to contain estimation error. The positive association between information risk and expected return is further investigated in the third paper, where information risk is measured by earnings quality metrics. Using a new approach to estimate the implied cost of capital, it is found that Swedish investors demand a higher expected return for firms with poor earnings quality, i.e. firms associated with higher information risk. / Diss. Stockholm : Handelshögskolan i Stockholm, 2011

WHAT WAS DONE? This study researches the success of several value investment strategies in the stock markets of the United Kingdom and Germany based on nine firm fundamentals that are extracted from listed firms annual financial statements. In this regard, we first examine alternative forecast combination methods in a novel way to utilise fully the financial information at hand. Second, we examine the drivers of investment returns, particularly the role of information uncertainty, for which a new direct measure is developed. Finally, we evaluate the performance of these financial health investment strategies in alternative institutional environments by focusing on the differences between the two markets regarding both their corporate culture and their legal environment. WHY WAS IT DONE? Similar to economics, the discipline of finance is a social science because its observations emanate from economic transactions between humans. Nevertheless, a significant part of the research in this area is undertaken by means that are almost exclusively applied to the natural sciences, such as mathematics or physics. Although the reasons seem manifold, an increased form of scientificity, in conjunction with greater credibility of the research process and results, is deemed to be of primary importance. However, the benchmark for evaluating these research outcomes differs from those used in the natural sciences. From the example of the efficient market hypothesis one can see that alternative research results that cast serious doubt upon efficiency per se are disregarded as aberrations, leading to the assumption that the hypothesis in its entirety is more or less valid. This study assumes that inefficiencies in the stock market do exist for prolonged periods of time and investors are actually able to benefit from them. HOW WAS IT DONE? Secondary financial statement data of listed companies in the United Kingdom and Germany were downloaded from Datastream for the period between 1992 and 2010. A quantitative analysis of the significance of the correlation between groups of firms with similar financial characteristics and their one-year-ahead stock returns was subsequently performed. Various combination methods for differential weighting of individual financial statement items were conducted. The aim was to increase the profitability of the investment strategy. WHAT WAS FOUND? In general, a classification of stocks according to certain internal criteria of financial health is capable of separating future winners from losers and at the same time confirms the results of a previous US study. More specifically, we first show that a wide range of combination methods generate profitable investment strategies whereby especially measures of profitability are the central indicator of a firm s future performance. Secondly, the more complex methods neither consistently nor substantively outperform the simpler methods. Thirdly, information uncertainty does not seem to be the prime driver of the profitability of an investment strategy. Lastly, we show that financial health investment strategies are profitable both in market-oriented, common law settings and in bank-oriented, code law settings.

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過去研究說明具產業專長之會計師仍能在客戶財務資訊不完整情況下，利用其行業特定知識與較高技術能力執行完善的審計工作(Thibodeau 2003; Moroney 2007; Hammersley 2006)。本論文定義資訊不確定性為客戶之財務資訊無法幫助預測公司的價值(Zhang 2006; Autore et al. 2009)。本論文推論若公司的財務報表具有不確定性會需要聘請產業專長會計師以減緩資訊不確定性的程度，並進一步研究具資訊不確定性公司若由非產業專長更換為產業專長會計師是否能提升其審計品質。由於審計工作目的在於提供資訊品質的確認(Dye 1993; Knechel et al. 2008)，審計人員會依據審計客戶的環境，設計和執行適當的審計計劃以減輕資訊不確定性情況。本論文以會計師角度建立一資訊不確定性架構，進一步將資訊不確定性分為基本價值波動不確定性與資訊品質不確定性，並推論產業專長會計師比較能在資訊品質不確定性中發揮其價值。本論文分為兩部分：第一部分檢驗資訊不確定性是否會影響產業專長會計師之選任，第二部分則檢測具資訊不確定性之審計客戶若選擇產業專長會計師之後，其審計品質是否會提升。 / Previous studies establish that a specialist auditor has more industry-specific knowledge and higher technological capability that can pertinently benefit situations in which client financial information is incomplete (Thibodeau 2003; Moroney 2007; Hammersley 2006). In this paper, we define information uncertainty as the ambiguity with respect to the implications of new information concerning a firm’s value (Zhang 2006; Autore et al. 2009). Because some financial statements present information in uncertain terms, we infer that companies whose financial statements provide uncertain information demand specialist auditors to alleviate the extent of information uncertainty. We further examine the improvements on audit quality made by those companies under information uncertainty which chose to switch from non-specialist auditors to specialist ones. As an assurance of information quality (Dye 1993; Knechel et al. 2008), an auditor, based on his knowledge of the auditee and its environment, will alleviate the uncertainty level of the auditee’s financial information through designing and executing an appropriate audit plan. We build a framework of information uncertainty and develop comprehensive measurements of information uncertainty from the auditor’s point of view. Moreover, this study disentangles the information uncertainty effects into fundamental volatility uncertainty and information quality uncertainty, and proposes that specialist auditors manifest their merits more under information quality uncertainty than under fundamental volatility uncertainty. In the first part of this study, we examine the auditors chosen by companies whose financial statements are characterized by information uncertainty. Previous studies on auditor choice address many reasons why companies switch their auditors (Lennox 2000; Carcello and Neal 2003; Blouin et al. 2007). Information uncertainty makes stakeholders lower their reliance upon company financials and even downgrade the filers, triggering negative stock price reactions (Merton 1987; Beneish et al. 2005; Beneish et al. 2008; Hammersley et al. 2008). Based on prior research, we can infer that a company under information uncertainty chooses to hire a specialist auditor to signal the credibility of the financial statements and improve market perception. We hypothesize that companies suffering uncertainty demand specialist auditors to alleviate their information uncertainty. The auditor’s information role is to ensure the reliability of financial information, and a specialist auditor is equipped with superior audit knowledge and technology. Therefore, we further infer that a company whose specific information uncertainty is attributable to information quality issues (rather than fundamental volatility issues) is more inclined to choose a specialist auditor. This is because a specialist auditor improves the credibility of financial information instead of being involved with the client’s business decisions. We use an auditor switching sample of U.S. companies from 2001-2009 to examine whether the information uncertainty is an issue of auditor choice or not. Consistent with our conjecture, companies under information uncertainty prefer to hire specialist auditors. Evidence partially supports that relative to companies under fundamental volatility uncertainty, companies suffering information quality uncertainty are more inclined to choose specialist auditors. In the second part of this study, we find evidence for the economic consequences of upgrading switches to a specialist auditor when the company is experiencing information uncertainty. After the Sarbanes-Oxley Act (hereafter, SOX), many companies began to take the cost-effect issue into consideration; they ultimately decided to go private (Zhang 2006; Engel et al. 2007) in order to avoid the high-cost of Section 404 or switch to a non-Big N audit firm (Calderon et al. 2007). There's no such thing as free lunch; the specialist auditor usually has greater ability and concomitant higher charges (Craswell et al. 1995; DeFond et al. 2000; Francis et al. 2005; Cahan et al. 2008). It is natural to question whether every company needs to engage specialist auditors if it has to pay high audit fees. In this paper, we attempt to determine in which circumstances specialist auditors can make a significant difference in improving audit quality. We investigate the relationship between auditor specialization and audit quality in an information uncertainty setting using an auditor switching sample taken from 2001 to 2009 in the United States. We examine ex post facto whether (1) specialist auditors improve audit quality more than their non-specialist counterparts; and (2) specialist auditors manifest their merits more under information quality uncertainty than the fundamental volatility uncertainty. Since the value of auditor industry specialization is reflected by the perceived and actual audit quality (Balsam et al. 2003; Nagy 2005), we examine both earnings response coefficient (ERC) and accruals quality to proxy audit quality (DAC). In both models, the audit quality of companies that suffer fundamental volatility uncertainty along with comprehensive uncertainty is not enhanced substantially following upgrade switching to a specialist auditor. We find strong empirical results that demonstrate companies under information quality uncertainty show significant improvements in audit quality after switching to specialist auditors. However, specialist auditors are significantly more capable of mitigating the information quality uncertainty than the fundamental volatility uncertainty. That is, auditor specialization is a critical solution when companies encounter information quality uncertainty.