New Evidence on the Properties of the Financial Statement Information Pricing Process

This study contributes to our knowledge of how information contained in financial statements is interpreted and priced by the stock market in two aspects. First, the empirical findings indicate that investors interpret some of the information contained in new financial statements in the context of the information of prior financial statements. Second, two central hypotheses offered in earlier literature to explain the significant connection between publicly available financial statement information and future abnormal returns, that the signals proxy for risk and that the information is priced with a delay, are evaluated utilizing a new methodology. It is found that the mentioned significant connection for some financial statement signals can be explained by that the signals proxy for risk and for other financial statement signals by that the information contained in the signals is priced with a delay.

How Do Different Types of Investors React to New Financial Statement Information?

The study contributes to our understanding of the forces that drive the stock market by investigating how different types of investors react to new financial statement information. Using the extremely comprehensive official register of share holdings in Finland, we find that the majority of investors are more probable to sell (buy) stocks in a company after a positive (negative) earnings surprise, and show a bias towards buying after the disclosure of new financial statement information. Large investors, on the other hand, show behavior opposite to that of the majority of investors in the market. Further, foreign investors show behavior similar to that of domestic investors. We suggest investor overconfidence and asymmetric information as possible explanations for the documented behavior.

Essays on Stock Market Reactions to New Information

A functioning stock market is an essential component of a competitive economy, since it provides a mechanism for allocating the economy’s capital stock. In an ideal situation, the stock market will steer capital in a manner that maximizes the total utility of the economy. As prices of traded stocks depend on and vary with information available to investors, it is apparent that information plays a crucial role in a functioning stock market. However, even though information indisputably matters, several issues regarding how stock markets process and react to new information still remain unanswered. The purpose of this thesis is to explore the link between new information and stock market reactions. The first essay utilizes new methodological tools in order to investigate the average reaction of investors to new financial statement information. The second essay explores the behavior of different types of investors when new financial statement information is disclosed to the market. The third essay looks into the interrelation between investor size, behavior and overconfidence. The fourth essay approaches the puzzle of negative skewness in stock returns from an altogether different angle than previous studies. The first essay presents evidence of the second derivatives of some financial statement signals containing more information than the first derivatives. Further, empirical evidence also indicates that some of the investigated signals proxy risk while others contain information priced with a delay. The second essay documents different categories of investors demonstrating systematical differences in their behavior when new financial statement information arrives to the market. In addition, a theoretical model building on differences in investor overconfidence is put forward in order to explain the observed behavior. The third essay shows that investor size describes investor behavior very well. This finding is predicted by the model proposed in the second essay, and hence strengthens the model. The behavioral differences between investors of different size furthermore have significant economic implications. Finally, the fourth essay finds strong evidence of management news disclosure practices causing negative skewness in stock returns.

Essays on Financial Analyst Forecasts and Recommendations

The trade of the financial analyst is currently a much-debated issue in today’s media. As a large part of the investment analysis is conducted under the broker firms’ regime, the incentives of the financial analyst and the investor do not always align. The broker firm’s commercial incentives may be to maximise its commission from securities trading and underwriting fees. The purpose of this thesis is to extend our understanding of the work of a financial analyst, the incentives he faces and how these affect his actions. The first essay investigates how the economic significance of the coverage of a particular firm impacts the analysts’ accuracy of estimation. The hypothesis is that analysts put more effort in analysing firms with a relatively higher trading volume, as these firms usually yield higher commissions. The second essay investigates how analysts interpret new financial statement information. The essay shows that analysts underreact or overreact to prior reported earnings, depending on the short-term pattern in reported earnings. The third essay investigates the possible investment value in Finnish stock recommendations, issued by sell side analysts. It is established that consensus recommendations issued on Finnish stocks contain investment value. Further, the investment value in consensus recommendations improves significantly through the exclusion of recommendations issued by banks. The fourth essay investigates investors’ behaviour prior to financial analysts’ earnings forecast revisions. Lately, the financial press have reported cases were financial analysts warn their preferred clients of possible earnings forecast revisions. However, in the light of the empirical results, it appears that the problem of analysts leaking information to some selected customers does not appear systematically on the Finnish stock market.

Do Analysts Leak Information to Preferred Customers?

Inspired by the recent debate in the financial press, we set out to investigate if financial analysts warn their preferred customers of possible earnings forecast revisions. The issue is explored by monitoring investors’ trading behavior during the weeks prior to analyst earnings forecast revisions, using the unique official stock transactions data set from Finland. In summary, we do not find evidence of large investors systematically being warned of earnings forecast revisions. However, the results indicate that the very largest investors show trading behavior partly consistent with being informed of future earnings forecast revisions.

Detecting Earnings Management Using Neural Networks

Detecting Earnings Management Using Neural Networks. Trying to balance between relevant and reliable accounting data, generally accepted accounting principles (GAAP) allow, to some extent, the company management to use their judgment and to make subjective assessments when preparing financial statements. The opportunistic use of the discretion in financial reporting is called earnings management. There have been a considerable number of suggestions of methods for detecting accrual based earnings management. A majority of these methods are based on linear regression. The problem with using linear regression is that a linear relationship between the dependent variable and the independent variables must be assumed. However, previous research has shown that the relationship between accruals and some of the explanatory variables, such as company performance, is non-linear. An alternative to linear regression, which can handle non-linear relationships, is neural networks. The type of neural network used in this study is the feed-forward back-propagation neural network. Three neural network-based models are compared with four commonly used linear regression-based earnings management detection models. All seven models are based on the earnings management detection model presented by Jones (1991). The performance of the models is assessed in three steps. First, a random data set of companies is used. Second, the discretionary accruals from the random data set are ranked according to six different variables. The discretionary accruals in the highest and lowest quartiles for these six variables are then compared. Third, a data set containing simulated earnings management is used. Both expense and revenue manipulation ranging between -5% and 5% of lagged total assets is simulated. Furthermore, two neural network-based models and two linear regression-based models are used with a data set containing financial statement data from 110 failed companies. Overall, the results show that the linear regression-based models, except for the model using a piecewise linear approach, produce biased estimates of discretionary accruals. The neural network-based model with the original Jones model variables and the neural network-based model augmented with ROA as an independent variable, however, perform well in all three steps. Especially in the second step, where the highest and lowest quartiles of ranked discretionary accruals are examined, the neural network-based model augmented with ROA as an independent variable outperforms the other models.

Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.

Reinventing Nordic Openness : Transparency and State Information in Finland

The study explores new ideational changes in the information strategy of the Finnish state between 1998 and 2007, after a juncture in Finnish governing in the early 1990s. The study scrutinizes the economic reframing of institutional openness in Finland that comes with significant and often unintended institutional consequences of transparency. Most notably, the constitutional principle of publicity (julkisuusperiaate), a Nordic institutional peculiarity allowing public access to state information, is now becoming an instrument of economic performance and accountability through results. Finland has a long institutional history in the publicity of government information, acknowledged by law since 1951. Nevertheless, access to government information became a policy concern in the mid-1990s, involving a historical narrative of openness as a Nordic tradition of Finnish governing Nordic openness (pohjoismainen avoimuus). International interest in transparency of governance has also marked an opening for institutional re-descriptions in Nordic context. The essential added value, or contradictory term, that transparency has on the Finnish conceptualisation of governing is the innovation that public acts of governing can be economically efficient. This is most apparent in the new attempts at providing standardised information on government and expressing it in numbers. In Finland, the publicity of government information has been a concept of democratic connotations, but new internationally diffusing ideas of performance and national economic competitiveness are discussed under the notion of transparency and its peer concepts openness and public (sector) information, which are also newcomers to Finnish vocabulary of governing. The above concepts often conflict with one another, paving the way to unintended consequences for the reforms conducted in their name. Moreover, the study argues that the policy concerns over openness and public sector information are linked to the new drive for transparency. Drawing on theories of new institutionalism, political economy, and conceptual history, the study argues for a reinvention of Nordic openness in two senses. First, in referring to institutional history, the policy discourse of Nordic openness discovers an administrative tradition in response to new dilemmas of public governance. Moreover, this normatively appealing discourse also legitimizes the new ideational changes. Second, a former mechanism of democratic accountability is being reframed with market and performance ideas, mostly originating from the sphere of transnational governance and governance indices. Mobilizing different research techniques and data (public documents of the Finnish government and international organizations, some 30 interviews of Finnish civil servants, and statistical time series), the study asks how the above ideational changes have been possible, pointing to the importance of nationalistically appealing historical narratives and normative concepts of governing. Concerning institutional developments, the study analyses the ideational changes in central steering mechanisms (political, normative and financial steering) and the introduction of budget transparency and performance management in two cases: census data (Population Register Centre) and foreign political information (Ministry for Foreign Affairs). The new policy domain of governance indices is also explored as a type of transparency. The study further asks what institutional transformations are to be observed in the above cases and in the accountability system. The study concludes that while the information rights of citizens have been reinforced and recalibrated during the period under scrutiny, there has also been a conversion of institutional practices towards economic performance. As the discourse of Nordic openness has been rather unquestioned, the new internationally circulating ideas of transparency and the knowledge economy have entered this discourse without public notice. Since the mid 1990s, state registry data has been perceived as an exploitable economic resource in Finland and in the EU public sector information. This is a parallel development to the new drive for budget transparency in organisations as vital to the state as the Population Register Centre, which has led to marketization of census data in Finland, an international exceptionality. In the Finnish Ministry for Foreign Affairs, the post-Cold War rhetorical shift from secrecy to performance-driven openness marked a conversion in institutional practices that now see information services with high regards. But this has not necessarily led to the increased publicity of foreign political information. In this context, openness is also defined as sharing information with select actors, as a trust based non-public activity, deemed necessary amid the global economic competition. Regarding accountability system, deliberation and performance now overlap, making it increasingly difficult to identify to whom and for what the public administration is accountable. These evolving institutional practices are characterised by unintended consequences and paradoxes. History is a paradoxical component in the above institutional change, as long-term institutional developments now justify short-term reforms.

Essays on the Linkages Between Financial Markets, and Risk Asymmetries (summary section only)

During the last few decades there have been far going financial market deregulation, technical development, advances in information technology, and standardization of legislation between countries. As a result, one can expect that financial markets have grown more interlinked. The proper understanding of the cross-market linkages has implications for investment and risk management, diversification, asset pricing, and regulation. The purpose of this research is to assess the degree of price, return, and volatility linkages between both geographic markets and asset categories within one country, Finland. Another purpose is to analyze risk asymmetries, i.e., the tendency of equity risk to be higher after negative events than after positive events of equal magnitude. The analysis is conducted both with respect to total risk (volatility), and systematic risk (beta). The thesis consists of an introductory part and four essays. The first essay studies to which extent international stock prices comove. The degree of comovements is low, indicating benefits from international diversification. The second essay examines the degree to which the Finnish market is linked to the “world market”. The total risk is divided into two parts, one relating to world factors, and one relating to domestic factors. The impact of world factors has increased over time. After 1993, when foreign investors were allowed to freely invest in Finnish assets, the risk level has been higher than previously. This was also the case during the economic recession in the beginning of the 1990’s. The third essay focuses on the stock, bond, and money markets in Finland. According to a trading model, the degree of volatility linkages should be strong. However, the results contradict this. The linkages are surprisingly weak, even negative. The stock market is the most independent, while the money market is affected by events on the two other markets. The fourth essay concentrates on volatility and beta asymmetries. Contrary to many international studies there are only few cases of risk asymmetries. When they occur, they tend to be driven by the market-wide component rather than the portfolio specific element.