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.

Mathematical Aspects of Financial Markets with Frictions

Frictions are factors that hinder trading of securities in financial markets. Typical frictions include limited market depth, transaction costs, lack of infinite divisibility of securities, and taxes. Conventional models used in mathematical finance often gloss over these issues, which affect almost all financial markets, by arguing that the impact of frictions is negligible and, consequently, the frictionless models are valid approximations. This dissertation consists of three research papers, which are related to the study of the validity of such approximations in two distinct modeling problems. Models of price dynamics that are based on diffusion processes, i.e., continuous strong Markov processes, are widely used in the frictionless scenario. The first paper establishes that diffusion models can indeed be understood as approximations of price dynamics in markets with frictions. This is achieved by introducing an agent-based model of a financial market where finitely many agents trade a financial security, the price of which evolves according to price impacts generated by trades. It is shown that, if the number of agents is large, then under certain assumptions the price process of security, which is a pure-jump process, can be approximated by a one-dimensional diffusion process. In a slightly extended model, in which agents may exhibit herd behavior, the approximating diffusion model turns out to be a stochastic volatility model. Finally, it is shown that when agents' tendency to herd is strong, logarithmic returns in the approximating stochastic volatility model are heavy-tailed. The remaining papers are related to no-arbitrage criteria and superhedging in continuous-time option pricing models under small-transaction-cost asymptotics. Guasoni, Rásonyi, and Schachermayer have recently shown that, in such a setting, any financial security admits no arbitrage opportunities and there exist no feasible superhedging strategies for European call and put options written on it, as long as its price process is continuous and has the so-called conditional full support (CFS) property. Motivated by this result, CFS is established for certain stochastic integrals and a subclass of Brownian semistationary processes in the two papers. As a consequence, a wide range of possibly non-Markovian local and stochastic volatility models have the CFS property.

Foreign Capital and Finland : Central government's first period of reliance on international financial markets, 1862-1938

The main objective of the study is to evaluate the Finnish central government s foreign borrowing between the years 1862 and 1938. Most of this period was characterised by deep capital market integration that bears resemblance to the liberal world financial order at the turn of the millennium. The main aim is to analyse the credit risk associated with the state and its determination by evaluating the world financial market centres perception of Finland. By doing this, the study is also expected to provide an additional dimension to Finland s political and economic history by incorporating into the research the assessments of international capital markets regarding Finland during a period that witnessed profound political and economic changes in Finnish society. The evaluation of the credit risk mainly relies on exchange-rate risk free time series of the state s foreign bonds. They have been collected from quotations in the stock exchanges in Helsinki, Hamburg, Paris and London. In addition, it investigates Finland s exposure to short-term debt and Moody s credit ratings assigned to Finland. The study emphasises the importance of the political risk. It suggests that the hey-day of the state s reliance on foreign capital markets took place during last few decades of the 19th century when Finland enjoyed a wide autonomy in the Russian Empire and prudently managed its economy, highlighted in Finland s adherence to the international gold standard. Political confrontations in Finland and, in particular, in Russia and the turbulence of the world financial system prevented the return of this beneficial position again. Through its issuance of foreign bonds the state was able to import substantial amounts of foreign capital, which was sorely needed to foster economic development in Finland. Moreover, the study argues that the state s presence in the western capital markets not only had economic benefits, but it also increased the international awareness of Finland s distinct and separate status in the Russian Empire and later underlined its position as an independent republic.

Country-scale carbon accounting of the vegetation and mineral soils of Finland

The increase in global temperature has been attributed to increased atmospheric concentrations of greenhouse gases (GHG), mainly that of CO2. The threat of severe and complex socio-economic and ecological implications of climate change have initiated an international process that aims to reduce emissions, to increase C sinks, and to protect existing C reservoirs. The famous Kyoto protocol is an offspring of this process. The Kyoto protocol and its accords state that signatory countries need to monitor their forest C pools, and to follow the guidelines set by the IPCC in the preparation, reporting and quality assessment of the C pool change estimates. The aims of this thesis were i) to estimate the changes in carbon stocks vegetation and soil in the forests in Finnish forests from 1922 to 2004, ii) to evaluate the applied methodology by using empirical data, iii) to assess the reliability of the estimates by means of uncertainty analysis, iv) to assess the effect of forest C sinks on the reliability of the entire national GHG inventory, and finally, v) to present an application of model-based stratification to a large-scale sampling design of soil C stock changes. The applied methodology builds on the forest inventory measured data (or modelled stand data), and uses statistical modelling to predict biomasses and litter productions, as well as a dynamic soil C model to predict the decomposition of litter. The mean vegetation C sink of Finnish forests from 1922 to 2004 was 3.3 Tg C a-1, and in soil was 0.7 Tg C a-1. Soil is slowly accumulating C as a consequence of increased growing stock and unsaturated soil C stocks in relation to current detritus input to soil that is higher than in the beginning of the period. Annual estimates of vegetation and soil C stock changes fluctuated considerably during the period, were frequently opposite (e.g. vegetation was a sink but soil was a source). The inclusion of vegetation sinks into the national GHG inventory of 2003 increased its uncertainty from between -4% and 9% to ± 19% (95% CI), and further inclusion of upland mineral soils increased it to ± 24%. The uncertainties of annual sinks can be reduced most efficiently by concentrating on the quality of the model input data. Despite the decreased precision of the national GHG inventory, the inclusion of uncertain sinks improves its accuracy due to the larger sectoral coverage of the inventory. If the national soil sink estimates were prepared by repeated soil sampling of model-stratified sample plots, the uncertainties would be accounted for in the stratum formation and sample allocation. Otherwise, the increases of sampling efficiency by stratification remain smaller. The highly variable and frequently opposite annual changes in ecosystem C pools imply the importance of full ecosystem C accounting. If forest C sink estimates will be used in practice average sink estimates seem a more reasonable basis than the annual estimates. This is due to the fact that annual forest sinks vary considerably and annual estimates are uncertain, and they have severe consequences for the reliability of the total national GHG balance. The estimation of average sinks should still be based on annual or even more frequent data due to the non-linear decomposition process that is influenced by the annual climate. The methodology used in this study to predict forest C sinks can be transferred to other countries with some modifications. The ultimate verification of sink estimates should be based on comparison to empirical data, in which case the model-based stratification presented in this study can serve to improve the efficiency of the sampling design.

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.

Drivers of ERP Systems´ Business Value

ERP system implementations have evolved so rapidly that now they represent a must-have within industries. ERP systems are viewed as the cost of doing business. Yet, the research that adopted the resource-based view on the business value of ERP systems concludes that companies may gain competitive advantage when they successfully manage their ERP projects, when they carefully reengineer the organization and when they use the system in line with the organizational strategies. This thesis contributes to the literature on ERP business value by examining key drivers of ERP business value in organizations. The first research paper investigates how ERP systems with different degrees of system functionality are correlated with the development of the business performance after the completion of the ERP projects. The companies with a better perceived system functionality obtained efficiency benefits in the first two years of post-implementation. However, in the third year there is no significant difference in efficiency benefits between successfully and less successfully managed ERP projects. The second research paper examines what business process changes occur in companies implementing ERP for different motivations and how these changes impact the business performance. The findings show that companies reported process changes mainly in terms of workflow changes. In addition, the companies having a business-led motivation focused more on observing average costs of each increase in the input unit. Companies having a technological-led motivation focused more on the benefits coming from the fit of the system with the organizational processes. The third research paper considers the role of alignment between ERP and business strategies for the realization of business value from ERP use. These findings show that strategic alignment and business process changes are significantly correlated with the perceived benefits of ERP at three levels: internal efficiency, customers and financial. Overall, by combining quantitative and qualitative research methods, this thesis puts forward a model that illustrates how successfully managed ERP projects, aligned with the business strategy, have automate and informate effects on processes that ultimately improve the customer service and reduce the companies’ costs.

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.

Political Risk in Credit Evaluation: Empirical Studies and Survey Results

Financing trade between economic agents located in different countries is affected by many types of risks, resulting from incomplete information about the debtor, the problems of enforcing international contracts, or the prevalence of political and financial crises. Trade is important for economic development and the availability of trade finance is essential, especially for developing countries. Relatively few studies treat the topic of political risk, particularly in the context of international lending. This thesis explores new ground to identify links between political risk and international debt defaults. The core hypothesis of the study is that the default probability of debt increases with increasing political risk in the country of the borrower. The thesis consists of three essays that support the hypothesis from different angles of the credit evaluation process. The first essay takes the point of view of an international lender assessing the credit risk of a public borrower. The second investigates creditworthiness assessment of companies. The obtained results are substantiated in the third essay that deals with an extensive political risk survey among finance professionals in developing countries. The financial instruments of core interest are export credit guaranteed debt initiated between the Export Credit Agency of Finland and buyers in 145 countries between 1975 and 2006. Default events of the foreign credit counterparts are conditioned on country-specific macroeconomic variables, corporate-specific accounting information as well as political risk indicators from various international sources. Essay 1 examines debt issued to government controlled institutions and conditions public default events on traditional macroeconomic fundamentals, in addition to selected political and institutional risk factors. Confirming previous research, the study finds country indebtedness and the GDP growth rate to be significant indicators of public default. Further, it is shown that public defaults respond to various political risk factors. However, the impact of the risk varies between countries at different stages of economic development. Essay 2 proceeds by investigating political risk factors as conveivable drivers of corporate default and uses traditional accounting variables together with new political risk indicators in the credit evaluation of private debtors. The study finds links between corporate default and leverage, as well as between corporate default and the general investment climate and measeures of conflict in the debtor country. Essay 3 concludes the thesis by offering survey evidence on the impact of political risk on debt default, as perceived and experienced by 103 finance professionals in 38 developing countries. Taken together, the results of the thesis suggest that various forms of political risk are associated with international debt defaults and continue to pose great concerns for both international creditors and borrowers in developing countries. The study provides new insights on the importance of variable selection in country risk analysis, and shows how political risk is actually perceived and experienced in the riskier, often lower income countries of the global economy.

Essays on Corporate Governance and the Quality of Disclosed Earnings: Across Transitional Europe

A growing body of empirical research examines the structure and effectiveness of corporate governance systems around the world. An important insight from this literature is that corporate governance mechanisms address the excessive use of managerial discretionary powers to get private benefits by expropriating the value of shareholders. One possible way of expropriation is to reduce the quality of disclosed earnings by manipulating the financial statements. This lower quality of earnings should then be reflected by the stock price of firm according to value relevance theorem. Hence, instead of testing the direct effect of corporate governance on the firm’s market value, it is important to understand the causes of the lower quality of accounting earnings. This thesis contributes to the literature by increasing knowledge about the extent of the earnings management – measured as the extent of discretionary accruals in total disclosed earnings - and its determinants across the Transitional European countries. The thesis comprises of three essays of empirical analysis of which first two utilize the data of Russian listed firms whereas the third essay uses data from 10 European economies. More specifically, the first essay adds to existing research connecting earnings management to corporate governance. It testifies the impact of the Russian corporate governance reforms of 2002 on the quality of disclosed earnings in all publicly listed firms. This essay provides empirical evidence of the fact that the desired impact of reforms is not fully substantiated in Russia without proper enforcement. Instead, firm-level factors such as long-term capital investments and compliance with International financial reporting standards (IFRS) determine the quality of the earnings. The result presented in the essay support the notion proposed by Leuz et al. (2003) that the reforms aimed to bring transparency do not correspond to desired results in economies where investor protection is lower and legal enforcement is weak. The second essay focuses on the relationship between the internal-control mechanism such as the types and levels of ownership and the quality of disclosed earnings in Russia. The empirical analysis shows that the controlling shareholders in Russia use their powers to manipulate the reported performance in order to get private benefits of control. Comparatively, firms owned by the State have significantly better quality of disclosed earnings than other controllers such as oligarchs and foreign corporations. Interestingly, market performance of firms controlled by either State or oligarchs is better than widely held firms. The third essay provides useful evidence on the fact that both ownership structures and economic characteristics are important factors in determining the quality of disclosed earnings in three groups of countries in Europe. Evidence suggests that ownership structure is a more important determinant in developed and transparent countries, while economic determinants are important determinants in developing and transitional countries.