A Comparison of Managers’ Perception of Short-Termism in Finland, Sweden and the U.S

Increased media exposure to layoffs and corporate quarterly financial reporting have created arguable a common perception – especially favored by the media itself – that the companies have been forced to improve their financial performance from quarter to quarter. Academically the relevant question is whether companies themselves feel that they are exposed to short-term pressure to perform even if it means that they have to compromise company’s long-term future. This paper studies this issue using results from a survey conducted among the 500 largest companies in Finland. The results show that companies in general feel moderate short-term pressure, with reasonable dispersion across firms. There seems to be a link between the degree of pressure felt, and the firm’s ownership structure, i.e. we find support for the existence of short-term versus long-term owners. We also find significant ownership related differences, in line with expectations, in how such short-term pressure is reflected in actual decision variables such as the investment criteria used.

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.

Determinants and Consequences of Information Sharing with Key Suppliers

As companies become more efficient with respect to their internal processes, they begin to shift the focus beyond their corporate boundaries. Thus, the recent years have witnessed an increased interest by practitioners and researchers in interorganizational collaboration, which promises better firm performance through more effective supply chain management. It is no coincidence that this interest comes in parallel with the recent advancements in Information and Communication Technologies, which offer many new collaboration possibilities for companies. However, collaboration, or any other type of supply chain integration effort, relies heavily on information sharing. Hence, this study focuses on information sharing, in particular on the factors that determine it and on its value. The empirical evidence from Finnish and Swedish companies suggests that uncertainty (both demand and environmental) and dependency in terms of switching costs and asset specific investments are significant determinants of information sharing. Results also indicate that information sharing improves company performance regarding resource usage, output, and flexibility. However, companies share information more intensely at the operational rather than the strategic level. The use of supply chain practices and technologies is substantial but varies across the two countries. This study sheds light on a common trend in supply chains today. Whereas the results confirm the value of information sharing, the contingent factors help to explain why the intensity of information shared across companies differ. In the future, competitive pressures and uncertainty are likely to intensify. Therefore, companies may want to continue with their integration efforts by focusing on the determinants discussed in this study. However, at the same time, the possibility of opportunistic behavior by the exchange partner cannot be disregarded.

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 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 the Modeling and Prediction of Volatility and Higher Moments of Stock Returns (summary section only)

One of the most fundamental and widely accepted ideas in finance is that investors are compensated through higher returns for taking on non-diversifiable risk. Hence the quantification, modeling and prediction of risk have been, and still are one of the most prolific research areas in financial economics. It was recognized early on that there are predictable patterns in the variance of speculative prices. Later research has shown that there may also be systematic variation in the skewness and kurtosis of financial returns. Lacking in the literature so far, is an out-of-sample forecast evaluation of the potential benefits of these new more complicated models with time-varying higher moments. Such an evaluation is the topic of this dissertation. Essay 1 investigates the forecast performance of the GARCH (1,1) model when estimated with 9 different error distributions on Standard and Poor’s 500 Index Future returns. By utilizing the theory of realized variance to construct an appropriate ex post measure of variance from intra-day data it is shown that allowing for a leptokurtic error distribution leads to significant improvements in variance forecasts compared to using the normal distribution. This result holds for daily, weekly as well as monthly forecast horizons. It is also found that allowing for skewness and time variation in the higher moments of the distribution does not further improve forecasts. In Essay 2, by using 20 years of daily Standard and Poor 500 index returns, it is found that density forecasts are much improved by allowing for constant excess kurtosis but not improved by allowing for skewness. By allowing the kurtosis and skewness to be time varying the density forecasts are not further improved but on the contrary made slightly worse. In Essay 3 a new model incorporating conditional variance, skewness and kurtosis based on the Normal Inverse Gaussian (NIG) distribution is proposed. The new model and two previously used NIG models are evaluated by their Value at Risk (VaR) forecasts on a long series of daily Standard and Poor’s 500 returns. The results show that only the new model produces satisfactory VaR forecasts for both 1% and 5% VaR Taken together the results of the thesis show that kurtosis appears not to exhibit predictable time variation, whereas there is found some predictability in the skewness. However, the dynamic properties of the skewness are not completely captured by any of the models.

Intraday Dynamics of International Equity Markets

The increased availability of high frequency data sets have led to important new insights in understanding of financial markets. The use of high frequency data is interesting and persuasive, since it can reveal new information that cannot be seen in lower data aggregation. This dissertation explores some of the many important issues connected with the use, analysis and application of high frequency data. These include the effects of intraday seasonal, the behaviour of time varying volatility, the information content of various market data, and the issue of inter market linkages utilizing high frequency 5 minute observations from major European and the U.S stock indices, namely DAX30 of Germany, CAC40 of France, SMI of Switzerland, FTSE100 of the UK and SP500 of the U.S. The first essay in the dissertation shows that there are remarkable similarities in the intraday behaviour of conditional volatility across European equity markets. Moreover, the U.S macroeconomic news announcements have significant cross border effect on both, European equity returns and volatilities. The second essay reports substantial intraday return and volatility linkages across European stock indices of the UK and Germany. This relationship appears virtually unchanged by the presence or absence of the U.S stock market. However, the return correlation among the U.K and German markets rises significantly following the U.S stock market opening, which could largely be described as a contemporaneous effect. The third essay sheds light on market microstructure issues in which traders and market makers learn from watching market data, and it is this learning process that leads to price adjustments. This study concludes that trading volume plays an important role in explaining international return and volatility transmissions. The examination concerning asymmetry reveals that the impact of the positive volume changes is larger on foreign stock market volatility than the negative changes. The fourth and the final essay documents number of regularities in the pattern of intraday return volatility, trading volume and bid-ask spreads. This study also reports a contemporaneous and positive relationship between the intraday return volatility, bid ask spread and unexpected trading volume. These results verify the role of trading volume and bid ask quotes as proxies for information arrival in producing contemporaneous and subsequent intraday return volatility. Moreover, asymmetric effect of trading volume on conditional volatility is also confirmed. Overall, this dissertation explores the role of information in explaining the intraday return and volatility dynamics in international stock markets. The process through which the information is incorporated in stock prices is central to all information-based models. The intraday data facilitates the investigation that how information gets incorporated into security prices as a result of the trading behavior of informed and uninformed traders. Thus high frequency data appears critical in enhancing our understanding of intraday behavior of various stock markets’ variables as it has important implications for market participants, regulators and academic researchers.

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

Modelling and Forecasting Property Rents and Returns (summary section only)

Recently, focus of real estate investment has expanded from the building-specific level to the aggregate portfolio level. The portfolio perspective requires investment analysis for real estate which is comparable with that of other asset classes, such as stocks and bonds. Thus, despite its distinctive features, such as heterogeneity, high unit value, illiquidity and the use of valuations to measure performance, real estate should not be considered in isolation. This means that techniques which are widely used for other assets classes can also be applied to real estate. An important part of investment strategies which support decisions on multi-asset portfolios is identifying the fundamentals of movements in property rents and returns, and predicting them on the basis of these fundamentals. The main objective of this thesis is to find the key drivers and the best methods for modelling and forecasting property rents and returns in markets which have experienced structural changes. The Finnish property market, which is a small European market with structural changes and limited property data, is used as a case study. The findings in the thesis show that is it possible to use modern econometric tools for modelling and forecasting property markets. The thesis consists of an introduction part and four essays. Essays 1 and 3 model Helsinki office rents and returns, and assess the suitability of alternative techniques for forecasting these series. Simple time series techniques are able to account for structural changes in the way markets operate, and thus provide the best forecasting tool. Theory-based econometric models, in particular error correction models, which are constrained by long-run information, are better for explaining past movements in rents and returns than for predicting their future movements. Essay 2 proceeds by examining the key drivers of rent movements for several property types in a number of Finnish property markets. The essay shows that commercial rents in local markets can be modelled using national macroeconomic variables and a panel approach. Finally, Essay 4 investigates whether forecasting models can be improved by accounting for asymmetric responses of office returns to the business cycle. The essay finds that the forecast performance of time series models can be improved by introducing asymmetries, and the improvement is sufficient to justify the extra computational time and effort associated with the application of these techniques.

Essays on the Role of Time in Price Discovery (summary section only)

The purpose of this thesis is to examine the role of trade durations in price discovery. The motivation to use trade durations in the study of price discovery is that durations are robust to many microstructure effects that introduce a bias in the measurement of returns volatility. Another motivation to use trade durations in the study of price discovery is that it is difficult to think of economic variables, which really are useful in the determination of the source of volatility at arbitrarily high frequencies. The dissertation contains three essays. In the first essay, the role of trade durations in price discovery is examined with respect to the volatility pattern of stock returns. The theory on volatility is associated with the theory on the information content of trade, dear to the market microstructure theory. The first essay documents that the volatility per transaction is related to the intensity of trade, and a strong relationship between the stochastic process of trade durations and trading variables. In the second essay, the role of trade durations in price discovery is examined with respect to the quantification of risk due to a trading volume of a certain size. The theory on volume is intrinsically associated with the stock volatility pattern. The essay documents that volatility increases, in general, when traders choose to trade with large transactions. In the third essay, the role of trade durations in price discovery is examined with respect to the information content of a trade. The theory on the information content of a trade is associated with the theory on the rate of price revisions in the market. The essay documents that short durations are associated with information. Thus, traders are compensated for responding quickly to information

Essays on the Costs and Benefits of Large Shareholders in Corporate Governance (summary section only)

“Corporate governance deals with the ways in which suppliers of finance to firms assure themselves of getting a return on their investment” (Shleifer and Vishny (1997, p. 737). According to La Porta et al. (1999), research in corporate finance relevant for most countries should focus on the incentives and capabilities of controlling shareholders to treat themselves preferentially at the expense of minority shareholders. Accordingly, this thesis sets out to answer a number of research questions regarding the role of large shareholders in public firms that have received little attention in the literature so far. A common theme in the essays stems from the costs and benefits of individual large-block owners and the role of control contestability from the perspective of outside minority shareholders. The first essay empirically examines whether there are systematic performance differences between family controlled and nonfamily controlled firms in Western Europe. In contrast to the widely held view that family control penalizes firm value, the essay shows that publicly traded family firms have higher performance than comparable firms. In the second essay, we present both theoretical and empirical analysis on the effects of control contestability on firm valuation. Consistent with the theoretical model, the empirical results show that minority shareholders benefit from a more contestable control structure. The third essay explores the effects of individual large-block owners on top management turnover and board appointments in Finnish listed firms. The results indicate that firm performance is an important determinant for management and board restructurings. For certain types of turnover decisions the corporate governance structure influences the performance / turnover sensitivity. In the fourth essay, we investigate the relation between the governance structure and dividend policy in Finnish listed firms. We find evidence in support of the outcome agency model of dividends stating that lower agency conflicts should be associated with higher dividend payouts.

Essays on Risk Modeling. Applications to Portfolio and Risk Management (summary section only)

In this thesis we deal with the concept of risk. The objective is to bring together and conclude on some normative information regarding quantitative portfolio management and risk assessment. The first essay concentrates on return dependency. We propose an algorithm for classifying markets into rising and falling. Given the algorithm, we derive a statistic: the Trend Switch Probability, for detection of long-term return dependency in the first moment. The empirical results suggest that the Trend Switch Probability is robust over various volatility specifications. The serial dependency in bear and bull markets behaves however differently. It is strongly positive in rising market whereas in bear markets it is closer to a random walk. Realized volatility, a technique for estimating volatility from high frequency data, is investigated in essays two and three. In the second essay we find, when measuring realized variance on a set of German stocks, that the second moment dependency structure is highly unstable and changes randomly. Results also suggest that volatility is non-stationary from time to time. In the third essay we examine the impact from market microstructure on the error between estimated realized volatility and the volatility of the underlying process. With simulation-based techniques we show that autocorrelation in returns leads to biased variance estimates and that lower sampling frequency and non-constant volatility increases the error variation between the estimated variance and the variance of the underlying process. From these essays we can conclude that volatility is not easily estimated, even from high frequency data. It is neither very well behaved in terms of stability nor dependency over time. Based on these observations, we would recommend the use of simple, transparent methods that are likely to be more robust over differing volatility regimes than models with a complex parameter universe. In analyzing long-term return dependency in the first moment we find that the Trend Switch Probability is a robust estimator. This is an interesting area for further research, with important implications for active asset allocation.

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.

Essays on Risk and Return

Perhaps the most fundamental prediction of financial theory is that the expected returns on financial assets are determined by the amount of risk contained in their payoffs. Assets with a riskier payoff pattern should provide higher expected returns than assets that are otherwise similar but provide payoffs that contain less risk. Financial theory also predicts that not all types of risks should be compensated with higher expected returns. It is well-known that the asset-specific risk can be diversified away, whereas the systematic component of risk that affects all assets remains even in large portfolios. Thus, the asset-specific risk that the investor can easily get rid of by diversification should not lead to higher expected returns, and only the shared movement of individual asset returns – the sensitivity of these assets to a set of systematic risk factors – should matter for asset pricing. It is within this framework that this thesis is situated. The first essay proposes a new systematic risk factor, hypothesized to be correlated with changes in investor risk aversion, which manages to explain a large fraction of the return variation in the cross-section of stock returns. The second and third essays investigate the pricing of asset-specific risk, uncorrelated with commonly used risk factors, in the cross-section of stock returns. The three essays mentioned above use stock market data from the U.S. The fourth essay presents a new total return stock market index for the Finnish stock market beginning from the opening of the Helsinki Stock Exchange in 1912 and ending in 1969 when other total return indices become available. Because a total return stock market index for the period prior to 1970 has not been available before, academics and stock market participants have not known the historical return that stock market investors in Finland could have achieved on their investments. The new stock market index presented in essay 4 makes it possible, for the first time, to calculate the historical average return on the Finnish stock market and to conduct further studies that require long time-series of data.

Essays on Stock Option Compensation and the Role of Incentives and Risk (summary section only)

Managerial pay-for-performance sensitivity has increased rapidly around the world. Early empirical research showed that pay-for-performance sensitivity resulting from stock ownership and stock options appeared to be quite low during the 1970s and early 1980s in the U.S. However, recent empirical research from the U.S. shows an enormous increase in pay-for-performance sensitivity. The global trend has also reached Finland, where stock options have become a major ingredient of executive compensation. The fact that stock options seem to be an appealing form of remuneration from a theoretical point of view combined with the observation that the use of this compensation form has increased significantly during the recent years, implies that research on the dynamics of stock option compensation is highly relevant for the academic community, as well as for practitioners and regulators. The research questions of the thesis are analyzed in four separate essays. The first essay examines whether stock option compensation practices of Finnish firms are consistent with predictions from principal-agent theory. The second essay explores one of the major puzzles in the compensation literature by studying determinants of stock option contract design. In theory, optimal contract design should vary according to firm characteristics. However, in the U.S., variation in contract design seems to be surprisingly low, a phenomenon generally attributed to tax and accounting considerations. In Finland, however, firms are not subject to stringent contracting restrictions, and the variation in contract design tends, in fact, to be quite substantial. The third essay studies the impact of price- and risk incentives arising from stock option compensation on firm investment. In addition, the essay explores one of the most debated questions in the literature, in particular, the relation between incentives and firm performance. Finally, several strands of literature in both economics and corporate finance hypothesize that economic uncertainty is related to corporate decision-making. Previous research has shown that risk tends to slow down firm investment. In the fourth essay, it is hypothesized that firm risk slows down growth from a more universal perspective. Consistent with this view, it is shown that risk not only tends to slow down firm investment, but also employment growth. Moreover, the essay explores whether the nature of firms’ compensation policies, in particular, whether firms make use of stock option compensation, affects the relation between risk and firm growth. In summary, the four essays contribute to the current understanding of stock options as a form of equity incentives, and how incentives and risk affect corporate decision-making. By this, the thesis promotes the knowledge related to the modern theory of the firm.