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.

Customer asset management in action: using customers portfolio for allocating resources across business-to-business relationships for improved shareholder value

Suvi Nenonen Customer asset management in action: using customer portfolios for allocating resources across business-to-business relationships for improved shareholder value Customers are crucial assets to all firms as customers are the ultimate source of all cash flows. Regardless this financial importance of customer relationships, for decades there has been a lack of suitable frameworks explaining how customer relationships contribute to the firm financial performance and how this contribution can be actively managed. In order to facilitate a better understanding of the customer asset, contemporary marketing has investigated the use of financial theories and asset management practices in the customer relationship context. Building on this, marketing academics have promoted the customer lifetime value concept as a solution for valuating and managing customer relationships for optimal financial outcomes. However, the empirical investigation of customer asset management lags behind the conceptual development steps taken. Additionally, the practitioners have not embraced the use of customer lifetime value in guiding managerial decisions - especially in the business-to-business context. The thesis points out that there are fundamental differences between customer relationships and investment instruments as investment targets, effectively eliminating the possibility to use financial theories in a customer relationships context or to optimize the customer base as a single investment portfolio. As an alternative, the thesis proposes the use of customer portfolio approach for allocating resources across the customer base for improved shareholder value. In the customer portfolio approach, the customer base of a firm is divided into multiple portfolios based on customer relationships’ potential to contribute to the shareholder value creation. After this, customer management concepts are tailored to each customer portfolio, designed to improve the shareholder value in their own respect. Therefore, effective customer asset management with the customer portfolio approach necessitates that firms are able to manage multiple parallel customer management concepts, or business models, simultaneously. The thesis is one of the first empirical studies on customer asset management, bringing empirical evidence from multiple business-to-business case studies on how customer portfolio models can be formed, how customer portfolios can be managed, and how customer asset management has contributed to the firm financial performance.

Customer asset management in action: using customers portfolio for allocating resources across business-to-business relationships for improved shareholder value

Suvi Nenonen Customer asset management in action: using customer portfolios for allocating resources across business-to-business relationships for improved shareholder value Customers are crucial assets to all firms as customers are the ultimate source of all cash flows. Regardless this financial importance of customer relationships, for decades there has been a lack of suitable frameworks explaining how customer relationships contribute to the firm financial performance and how this contribution can be actively managed. In order to facilitate a better understanding of the customer asset, contemporary marketing has investigated the use of financial theories and asset management practices in the customer relationship context. Building on this, marketing academics have promoted the customer lifetime value concept as a solution for valuating and managing customer relationships for optimal financial outcomes. However, the empirical investigation of customer asset management lags behind the conceptual development steps taken. Additionally, the practitioners have not embraced the use of customer lifetime value in guiding managerial decisions - especially in the business-to-business context. The thesis points out that there are fundamental differences between customer relationships and investment instruments as investment targets, effectively eliminating the possibility to use financial theories in a customer relationships context or to optimize the customer base as a single investment portfolio. As an alternative, the thesis proposes the use of customer portfolio approach for allocating resources across the customer base for improved shareholder value. In the customer portfolio approach, the customer base of a firm is divided into multiple portfolios based on customer relationships’ potential to contribute to the shareholder value creation. After this, customer management concepts are tailored to each customer portfolio, designed to improve the shareholder value in their own respect. Therefore, effective customer asset management with the customer portfolio approach necessitates that firms are able to manage multiple parallel customer management concepts, or business models, simultaneously. The thesis is one of the first empirical studies on customer asset management, bringing empirical evidence from multiple business-to-business case studies on how customer portfolio models can be formed, how customer portfolios can be managed, and how customer asset management has contributed to the firm financial performance.

Kin selection, social polymorphism, and reproductive allocation in ants

Social groups are common across animal species. The reasons for grouping are straightforward when all individuals gain directly from cooperating. However, the situation becomes more complex when helping entails costs to the personal reproduction of individuals. Kin selection theory has offered a fruitful framework to explain such cooperation by stating that individuals may spread their genes not only through their own reproduction, but also by helping related individuals reproduce. However, kin selection theory also implicitly predicts conflicts when groups consist of non-clonal individuals, i.e. relatedness is less than one. Then, individual interests are not perfectly aligned, and each individual is predicted to favour the propagation of their own genome over others. Social insects provide a solid study system to study the interplay between cooperation and conflict. Breeding systems in social insects range from solitary breeding to eusocial colonies displaying complete division of reproduction between the fertile queen and the sterile worker caste. Within colonies, additional variation is provided by the presence of several reproductive individuals. In many species, the queen mates multiply, which causes the colony to consist of half-sib instead of full-sib offspring. Furthermore, in many species colonies contain multiple breeding queens, which further dilutes relatedness between colony members. Evolutionary biology is thus faced with the challenge to answer why such variation in social structure exists, and what the consequences are on the individual and population level. The main part of this thesis takes on this challenge by investing the dynamics of socially polymorphic ant colonies. The first four chapters investigate the causes and consequences of different social structures, using a combination of field studies, genetic analyses and laboratory experiments. The thesis ends with a theoretical chapter focusing on different social interactions (altruism and spite), and the evolution of harming traits. The main results of the thesis show that social polymorphism has the potential to affect the behaviour and traits of both individuals and colonies. For example, we found that genetic polymorphism may increase the phenotypic variation between individuals in colonies, and that socially polymorphic colonies may show different life history patterns. We also show that colony cohesion may be enhanced even in multiple-queen colonies through patterns of unequal reproduction between queens. However, the thesis also demonstrates that spatial and temporal variation between both populations and environments may affect individual and colony traits, to the degree that results obtained in one place or at one time may not be applicable in other situations. This opens up potential further areas of research to explain these differences.

Conditional Moments in Asset Pricing

A better understanding of stock price changes is important in guiding many economic activities. Since prices often do not change without good reasons, searching for related explanatory variables has involved many enthusiasts. This book seeks answers from prices per se by relating price changes to their conditional moments. This is based on the belief that prices are the products of a complex psychological and economic process and their conditional moments derive ultimately from these psychological and economic shocks. Utilizing information about conditional moments hence makes it an attractive alternative to using other selective financial variables in explaining price changes. The first paper examines the relation between the conditional mean and the conditional variance using information about moments in three types of conditional distributions; it finds that the significance of the estimated mean and variance ratio can be affected by the assumed distributions and the time variations in skewness. The second paper decomposes the conditional industry volatility into a concurrent market component and an industry specific component; it finds that market volatility is on average responsible for a rather small share of total industry volatility — 6 to 9 percent in UK and 2 to 3 percent in Germany. The third paper looks at the heteroskedasticity in stock returns through an ARCH process supplemented with a set of conditioning information variables; it finds that the heteroskedasticity in stock returns allows for several forms of heteroskedasticity that include deterministic changes in variances due to seasonal factors, random adjustments in variances due to market and macro factors, and ARCH processes with past information. The fourth paper examines the role of higher moments — especially skewness and kurtosis — in determining the expected returns; it finds that total skewness and total kurtosis are more relevant non-beta risk measures and that they are costly to be diversified due either to the possible eliminations of their desirable parts or to the unsustainability of diversification strategies based on them.

Modeling Nonlinearities and Asymmetries in Asset Pricing

Financial time series tend to behave in a manner that is not directly drawn from a normal distribution. Asymmetries and nonlinearities are usually seen and these characteristics need to be taken into account. To make forecasts and predictions of future return and risk is rather complicated. The existing models for predicting risk are of help to a certain degree, but the complexity in financial time series data makes it difficult. The introduction of nonlinearities and asymmetries for the purpose of better models and forecasts regarding both mean and variance is supported by the essays in this dissertation. Linear and nonlinear models are consequently introduced in this dissertation. The advantages of nonlinear models are that they can take into account asymmetries. Asymmetric patterns usually mean that large negative returns appear more often than positive returns of the same magnitude. This goes hand in hand with the fact that negative returns are associated with higher risk than in the case where positive returns of the same magnitude are observed. The reason why these models are of high importance lies in the ability to make the best possible estimations and predictions of future returns and for predicting risk.