Tests of International Asset Pricing Models in Scandinavian Stock Markets

This thesis examines whether global, local and exchange risks are priced in Scandinavian countries’ equity markets by using conditional international asset pricing models. The employed international asset pricing models are the world capital asset pricing model, the international asset pricing model augmented with the currency risk, and the partially segmented model augmented with the currency risk. Moreover, this research traces estimated equity risk premiums for the Scandinavian countries. The empirical part of the study is performed using generalized method of moments approach. Monthly observations from February 1994 to June 2007 are used. Investors’ conditional expectations are modeled using several instrumental variables. In order to keep system parsimonious the prices of risk are assumed to be constant whereas expected returns and conditional covariances vary over time. The empirical findings of this thesis suggest that the prices of global and local market risk are priced in the Scandinavian countries. This indicates that the Scandinavian countries are mildly segmented from the global markets. Furthermore, the results show that the exchange risk is priced in the Danish and Swedish stock markets when the partially segmented model is augmented with the currency risk factor.

Empirical Tests of Asset Pricing Models in Finnish Stock Market

Tämän tutkielman tavoitteena on selvittää mitkä riskitekijät vaikuttavat osakkeiden tuottoihin. Arvopapereina käytetään kuutta portfoliota, jotka ovat jaoteltu markkina-arvon mukaan. Aikaperiodi on vuoden 1987 alusta vuoden 2004 loppuun. Malleina käytetään pääomamarkkinoiden hinnoittelumallia, arbitraasihinnoitteluteoriaa sekä kulutuspohjaista pääomamarkkinoiden hinnoittelumallia. Riskifaktoreina kahteen ensimmäiseen malliin käytetään markkinariskiä sekä makrotaloudellisia riskitekijöitä. Kulutuspohjaiseen pääomamarkkinoiden hinnoinoittelumallissa keskitytään estimoimaan kuluttajien riskitottumuksia sekä diskonttaustekijää, jolla kuluttaja arvostavat tulevaisuuden kulutusta. Tämä työ esittelee momenttiteorian, jolla pystymme estimoimaan lineaarisia sekä epälineaarisia yhtälöitä. Käytämme tätä menetelmää testaamissamme malleissa. Yhteenvetona tuloksista voidaan sanoa, että markkinabeeta onedelleen tärkein riskitekijä, mutta löydämme myös tukea makrotaloudellisille riskitekijöille. Kulutuspohjainen mallimme toimii melko hyvin antaen teoreettisesti hyväksyttäviä arvoja.

Essays on pricing of risk and international linkage of Russian stock market

Last two decades have seen a rapid change in the global economic and financial situation; the economic conditions in many small and large underdeveloped countries started to improve and they became recognized as emerging markets. This led to growth in the amounts of global investments in these countries, partly spurred by expectations of higher returns, favorable risk-return opportunities, and better diversification alternatives to global investors. This process, however, has not been without problems and it has emphasized the need for more information on these markets. In particular, the liberalization of financial markets around the world, globalization of trade and companies, recent formation of economic and regional blocks, and the rapid development of underdeveloped countries during the last two decades have brought a major challenge to the financial world and researchers alike. This doctoral dissertation studies one of the largest emerging markets, namely Russia. The motivation why the Russian equity market is worth investigating includes, among other factors, its sheer size, rapid and robust economic growth since the turn of the millennium, future prospect for international investors, and a number of important major financial reforms implemented since the early 1990s. Another interesting feature of the Russian economy, which gives motivation to study Russian market, is Russia’s 1998 financial crisis, considered as one of the worst crisis in recent times, affecting both developed and developing economies. Therefore, special attention has been paid to Russia’s 1998 financial crisis throughout this dissertation. This thesis covers the period from the birth of the modern Russian financial markets to the present day, Special attention is given to the international linkage and the 1998 financial crisis. This study first identifies the risks associated with Russian market and then deals with their pricing issues. Finally some insights about portfolio construction within Russian market are presented. The first research paper of this dissertation considers the linkage of the Russian equity market to the world equity market by examining the international transmission of the Russia’s 1998 financial crisis utilizing the GARCH-BEKK model proposed by Engle and Kroner. Empirical results shows evidence of direct linkage between the Russian equity market and the world market both in regards of returns and volatility. However, the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market, even though the contagion can be clearly seen during the time of the crisis period. The second and the third paper, co-authored with Mika Vaihekoski, investigate whether global, local and currency risks are priced in the Russian stock market from a US investors’ point of view. Furthermore, the dynamics of these sources of risk are studied, i.e., whether the prices of the global and local risk factors are constant or time-varying over time. We utilize the multivariate GARCH-M framework of De Santis and Gérard (1998). Similar to them we find price of global market risk to be time-varying. Currency risk also found to be priced and highly time varying in the Russian market. Moreover, our results suggest that the Russian market is partially segmented and local risk is also priced in the market. The model also implies that the biggest impact on the US market risk premium is coming from the world risk component whereas the Russian risk premium is on average caused mostly by the local and currency components. The purpose of the fourth paper is to look at the relationship between the stock and the bond market of Russia. The objective is to examine whether the correlations between two classes of assets are time varying by using multivariate conditional volatility models. The Constant Conditional Correlation model by Bollerslev (1990), the Dynamic Conditional Correlation model by Engle (2002), and an asymmetric version of the Dynamic Conditional Correlation model by Cappiello et al. (2006) are used in the analysis. The empirical results do not support the assumption of constant conditional correlation and there was clear evidence of time varying correlations between the Russian stocks and bond market and both asset markets exhibit positive asymmetries. The implications of the results in this dissertation are useful for both companies and international investors who are interested in investing in Russia. Our results give useful insights to those involved in minimising or managing financial risk exposures, such as, portfolio managers, international investors, risk analysts and financial researchers. When portfolio managers aim to optimize the risk-return relationship, the results indicate that at least in the case of Russia, one should account for the local market as well as currency risk when calculating the key inputs for the optimization. In addition, the pricing of exchange rate risk implies that exchange rate exposure is partly non-diversifiable and investors are compensated for bearing the risk. Likewise, international transmission of stock market volatility can profoundly influence corporate capital budgeting decisions, investors’ investment decisions, and other business cycle variables. Finally, the weak integration of the Russian market and low correlations between Russian stock and bond market offers good opportunities to the international investors to diversify their portfolios.

Market anomalies and tactical asset allocation: Utilising market anomalies in multiple asset class portfolios with the Black−Litterman model

This thesis discusses the basic problem of the modern portfolio theory about how to optimise the perfect allocation for an investment portfolio. The theory provides a solution for an efficient portfolio, which minimises the risk of the portfolio with respect to the expected return. A central feature for all the portfolios on the efficient frontier is that the investor needs to provide the expected return for each asset. Market anomalies are persistent patterns seen in the financial markets, which cannot be explained with the current asset pricing theory. The goal of this thesis is to study whether these anomalies can be observed among different asset classes. Finally, if persistent patterns are found, it is investigated whether the anomalies hold valuable information for determining the expected returns used in the portfolio optimization Market anomalies and investment strategies based on them are studied with a rolling estimation window, where the return for the following period is always based on historical information. This is also crucial when rebalancing the portfolio. The anomalies investigated within this thesis are value, momentum, reversal, and idiosyncratic volatility. The research data includes price series of country level stock indices, government bonds, currencies, and commodities. The modern portfolio theory and the views given by the anomalies are combined by utilising the Black-Litterman model. This makes it possible to optimise the portfolio so that investor’s views are taken into account. When constructing the portfolios, the goal is to maximise the Sharpe ratio. Significance of the results is studied by assessing if the strategy yields excess returns in a relation to those explained by the threefactormodel. The most outstanding finding is that anomaly based factors include valuable information to enhance efficient portfolio diversification. When the highest Sharpe ratios for each asset class are picked from the test factors and applied to the Black−Litterman model, the final portfolio results in superior riskreturn combination. The highest Sharpe ratios are provided by momentum strategy for stocks and long-term reversal for the rest of the asset classes. Additionally, a strategy based on the value effect was highly appealing, and it basically performs as well as the previously mentioned Sharpe strategy. When studying the anomalies, it is found, that 12-month momentum is the strongest effect, especially for stock indices. In addition, a high idiosyncratic volatility seems to be positively correlated with country indices on stocks.

Liquidity and Asset Pricing in the French Stock Market

This thesis investigates pricing of liquidity in the French stock market. The study covers 835 ordinary shares traded in the period of 1996-2014 on Paris Euronext. The author utilizes the Liquidity-Adjusted Capital Asset Pricing Model (LCAPM) recently developed by Acharya and Pedersen (2005) to test whether liquidity level and risks significantly affect stock returns. Three different liquidity measures – Amihud, FHT, and PQS – are incorporated into the model to find any difference between the results they could provide. It appears that the findings largely depend on the liquidity measure used. In general the results exhibit more evidence for insignificant influence of liquidity level and risks as well as market risk on stock returns. The similar conclusion was reported earlier by Lee (2011) for several regions, including France. This finding of the thesis, however, is not consistent across all the liquidity measures. Nevertheless, the difference in the results between these measures provides new insight to the existing literature on this topic. The Amihud-based findings might indicate that market resiliency is not priced in the French stock market. At the same time the contradicting results from FHT and PQS provide some foundation for the hypothesis that one of two leftover liquidity dimensions – market depth or breadth – could significantly affect stock returns. Therefore, the thesis’ findings suggest a conjecture that different liquidity dimensions have different impacts on stock returns.

Reflexivity in sovereign debt markets

Finanssi-instrumentin hinta määräytyy sen fundamenttitekijöiden perusteella, eikä päinvastoin. Tämä tutkimus osoittaa, että myös instrumentin hinta voi vaikuttaa fundamenttitekijöihin. Yhteys havainnollistetaan tapaustukimuksella Kreikan velkakriisistä. Hinnan ja fundamenttien välistä yhteyttä arvioidaan ja käänteisen kausaliteetin olemassaolo testataan. Tulokset tukevat ajatusta, jonka mukaan tarvitsemme dynaamisempia valuaatiomenetelmiä, jotka ottavat huomioon myös mahdolliset itseään vahvistavat hintakierteet.

Konkurssin ennustaminen ja makrotaloudelliset muuttujat: rakennusalan pk-yritykset

Tämän tutkimuksen tavoitteena on selvittää kannattaako makrotaloudellisia muuttujia käyttää tunnuslukujen lisäksi yrityksen konkurssin ennustamisessa. Perinteiset konkurssinennustamismallit hyödyntävät pelkästään tilinpäätöksestä saatavia tunnuslukuja eivätkä huomioi yrityksen toimintaympäristöä ja sen muutoksia. Aiemmissa tutkimuksissa makrotaloudellisilla muuttujilla on pystytty parantamaan perinteisiä ennustamismalleja. Tutkimus toteutetaan luomalla kolme erilaista konkurssinennustamismallia logistista regressioanalyysiä hyödyntäen ja vertailemalla niiden paremmuutta. Tutkimustulokset osoittavat, että rakennusalan pk-yritysten konkursseja pystytään ennustamaan kolmen tunnusluvun mallilla. Taloudellisen ajanjakson, jolta yrityksen tiedot ovat peräisin, huomioiminen ei tuo malliin lisäarvoa eikä paranna ennustamiskykyä merkittävästi.

Konkurssin ennustaminen ja makrotaloudelliset muuttujat: rakennusalan pk-yritykset

Tämän tutkimuksen tavoitteena on selvittää kannattaako makrotaloudellisia muuttujia käyttää tunnuslukujen lisäksi yrityksen konkurssin ennustamisessa. Perinteiset konkurssinennustamismallit hyödyntävät pelkästään tilinpäätöksestä saatavia tunnuslukuja eivätkä huomioi yrityksen toimintaympäristöä ja sen muutoksia. Aiemmissa tutkimuksissa makrotaloudellisilla muuttujilla on pystytty parantamaan perinteisiä ennustamismalleja. Tutkimus toteutetaan luomalla kolme erilaista konkurssinennustamismallia logistista regressioanalyysiä hyödyntäen ja vertailemalla niiden paremmuutta. Tutkimustulokset osoittavat, että rakennusalan pk-yritysten konkursseja pystytään ennustamaan kolmen tunnusluvun mallilla. Taloudellisen ajanjakson, jolta yrityksen tiedot ovat peräisin, huomioiminen ei tuo malliin lisäarvoa eikä paranna ennustamiskykyä merkittävästi.

Risk-return trade-off and autocorrelation

A trade-off between return and risk plays a central role in financial economics. The intertemporal capital asset pricing model (ICAPM) proposed by Merton (1973) provides a neoclassical theory for expected returns on risky assets. The model assumes that risk-averse investors (seeking to maximize their expected utility of lifetime consumption) demand compensation for bearing systematic market risk and the risk of unfavorable shifts in the investment opportunity set. Although the ICAPM postulates a positive relation between the conditional expected market return and its conditional variance, the empirical evidence on the sign of the risk-return trade-off is conflicting. In contrast, autocorrelation in stock returns is one of the most consistent and robust findings in empirical finance. While autocorrelation is often interpreted as a violation of market efficiency, it can also reflect factors such as market microstructure or time-varying risk premia. This doctoral thesis investigates a relation between the mixed risk-return trade-off results and autocorrelation in stock returns. The results suggest that, in the case of the US stock market, the relative contribution of the risk-return trade-off and autocorrelation in explaining the aggregate return fluctuates with volatility. This effect is then shown to be even more pronounced in the case of emerging stock markets. During high-volatility periods, expected returns can be described using rational (intertemporal) investors acting to maximize their expected utility. During lowvolatility periods, market-wide persistence in returns increases, leading to a failure of traditional equilibrium-model descriptions for expected returns. Consistent with this finding, traditional models yield conflicting evidence concerning the sign of the risk-return trade-off. The changing relevance of the risk-return trade-off and autocorrelation can be explained by heterogeneous agents or, more generally, by the inadequacy of the neoclassical view on asset pricing with unboundedly rational investors and perfect market efficiency. In the latter case, the empirical results imply that the neoclassical view is valid only under certain market conditions. This offers an economic explanation as to why it has been so difficult to detect a positive tradeoff between the conditional mean and variance of the aggregate stock return. The results highlight the importance, especially in the case of emerging stock markets, of noting both the risk-return trade-off and autocorrelation in applications that require estimates for expected returns.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Public-private partnership investments in dry ports – Russian logistics markets and risks

The investments have always been considered as an essential backbone and so-called ‘locomotive’ for the competitive economies. However, in various countries, the state has been put under tight budget constraints for the investments in capital intensive projects. In response to this situation, the cooperation between public and private sector has grown based on public-private mechanism. The promotion of favorable arrangement for collaboration between public and private sectors for the provision of policies, services, and infrastructure in Russia can help to address the problems of dry ports development that neither municipalities nor the private sector can solve alone. Especially, the stimulation of public-private collaboration is significant under the exposure to externalities that affect the magnitude of the risks during all phases of project realization. In these circumstances, the risk in the projects also is becoming increasingly a part of joint research and risk management practice, which is viewed as a key approach, aiming to take active actions on existing global and specific factors of uncertainties. Meanwhile, a relatively little progress has been made on the inclusion of the resilience aspects into the planning process of a dry ports construction that would instruct the capacity planner, on how to mitigate the occurrence of disruptions that may lead to million dollars of losses due to the deviation of the future cash flows from the expected financial flows on the project. The current experience shows that the existing methodological base is developed fragmentary within separate steps of supply chain risk management (SCRM) processes: risk identification, risk evaluation, risk mitigation, risk monitoring and control phases. The lack of the systematic approach hinders the solution of the problem of risk management processes of dry port implementation. Therefore, management of various risks during the investments phases of dry port projects still presents a considerable challenge from the practical and theoretical points of view. In this regard, the given research became a logical continuation of fundamental research, existing in the financial models and theories (e.g., capital asset pricing model and real option theory), as well as provided a complementation for the portfolio theory. The goal of the current study is in the design of methods and models for the facilitation of dry port implementation through the mechanism of public-private partnership on the national market that implies the necessity to mitigate, first and foremost, the shortage of the investments and consequences of risks. The problem of the research was formulated on the ground of the identified contradictions. They rose as a continuation of the trade-off between the opportunities that the investors can gain from the development of terminal business in Russia (i.e. dry port implementation) and risks. As a rule, the higher the investment risk, the greater should be their expected return. However, investors have a different tolerance for the risks. That is why it would be advisable to find an optimum investment. In the given study, the optimum relates to the search for the efficient portfolio, which can provide satisfaction to the investor, depending on its degree of risk aversion. There are many theories and methods in finance, concerning investment choices. Nevertheless, the appropriateness and effectiveness of particular methods should be considered with the allowance of the specifics of the investment projects. For example, the investments in dry ports imply not only the lump sum of financial inflows, but also the long-term payback periods. As a result, capital intensity and longevity of their construction determine the necessity from investors to ensure the return on investment (profitability), along with the rapid return on investment (liquidity), without precluding the fact that the stochastic nature of the project environment is hardly described by the formula-based approach. The current theoretical base for the economic appraisals of the dry port projects more often perceives net present value (NPV) as a technique superior to other decision-making criteria. For example, the portfolio theory, which considers different risk preference of an investor and structures of utility, defines net present value as a better criterion of project appraisal than discounted payback period (DPP). Meanwhile, in business practice, the DPP is more popular. Knowing that the NPV is based on the assumptions of certainty of project life, it cannot be an accurate appraisal approach alone to determine whether or not the project should be accepted for the approval in the environment that is not without of uncertainties. In order to reflect the period or the project’s useful life that is exposed to risks due to changes in political, operational, and financial factors, the second capital budgeting criterion – discounted payback period is profoundly important, particularly for the Russian environment. Those statements represent contradictions that exist in the theory and practice of the applied science. Therefore, it would be desirable to relax the assumptions of portfolio theory and regard DPP as not fewer relevant appraisal approach for the assessment of the investment and risk measure. At the same time, the rationality of the use of both project performance criteria depends on the methods and models, with the help of which these appraisal approaches are calculated in feasibility studies. The deterministic methods cannot ensure the required precision of the results, while the stochastic models guarantee the sufficient level of the accuracy and reliability of the obtained results, providing that the risks are properly identified, evaluated, and mitigated. Otherwise, the project performance indicators may not be confirmed during the phase of project realization. For instance, the economic and political instability can result in the undoing of hard-earned gains, leading to the need for the attraction of the additional finances for the project. The sources of the alternative investments, as well as supportive mitigation strategies, can be studied during the initial phases of project development. During this period, the effectiveness of the investments undertakings can also be improved by the inclusion of the various investors, e.g. Russian Railways’ enterprises and other private companies in the dry port projects. However, the evaluation of the effectiveness of the participation of different investors in the project lack the methods and models that would permit doing the particular feasibility study, foreseeing the quantitative characteristics of risks and their mitigation strategies, which can meet the tolerance of the investors to the risks. For this reason, the research proposes a combination of Monte Carlo method, discounted cash flow technique, the theory of real options, and portfolio theory via a system dynamics simulation approach. The use of this methodology allows for comprehensive risk management process of dry port development to cover all aspects of risk identification, risk evaluation, risk mitigation, risk monitoring, and control phases. A designed system dynamics model can be recommended for the decision-makers on the dry port projects that are financed via a public-private partnership. It permits investors to make a decision appraisal based on random variables of net present value and discounted payback period, depending on different risks factors, e.g. revenue risks, land acquisition risks, traffic volume risks, construction hazards, and political risks. In this case, the statistical mean is used for the explication of the expected value of the DPP and NPV; the standard deviation is proposed as a characteristic of risks, while the elasticity coefficient is applied for rating of risks. Additionally, the risk of failure of project investments and guaranteed recoupment of capital investment can be considered with the help of the model. On the whole, the application of these modern methods of simulation creates preconditions for the controlling of the process of dry port development, i.e. making managerial changes and identifying the most stable parameters that contribute to the optimal alternative scenarios of the project realization in the uncertain environment. System dynamics model allows analyzing the interactions in the most complex mechanism of risk management process of the dry ports development and making proposals for the improvement of the effectiveness of the investments via an estimation of different risk management strategies. For the comparison and ranking of these alternatives in their order of preference to the investor, the proposed indicators of the efficiency of the investments, concerning the NPV, DPP, and coefficient of variation, can be used. Thus, rational investors, who averse to taking increased risks unless they are compensated by the commensurate increase in the expected utility of a risky prospect of dry port development, can be guided by the deduced marginal utility of investments. It is computed on the ground of the results from the system dynamics model. In conclusion, the outlined theoretical and practical implications for the management of risks, which are the key characteristics of public-private partnerships, can help analysts and planning managers in budget decision-making, substantially alleviating the effect from various risks and avoiding unnecessary cost overruns in dry port projects.

Modelling flexible asset management in industrial maintenance companies and networks

The tightening competition and increasing dynamism have created an emerging need for flexible asset management. This means that the changes of market demand should be responded to with adjustments in the amount of assets tied to the balance sheets of companies. On the other hand, industrial maintenance has recently experienced drastic changes, which have led to an increase in the number of maintenance networks (consisting of customer companies that buy maintenance services, as well as various supplier companies) and inter-organizational partnerships. However, the research on maintenance networks has not followed the changes in the industry. Instead, there is a growing need for new ways of collaboration between partnering companies to enhance the competitiveness of the whole maintenance network. In addition, it is more and more common for companies to pursue lean operations in their businesses. This thesis shows how flexible asset management can increase the profitability of maintenance companies and networks under dynamic operating conditions, and how the additional value can then be shared between the network partners. Firstly, I have conducted a systematic literature review to identify what kind of requirements for asset management models are set by the increasing dynamism. Then I have responded to these requirements by constructing an analytical model for flexible asset management, linking asset management to the profitability and financial state of a company. The thesis uses the model to show how flexible asset management can increase profitability in maintenance companies and networks, and how the created value can be shared in the networks to reach a win-win situation. The research indicates that the existing models for asset management are heterogeneous by nature due to the various definitions of ‘asset management’. I conclude that there is a need for practical asset management models which address assets comprehensively with an inter-organizational, strategic view. The comprehensive perspective, taking all kinds of asset types into account, is needed to integrate the research on asset management with the strategic management of companies and networks. I will show that maintenance companies can improve their profitability by increasing the flexibility of their assets. In maintenance networks, reorganizing the ownership of the assets among the different network partners can create additional value. Finally, I will introduce flexible asset management contracts for maintenance networks. These contracts address the value sharing related to reorganizing the ownership of assets according to the principles of win-win situations.