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.

The role of auditors in the Finnish limited liability companies as to solvency test in the context of asset distribution

Suomen osakeyhtiölain mukaan varoja ei saa jakaa, jos jaosta päätettäessä tiedetään tai pitäisi tietää yhtiön olevan maksukyvytön tai jaon aiheuttavan maksukyvyttömyyden. Ongelmallista on, että maksukykyä ei ole selvästi määritelty laissa tai hallituksen esityksessä. Tilintarkastuslain mukaan tilintarkastajan on siten huomautettava, jos maksukykytestiä on rikottu, mutta tilintarkastaja joutuu yleensä määrittelemään tällaiset huomauttamista vaativat tilanteet itse. Maksukykytestistä on kirjoitettu suomalaisessa yhtiöoikeuden ja laskentatoimen kirjallisuudessa melko kattavasti. Kuitenkin tilintarkastajaa koskeva näkökulma on saanut osakseen suhteellisen vähän huomiota. Tästä näkökulmasta on kirjoitettu vain joitakin korkeakoulujen tutkielmia sekä lyhyehköjä ammatillisia seminaariesityksiä. Tämän tutkielman tavoitteena on ollut koota laaja yleiskuva siitä, miten tilintarkastajat itse kokevat asemansa ja tehtävänsä yllä kuvatuissa tilanteessa. Tutkielmassa on käyty läpi aikaisempaa yhtiöoikeuden ja laskentatoimen kirjallisuudessa ja seminaariesityksissä esitettyä aineistoa. Lisäksi tutkielmaa varten tehtiin suomalaisille tilintarkastajille kohdennettu Internet-pohjainen kysely. Tutkielma selkeyttää kuvaa siitä, miten tilintarkastajat toimivat yllä kuvatussa tilanteessa ja miten he ovat sopeuttaneet toimiaan yhteiskunnan institutionaalisen asetelman muututtua. Kirjallisuuden pohjalta tapahtuva teoreettinen analyysi on yhdistetty kyselyyn siitä, miten tilintarkastajat käytännössä toimivat. Tutkimuksen perustana olevaa tietoa on analysoitu pääosin kyselytutkimuksen menetelmin, mutta myös tilastollisen tutkimuksen menetelmiä on käytetty. Tutkielman tuloksena tutkielmassa selvitetään tilintarkastajan tehtäviä maksukykytestin yhteydessä. Tuloksena voidaan myös todeta, että tilintarkastaja ei suorita varojenjaossa tarvittavan maksukyvyn arvioinnin kannalta keskeisiä tarkastustoimenpiteitä ainoastaan tilikauden päättymisen jälkeen. Päinvastoin, tällaisia tarkastustoimenpiteitä suoritetaan enemmän tai vähemmän koko tilintarkastuksen aikana. Lisäksi vaikuttaisi siltä, että tilintarkastajan oma suhtautuminen maksukykytestiin on ainakin jossain määrin merkityksellinen sen kannalta, kuinka paljon tarkastustoimenpiteitä tehdään ja kuinka paljon maksukyvystä ja siihen liittyvistä puutteista raportoidaan yhtiön johdolle.

PERFORMANCE ANALYSIS OF A TACTICAL ASSET ALLOCATION – Evidence from the Black–Litterman model based fixed income portfolio

Over time the demand for quantitative portfolio management has increased among financial institutions but there is still a lack of practical tools. In 2008 EDHEC Risk and Asset Management Research Centre conducted a survey of European investment practices. It revealed that the majority of asset or fund management companies, pension funds and institutional investors do not use more sophisticated models to compensate the flaws of the Markowitz mean-variance portfolio optimization. Furthermore, tactical asset allocation managers employ a variety of methods to estimate return and risk of assets, but also need sophisticated portfolio management models to outperform their benchmarks. Recent development in portfolio management suggests that new innovations are slowly gaining ground, but still need to be studied carefully. This thesis tries to provide a practical tactical asset allocation (TAA) application to the Black–Litterman (B–L) approach and unbiased evaluation of B–L models’ qualities. Mean-variance framework, issues related to asset allocation decisions and return forecasting are examined carefully to uncover issues effecting active portfolio management. European fixed income data is employed in an empirical study that tries to reveal whether a B–L model based TAA portfolio is able outperform its strategic benchmark. The tactical asset allocation utilizes Vector Autoregressive (VAR) model to create return forecasts from lagged values of asset classes as well as economic variables. Sample data (31.12.1999–31.12.2012) is divided into two. In-sample data is used for calibrating a strategic portfolio and the out-of-sample period is for testing the tactical portfolio against the strategic benchmark. Results show that B–L model based tactical asset allocation outperforms the benchmark portfolio in terms of risk-adjusted return and mean excess return. The VAR-model is able to pick up the change in investor sentiment and the B–L model adjusts portfolio weights in a controlled manner. TAA portfolio shows promise especially in moderately shifting allocation to more risky assets while market is turning bullish, but without overweighting investments with high beta. Based on findings in thesis, Black–Litterman model offers a good platform for active asset managers to quantify their views on investments and implement their strategies. B–L model shows potential and offers interesting research avenues. However, success of tactical asset allocation is still highly dependent on the quality of input estimates.

Developing asset management in district heating and cooling business in a large energy company

The purpose of this Master´s Thesis is to develop asset management and its practices in case company. District heating and cooling systems operated by case company around Finland, Sweden, Poland and the Baltics form an enormous-sized asset base where some parts are starting to reach their end of life-cycles. Large-sized asset renewal actions are under discussion and maintenance spending is increasing. Financially justified decisions in changing business environment are needed. Asset management is one of the most important concepts for production organization which operates with capital-intensive production assets. Organizations profitability is highly dependent on assets´ performance. Such assets, like district heating and cooling systems, should be utilized as efficiently as possible within their life-cycles but also maintained and renewed optimally. In this qualitative thesis, empirical interview study was conducted to describe the current situation on how the assets are managed in the case company and to examine the readiness to implement a new, risk-based solution. Asset management revealed to be a very well-known concept. From proposed risk-based asset management point of view, several key observations were made. It was seen as a suitable solution, but further development will be needed. Based on the need and findings, several key processes and frameworks were created and also tested with a case study. Assets` condition monitoring should be improved, which would have a positive impact on event probability assessment. Risk acceptance is also a thing to be discussed further. When the evaluation becomes fluent in single investment cases, portfolio-level expansion should be considered and started. As a result, thesis proposes a solution how risk-based asset management could be performed practically in a capital-intensive case company in order to optimize the maintenance spending in a long run. Created practical framework is made universal: similar principles can be applied into multiple cases in case company but also in other energy companies. Risk-based asset management`s benefits could be utilized best in portfolio-level optimization where the capital would be invested to the most important objects from total risk point of view. Eventually, such approach would allow case company to optimize capital spending in a situation where funds are not adequate to cover all the mandatory needs and prioritization between the investment alternatives will truly be needed.

Is Brand Equity an Asset or a Liability in Brand Harm Crisis? Buffering and Amplifying Effects and Contingent Conditions

Brand harm crisis often result in negative consumer responses. This thesis addresses the buffering and amplifying theoretical perspectives of brand equity effects. We theorize that brand equity may interplay with the nature of brand-harm crisis in shaping consumer reactions. Results from focus group studies provide interesting insights into the amplifying and buffering effects. Moreover, research findings from two experiment studies show that brand equity amplifies consumer negative responses in a performance-related crisis but only when the crisis is extremely severe. When the crisis becomes less severe, the amplifying effect diminishes from outset. However, in a value-related crisis, the amplifying effect of brand equity is pervasive regardless of the level of crisis severity. The current thesis adds to the extant literature by demonstrating that brand equity can have very complex effects on consumer responses, which are contingent on the severity and domain of a crisis. Theoretical and managerial implications are discussed.

Tests of Conditional Asset Pricing Models in the Brazilian Stock Market

In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the 1976-1992 period. We also test a conditional APT model by using the difference between the 30-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. The conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from a total of 25 securities exchanged on the Brazilian markets. The inclusion of this second factor proves to be crucial for the appropriate pricing of the portfolios.

Tests of Conditional Asset Pricing Models in the Brazilian Stock Market

In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the 1976-1992 period. We also test a conditional APT model by using the difference between the 30-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. the conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from a total of 25 securities exchanged on the Brazilian markets. the inclusion of this second factor proves to be crucial for the appropriate pricing of the portfolios.

Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models

In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR) with applications to asset pricing models. We focus on departures from the assumption of i.i.d. errors assumption, at univariate and multivariate levels, with Gaussian and non-Gaussian (including Student t) errors. The univariate tests studied extend existing exact procedures by allowing for unspecified parameters in the error distributions (e.g., the degrees of freedom in the case of the Student t distribution). The multivariate tests are based on properly standardized multivariate residuals to ensure invariance to MLR coefficients and error covariances. We consider tests for serial correlation, tests for multivariate GARCH and sign-type tests against general dependencies and asymmetries. The procedures proposed provide exact versions of those applied in Shanken (1990) which consist in combining univariate specification tests. Specifically, we combine tests across equations using the MC test procedure to avoid Bonferroni-type bounds. Since non-Gaussian based tests are not pivotal, we apply the “maximized MC” (MMC) test method [Dufour (2002)], where the MC p-value for the tested hypothesis (which depends on nuisance parameters) is maximized (with respect to these nuisance parameters) to control the test’s significance level. The tests proposed are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995. Our empirical results reveal the following. Whereas univariate exact tests indicate significant serial correlation, asymmetries and GARCH in some equations, such effects are much less prevalent once error cross-equation covariances are accounted for. In addition, significant departures from the i.i.d. hypothesis are less evident once we allow for non-Gaussian errors.

Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-fit in Multivariate Regressions with Application to Asset Pricing Models

We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross-equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared to simulation-based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal, Student t; normal mixtures and stable error models. In the Gaussian case, finite-sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi-stage Monte Carlo test methods. For non-Gaussian distribution families involving nuisance parameters, confidence sets are derived for the the nuisance parameters and the error distribution. The procedures considered are evaluated in a small simulation experi-ment. Finally, the tests are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995.

Exact Multivariate Tests of Asset Pricing Models with Stable Asymmetric Distributions

In this paper, we propose exact inference procedures for asset pricing models that can be formulated in the framework of a multivariate linear regression (CAPM), allowing for stable error distributions. The normality assumption on the distribution of stock returns is usually rejected in empirical studies, due to excess kurtosis and asymmetry. To model such data, we propose a comprehensive statistical approach which allows for alternative - possibly asymmetric - heavy tailed distributions without the use of large-sample approximations. The methods suggested are based on Monte Carlo test techniques. Goodness-of-fit tests are formally incorporated to ensure that the error distributions considered are empirically sustainable, from which exact confidence sets for the unknown tail area and asymmetry parameters of the stable error distribution are derived. Tests for the efficiency of the market portfolio (zero intercepts) which explicitly allow for the presence of (unknown) nuisance parameter in the stable error distribution are derived. The methods proposed are applied to monthly returns on 12 portfolios of the New York Stock Exchange over the period 1926-1995 (5 year subperiods). We find that stable possibly skewed distributions provide statistically significant improvement in goodness-of-fit and lead to fewer rejections of the efficiency hypothesis.