Insurance companies offer business and individuals the possibility to reduce the financial impact of a risk occurring by transferring it away from themselves onto someone. For taking on risk on behalf of someone else the insurance company requires a premium from the policyholder which is pooled and invested in order to meet future obligations towards the policyholder. However, the importance of the European insurance industry goes beyond economic protection of the policyholder as the industry with its EUR8.4 trillion or 58 percent of EU GDP in assets is the largest institutional investor in Europe. As the financial system has undergone dramatic transformation over time, so have the role and function of intermediaries changed. While traditional tasks like reducing transaction costs and asymmetric information became less relevant, facilitating of risk transfer and dealing with the increasing breadth and depth of financial markets are gaining more and more importance. While insurers have been able to hold illiquid asset to a larger extent arguments from the industry are made that the planned introduction of Solvency II will limit insurers and overlook their investment abilities, which is something that can affect the region’s economic development. The above mention aspect combined with the limited research that has been conducted on insurers’ asset allocation and the performance of it resulted in the following research question: Does asset allocation impact insurance company's performance? The question focuses on insurers within the European Union (EU) which is enlarged by the European Economic Area (EEA) and Switzerland, where performance is measured as the return on investment (ROI). To answer the research question in the best possible way, relevant theories such as Modern Portfolio Theory or Efficient Market Hypothesis are presented and discussed as well as previous research on asset allocation. Earlier studies about asset allocation policy and its power to explain the investment return came to different conclusions which can be due to variation in the interpretation of the findings or difficulties by distinguishing between asset allocation policy and active asset allocation. Census is used to investigate in the topic as the population of listed insurance companies within the selected region was rather small which finally came down to 42 firms due to the timeframe of 11 years. Data regarding insurer’s asset class weights in debt securities, equity, real estate, derivatives, cash and equivalent, loans and receivables and the category of others were collected. The return on investment was also collected for each year of the time period and for each insurance company. Benchmarks were constructed in order to replicate what the return of a passive investment of the same proportion would have yielded. The result was inconclusive as it was not possible to determine if asset allocation policy or active management have the greatest impact on the return on investment. This is contradicting previous research of asset allocation and performance as researchers have found that asset allocation policy explains most or all of the return.

After the 2008 financial crisis, some have questioned the historically positive benefits ofdiversification, meanwhile others have stated a clear misunderstanding of whatdiversification entails. This study argues diversification is still viable in portfolio theory,and that more effort should be emphasized on macroeconomic factors’ role in theoptimal portfolio. According to the Rational choice theory, investors want to reduce riskwithout lowering expected returns. Modern portfolio theory believes it is possible to doso, by combining less-than-perfect correlated asset classes in a portfolio. The businesscycle theory adds a further perspective by considering cycling movements in themacroeconomic environment, which this study ties to the correlation of asset classes.This study enriches the range of macroeconomic factors and asset classes, focusing onthe EU area, and subsequently, identifies existing relationships. Hence, the researchquestion, “Do macroeconomic factors moderate diversification effect across assetclasses in the EU?” is answered.Results are achieved through the positivist paradigm and the deductive researchapproach, and further, a panel data analysis including 18 macroeconomic factors and 8asset classes during the 2013 to 2022 time periods. The OLS single regression model isused, and results are compared to the previous literature.The characteristics of these 70 relationships are presented. Further, the level of impactfor 18 macroeconomic factors is ranked, the unemployment rate is the most impactfulfactor and GDP impact on gross public debt is the least impactful factor. An investor'sperspective is kept during the thesis to inspire professional investors, especiallyportfolio managers to be detail-oriented when they design diversification strategies andconstruct the optimal portfolios. Also, the results regarding institutional quality indexesincrease the importance of the social and sustainable segment of macroeconomicfactors, which should be considered by investors in the future. Ultimately, this studycontributes to previous literature by examining the empirical results through the lens ofRational choice theory, Business cycle theory, and Modern portfolio theory.

Made available in DSpace on 2014-12-17T13:53:38Z (GMT). No. of bitstreams: 1 JoyceMMC_DISSERT.pdf: 1307327 bytes, checksum: 1a2f420e00204b3d8c059a84165a14a0 (MD5) Previous issue date: 2014-01-21 / This study aims to investigate the influence of the asset class and the breakdown of tangibility as determinant factors of the capital structure of companies listed on the BM & FBOVESPA in the period of 2008-2012. Two current assets classes were composed and once they were grouped by liquidity, they were also analyzed by the financial institutions for credit granting: current resources (Cash, Bank and Financial Applications) and operations with duplicates (Stocks and Receivables). The breakdown of the tangible assets was made based on its main components provided as warrantees for loans like Machinery & Equipment and Land & Buildings. For an analysis extension, three metrics for leverage (accounting, financial and market) were applied and the sample was divided into economic sectors, adopted by BM&FBOVESPA. The data model in dynamic panel estimated by a systemic GMM of two levels was used in this study due its strength to problems of endogenous relationship as well as the omitted variables bias. The found results suggest that current resources are determinants of the capital structure possibly because they re characterized as proxies for financial solvency, being its relationship with debt positive. The sectorial analysis confirmed the results for current resources. The tangibility of assets has inverse proportional relationship with the leverage. As it is disintegrated in its main components, the significant and negative influence of machinery & equipment was more marked in the Industrial Goods sector. This result shows that, on average, the most specific assets from operating activities of a company compete for a less use of third party resources. As complementary results, it was observed that the leverage has persistence, which is linked with the static trade-off theory. Specifically for financial leverage, it was observed that the persistence is relevant when it is controlled for the lagged current assets classes variables. The proxy variable for growth opportunities, measured by the Market -to -Book, has the sign of its contradictory coefficient. The company size has a positive relationship with debt, in favor of static trade-off theory. Profitability is the most consistent variable in all the performed estimations, showing strong negative and significant relationship with leverage, as the pecking order theory predicts / Este estudo teve como objetivo investigar a influ?ncia das classes de ativos e da desagrega??o da tangibilidade como fatores determinantes da estrutura de capital das empresas listadas na BM&FBOVESPA no per?odo de 2008 a 2012. Foram compostas duas classes de ativos circulantes que, agrupadas por liquidez, s?o analisadas pelas institui??es financeiras para concess?o de cr?dito: recursos correntes (Disponibilidades e Aplica??es Financeiras) e opera??es com duplicatas (Estoques e Clientes a Receber). A desagrega??o dos ativos tang?veis foi feita com base em seus principais componentes fornecidos como garantias para empr?stimos, como M?quinas & Equipamentos e Terrenos & Edifica??es. Para extens?o das an?lises, tr?s m?tricas para alavancagem (cont?bil, financeira e de mercado) foram empregadas e a amostra foi dividida em setores econ?micos adotados pela BM&FBOVESPA. O modelo de dados em painel din?mico estimado por GMM sist?mico de dois est?gios foi utilizado neste estudo por ser robusto ? problemas de rela??es end?genas assim como para vieses de vari?veis omitidas. Os resultados encontrados sugerem que os recursos correntes s?o determinantes da estrutura de capital possivelmente por serem caracterizados como proxies para solv?ncia financeira, sendo sua rela??o positiva com o endividamento. A an?lise setorial corroborou os resultados para recursos correntes. A tangibilidade de ativos possui rela??o inversamente proporcional com a alavancagem. Ao desagreg?-la em seus principais componentes, a influ?ncia negativa e significativa das M?quinas & Equipamentos foi mais acentuada no setor de Bens Industriais. Esse resultado demonstra que, em m?dia, os ativos mais espec?ficos da atividade operacional de uma empresa concorrem para menor uso de recursos de terceiros. Como resultados complementares, verificou-se que a alavancagem possui persist?ncia, o que coaduna com a teoria do static trade-off. Especificamente para alavancagem financeira, observou-se que a persist?ncia ? significativa quando controlada para as vari?veis de classes de ativos circulantes defasadas. A vari?vel proxy para oportunidades de crescimento, medida pelo Market-to-Book, tem o sinal de seu coeficiente controverso. O tamanho da empresa tem rela??o positiva com o endividamento, a favor da teoria do static trade-off. A lucratividade ? a vari?vel mais consistente em todas as estima??es realizadas, apresentando rela??o fortemente negativa e significativa com a alavancagem, conforme prediz a teoria do pecking order