The goal of this thesis is to increase the understanding of 'alternative assets' and their interaction with other asset classes. This is a relevant area of focus as there are currently more assets available to investors than at any other time. Firstly several assets are reviewed to see if they should be considered for further analysis. This process examines the philosophical question of what is an asset class and also considers the ease of investing in each. The asset's return drivers are analysed using statistical and macroeconomic factor models. Most assets are found to be explained by up to seven macroeconomic factors; however, assets such as real estate, gold and wine are not explained well and thus may have portfolio diversification benefits. I then focus my study on the correlation structures of the asset returns. These are examined using rolling correlations and statistical testing of the stability of correlation matrices and correlations are found to time vary. Semicorrelation is adopted to differentiate correlations between those in outperforming and underperforming markets. I find that for many assets, correlations increase in underperforming markets and thus diversification fails when it is needed the most. Government bonds' diversification power is found to improve during underperforming markets and thus these are important for diversification. The final section applies an AG-DCC model to retrieve conditional correlations and study their driving factors using macroeconomic factor models. This model proves that correlations change over time and are asymmetric. I correct for overestimation of goodness-of-fit and my models show an average ability to explain changes in conditional correlations of approximately 7.5%, in some cases this is up to 30%. Two key factors that are found to drive correlations are dividend yield and the oil price; correlations response to factors implies that higher correlations occur during periods of economic underperformance.

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Liquidity pricing is very critical in explaining fund performances, especially during periods where liquidity experiences sudden surges or dry-ups (i.e. liquidity imbalances, LIs) connected with a significant price movements. Hence, in the first part of the thesis we decided to investigate this relationship, focusing on an illiquid markets where the effect should be more evident. Even if transaction volumes do not seem to provide any pricing information, we find that return chasing behaviour and smart effects coexist, with the former being associated to investment activities and the latter to disinvestments. Since our empirical results confirm that liquidity and prices influences each other, we decide to investigate the formation of investors' choices through a theoretical model that embeds liquidity, risk and return expectations in the pricing of mutual funds. We model net flows at fund-level and we observe a LI upon the occurrence of four market conditions: high transaction costs, wrong endogenous pricing policy, growing uncertainty of fund returns and a negative "tail" state of the economy. Finally, since manager's actions are not considered in our models but seem to be important in the pricing of such vehicles, we study their effect on investors' decisions via a principal-agent dilemma setting. We discover that among "direct" (i.e. remuneration policies) measures, fund price volatility sensitive-remuneration solves the dilemma and different patterns among specialised investors and the aggregate market exist. Although similar variables drive preferences in direct real estate and the equity market, with performance related variables leading the trend, they often present opposite effects. We conclude that a limited and time-varying rationality and predictability exist in mutual fund markets.

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