Pricing Liquidity Risk with Heterogeneous Investment Horizons

We develop an asset pricing model with stochastic transaction costs and investors with heterogeneous horizons. Depending on their horizon, investors hold different sets of assets in equilibrium. This generates segmentation and spillover effects for expected returns, where the liquidity (risk) premium of illiquid assets is determined by investor horizons and the correlation between liquid and illiquid asset returns. We estimate our model for the cross-section of U.S. stock returns and find that it generates a good fit, mainly due to a combination of a substantial expected liquidity premium and segmentation effects, while the liquidity risk premium is small

Empirical tests on the Hungarian stock market efficiency: economic value of stock return forecasts

This paper focuses on the Hungarian stock market efficiency by applying a customized version of the recursive modeling approach and the switching portfolio strategy employed by Pesaran and Timmermann (1995). I investigate whether this modeling technique could have been more profitable comparing to a passive investment. I discover that the variables’ predictive power and the economic value of the forecasts are liable to changes during the examined timeframe and the switching trading strategy cannot beat the market in the full sample. It provides approximately 1.5 times higher wealth, than the portfolios under the different model selection criterions. However, splitting the sample into two, the economic value of the forecasts becomes significant and the switching strategy can result economic profit

How do Regimes Affect Asset Allocation?

International equity returns are characterized by episodes of high volatility and unusually high correlations coinciding with bear markets. We develop models of asset returns that match these patterns and use them in asset allocation. First, the presence of regimes with different correlations and expected returns is difficult to exploit within a framework focused on global equities. Nevertheless, for all-equity portfolios, a regime-switching strategy dominates static strategies out-of-sample. Second, substantial value is added when an investor chooses between cash, bonds and equity investments. When a persistent bear market hits, the investor switches primarily to cash. There are large market timing benefits because the bear market regimes tend to coincide with periods of relatively high interest rates.

Household Portfolios in Italy

We provide a detailed account of the portfolio of Italian households and its evolution, using repeated cross-sectional and panel data drawn from the 1989-98 Bank of Italy Survey of Household Income and Wealth. We offer an in-depth description of the lifetime pattern of asset holdings and their composition, the degree of asset diversification, and the propensity to invest in risky assets. The data also allow us to address some more fundamental issues on the determinants of household portfolios. We look at portfolio mobility and elaborate on the relevance of entry and exit costs. We also provide new evidence on the effect of income risk and information acquisition on portfolio choice.portfolio choice, diversification, portfolio mobility, information

A mean-variance Portfolio Optimizing Trading Algorithm using regime-switching Economic Parameters

In this master's thesis a model of algorithmic trading is constructed. The model aims to create an optimal investment portfolio consisting of a risk-free asset and a risky asset. The risky asset is in the form of a stock generated using regime-switching parameters with a Markov chain explaining the state of the economy. The optimization of the portfolio is carried out under certain assumptions and reasonable constraints on risk, transaction costs and amount traded. The constraint on nancial risk is implemented through the recognized mean-variance criterion, balancing the expected value of the portfolio against the variance of the portfolio after every time period. The algorithm is implemented using quadratic programming techniques in Matlab. By varying parameters of the model a sensitivity analysis is performed. Simulated scenarios and the behaviour of the algorithm is presented in graphs. The algorithm is found to be rational and outperforms a static portfolio in every scenario

Risk modelling in times of crisis

Financial market states of high volatility in bear markets are often characterized by an increase in correlation, decreasing the diversification benefits as markets behave more homogeneously. This research focuses on the expectations of correlation and volatility across different asset classes on a risk-parity portfolio by using different measurements of risk to analyze how differently they perform, especially in times of higher volatility and correlation. This work project objective is to measure the impact of dynamically adjusting the variance-covariance matrix when such risk measures alter significantly. Moreover, a clustered risk parity portfolio will be computed with the optimal returns from the asset classes, further improving performance

Real World Pricing of Long Term Contracts

Long dated contingent claims are relevant in insurance, pension fund management and derivative pricing. This paper proposes a paradigm shift in the valuation of long term contracts, away from classical no-arbitrage pricing towards pricing under the real world probability measure. In contrast to risk neutral pricing, the long term excess return of the equity market, known as the equity premium, is taken into account. Further, instead of the savings account, the numeraire portfolio isused, as the fundamental unit of value in the analysis. The numeraire portfolio is the strictly positive, tradable portfolio that when used as benchmark makes all benchmarked non negative portfolios supermartingales, which means intuitively that these are downward trending or at least trendless. Furthermore, the benchmarked real world price of a benchmarked claimis defined to be its real world conditional expectation. This yields the minimal possible price for its hedgable part and minimizes the variance of the benchmarked hedge error. The pooled total benchmarked replication error of a large insurance company or bank essentially vanishes due to diversification. Interestingly, in long terml iability and asset valuation, real world pricing can lead to significantly lower prices than suggested by classical no-arbitragea rguments. Moreover, since the existence of some equivalent risk neutral probability measure is no longer required, a wider and more realistic modeling framework is available for exploration. Classical actuarial and risk neutral pricing emerge as special cases of real world pricing.long term pricing; real world pricing; risk neutral pricing; numeraire portfolio; law of the minimal price; strong arbitrage; hedges imulation; diversification; liquidity premium