We introduce a generic solver for dynamic portfolio allocation problems when the market exhibits return predictability, price impact and partial observability. We assume that the price modeling can be encoded into a linear state-space and we demonstrate how the problem then falls into the LQG...

Protecting portfolio against extreme losses is a fundamentally difficult task since past experience provides a poor guidance for the future. This paper focuses on a robust approach to the portfolio insurance, which does not require historical calibration, and therefore avoids the hazards of data...

We consider an investor faced with the utility maximization problem in which the risky asset price process has pure-jump dynamics affected by an unobservable continuous-time finite-state Markov chain, the intensity of which can also be controlled by actions of the investor. Using the classical...

Investors typically measure an asset’s potential to diversify a portfolio by its correlations with the portfolio’s other assets, but correlation is useful only if it provides a good estimate of how an asset’s returns co-occur cumulatively with the other asset returns over the investor’s...

The Kelly Capital Growth Investment Strategy (KCGIS) is to maximize the expected utility of nal wealth with a logarithmic utility function. This approach dates to Bernoulli's 1738 suggestion of log as the utility function arguing that marginal utility was proportional to the reciprocal of...

This paper discusses multi-period investment processes under parameter uncer- tainty and criteria to maximize exponential growth. Applying an information- theoretical argument, we find, for a Bernoulli process, the least biased investment strategy consistent with an expected exponential growth...

In terms of regulatory and economic capital, credit risk is the most significant risk faced by banks. We implement a credit risk model - based on publicly available information . with the aim of developing a tool to monitor credit risk in a sample of large and complex banking groups (LCBGs) in...

We formulate a distributionally robust optimization problem where the deviation of the alternative distribution is controlled by a φ-divergence penalty in the objective, and show that a large class of these problems are essentially equivalent to a mean-variance problem. We also show that while...

The NP-hard nature of cardinality constrained mean-variance portfolio optimization problems has led to a variety of different algorithms with varying degrees of success in reaching optimality given limited computational resources and under the presence of strict time constraints in practice. The...