Here we present a novel approach to how the Chief Investment Office (CIO) can select investment strategies to allocate to and to decide the percentage allocation to them. The method that we outline here is a continuation of our previous research on recommender systems science[13]. The aim of...

We adopt deep learning models to directly optimize the portfolio Sharpe ratio. The framework we present circumvents the requirements for forecasting expected returns and allows us to directly optimize portfolio weights by updating model parameters. Instead of selecting individual assets, we...

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...

We consider a general continuous mean-variance problem where the cost functional has an integral and a terminal-time component. We transform the problem into a superposition of a static and a dynamic optimization problem. The value function of the latter can be considered as the solution to a...

Covariance appears throughout investment management, e.g., in risk reporting and control, portfolio construction, risk parity, smart beta, algorithmic trading, and hedging. It is usually represented via multi-factor model. The form’s fewer parameters and structure—comovement through...

Robust optimization (RO) is a young and active research field that has been mainly developed in the last 15 years. RO techniques are very useful for practice and not difficult to understand for practitioners. It is therefore remarkable that real-life applications of RO are still lagging behind;...

In this paper, we treat an optimal control problem of a stochastic two-machine flowshop with machines subject to random breakdown and repair. While the problem is difficult to solve, it can be approximated by a deterministic problem when the rates of machine failure and repair become large....

This paper presents the relations of optimized combination with traditional combination and permutation. Combinatorics is a collection of several computing techniques used in science and management. In this research paper, new results on both combination and permutation are introduced for the...

We present a model for optimal execution of the financial derivatives. We show that if rehedging of the underwriter of the derivative is considered, the optimal strategy is generally non-deterministic even for deterministic price impact functions. This approach can be utilized for optimal...