Optimizing investment allocation: a combination of Logistic Regression and Markowitz model

One of the biggest challenges in quantitative finance is the efficient allocation of capital. Thus, in this study, a two-step methodology was proposed, in which a combination of logistic regression and Markowitz model was performed to determine optimized portfolios. In this context, in the first step, fundamentalist indicators were used as inputs to the logistic … Read more

A New Coherent Multivariate Average-Value-at-Risk

A new multivariate performance measure Average-Value-at-Risk, mAVaR αevaluating the sum of N risky assets composing the portfolio of an investor with respect to riskN-dimensional risk level vectorαis proposed. We show that the proposed operator satisfies the four axioms of a coherent risk measure, while reducing to the one variableAverage-Value-at-RiskAVaR, in caseN= 1. In that respect, … Read more

Application of outer approximation to forecasting losses and scenarios in the target of portfolios with high of nonlinear risk

The purpose of this paper is to find appropriate solutions to concave quadratic programming using outer approximation algorithm, which is one of the algorithm of global optimization, in the target of the strong of concavity of object function i.e. high of nonlinear risk of portfolio. Firstly, my target model is a mathematical optimization programming to … Read more

Forecasting conceivable interest rate market scenarios and significant losses on interest rate portfolios using mathematical optimization

This study proposes a mathematical optimization programming model that simultaneously forecasts interest rate market scenarios and significant losses on interest rate market portfolios. The model includes three main components. A constraint condition is set using the Mahalanobis distance, which consists of innovation terms in a dynamic conditional correlation-generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model that represent … Read more

Risk management for forestry planning under uncertainty in demand and prices.

The forest-harvesting and road-construction planning problem basically consists of managing land designated for timber production and divided into harvest cells. For each time period in the given time horizon one must decide which cells to cut and what access roads to build in order to maximize expected net profit under a risk manageable scheme to … Read more

A CVaR Scenario-based Framework: Minimizing Downside Risk of Multi-asset Class Portfolios

Multi-asset class (MAC) portfolios can be comprised of investments in equities, fixed-income, commodities, foreign-exchange, credit, derivatives, and alternatives such as real-estate and private equity. The return for such {\em non-linear} portfolios is {\em asymmetric} with significant tail risk. The traditional Markowitz Mean-Variance Optimization (MVO) framework, that linearizes all the assets in the portfolio and uses … Read more

Concepts and Applications of Stochastically Weighted Stochastic Dominance

Stochastic dominance theory provides tools to compare random entities. When comparing random vectors (say X and Y ), the problem can be viewed as one of multi-criterion decision making under uncertainty. One approach is to compare weighted sums of the components of these random vectors using univariate dominance. In this paper we propose new concepts … Read more

Multistage Stochastic Portfolio Optimisation in Deregulated Electricity Markets Using Linear Decision Rules

The deregulation of electricity markets increases the financial risk faced by retailers who procure electric energy on the spot market to meet their customers’ electricity demand. To hedge against this exposure, retailers often hold a portfolio of electricity derivative contracts. In this paper, we propose a multistage stochastic mean-variance optimisation model for the management of … Read more