Sparse and Stable International Portfolio Optimization and Currency Risk Management

2022 ◽  
Author(s):  
Raphael Burkhardt ◽  
Urban Ulrych
Keyword(s):  
Risk Management ◽  
Portfolio Optimization ◽  
Currency Risk ◽  
International Portfolio

Recent Developments in International Asset Allocation and Currency Risk Management

CFA Digest ◽  
1999 ◽  
Vol 29 (1) ◽  
pp. 53-54
Author(s):  
William H. Sackley
Keyword(s):  
Risk Management ◽  
Asset Allocation ◽  
Currency Risk ◽  
Recent Developments ◽  
International Asset Allocation

scholarly journals Currency risk management and hedge accounting - comparison of Polish and Ukrainian regulations

2018 ◽  
Vol 0 (2(40)) ◽  
pp. 37-43
Author(s):  
Мажена Ремлейн ◽  
Валентина Витальевна Ксендзук
Keyword(s):  
Risk Management ◽  
Currency Risk ◽  
Hedge Accounting

Risk management strategies via minimax portfolio optimization

2010 ◽  
Vol 207 (1) ◽  
pp. 409-419 ◽  
Author(s):  
George G. Polak ◽  
David F. Rogers ◽  
Dennis J. Sweeney
Keyword(s):  
Risk Management ◽  
Portfolio Optimization ◽  
Management Strategies ◽  
Risk Management Strategies

Currency Risk Management

2020 ◽  
pp. 261-279
Author(s):  
Hennie Van Greuning ◽  
Sofija-Sonja Brajovic Bratanovic
Keyword(s):  
Risk Management ◽  
Currency Risk

Multivariate portfolio optimization under illiquid market prospects: a review of theoretical algorithms and practical techniques for liquidity risk management

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mazin A. M. Al Janabi
Keyword(s):  
Risk Management ◽  
Portfolio Optimization ◽  
Real World ◽  
Optimization Algorithms ◽  
Liquidity Risk ◽  
Portfolio Risk ◽  
Market Conditions ◽  
Content Type ◽  
Illiquid Market ◽  
Investment Portfolios

Purpose This study aims to examine the theoretical foundations for multivariate portfolio optimization algorithms under illiquid market conditions. In this study, special emphasis is devoted to the application of a risk-engine, which is based on the contemporary concept of liquidity-adjusted value-at-risk (LVaR), to multivariate optimization of investment portfolios. Design/methodology/approach This paper examines the modeling parameters of LVaR technique under event market settings and discusses how to integrate asset liquidity risk into LVaR models. Finally, the authors discuss scenario optimization algorithms for the assessment of structured investment portfolios and present a detailed operational methodology for computer programming purposes and prospective research design with the backing of a graphical flowchart. Findings To that end, the portfolio/risk manager can specify different closeout horizons and dependence measures and calculate the necessary LVaR and resulting investable portfolios. In addition, portfolio managers can compare the return/risk ratio and asset allocation of obtained investable portfolios with different liquidation horizons in relation to the conventional Markowitz´s mean-variance approach. Practical implications The examined optimization algorithms and modeling techniques have important practical applications for portfolio management and risk assessment, and can have many uses within machine learning and artificial intelligence, expert systems and smart financial applications, financial technology (FinTech), and within big data environments. In addition, it provide key real-world implications for portfolio/risk managers, treasury directors, risk management executives, policymakers and financial regulators to comply with the requirements of Basel III best practices on liquidly risk. Originality/value The proposed optimization algorithms can aid in advancing portfolios selection and management in financial markets by assessing investable portfolios subject to meaningful operational and financial constraints. Furthermore, the robust risk-algorithms and portfolio optimization techniques can aid in solving some real-world dilemmas under stressed and adverse market conditions, such as the effect of liquidity when it dries up in financial and commodity markets, the impact of correlations factors when there is a switching in their signs and the integration of the influence of the nonlinear and non-normal distribution of assets’ returns in portfolio optimization and management.

Effectiveness of developed and emerging market FX options in active currency risk management

2019 ◽  
Vol 96 ◽  
pp. 130-146
Author(s):  
Suprita Vohra ◽  
Frank J. Fabozzi
Keyword(s):  
Risk Management ◽  
Emerging Market ◽  
Currency Risk
Sign in / Sign up

Export Citation Format

Share Document