Robust Near-Optimal Portfolio Construction - Ortec Finance
Robust Near-OptimalPortfolio ConstructionUse case4-stepsapproachApplicationsIntroductionLearn about smart algorithms to support robustinvestment portfolio constructing with quantitativeand qualitative input1
IntroductionGoal: constructing a realistic portfolio that is within the risk budget and robust for the assumptions madeNear-optimal optimization is a smart technique that enables you to find these portfolios in an efficient wayIt generates multiple asset allocations with a similar risk-return profileThe near-optimal portfolios are robust to changes in economic assumptionsIt enables to incorporate quantitative and qualitative input in the ultimate portfolio construction processRobust Near-Optimal Portfolio ConstructionUse case2
4-steps approach1. Define the risk budget2. Find all portfolios within the risk budget3. Incorporate qualitative arguments4. Construct a robust investment portfolioRobust Near-Optimal Portfolio ConstructionUse case3
4-steps approach1. Define the risk budgetSolvency ratio (average)Reflected by a relevant risk metric and horizon tailored to your organizationEfficientfrontierSolvency ratio (5% worst case)Example risk metrics for this use case: expected 1-year solvency ratio and the average1-year loss in the 5% worst case solvency ratio scenariosGrey area: risk budgetRobust Near-Optimal Portfolio ConstructionUse case4
4-steps approach2. Find all portfolios within the risk budgetApply the innovative Ortec Finance optimization techniques and let smart algorithmsfind all ‘near optimal’ portfolios within the risk budget(average)ratio (average)SolvencySolvencyFundingratioEfficient frontier and near-optimal areaNear-optimal ncyratio(5%worstcase)Near-optimal portfolios show similar risk and return characteristics for multiple assetallocationsRobust Near-Optimal Portfolio ConstructionUse case5
4-steps approach3. Incorporate qualitative argumentsIncorporate qualitative arguments such as ESG criteria, transaction costs, marketviews, and combine this with the robust quantitative asset allocation insights tofacilitate discussions with your investment committee(average)ratio (average)SolvencySolvencyFundingratioEfficient frontier and near-optimal areaNear-optimal ncyratio(5%worstcase)This example: High Yield credits are not preferred for due to a low ESG score of the currentmandateRobust Near-Optimal Portfolio ConstructionUse case6
4-steps approach4. Construct a robust investment portfolioIn construction, use a combination of (weighted) near-optimal portfolios thatsatisfies the risk budget and incorporates qualitative criteriaOPT3578A risk decomposition shows higher diversification benefits for portfolios 3, 5 and 7Robust Near-Optimal Portfolio ConstructionUse case7
4-steps approach4. Construct a robust investment portfolioIn construction, use a combination of (weighted) near-optimal portfolios thatsatisfies the risk budget and incorporates qualitative criteria(average)ratio (average)Solvency ratioSolvencyEfficient frontier and near-optimal areaEfficientEfficientfrontierfrontierNear-optimal portfoliosNear-optimal portfoliosGov. bondsCorp. bonds IGCorp. bonds HYCashEquity Dev. M.Equity EM M.Private EquityReal EstateSolvencySolvency ratioratio (5%(5% worstworst case)case)The candidate portfolio is a weighted combination of near-optimal portfolios 3, 5 and 7This portfolio is a realistic portfolio that is near optimal and within the risk budgetRobust Near-Optimal Portfolio ConstructionUse case8
ApplicationsImprove the riskadjusted return of theannual investment plan(robust portfolioconstruction)Robust Near-Optimal Portfolio ConstructionUse case9Facilitate thediscussion and align allstakeholders in theinvestment decisionprocessAvoid unnecessarytransaction costs
Learn moreLearn more about the underlying robust optimization technique with the technical paperRead paperRobust Near-Optimal Portfolio ConstructionUse case10
For more information, please contactAbout Ortec FinanceOrtec Finance is the leading provider of technologyand solutions for risk and return management.It is Ortec Finance’s purpose to enable people tomanage the complexity of investment decisions. Wedo this through delivering leading technologies andsolutions for investment decision making to financialinstitutions around the world. Our strength lies in aneffective combination of advanced models, innovativetechnology and in-depth market knowledge.Headquartered in Rotterdam, Ortec Finance has officesAmsterdam, London, Toronto, Zurich and in Hong Kong.John KuijtConsultantTessa KuijlSenior lead ortec-finance.com 20 countries represented500 customers96% retention rate3 trillion euro total assets managed by our clients.We enable people to manage the complexity of investment decision making11
The candidate portfolio is a weighted combination of near-optimal portfolios 3, 5 and 7 This portfolio is a realistic portfolio that is near optimal and within the risk budget Near-optimal portfolios Gov. bonds Corp. bonds IG Corp. bonds HY Cash Equity Dev. M. Equity EM M. Private Equity Real Estate Robust Near-Optimal Portfolio Construction .
Portfolio management Portfolio delivery cycle: ensures robust oversight over all programs and projects within a portfolio Review of portfolio performance: holistic review of the overall portfolio or specific elements, as well as a fact-based assessment of performance Portfolio management maturity assessment: independent review and
smaller standard deviation and turnover ratios which reduce the Sharpe ratios of optimal portfolio, compared with some well-known models in the literature. Keywords. Risk management, Robust portfolio optimization, Lower partial moment, Asym-metric uncertainty set, Multi-period portfolio selection. JEL. C61, G11 1 Introduction
Average k-shortest path length Load balancing property RRG is near optimal in terms of average k-shortest path length RRG is far from optimal for all other metrics GDBG was found near optimal for all metrics GDBG was used as a simulation benchmark to evaluate RRG Depending on traffic pattern, RRG is not always near optimal
2) Establish the best risk measure for Portfolio Optimization for the USE. 3) Develop portfolio optimization models to select an optimal portfolio for investment at Uganda Securities Market and other Ugandan financial institu-tions with interest in portfolio investment. 4) Add on the foundation and further research portfolio optimization on Se-
Alternative portfolio construction techniques: Use optimization but impose constraints (e.g., long only) Forego optimization entirely and use 1/N portfolio (equal weights) For very short HL, the 1/N portfolio indeed outperforms the unconstrained optimal portfolio (but not the long-only portfolio) For well-conditioned covariance
While there are many advanced robust portfolio optimization models, we focus on a number of basic robust formulations based on the classical mean-variance model. The main contribution of the paper is to examine if even the simplest robust portfolio models achieve robust performance compared to other port-folio strategies.
solutions of the robust portfolio optimization problem with the lower partial mo-ments (LPM), value-at-risk (VaR) or conditional value-at-risk (CVaR), as a risk measure, are presented. The application of the worst-case conditional value-at-risk (WCVaR) to robust portfolio management is proposed. This thesis considers
Business Certificates comprise tests of Reading, Writing, Listening and Speaking. In B1 Business Preliminary the tests for Reading and Writing are combined into one question paper. In C1 Business Higher and B2 Business Vantage there are separate Reading and Writing papers. Each test carries 25% of the total marks. Detailed information on each test paper follows later in this handbook. Marks .
