Portfolio optimisation
Quant funds look to AI to master correlations
Machine learning shows promise in grouping assets better, predicting regime shifts
Stock-picking finds unlikely champion in ex-Winton CIO
Matthew Beddall’s Havelock restyles value investing for the big data age
The standard market risk model of the Swiss solvency test: an analytic solution
This paper derives an alternative fast Fourier transform-based computational approach for calculating the target capital of the SST that is more than 600 times faster than a Monte Carlo simulation.
Factor investing: get your exposures right!
This paper is devoted to the question of optimal portfolio construction for equity factor investing. The authors discuss the question of multifactor portfolio construction and show that the simplistic approaches often used by practitioners tend to be…
Risk premia strategies – Lessons learned for the future
After a difficult 2018, investors are increasingly wary of risk premia, concerned that factors leading to underperformance might be a recurring problem. Imene Moussa, executive director at UBS, clarifies this issue
From log-optimal portfolio theory to risk measures: logarithmic expected shortfall
In this paper, the authors propose a modification of expected shortfall that does not treat all losses equally. We do this in order to represent the worries surrounding big drops that are typical of multiperiod investors.
Time to put real problems to the quantum machines
There is a lot to learn before quantum computers can be applied to specific financial problems
Skewed target range strategy for multiperiod portfolio optimization using a two-stage least squares Monte Carlo method
In this paper, the authors propose a novel investment strategy for portfolio optimization problems.
Portfolio optimization for American options
In this paper, the authors construct strategies for an American option portfolio by exercising options at optimal timings with optimal weights determined concurrently.
Risk Markets Technology Awards 2019: Vendors enter the pick-and-mix era
Modular tech and micro-services – plus new risk and regulatory needs – are creating openings for insurgents and incumbents
Value-ranked equity portfolios via entropy pooling
This paper demonstrates how to directly incorporate common value-investing idea into the portfolio optimization process.
Genetic algorithm-based portfolio optimization with higher moments in global stock markets
This paper investigates the distributional characteristics of stock market returns and analyzes the significance of higher moments.
The Kelly criterion in portfolio optimization: a decoupled problem
This paper examines how the Kelly criterion can be implemented into a portfolio optimization model that combines risk and return into a single objective function using a risk parameter.
Equity derivatives now biggest consumer of initial margin
Fragmented product set is 1.3% of OTC notional but attracts more margin than rates and forex
StanChart and Nasa join forces for quantum computing project
Bank is exploring quicker ways to solve portfolio optimisation
Efficient trading in taxable portfolios
This paper determines life-cycle trading strategies for portfolios subject to the US tax system.
Asset price bubbles and risk management
The purpose of this paper is to review the literature on asset price bubbles to study the impact that the existence of bubbles has on standard risk management methodologies.
A generalized risk budgeting approach to portfolio construction
This paper proposes a generalized risk budgeting approach to portfolio construction.
The untapped potential of stress tests
Quants propose technique to include stress testing in portfolio allocation
Stress hedging in portfolio construction
Bilgili, Ferconi and Ulitsky propose a constrained portfolio optimisation approach incorporating stress scenarios
Interconnectedness risk and active portfolio management
This paper studies centrality (interconnectedness risk) measures and their added value in an active portfolio optimization framework.
Insights into robust optimization: decomposing into mean–variance and risk-based portfolios
The authors of this paper aim to demystify portfolios selected by robust optimization by looking at limiting portfolios in the cases of both large and small uncertainty in mean returns.
Decomposition of portfolio risk into independent factors using an inductive causal search algorithm
This paper presents a method to estimate and decompose a portfolio’s risk along independent factors.
Stable linear-time optimisation in arbitrage pricing theory models
Gordon Ritter proposes a stable mean-variance optimisation for APT models