The article develops a model for skewness risk in risk parity portfolios.
problem Managing skewness risk in asset allocation models.
method Modeling asset returns with skewness and jumps, deriving analytical formulas for risk contributions.
result Skewness-based risk parity portfolios outperform volatility-based portfolios in managing jump risks.
The paper proposes a new model using financial big data to improve portfolio risk analysis.
problem Addressing potential information loss in portfolio risk measurement.
method Uses financial big data to incorporate out-of-target-portfolio information and overcomes the curse of dimensionality.
result The use of financial big data improves small portfolio risk analysis.
Study proposes a new risk measure for optimal portfolio allocation.
problem Challenges in estimating optimal portfolios based on pessimistic risk.
method Introduces uniform pessimistic risk and computational algorithm.
result Demonstrates the usefulness of the proposed risk and portfolio model with real data analysis.
Hybrid model combines risk measures for better portfolio allocation.
problem Optimizing portfolios with various risk measures.
method Mean-variance hybrid model combining spectral risk measure and quantile optimization.
result Hybrid model outperforms classical mean-variance model in risk allocation.
Managing a portfolio to a risk model can tilt the portfolio toward weaknesses of the model. As a result, the optimized portfolio acquires downside exposure to uncertainty in the model itself, what we call "second order risk." We propose a risk measure that accounts for this bias. Studies of real portfolios, in asset-by…
New vine copula method forecasts portfolio risk measures robust to market downturns.
problem Inaccurate risk measure estimation for financial portfolios due to lack of cross-dependency capture.
method Combines vine copulas with ARMA-GARCH models for marginal risk estimation.
result Portfolio is robust to American market downturns but not European market.
Paper optimizes trend-following portfolios using autocorrelation models.
problem Developing an optimal trend-following portfolio strategy.
method Introduces a unifying theoretical setting with autocorrelation models for covariance matrices of trends and risk premia. Specifies practical models for covariance matrices. Decomposes optimal portfolio into four basic components.
result Empirical backtests confirm overperformance of the proposed optimal portfolio.
New method to handle credit portfolio model uncertainties.
problem Model risk in credit portfolio models.
method Demonstrates comprehensive yet easy-to-implement approach to uncertainty in model parameters.
result Comprehensive method to deal with model uncertainties.
This note finds closed-form solutions for mean-risk portfolios using a specific type of mixture distribution.
problem Finding optimal portfolios under mean-risk criteria for general distributions.
method Using normal mean-variance mixture (NMVM) distributions, the paper derives closed-form expressions for mean-risk frontiers by optimizing a Markowitz model with adjusted return vectors.
result Closed-form solutions for mean-risk portfolios are found for return vectors following NMVM distributions.
MILLION framework optimizes portfolio risk and return efficiently.
problem Optimizing risk and return in AI for FinTech portfolio management.
method Two phases: return maximization with auxiliary objectives and risk control with portfolio interpolation and improvement.
result Framework achieves fine-grained risk control and improved return rates.
Paper compares credit portfolio risks using robust Bernoulli mixture models.
problem Tackles risk bounds and comparison of credit portfolio losses.
method Uses Bernoulli mixture models with conditional independence and stochastic increasing defaults.
result Provides conditions for comparing conditional default probabilities and portfolio losses.
New formula for portfolio risk management using conditional PDEs.
problem Optimal diversification and risk management of portfolios.
method Closed-form formula for conditional probability, Gaussian copulas, conditional risk-neutral PDE.
result Dynamic monitoring of portfolio volatilities and weights from PDEs.
Framework for systemic risk modeling using jointly exchangeable arrays.
problem Systemic risk in insurance portfolios with interactions.
method Jointly exchangeable arrays, central limit theorems, simulation-based validation.
result Asymptotic approximations for total portfolio losses in large portfolios over long time horizons.
New risk measures improve portfolio diversification and stability.
problem Concentration risk in traditional portfolio optimization methods.
method Equal-correlation portfolio strategy with mathematical optimization.
result Improved risk diversification and stable returns.
We derive simple return models for several classes of bond portfolios. With only one or two risk factors our models are able to explain most of the return variations in portfolios of fixed rate government bonds, inflation linked government bonds and investment grade corporate bonds. The underlying risk factors have nat…
Extends ASRF model for green and brown loans, accounting for systematic and idiosyncratic risks.
problem Credit risk assessment for portfolios of green and brown loans.
method Two-factor copula structure, skewed distributions for systematic risk, Gaussian for idiosyncratic risk, non-uniform exposure setting.
result Portfolio loss convergence to a limit reflecting green and brown loan characteristics.
This paper compares modern portfolio theories and applies them to real-world portfolio selection.
problem Balancing risk and return in financial investments.
method Introduction of Markowitz's MPT and Fernholz's SPT, application of four models (Markowitz, Constant Correlation, Single Index, Multi-Factor), and use of Portfolio Algorithm and time series models for prediction.
result Comparison and evaluation of portfolio performance and risk management strategies.
Research evaluates three risk models for portfolio construction during market downturns.
problem Challenges in constructing quantitative portfolios using statistical risk models.
method Three statistical risk models tested on 1,000 stocks across four periods.
result Models consistently outperform market returns in various crises.
The paper optimizes portfolios using a new GARCH model with regime switching and tempered stable innovations.
problem Mitigating left tail risk in multi-asset portfolios.
method Proposes a Markov regime-switching GARCH model with multivariate normal tempered stable innovation (MRS-MNTS-GARCH) for portfolio optimization.
result Optimal portfolios with tail risk measures outperform standard deviation-based portfolios and equally weighted portfolios in various performance metrics.
Limited liability reduces leveraged risk in loan portfolio management models.
problem The impact of limited liability on risk in loan portfolio management models is not well understood.
method Formulated four models to analyze the effect of limited liability on risk and return in loan portfolio management.
result Including limited liability in loan portfolio management models produces better results in minimizing risk and maximizing expected return.
Paper uses DRL to optimize portfolios, balancing risk and return.
problem Optimizing portfolios under market uncertainty and risk constraints.
method Integrates Sharpe ratio-based reward with risk control mechanisms, uses PPO for adaptive asset allocation.
result DRL agent stabilizes volatility but sacrifices risk-adjusted returns.
Study quantifies model risk in dynamic portfolio selection using KL divergence.
problem Model risk in financial portfolio selection under uncertainty.
method Defined model risk as KL divergence loss, solved nonlinear equations for optimal robust strategy.
result Optimal robust strategy can be obtained semi-analytically in worst case scenario.
The paper optimizes portfolios using relative tail risk measures.
problem Optimizing portfolios with respect to relative tail risk.
method Analytic forms of portfolio CoVaR and CoCVaR derived on a market model. Monte-Carlo simulation for CoCVaR and marginal contributions. Risk budgeting method applied.
result Derivation of analytic forms for CoVaR and CoCVaR, and their marginal contributions.
A model-free hedging method using stock crowding scores.
problem Designing costless portfolio strategies to hedge market risk.
method Network analysis of fund holdings to compute crowding scores, constructing long-short portfolios without numerical optimization.
result Long-short portfolios provide protection against both small and large market price fluctuations.
The study assesses carbon risk in investment portfolios and proposes new management strategies.
problem The impact of carbon risk on stock pricing and portfolio construction.
method Developed a BMG risk factor and estimated time-varying carbon beta using a multi-factor model.
result Carbon risk can be incorporated into portfolio construction to reduce unrewarded financial risks.
PredACGAN optimizes portfolios by balancing returns and risk.
problem Difficulty in considering portfolio risk with deterministic deep learning models.
method PredACGAN uses ACGAN structure for probabilistic predictions and risk measurement.
result PredACGAN portfolios outperform non-PredACGAN portfolios in terms of returns and risk metrics.
Optimizes cryptocurrency portfolios using MNTS GARCH model.
problem Optimizing cryptocurrency portfolios with non-Gaussian return dynamics.
method Multivariate normal tempered stable (MNTS) GARCH model for non-Gaussian returns, Foster-Hart risk optimization.
result Foster-Hart optimization yields a more profitable portfolio with better risk-return balance.
Paper uses neural networks to compress large portfolios of options, reducing risk and capital requirements.
problem Managing risk and capital requirements for large portfolios of financial options.
method Artificial neural network framework for portfolio compression, static hedging, and risk management.
result The compressed portfolio's risk profiles align closely with the target portfolio's, reducing capital requirements.
Bayesian Parametric Portfolio Policies corrects overestimation of utility and risk in traditional PPP.
problem Traditional Parametric Portfolio Policies ignore policy risk, leading to overestimation of expected utility and understatement of portfolio risk.
method Developed Bayesian Parametric Portfolio Policies (BPPP) by placing a prior on policy coefficients to correct the decision rule.
result BPPP delivers higher Sharpe ratios, lower turnover, larger investor welfare, and lower tail risk compared to traditional PPP.
Risk diversification is one of the dominant concerns for portfolio managers. Various portfolio constructions have been proposed to minimize the risk of the portfolio under some constrains including expected returns. We propose a portfolio construction method that incorporates the complex valued principal component anal…
The paper develops diverse risk models for US stock portfolios.
problem Maximizing profits while minimizing risk in stock markets.
method Various high-dimensional risk models and investment strategies tested.
result Out-of-sample tests show improved portfolio performance.
A new framework for robust risk measurement and portfolio optimization.
problem Uncertainty in mean-covariance space and portfolio optimization challenges.
method Modeling uncertainty with Gelbrich distance and prior structural information, related to optimal transport theory.
result Mean-covariance robust portfolio optimization simplifies to Markowitz model with a regularization term.
Proposes a network-based strategy to manage financial market risks.
problem Managing extreme events in volatile financial markets.
method Extreme value theory, network model, maximum independent set, value at risk, expected shortfall.
result Developed portfolio strategies improve risk diversification.
Efficiently simulates risk budgeting portfolios using novel algorithms.
problem Estimating risk contributions in portfolios efficiently.
method Cutting planes algorithm, specialised SGD for Expected Shortfall, numerical simulations.
result Outperforms standard convex optimisation solvers in estimating risk budgeting portfolios.
Paper studies optimal investing for retirees with risk constraints.
problem Retirees' longevity and living standard risks in a fluctuating market.
method Formulated as a portfolio choice problem under time-varying risk capacity constraint. Derived optimal investment strategy using differential equations. Demonstrated endogenous spending measure and active investment strategy.
result Time-varying risk capacity constraint impacts asset allocation in retirement.
We discuss a class of risk-sensitive portfolio optimization problems. We consider the portfolio optimization model investigated by Nagai in 2003. The model by its nature can include fixed income securities as well in the portfolio. Under fairly general conditions, we prove the existence of optimal portfolio in both fin…
Deep neural networks improve portfolio construction by jointly modeling returns and risks.
problem Traditional portfolio construction methods fail under time-varying market conditions.
method Jointly modeling dynamic expected returns and risk structures using deep neural networks.
result Deep forecasting model achieves competitive predictive accuracy and economically meaningful directional accuracy.
In the paper, we use and investigate copulas models to represent multivariate dependence in financial time series. We propose the algorithm of risk measure computation using copula models. Using the optimal mean-CVaR portfolio we compute portfolio's Profit and Loss series and corresponded risk measures curves. Value-…
The paper proposes a new approach to portfolio selection that maximizes diversification and return.
problem Maximizing diversification and return in portfolio selection.
method A bi-objective model that maximizes a diversification measure and portfolio expected return.
result The return-diversification approach outperforms strategies based on diversification or classical risk-return approaches.
Paper proposes a CNN model for improved multi-asset portfolio risk prediction.
problem Challenges in risk management of multi-asset portfolios due to limited correlation capture.
method Uses CNN and image processing to convert financial data into images for enhanced feature extraction.
result CNN model significantly outperforms traditional methods in risk prediction accuracy.
TDA-based portfolios show better risk-adjusted returns than classical methods.
problem Traditional portfolio selection methods fail to capture complex asset dynamics.
method Topological Data Analysis (TDA) using persistence landscapes to quantify portfolio risk.
result TDA-based portfolios outperform classical models in excess mean return and financial ratios.
A new portfolio method using quantum mechanics improves risk diversification.
problem Improving risk-based portfolio construction methods for multi-asset portfolios.
method Schrödinger principal component analysis applied to extract common factors from asset fluctuations.
result The proposed method outperforms conventional risk parity and other risk diversification methods.
Paper studies portfolio investment under volatility uncertainty and short-sale constraints, improving risk-adjusted returns.
problem Investment portfolio optimization under volatility uncertainty and short-sale constraints.
method Sublinear expectation model to handle volatility uncertainty, constructing SLE-MUV model.
result Pareto frontier of SLE-MUV model is a continuous convex curve with polynomial analytical expression.
New model optimizes portfolios over multiple periods using predictive control.
problem Optimizing multi-period portfolios with risk and variance objectives.
method Model Predictive Control with Mean-Variance and Risk Parity.
result 30x faster and more robust solutions compared to single period models.
Paper proves existence and computation of Risk Budgeting portfolios.
problem Challenges to mean-variance framework sensitivity.
method Mathematical proofs and stochastic algorithms for risk measures.
result Existence and uniqueness of Risk Budgeting portfolios for various risk measures.
Study on risk contributions of portfolios using lambda quantile risk measures.
problem No known allocation rule for non-positively homogeneous risk measures.
method Defined lambda quantiles on portfolio compositions, derived derivatives, and introduced generalized Euler contributions.
result Explicit formulae for the derivatives of lambda quantiles, showing their homogeneity properties.
Investigates MAD-RP portfolios for asset allocation.
problem Finding optimal asset allocation strategies.
method Uses MAD as risk measure and proposes computational formulations for MAD-RP portfolios.
result MAD-RP portfolios offer balanced risk and profitability.
CERM calculates climate risks in bank loans.
problem Estimating climate risks in bank credit portfolios.
method Adapts credit risk models to include physical and transition risks.
result Calculates incremental credit losses due to climate risks.