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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,291 papers · 148 categories

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106212317423 · Jun 202019922001200920182026
48 results for portfolio success rate

Proposes a new framework to manage venture capital portfolio risk by focusing on deal-level correlations.

problem Managing venture capital portfolio risk, especially extreme outcomes.
method Gaussian-copula-based framework that learns deal-level dependence from observed joint success frequencies.
result Correlation amplifies extreme upside outcomes, shifting portfolio distribution toward heavier right tails.

A model explains why 4% is a safe retirement withdrawal rate.

problem Determining a safe withdrawal rate for American retirees.
method Discrete-time model of stochastic returns on assets and their moments.
result The 4% rule emerges from adjusting high expected rates of return for various risks.

The paper defines successful active management and introduces a framework.

problem The elusive criteria for successful active management in the literature.
method Introducing definitions of key concepts and a logically coherent evaluation framework.
result A strong defense of active management emerges through the defined concepts.

Study analyzes costs of managing research funds, developing a model for optimal administration.

problem High variability in administration costs among research funding agencies.
method Identified standard agency activities, developed a model estimating optimum portfolio success rate and administration ratio.
result Model estimates optimum portfolio success rate and administration ratio based on input variables.

Model predicts startup success based on data-driven analysis.

problem Evaluating the quality of startup companies.
method Developed a model using a dataset of startup companies, their founders, and investors. Used a Bayesian approach to calculate features and exit probabilities.
result Model constructs portfolios with high exit rates, nearly double that of top venture capital firms.

Paper proposes an efficient algorithm to handle high-order portfolio moments.

problem Designing portfolios with high-order moments (skewness and kurtosis) is computationally challenging.
method Proposes a SCA algorithm framework for solving high-order portfolios efficiently.
result Demonstrates the efficiency of the proposed algorithm through numerical experiments.

Optimal portfolio design for statistical arbitrage in finance.

problem Designing optimal mean-reverting portfolios for statistical arbitrage.
method General problem formulation with investment leverage constraint, followed by successive convex approximation method.
result The proposed model and algorithms effectively construct portfolios with satisfactory mean reversion and variance properties.

Optimizes Iron Condor portfolios for better risk and profit management.

problem Transient value process of Iron Condor portfolios not well studied.
method Formulated as a stochastic optimal control problem, using bounded martingale assumption.
result Optimal stopping time aligns with expiration for submartingale value process.

We solve a multi-period portfolio optimization problem using D-Wave Systems' quantum annealer. We derive a formulation of the problem, discuss several possible integer encoding schemes, and present numerical examples that show high success rates. The formulation incorporates transaction costs (including permanent and t…

2015-08-22abs ↗pdf ↗

Unified framework for ESG-inclusive portfolio optimization and pricing.

problem Incorporating ESG ratings into dynamic asset pricing theory.
method Introducing ESG-valued return as a linear transformation of financial and ESG scores, preserving traditional risk aversion with an ESG affinity parameter.
result Developed a more complex portfolio optimization problem in a space governed by reward, risk, and ESG score.

Proposes a bond portfolio solution for managing interest rate risk.

problem Managing long-term assets and liabilities under interest rate risk.
method Proposes a bond portfolio solution based on ambiguity-averse preferences, accommodating various constraints and interest rate perturbations.
result Optimal portfolio can be computed as a simple generalized least squares problem, enhancing out-of-sample performance.

We define risk-free portfolios using three gauge invariant differential operators that require such portfolios to be insensitive to price changes, to be self-financing, and to produce a zero real return so there are no risk-free profits. This definition identifies the risk-free rate as the return of an infinitely diver…

2016-05-11abs ↗pdf ↗

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.

A simplified model for fixed income portfolio optimisation.

problem Modeling interest rates and credit risk in fixed income portfolios.
method Proposes a two-factor model for the time evolution of the efficient frontier.
result The efficient frontier is mainly controlled by linear constraints, with standard deviation less important.

Paper tackles ESG rating disagreement in sustainable investing portfolios.

problem Lack of alignment between ESG ratings from different agencies affects investment decisions.
method Proposes a nonlinear optimization model reformulated as a convex quadratic program to address ESG rating disagreement.
result The proposed model can effectively manage ESG rating disagreement and improve investment decisions.

Optimizes portfolios using anticipated interest rate information.

problem Maximizing utility in financial models with future interest rate trends.
method Enlargement of filtrations, affine diffusion process, Markov chain modeling.
result Explicit formulas for expected logarithmic utility.

Study optimal portfolio strategies with time-varying discount rates.

problem Optimizing portfolio decisions with a non-constant discount rate.
method Introduced subgame perfect strategies to handle time inconsistency, using fixed point iteration to find the utility-weighted discount rate.
result Subgame perfect strategies are equivalent to optimal strategies under certain utility function assumptions.

Study benchmarks cryptocurrency risk using GBM, revealing Lognormal limitations.

problem Tackles limitations of Lognormal assumption in modeling cryptocurrency volatility and VaR.
method Applies Geometric Brownian Motion (GBM) with Maximum Likelihood Estimation and correlated Monte Carlo Simulation.
result Observed limitations of Lognormal assumption in cryptocurrency volatility and VaR calculations.

The paper develops ML algorithms for calibrating credit rating transition models for high and low default portfolios.

problem Calibration of credit rating transition models for high and low default portfolios.
method Developed Maximum likelihood (ML) algorithms, including Laplace approximation for high-default portfolios and particle filter with Gaussian process regression for low-default portfolios.
result Both algorithms produce accurate approximations of the likelihood function and ML estimates of model parameters.

A declining CVaR glidepath framework for TDF design with Chilean pension system application

problem Designing Target-Date Funds around an explicit return objective while controlling risk
method Propose a framework for designing TDFs with a declining CVaR constraint
result Key feature: conservative evaluation of each glidepath

Investigates optimal portfolio strategies in markets with latent side information.

problem Investment problem in markets with latent dependence structure and side information.
method Dynamic and constant portfolio strategies, analyzing log-optimal portfolio as benchmark.
result Optimal dynamic strategy growth rate asymptotically converges to constant strategy in stationary markets.

Paper models foreign exchange markets and develops an on-line portfolio selection algorithm.

problem Modeling and predicting returns in foreign exchange markets.
method Matrix-valued time series model, trading matrices, and cross rate method.
result Proves the profitability and universality of the on-line portfolio selection algorithm.

The paper calculates how fast optimal investment strategies approach CRRA strategies in stochastic factor models.

problem Understanding convergence rates of optimal investment strategies in stochastic factor models.
method Analyzes optimal feedback functions in nonlinear and quadratic term structure models, considering decay of bond prices and power-like utility at high wealth levels.
result Convergence rates of optimal investment strategies to CRRA strategies are determined by bond price decay and power-like utility behavior.

A new factor analysis method using ICA reduces portfolio concentration and diversifies excess kurtosis.

problem Standard factor analysis suffers from issues with pairwise correlations of asset returns.
method Identifies factors based on non-Gaussianity instead of variance, using ICA.
result Fat-tailed portfolios significantly reduce portfolio concentration and winner-takes-all problem.

Paper tackles time inconsistency in portfolio management with stochastic volatility and power utility.

problem Time inconsistency in portfolio management with stochastic volatility and power utility.
method Extended Hamilton Jacobi Bellman (HJB) equation, fixed point iteration, and linear parabolic PDE.
result Subgame perfect strategies are characterized and solved through numerical experiments.

Study introduces AMVP and AMRR for dynamic portfolio optimization in volatile markets.

problem Optimizing portfolios in volatile and nonstationary financial markets.
method Adaptive Minimum-Variance Portfolio (AMVP) framework with ARFIMA-FIGARCH processes and non-Gaussian innovations.
result Demonstrated superior performance in risk reduction and portfolio stability during market breaks.

This paper optimizes international portfolios considering currency overlay costs and constraints.

problem Limited risk diversification in multi-currency portfolios due to currency concentration.
method Proposes a model integrating currency overlay and asset allocation optimization, accounting for costs and constraints.
result Inclusion of costs significantly alters optimal portfolio decisions and risk-return trade-offs.

This paper models how funds choose between competing ESG rating methodologies based on investor preferences.

problem Competing ESG rating methodologies lead to different portfolio rewards and fund fees.
method Modeling funds with heterogeneous ESG priorities and analyzing portfolio changes and investor demand.
result Funds specialize more, but provider scores, investor participation, and equilibrium fees decrease in the benchmark equilibrium.

Paper solves high-order portfolio optimization with cardinality constraint.

problem Solving non-convex cardinality constrained high-order portfolio optimization.
method Transformed cardinality constraint into penalty term, proposed pDCA, pDCAe, and SCA algorithms.
result Proposed algorithms achieve high utility and sparse solutions efficiently.

Maximizing withdrawal success in a pooled annuity fund with multiple annuitants.

problem Optimizing withdrawal success in a pooled annuity fund with homogeneous annuitants.
method Maximizing the probability of completing withdrawals until death over portfolio weight functions.
result Increasing the number of annuitants can significantly increase the maximum probability of withdrawal success.

Investment strategy using fractional Kelly portfolios for better growth expectations.

problem Understanding optimal growth strategies for investors with varying risk appetites.
method Developed a mathematical framework for fractional-Kelly portfolios, analyzing Sharpe ratios and log-returns.
result Fractional Kelly portfolios provide a simple distributional relationship between Sharpe ratio, fractional coefficient, and log-returns.

The study analyzes how covariance estimation errors affect the global minimum-variance portfolio under heavy-tailed distributions.

problem The impact of covariance estimation errors on the global minimum-variance portfolio under heavy-tailed distributions.
method Characterization of covariance-estimation error's effect on GMVP suboptimality, derivation of regret identity and bound, application to heavy-tailed returns.
result The decision geometry of GMVP regret is invariant to a (p-1)-dimensional projection of the error matrix, with invariance to the covariance-scale direction as an exact special case.

A new portfolio model improves on Kelly's by accounting for estimation error.

problem Estimation error in Kelly portfolio optimization.
method Wasserstein distributionally robust optimization (DRO) to define a robust log-optimal portfolio.
result The Wasserstein-Kelly portfolio outperforms the Kelly portfolio in out-of-sample testing.

The study proposes a framework to assess sustainability of firms using fund-level classifications and portfolio holdings.

problem To capture market-based sustainability assessments of firms.
method Exploiting fund-level sustainability classifications and granular portfolio holdings to construct Market-Implied Sustainability (MIS) scores.
result MIS scores capture sustainability dimensions different from conventional ESG ratings and improve portfolio performance.

We give a detailed account of correlations between credit sector/quality and treasury curve factors, using the robust framework of the Barclays POINT Global Risk Model. Consistent with earlier studies, we find a strong negative correlation between sector spreads and rate shifts. However, we also observe that the correl…

2013-12-05abs ↗pdf ↗

Maximizes probability of completing investment schedules with optimal portfolio weights.

problem Optimizing probability of completing investment schedules with optimal portfolio weights.
method Computing maximum probability and optimal portfolio weight functions for various rebalancing schedules.
result Noticeable improvements in probability to complete schedules with optimal portfolio weights.

Paper proposes a surrogate model for efficient experience rating in large insurance portfolios.

problem Inexpensive and transparent computation of Bayesian premiums for large insurance portfolios.
method Surrogate modeling approach using likelihood-based summary statistics.
result Reduced computational burden and provided a transparent way of computing Bayesian premiums.