The paper optimizes dynamic portfolios using utility maximization and risk measures.
problem Maximizing expected utility in dynamic stochastic portfolio optimization.
method Solves a dynamic stochastic portfolio optimization problem numerically using evolutionary Hamilton-Jacobi-Bellman equations and Riccati transformations.
result Defines and computes the Conditional Value-at-Risk deviation (CVaRD) based Sharpe ratio for risk-adjusted performance.
Investors optimize their portfolios to maximize utility under drawdown constraints and stochastic volatility.
problem Maximizing utility relative to maximum performance under drawdown constraints and stochastic volatility.
method Approximations through coefficient expansion and nonlinear transformations, numerically computed.
result Investors need a different portfolio strategy in stochastic volatility compared to constant volatility.
Quantum stochastic walks optimize portfolios by leveraging financial networks, improving Sharpe ratios and reducing turnover.
problem Optimizing portfolios in noisy financial markets with superior risk-adjusted returns.
method Embed assets in a weighted graph, using quantum stochastic walks to derive optimal portfolio weights from the stationary distribution.
result Quantum stochastic walks can lift Sharpe ratios by up to 27% and reduce turnover from 480% to 2-90%.
The Fano ratio offers a more diversified portfolio than the Sharpe ratio in optimization.
problem Optimizing portfolio performance using the Sharpe ratio.
method Introducing and optimizing the Fano ratio as an alternative to the Sharpe ratio.
result Optimizing for the Fano ratio leads to more diversified and less skewed portfolios.
The Sharpe ratio, which is defined as the ratio of the excess expected return of an investment to its standard deviation, has been widely cited in the financial literature by researchers and practitioners. However, very little attention has been paid to the statistical properties of the estimation of the ratio. Lo (200…
Tests Sharpe ratio for skill vs luck in asset management.
problem Accuracy of Sharpe ratio in measuring skill vs luck.
method Statistical tests to assess the significance of Sharpe ratios.
result Tests reveal the statistical significance of Sharpe ratios and their impact of auto-correlation.
Unified framework linking firm signals and cross-asset spillovers for SDF estimation.
problem Estimating SDF with cross-asset spillovers and firm-level predictive signals.
method Maximizing Sharpe ratio to jointly estimate signals and spillovers, yielding interpretable SDF.
result SDF consistently outperforms benchmarks across various investment universes and market states.
Optimal option portfolios under Sharpe Ratio maximization with skew-elliptical t-distributed returns
problem Optimal option portfolios under Sharpe Ratio maximization
method Formulation for explicit portfolio weights
result Different optimal portfolios for Sharpe Ratio and return-to-Value-at-Risk (VaR) ratio
We develop a pricing rule for life insurance under stochastic mortality in an incomplete market by assuming that the insurance company requires compensation for its risk in the form of a pre-specified instantaneous Sharpe ratio. Our valuation formula satisfies a number of desirable properties, many of which it shares w…
Omega ratio is shown to be equivalent to Sharpe ratio under certain distributional assumptions.
problem Comparing Omega ratio to Sharpe ratio as performance indicators.
method Computation and analysis of Omega ratio for normal distribution and proof for elliptic distributions.
result Omega ratio is equivalent to Sharpe ratio for returns with elliptic distributions.
Paper connects Sharpe ratio and Student t-statistic, providing exact distribution and asymptotic behavior.
problem Error-prone Sharpe ratio due to statistical estimation of expected returns and volatilities.
method Derive exact distribution of Sharpe ratio for independent normally distributed returns, extend to AR(1) assumptions.
result Empirical Sharpe ratio is asymptotically optimal and achieves Cramer Rao bound.
The Sharpe ratio is a way to compare the excess returns (over the risk free asset) of portfolios for each unit of volatility that is generated by a portfolio. In this paper we introduce a robust Sharpe ratio portfolio under the assumption that the risk free asset is unknown. We propose a robust portfolio that maximizes…
New monotone Sharpe ratio measures investment performance.
problem Investment performance measurement.
method Introducing a new monotone Sharpe ratio and studying its properties.
result Established a connection with coherent risk measures and obtained an efficient representation.
Everyone misunderstands the Sharpe ratio, which measures risk in finance.
problem Misunderstanding of the Sharpe ratio as a risk metric.
method A critical analysis and rectification of the Sharpe ratio concept.
result Clarification of the Sharpe ratio's role in risk assessment.
We show that the martingale component in the long-term factorization of the stochastic discount factor due to Alvarez and Jermann (2005) and Hansen and Scheinkman (2009) is highly volatile, produces a downward-sloping term structure of bond Sharpe ratios, and implies that the long bond is far from growth optimality. In…
Tests factor models by decomposing market into body and tail legs, revealing inconsistent results.
problem Inconsistency between factor models and market behavior.
method Decomposes market into body and tail legs, testing factor models at daily and monthly frequencies.
result q5 model shows inconsistent results, with negative body and positive tail alphas at all split ratios.
We develop a theory for pricing non-diversifiable mortality risk in an incomplete market. We do this by assuming that the company issuing a mortality-contingent claim requires compensation for this risk in the form of a pre-specified instantaneous Sharpe ratio. We prove that our ensuing valuation formula satisfies a nu…
We study the finite horizon Merton portfolio optimization problem in a general local-stochastic volatility setting. Using model coefficient expansion techniques, we derive approximations for the both the value function and the optimal investment strategy. We also analyze the `implied Sharpe ratio' and derive a series a…
We use a continuous version of the standard deviation premium principle for pricing in incomplete equity markets by assuming that the investor issuing an unhedgeable derivative security requires compensation for this risk in the form of a pre-specified instantaneous Sharpe ratio. First, we apply our method to price opt…
New method to decompose portfolio performance ratios.
problem Understanding the drivers of portfolio performance ratios.
method Using Euler's theorem, decomposes performance ratios into modified ratios.
result Derives condition for new asset to improve portfolio performance.
A new measure, the implied Sharpe ratio, helps investors choose among European options.
problem No concise measure exists to compare different European options.
method Taylor series expansion of state-dependent coefficients in a nonlinear PDE.
result The option with the highest implied Sharpe ratio improves utility the most.
Post hoc test for Sharpe ratio improves pairwise comparisons.
problem Improving pairwise comparisons of Sharpe ratios.
method Analogous to Tukey's test, applied after rejecting equal Signal-Noise ratios.
result Maintains nominal type I rate and is moderately powerful.
Estimates true Sharpe ratio of selected assets with various methods.
problem Estimating the true Sharpe ratio of a selected asset with high in-sample ratio.
method Polyhedral lemma, James Stein shrinkage, debiasing, thresholding, empirical Bayes.
result James Stein estimator performs best across various parameter values.
A simple example shows that losing all money is compatible with a very high Sharpe ratio (as computed after losing all money). However, the only way that the Sharpe ratio can be high while losing money is that there is a period in which all or almost all money is lost. This note explores the best achievable Sharpe and …
When the in-sample Sharpe ratio is obtained by optimizing over a k-dimensional parameter space, it is a biased estimator for what can be expected on unseen data (out-of-sample). We derive (1) an unbiased estimator adjusting for both sources of bias: noise fit and estimation error. We then show (2) how to use the adjust…
We study hedging and pricing of unattainable contingent claims in a non-Markovian regime-switching financial model. Our financial market consists of a bank account and a risky asset whose dynamics are driven by a Brownian motion and a multivariate counting process with stochastic intensities. The interest rate, drift, …
New method for Sharpe ratio analysis in high dimensions using residual-based nodewise regression.
problem Consistency of Sharpe ratio estimators in high-dimensional portfolios.
method Residual-based nodewise regression for estimating precision matrix of errors and returns.
result Consistent Sharpe ratio estimators in various portfolio settings.
SGD favors flat minima exponentially more than sharp minima in deep learning.
problem Understanding how SGD selects flat minima in deep learning.
method Developed a density diffusion theory (DDT) to analyze minima selection.
result SGD exponentially favors flat minima over sharp minima due to Hessian-dependent noise.
Study decomposes market portfolio into body and tail legs, revealing systematic differences.
problem Understanding the relationship between body and tail components in market portfolios.
method Decomposes CRSP market portfolio into body and tail legs, analyzes their recombination identity.
result Recombination identity holds for all models but not for all, indicating systematic differences.
Investments with best performance are not associated with best Sharpe ratios.
problem The relationship between performance and risk-adjusted return (Sharpe ratio) is counterintuitive for heavy-tailed distributions.
method Synthetic and real data analysis of returns distributions.
result The best-performing investments are not the best in terms of Sharpe ratio, and vice versa.
The paper develops methods for conditional inference on the asset with the highest Sharpe ratio.
problem Performing inference on the asset with the highest Sharpe ratio among correlated assets.
method Conditional inference procedure using multivariate Sharpe ratio standard error, alternative tests, and asymptotic adjustments.
result The conditional inference procedure achieves nominal type I rate and maintains near-nominal rejection rates under the conditional null.
We prove that the Omega measure, which considers all moments when assessing portfolio performance, is equivalent to the widely used Sharpe ratio under jointly elliptic distributions of returns. Portfolio optimization of the Sharpe ratio is then explored, with an active-set algorithm presented for markets prohibiting sh…
Study applied stochastic spread pairs trading on Indian commodities.
problem Finding profitable trading pairs in Indian commodity market.
method Applied Johanssen Cointegration tests, selected cointegrated pairs, used single-factor stochastic model, optimized parameters using differential evolution and backtesting.
result Found 12 cointegrated pairs with a Sharpe ratio above 1.4.
Grover search for optimal portfolios based on Sharpe ratio.
problem Finding optimal portfolios with specific risk-return characteristics.
method Grover's algorithm applied to portfolio selection with oracles.
result Quantum algorithms can efficiently find optimal portfolios.
Double descent in portfolio optimization shows improved performance with complexity, then declines, due to overfitting.
problem Improving portfolio optimization performance with model complexity.
method Investigates the relationship between model complexity and out-of-sample performance in mean-variance portfolio optimization.
result Performance of low-dimensional models initially improves with complexity but declines due to overfitting. High-dimensional models show double ascent Sharpe ratio curve.
Study examines moving average trading rule's performance on stock indexes.
problem Linking trading rule performance to asset stochastic process.
method Calculated Sharpe ratio as a function of look-back period and asset distribution.
result Performance depends on autocorrelation vs. drift for different look-back periods.
The paper proposes an asset allocation strategy using the Sortino ratio for better performance.
problem Traditional asset allocation methods like the Sharpe ratio do not penalize negative returns adequately.
method The Sortino ratio is used to maximize asset allocation, penalizing only negative return variances.
result The Sortino ratio-based strategy outperforms traditional methods like the Kelly criterion.
The paper describes a method to infer the signal-to-noise ratio in portfolio optimization.
problem Estimating the signal-to-noise ratio in portfolio optimization problems.
method A statistic similar to the Sharpe Ratio Information Criterion is used for inference.
result The method works well for reasonable sample and asset universe sizes.
End-to-end neural network optimizes portfolios by directly learning allocations from features.
problem Error maximization in two-step portfolio optimization.
method Single feed-forward neural network combining prediction and optimization.
result Model-based end-to-end framework achieves Sharpe ratio of 1.16.
Paper derives a Pythagorean theorem for Sharpe ratio and validates a new method for portfolio optimization.
problem Optimizing investment risk with budget and return constraints.
method Replica analysis for portfolio optimization under non-specific probability distribution constraints.
result Derives a Pythagorean theorem for Sharpe ratio and validates new method effectiveness.
The paper optimizes portfolios using clustering and Sharpe ratio-based optimization.
problem Optimizing portfolio performance in financial modeling.
method Combines K-Means clustering for asset segmentation and Sharpe ratio-based optimization.
result Optimized portfolios outperform traditional equal-weighted benchmarks.
The VIX is used to enhance quantitative trading strategies.
problem Improving Sharpe ratio and reducing trading risks in quantitative strategies.
method Postprocessing quantitative strategies with VIX signals.
result Increased Sharpe ratio and reduced trading risks.
The question addressed in this paper is the performance of the optimal strategy, and the impact of partial information. The setting we consider is that of a stochastic asset price model where the trend follows an unobservable Ornstein-Uhlenbeck process. We focus on the optimal strategy with a logarithmic utility functi…
Study the impact of overfitting on linear predictive models' performance.
problem Overfitting reduces the out-of-sample performance of linear predictive trading strategies.
method Computed in- and out-of-sample means and variances of PnLs to derive replication ratios.
result Replication ratio diminishes for complex strategies with many assets.
Sharp volume growth ratio for 3D manifolds with positive scalar curvature.
problem Volume growth and scalar curvature in non-compact Riemannian manifolds.
method Analyzing 3D complete, non-compact manifolds with non-negative Ricci and positive scalar curvature.
result Obtained sharp linear volume growth ratio and rigidity.
Paper proposes new strategies for better portfolio estimation in long-term investments with unknown distributions.
problem Worse out-of-sample performance of estimated portfolios due to unknown future data distribution.
method Online learning framework, dynamic sequential portfolios, updating risk aversion coefficient.
result Dynamic strategies achieve asymptotically optimal utility, Sharpe ratio, and growth rate of true portfolios.
Sharp Sobolev and Michael-Simon inequalities on curved manifolds.
problem Proving inequalities on manifolds with nonnegative curvature.
method Analyzing asymptotic volume ratio and curvature properties.
result Sharp Sobolev and Michael-Simon inequalities established.
Sharp threshold for exact recovery in non-uniform hypergraph stochastic block model.
problem Community detection in random hypergraphs with non-uniform hyperedge probabilities.
method Sharp threshold established; two efficient algorithms for exact recovery.
result Sharp threshold for exact recovery; information-theoretic lower bound on misclassification.