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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.

168,878 papers · 148 categories

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48 results for ex-ante performance

The paper identifies regions where investment strategies match expected performance.

problem Inconsistent performance of Markowitz efficient portfolios.
method Density forecasting to measure ex-ante accuracy and identify the consistency region.
result Investment strategies based on consistent portfolios outperform efficient ones.

The paper predicts and explains the decay of stock anomaly performance over time.

problem Predicting and explaining the drop in risk-adjusted performance of stock anomalies.
method The authors propose ex-ante characteristics based on hypotheses of out-of-sample decay and in-sample overfitting.
result The year of publication explains 30% of the variance in Sharpe decay across factors.

Framework selects real estate redevelopment uses by integrating value, risk, complexity, and irreversibility.

problem Persistent underperformance of real estate assets due to structural misalignment.
method Integrates real-options logic and multi-criteria decision analysis.
result Reduces over-complexification and misalignment in strategic use selection.

AGFN improves causal discovery by integrating expert feedback and handling latent confounding.

problem Inaccurate causal discovery due to unreliable expert knowledge and latent confounding.
method Ancestral GFlowNet (AGFN) is a reinforcement learning algorithm that iteratively refines a policy based on noisy expert feedback to infer ancestral graphs.
result AGFN converges to the true ancestral graph given accurate expert responses and outperforms baselines in structural Hamming distance and Bayesian Information Criterion.

Proposes a method to infer the distributional impacts of predictive models on stakeholders.

problem The influence of predictive models on target variable distribution, leading to performative prediction.
method Modeling agents' responses as a cost-adjusted utility maximization problem and using optimal transport to align pre- and post-model distributions.
result Provides estimates for the cost associated with these responses and demonstrates the quality of these estimates.

The paper examines how risk reduction and insurance choices interact under convex premium principles.

problem Interaction between self-protection and insurance demand under convex premium principles.
method Investigates optimal prevention efforts and insurance shares using distortion risk measures.
result Self-protection and insurance are complementary, but ex ante moral hazard can turn this into a substitution effect.

Improved financial performance through better regime prediction.

problem Predicting financial market regimes for profitable trading.
method A novel method combining contrarian trading and frequent short positions.
result Significant performance improvements over four years across three asset classes.

This paper investigates the equilibrium interactions between trading targets and private information in a multi-period Kyle (1985) market. There are two investors who each follow dynamic trading strategies: A strategic portfolio rebalancer who engages in order splitting to reach a cumulative trading target and an uncon…

2015-02-07abs ↗pdf ↗

We propose the application of a high-speed maximum likelihood clustering algorithm to detect temporal financial market states, using correlation matrices estimated from intraday market microstructure features. We first determine the ex-ante intraday temporal cluster configurations to identify market states, and then st…

2015-08-20abs ↗pdf ↗

We introduce a natural generalization of the forward-starting options, first discussed by M. Rubinstein. The main feature of the contract presented here is that the strike-determination time is not fixed ex-ante, but allowed to be random, usually related to the occurrence of some event, either of financial nature or no…

2015-04-14abs ↗pdf ↗

Fair insurance contracts are designed to handle default risk using cooperative game theory.

problem Designing fair insurance contracts in the presence of default risk.
method Cooperative game theory to specify premiums and participation in benefit.
result Fair benefit participation emerges as a game outcome involving residual risks.

We show that, in a resource allocation problem, the ex ante aggregate utility of players with cumulative-prospect-theoretic preferences can be increased over deterministic allocations by implementing lotteries. We formulate an optimization problem, called the system problem, to find the optimal lottery allocation. The …

2018-12-03abs ↗pdf ↗

The study uses a multi-armed bandit model to analyze and mitigate hiring discrimination.

problem Hiring discrimination due to insufficient data on worker skill and characteristics.
method Multi-armed bandit model to simulate firms' learning process and policy solutions.
result Temporary affirmative actions effectively alleviate discrimination caused by data insufficiency.

Study shows SEC crypto classification led to significant market reactions.

problem Impact of SEC classification of crypto assets as securities.
method Event study methodology focusing on explicitly named crypto assets.
result Significant adverse market reactions, with returns plummeting 12% over one week.

This paper extends the MAB problem to consider risk-reward tradeoffs.

problem Maximizing reward while accounting for risk in multi-armed bandit problems.
method Introduced the Risk Aware Lower Confidence Bound (RALCB) algorithm to solve the mean-variance MAB problem.
result The RALCB algorithm performs better than the algorithm in Sani et al. (2012) in both independent and dependent scenarios.

This study improves audit sampling by using sequential procedures with statistical guarantees.

problem Improving audit efficiency and reliability with statistical methods.
method Formulated as a sequential testing problem, defining null and alternative hypotheses, stopping and decision rules, and exact boundary conditions.
result Exact design yields ex ante control of decision error probabilities, and simulation-based implementation approximates this design.

Proposes a machine learning predictor for survey data.

problem Limited integration of machine learning in traditional surveys.
method Predictor supported by machine learning algorithms, analyzing departures from model assumptions.
result Machine learning predictors are a good alternative, even under small departures from model assumptions.

A method for dynamic portfolio choice with uncertain parameters using Pontryagin projection.

problem Continuous-time CRRA portfolio choice in markets with estimated and uncertain coefficients.
method Simulation-based two-stage solver (DPO + Pontryagin projection) to maximize ex-ante objective.
result Projection stabilizes learning and accurately recovers analytic decisions, improving over model-free PPO.

It is not clear how to target patients who are most likely to benefit from digital care management programs ex-ante, a shortcoming of current risk score based approaches. This study focuses on defining impactability by identifying those patients most likely to benefit from technology enabled care management, delivered …

2019-04-19abs ↗pdf ↗

Study on optimal information acquisition in Kyle model with entropy cost.

problem Optimal information acquisition in Kyle model with entropy cost.
method Continuous signals are optimal, and any signal with a logit posterior distribution yields the same ex-ante value.
result Posterior expected payoff becomes normally distributed as information acquisition cost increases.

The paper tackles fair representation learning by smoothing feature mappings.

problem Legal liability for discriminatory use of data by organizations.
method Mapping features to a fair representation space, certifying fairness through chi-squared mutual information.
result Smoothing representation distribution provides generalization guarantees of fairness and maintains accuracy for downstream tasks.

The model of rational decision-making in most of economics and statistics is expected utility theory (EU) axiomatised by von Neumann and Morgenstern, Savage and others. This is less the case, however, in financial economics and mathematical finance, where investment decisions are commonly based on the methods of mean-v…

2013-06-12abs ↗pdf ↗

A new test evaluates risk estimation accuracy using probability integral transform.

problem Measuring the accuracy of financial market risk estimations.
method Probability Integral Transform (PIT) of ex post realized returns against ex ante probability distributions.
result The new test shows the importance of capturing the dynamic of financial markets.

This paper develops a method to select a reference contract for multi-contract quoting to minimize execution risk.

problem Minimizing execution risk in multi-contract quoting sequences.
method Develops a diagnostic framework using order-flow Hawkes forecasts and CLF to select a stable reference contract.
result Event-history and LOB-state signals offer complementary views for reference-contract selection.

Machine learning uses crowdworkers; determining their status as human subjects is tricky.

problem Determining the appropriate status of ML crowdworkers as human subjects.
method Investigation of natural language processing studies to expose challenges and propose solutions.
result Potential loophole in the U.S. Common Rule for ML research oversight.