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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.

168,695 papers · 148 categories

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4386129172 · May 202619922001200920172026
48 results for heterogeneous returns

The Split-Session Cluster GARCH model captures tail heterogeneity in overnight and intraday returns.

problem Capturing tail behavior and dependence in multivariate asset returns.
method Convolution-tt distributions, session and sector clustering, block-structured correlation matrices.
result Session-specific and sector-level tail parameters improve model fit and out-of-sample performance.

Study extends wealth tax neutrality framework to heterogeneous investors.

problem Analyzing wealth tax neutrality in populations with varying return-generating ability.
method Extended Fokker-Planck framework to heterogeneous investors, deriving extended Fokker-Planck equation.
result Proportional wealth tax no longer neutral due to varying return-generating ability, leading to different real incidence and wealth distribution changes.

Study resolves the Korean LVRP puzzle by showing HVRP exists but is masked by investor heterogeneity and improper intensity normalization.

problem Puzzling Low Volume Return Premium (LVRP) in Korea, contradicting global High Volume Return Premium (HVRP) evidence.
method Used Korean market data (2020-2024) to demonstrate HVRP exists but is masked by investor heterogeneity and improper intensity normalization. Normalized institutional buying intensity by market capitalization rather than trading value.
result Demonstrated a perfect monotonic relationship between highest-conviction institutional buying and positive cumulative abnormal returns, while lowest-intensity trades yield modest returns.

Study Nash equilibrium in market with relative wealth concerns under partial information and heterogeneous priors.

problem Analyzing Nash equilibrium in a market with unobservable return rates and heterogeneous priors.
method Established a Nash equilibrium through a separation result and martingale argument. Used fully-coupled linear FBSDEs and deep neural networks for numerical computation.
result Investment strategies under relative wealth concerns exhibit a herd effect, with accurate prior estimators leading the market.

Study shows different types of volatility and skewness changes affect stock prices.

problem Different types of volatility and skewness changes affect stock prices.
method Used intraday data for individual stocks to analyze cross-section of asset returns.
result Idiosyncratic transitory and persistent shocks to volatility and skewness are priced differently in stock returns.

TradeFM learns market microstructure from trade events, improving financial model accuracy.

problem Lack of generalizable models for market microstructure.
method Generative Transformer model trained on billions of trade events, using scale-invariant features and universal tokenization.
result TradeFM generates rollouts that match key stylized facts of financial returns and outperforms existing models.

Investigate the evolving structure of cryptocurrency interactions using high-frequency returns.

problem Evolution of cryptocurrency interactions
method Construct directed and weighted networks from Granger causal relationships between cryptocurrency log-returns.
result Normalized returns exhibit heavy-tailed distributions.

This paper develops statistical models for cryptocurrency returns using hidden Markov regression and copulas.

problem Capturing the interrelationships and serial heterogeneity of cryptocurrency returns.
method Hidden Markov regression models with regime-switching copulas for quantiles and expectiles.
result Captures extreme returns and their temporal evolution through a latent Markov chain.

In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we introduce investors with different investment horizons into the news-driven, analytic, agent-based market model developed in Gusev et al. (2015). This heterogeneous frame…

2015-08-18abs ↗pdf ↗

We study how trading costs are reflected in equilibrium returns. To this end, we develop a tractable continuous-time risk-sharing model, where heterogeneous mean-variance investors trade subject to a quadratic transaction cost. The corresponding equilibrium is characterized as the unique solution of a system of coupled…

2017-07-26abs ↗pdf ↗

Investment diversification affects financial stability, depending on network connectivity.

problem Analyzing stability of financial networks with diversified portfolios.
method Random matrix dynamical model with portfolio rebalancing, considering heterogeneity and diversification effects.
result Stability/instability transition depends on the largest eigenvalue of the random matrix.

Stock correlations is crucial to asset pricing, investor decision-making, and financial risk regulations. However, microscopic explanation based on agent-based modeling is still lacking. We here propose a model derived from minority game for modeling stock correlations, in which an agent's expected return for one stock…

2018-03-06abs ↗pdf ↗

Study how transaction costs impact stock returns and holdings in equilibrium.

problem Impact of quadratic transaction costs on equilibrium stock returns and holdings.
method Developed a continuous-time risk-sharing model with FBSDEs to characterize equilibrium stock holdings and trading rates.
result Equilibrium stock holdings and trading rates are uniquely determined by FBSDEs, and equilibrium return by a system of coupled FBSDEs.

CB-APM uses analyst consensus as a bottleneck to interpret stock returns.

problem Tackles the challenge of understanding and predicting stock returns using professional beliefs.
method Embeds analyst consensus as a structural bottleneck, treating it as a sufficient statistic for market information.
result CB-APM portfolios exhibit strong monotonic return gradients and robust across different economic conditions.

This paper studies the equilibrium price of an asset that is traded in continuous time between N agents who have heterogeneous beliefs about the state process underlying the asset's payoff. We propose a tractable model where agents maximize expected returns under quadratic costs on inventories and trading rates. The un…

2019-05-14abs ↗pdf ↗

We develop a behavioral asset pricing model in which agents trade in a market with information friction. Profit-maximizing agents switch between trading strategies in response to dynamic market conditions. Due to noisy private information about the fundamental value, the agents form different evaluations about heteroge…

2018-02-11abs ↗pdf ↗

Revisits behavioral finance option pricing model to align with rational asset pricing theory.

problem Inconsistency between behavioral finance and rational asset pricing models in option pricing.
method Introduces arbitrage transaction costs to modify the behavioral finance option pricing formula.
result Modifies behavioral finance option pricing formula to be consistent with rational asset pricing theory.

A time series model for the FX dynamics is presented which takes into account structural peculiarities of the market, namely its heterogeneity and an information flow from long to short time horizons. The model emerges from an analogy between FX dynamics and hydrodynamic turbulence. The heterogeneity of the market is m…

2000-04-11abs ↗pdf ↗

The total duration of drawdowns is shown to provide a moment-free, unbiased, efficient and robust estimator of Sharpe ratios both for Gaussian and heavy-tailed price returns. We then use this quantity to infer an analytic expression of the bias of moment-based Sharpe ratio estimators as a function of the return distrib…

2015-05-06abs ↗pdf ↗

Multiple regression has been the go-to method for data analysis for generations of scholars due to its transparency, interpretability, and desirable theoretical properties. However, the method's simplicity precludes the discovery of complex heterogeneities in the data. We introduce the Method of Direct Estimation and I…

2017-03-16abs ↗pdf ↗

This paper reviews some of the phenomenological models which have been introduced to incorporate the scaling properties of financial data. It also illustrates a microscopic model, based on heterogeneous interacting agents, which provides a possible explanation for the complex dynamics of markets' returns. Scaling and m…

2000-07-25abs ↗pdf ↗

A class of heterogeneous agent models is investigated where investors switch trading position whenever their motivation to do so exceeds some critical threshold. These motivations can be psychological in nature or reflect behaviour suggested by the efficient market hypothesis (EMH). By introducing different propensitie…

2006-07-31abs ↗pdf ↗

Study analyzes market equilibrium returns with price impact and transaction costs.

problem Modeling equilibrium returns in markets with strategic order placement and transaction costs.
method Analyzes frictionless and transaction-cost markets, characterizes Nash equilibrium via FBSDEs.
result Equilibrium returns are affected by transaction costs, especially with noise traders.

Study optimal investment decisions for diverse risk-tolerant agents.

problem Optimizing investment choices for agents with varying risk preferences.
method Characterizes optimal behavior using certainty equivalents and lognormal risks.
result Derives optimal decision menus under known and uncertain preference distributions.

The paper models financial markets and real economy interactions using a large agent framework.

problem Understanding capital allocation and accumulation in financial markets and real economy interactions.
method Developed a field-formalism model to analyze interactions between financial markets and real economy with a large number of heterogeneous agents.
result The number of firms in each sector depends on the aggregate financial capital invested and expected long-term returns.

VAIOM models financial returns using continuous input and categorical output.

problem Modeling continuous, noisy, and heterogeneous financial data.
method VAIOM is a decoder-only Transformer that separates input representation from output likelihood.
result VAIOM models outperform fixed single-bar LightGBM baseline in both Test halves.

Method identifies unknown intervention targets in structural causal models from diverse data.

problem Identifying unknown intervention targets in structural causal models from heterogeneous data.
method Two-phase approach: first recovers exogenous noises, second matches with endogenous variables.
result Proposed method uniquely identifies intervention targets under causal sufficiency assumption.

How do macro-financial shocks affect investor behavior and market dynamics? Recent evidence on experience effects suggests a long-lasting influence of personally experienced outcomes on investor beliefs and investment, but also significant differences across older and younger generations. We formalize experience-based …

2016-12-30abs ↗pdf ↗

Improved covariance matrix forecasting for S&P 500 using factor models and shrinkage.

problem Forecasting large covariance matrices of returns in finance.
method Decompose covariance matrix into firm-level factors and sectoral restrictions. Estimate using VHAR models with LASSO.
result Significantly improved forecasting precision compared to benchmarks.

A new model predicts financial volatility across firms using spatial correlations.

problem Predicting financial volatility across firms in a network.
method Heterogeneous spatiotemporal GARCH model with local likelihood estimation.
result The model captures spatial spillovers and contagion effects in financial networks.

The study reveals distinct patterns in retail investors' holding periods affecting stock returns.

problem Understanding the impact of retail investors' investment horizons on stock returns.
method Using self-reported holding periods from StockTwits, the study categorizes retail investors into long-horizon and short-horizon groups and analyzes their return patterns.
result Long-horizon retail investors exhibit underreaction to earnings announcements, while short-horizon investors show overreaction.