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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.

168,657 papers · 148 categories

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3877115153 · Jun 202019922001200920172026
48 results for long-term impact

Study historical cholera epidemics and simulate long-term mortality impacts.

problem Long-term impacts of mortality shocks on longevity.
method Historical analysis of cholera epidemics and mathematical modeling of stochastic Individual-Based models.
result Simulated long-term mortality impacts following a mortality shock.

Study on energy storage's impact on electricity prices and profitability.

problem Analyzing the profitability of energy storage in electricity markets.
method Characterized optimal operating strategy for storage systems, determined equilibrium price in a market with storage, renewables, and conventional producers, and characterized price process using stochastic differential equations.
result Increased average revenues and interquantile ranges for storage assets in energy transition scenarios.

Organic updates (from a member's network) and sponsored updates (or ads, from advertisers) together form the newsfeed on LinkedIn. The newsfeed, the default homepage for members, attracts them to engage, brings them value and helps LinkedIn grow. Engagement and Revenue on feed are two critical, yet often conflicting ob…

2019-01-29abs ↗pdf ↗

This paper balances short-term and long-term rewards in policy learning.

problem Balancing short-term and long-term rewards in policy learning.
method Formalizes a new framework to balance rewards, identifies rewards under mild assumptions, deduces efficiency bounds, and develops a policy learning approach.
result The proposed method improves the estimator of long-term reward and reduces regret.

We consider a stochastic multi-armed bandit (MAB) problem with delayed impact of actions. In our setting, actions taken in the past impact the arm rewards in the subsequent future. This delayed impact of actions is prevalent in the real world. For example, the capability to pay back a loan for people in a certain socia…

2020-02-24abs ↗pdf ↗

TimeBridge addresses non-stationarity in long-term time series forecasting.

problem Non-stationarity in multivariate time series leads to spurious regressions and obscures long-term relationships.
method TimeBridge segments series into patches, applying Integrated Attention for short-term non-stationarity and Cointegrated Attention for long-term cointegration.
result TimeBridge achieves state-of-the-art performance in both short-term and long-term forecasting.

Study examines cryptocurrency behavior during and after the pandemic.

problem Impact of the pandemic on cryptocurrency long-term memory and volatility.
method Used wavelet-based Hurst exponent analysis on eleven important coins.
result Long-term memory of returns mildly affected during pandemic, but volatility suffered temporary impact.

Study examines how risk tolerance impacts long-term investment returns.

problem Understanding the impact of risk tolerance on investment returns over time.
method Used Malliavin calculus and Hansen--Scheinkman decomposition.
result Risk aversion affects long-term investment utility through eigenvalues and eigenfunctions.

This paper is devoted to the important yet little explored subject of the market impact of limit orders. Our analysis is based on a proprietary database of metaorders - large orders that are split into smaller pieces before being sent to the market. We first address the case of aggressive limit orders and then, that of…

2018-02-23abs ↗pdf ↗

WayDCM predicts trajectories considering long-term goals, improving accuracy.

problem Predicting future trajectories of dynamic agents in complex environments.
method WayDCM combines DCM and NN to predict intermediate goals and trajectories, considering long-term goals.
result WayDCM outperforms previous methods on the Waymo Open dataset.

We present a thorough empirical analysis of market impact on the Bitcoin/USD exchange market using a complete dataset that allows us to reconstruct more than one million metaorders. We empirically confirm the "square-root law'' for market impact, which holds on four decades in spite of the quasi-absence of statistical …

2014-12-15abs ↗pdf ↗

The study analyzes macroeconomic factors affecting copper futures volatility and long-term correlation with S&P 500.

problem Understanding the impact of macroeconomic variables on copper futures volatility and long-term correlation.
method Employed GARCH-MIDAS and DCC-MIDAS modeling frameworks to examine the influence of low-frequency macroeconomic variables on copper futures returns and long-term correlation with S&P 500.
result PPI is the most efficient macroeconomic variable impacting copper futures returns, and MIDAS filter improves model fitness and long-run relationship.

This paper analyzes the robust growth rate of leveraged ETFs under uncertain parameters.

problem Analyzing the robust long-term growth rate of leveraged ETFs with uncertain parameters.
method Derive worst-case parameters using comparison principle and martingale extraction method.
result Explicitly obtain robust long-term growth rates under various models.

The paper targets optimal interventions for long-term outcomes using imputed data and policy learning.

problem Maximizing long-term outcomes observed only in the future.
method Imputing missing long-term outcomes and using a doubly-robust approach for policy evaluation and optimization.
result The approach outperforms simple short-term proxies and achieves significant revenue impact over three years.

Algorithm reduces long-term policy regret in ML decision-making.

problem Capturing long-term impacts of ML decisions in communities.
method Modeling communities as arms in a multi-armed bandit problem, defining policy regret as a stronger metric than external regret.
result Algorithm achieves provably sub-linear policy regret for long time horizons.

Research shows SBP's tone impacts stock market returns positively or negatively.

problem Impact of State Bank of Pakistan's monetary policy communications on stock market.
method Sentiment analysis and high frequency stock market returns analysis.
result Positive or negative tone in SBP communications affects stock returns positively or negatively.

Fairness in machine learning has predominantly been studied in static classification settings without concern for how decisions change the underlying population over time. Conventional wisdom suggests that fairness criteria promote the long-term well-being of those groups they aim to protect. We study how static fairne…

2018-03-12abs ↗pdf ↗

The paper examines how slightly biasing towards under-represented groups in sequential selection processes can lead to long-term fairness.

problem Designing fair sequential decision-making processes for long-term social fairness.
method Proposes Multi-agent Fair-Greedy policy to balance score maximization and fairness.
result Proves convergence to long-term fairness target set by agents when score distributions are identical.

The study identifies features making cross-impact relevant in explaining price variance of US assets.

problem Understanding the relevance of cross-impact in explaining price variance of US assets.
method Using tick-by-tick data spanning 5 years for 500 US assets, the study investigates the features making cross-impact relevant.
result Price formation is endogenous within highly liquid assets, influencing less liquid correlated products with a constrained impact velocity.

Study shows diverse data sources improve cryptocurrency forecasting models.

problem Improving cryptocurrency market forecasting accuracy.
method Integrating various data types, including on-chain metrics, traditional indices, and macroeconomic indicators.
result Data source diversity significantly enhances forecasting model performance.

Digital transformation boosts corporate financial asset allocation, especially short-term.

problem Understanding how digital transformation affects corporate financial decisions.
method Fixed-effects models and staggered DID design using A-share listed companies data.
result Digital transformation significantly promotes corporate financial asset allocation, more pronounced in short-term.

Flow prediction (e.g., crowd flow, traffic flow) with features of spatial-temporal is increasingly investigated in AI research field. It is very challenging due to the complicated spatial dependencies between different locations and dynamic temporal dependencies among different time intervals. Although measurements of …

2019-12-13abs ↗pdf ↗

Study shows long-term debt impacts financial growth of non-financial firms listed at Nairobi Securities Exchange.

problem Declining financial performance and reluctance to lend to non-financial firms listed at Nairobi Securities Exchange.
method Descriptive and panel data analysis of 45 non-financial firms over 10 years.
result Long-term debt positively and significantly influences financial growth measured by earnings per share and market capitalization.

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 develops a reinforcement learning model to estimate ad impact considering delayed and cumulative effects.

problem Accurately estimating ad impact considering delayed and long-term effects, cumulative impacts, and customer heterogeneity.
method Modeling ad bidding as a Contextual Markov Decision Process (CMDP) with delayed Poisson rewards, proposing a two-stage maximum likelihood estimator and reinforcement learning algorithm.
result Achieves a near-optimal regret bound of O~(dH2T)\tilde{O}{(dH^2\sqrt{T})}, validating the approach through simulation experiments.

Bayesian method optimizes rescheduling for multipurpose batch processes with incomplete look-ahead information.

problem Optimizing rescheduling for multipurpose batch processes under incomplete look-ahead information.
method Proposes a Bayesian dynamic scheduling method that learns from disturbances and updates schedules online.
result Achieves statistically better long-term costs and system nervousness compared to existing periodic rescheduling strategies.

The study improves Monte Carlo simulations for long-term investments using advanced financial models.

problem Improving the accuracy of long-term investment simulations.
method Developed a multivariate process incorporating recent financial models and probabilistic forecasts.
result Increased accuracy in predicting portfolio values over decades.

In the current environment of financial distress, many governments are likely to soon become major holders of financial assets, but the policy debate focuses only on the likelihood and extent of short-term market stabilization. This paper shows that government intervention and propping up are likely to lead to long-ter…

2010-02-11abs ↗pdf ↗

Framework for deferring decisions to experts in sequential medical settings.

problem Myopic and non-adaptive decision-making by ML models in sequential medical contexts.
method Sequential Learning-to-Defer (SLTD) framework using model-based reinforcement learning.
result Adaptive deferral policy improves trade-off between long-term outcomes and deferral frequency.

We study the dynamics of the `batch' minority game with market-impact correction using generating functional techniques to carry out the quenched disorder average. We find that the assumption of weak long-term memory, which one usually makes in order to calculate ergodic stationary states, breaks down when the persiste…

2001-08-03abs ↗pdf ↗

This study examines investor sentiment's impact on stock market liquidity and volatility using deep learning and TVP-VAR models.

problem Investor sentiment's impact on stock market liquidity and volatility.
method Deep learning BERT model for sentiment extraction and TVP-VAR model for time-varying analysis.
result Investor sentiment has a stronger impact on stock market liquidity and volatility, with more pronounced effects in short-term shocks.

The purpose of this paper relies on the study of long term affine yield curves modeling. It is inspired by the Ramsey rule of the economic literature, that links discount rate and marginal utility of aggregate optimal consumption. For such a long maturity modelization, the possibility of adjusting preferences to new ec…

2014-04-07abs ↗pdf ↗

Professional baseball players are increasingly guaranteed expensive long-term contracts, with over 70 deals signed in excess of \$90 million, mostly in the last decade. These are substantial sums compared to a typical franchise valuation of \$1-2 billion. Hence, the players to whom a team chooses to give such a contrac…

2017-12-15abs ↗pdf ↗

Study examines impact of capital structure on Indian auto companies' profitability.

problem Understanding the impact of capital structure on profitability of Indian auto companies.
method Used fixed and random effect models with 10 years of data from 17 companies.
result Optimal capital structure improves company performance and maintains capital adequacy.

Study uses Bayesian regression to analyze consumer behavior changes in restaurants post-COVID-19.

problem Impact of COVID-19 on consumer behavior in the restaurant industry.
method Bayesian regression with Hamiltonian Monte Carlo.
result Estimates change in consumer behavior before and after the pandemic.

Study shows big winner stocks significantly impact passive and active investment strategies.

problem Impact of big winner stocks on passive and active investment strategies.
method Numerical and analytical techniques applied to historical stock price data.
result Concentrated portfolios underperform equally weighted indexes due to missing big winner stocks.