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Results for “retail” · papers 18 · wiki 5
Academic Papers · 18arXiv q-fin live 8 · desk corpus 26
arXiv · arXiv q-fin · 2015

Twitter Sentiment Analysis Applied to Finance: A Case Study in the Retail Industry

This paper presents a financial analysis over Twitter sentiment analytics extracted from listed retail brands. We investigate whether there is statistically-significant information between the Twitter sentiment and volume, and stock returns and volatility. Traditional newswires are also considered as a proxy for the market sentiment for comparative purpose. The results suggest that social media is indeed a valuable s

Thársis Tuani Pinto Souza, Olga Kolchyna, Philip C. Treleaven, Tomaso Aste
arXiv · arXiv · 2026

Gate Design and Stage-Dependent Incentives in Retail Proprietary-Trading Evaluations: Why Passing Is Not Standalone Evidence of Skill, and Why the Product Fails to Pay Under Measured Trading Constraints

Retail proprietary-trading firms sell a two-stage product: a paid evaluation that must reach a profit target before breaching a trailing drawdown, then a funded account that must survive a minimum window and a consistency rule before a payout. We show the geometry of this contract creates incentives that differ by stage and make passing a poor standalone signal of skill. Under end-of-day trailing the evaluation rewar

Nicholas Hall
arXiv · arXiv · 2026

RetailAgent: Structured Adverse Timing in Self-Conditioned Multimodal LLM Trading Agents

In financial markets, a sequential policy that reacts systematically to price movements may become predictable to other market participants. This paper studies whether large language model (LLM) agents exhibit such directional structure through RetailAgent, an experimental framework in which an LLM observes anonymized intraday equity price histories and permitted state, then repeatedly chooses long (hold the stock) o

Yupeng Zhang, Liuyuan Jiang, Hongyi Huang, Bingheng Li, Lisha Chen
arXiv · arXiv · 2026

Retail Trader's Ruin: An Anatomy of Popular Signal Failure

We test whether five widely promoted retail signal families - trend, oscillator, candlestick, volume, and calendar rules - deliver a positive, economically meaningful, net-of-cost, and survivable edge. Practical viability is the conjunction of three predeclared gates: statistical edge after multiplicity correction, economic viability after trading costs, and finite-bankroll survival under leverage. Exposure-matched b

Adam Darmanin
arXiv · arXiv · 2025

Retail Investor Horizon and Earnings Announcements

This paper moves beyond aggregate measures of retail intensity to explore investment horizon as a distinguishing feature of earnings-related return patterns. Using self-reported holding periods from StockTwits (2010-2021), we observe that separating retail activity into "long-horizon" and "short-horizon" cohorts reveals divergent price anomalies. Long-horizon composition is associated with underreaction, characterize

Domonkos F. Vamossy
arXiv · arXiv · 2025

Sentiment Feedback in Equity Markets: Asymmetries, Retail Heterogeneity, and Structural Calibration

We study how sentiment shocks propagate through equity returns and investor clientele using four independent proxies with sign-aligned kappa-rho parameters. A structural calibration links a one standard deviation innovation in sentiment to a pricing impact of 1.06 basis points with persistence parameter rho = 0.940, yielding a half-life of 11.2 months. The impulse response peaks around the 12-month horizon, indicatin

Lucas Marques Sneller
arXiv · arXiv · 2025

Modeling for the Growth of Unorganized Retailing in the Presence of Organized and E-Retailing in Indian Pharmaceutical Industry

The present study considers the rural pharmaceutical retail sector in India, where the arrival of organized retailers and e-retailers is testing the survival strategies of unorganized retailers. Grounded in a field investigation of the Indian pharmaceutical retail sector, this study integrates primary data collection, consumer conjoint analysis and design of experiments to develop an empirically grounded agent-based

Koushik Mondal, Balagopal G Menon, Sunil Sahadev
arXiv · arXiv · 2025

Retail Market Analysis

This project focuses on analyzing retail market trends using historical sales data, search trends, and customer reviews. By identifying the patterns and trending products, the analysis provides actionable insights for retailers to optimize inventory management and marketing strategies, ultimately enhancing customer satisfaction and maximizing revenue.

Ke Yuan, Yaoxin Liu, Shriyesh Chandra, Rishav Roy
arXiv · arXiv · 2024

Correlation without Factors in Retail Cryptocurrency Markets

A simple model-free and distribution-free statistic, the functional relationship between the number of "effective" degrees of freedom and portfolio size, or N*(N), is used to discriminate between two alternative models for the correlation of daily cryptocurrency returns within a retail universe of defined by the list of tradable assets available to account holders at the Robinhood brokerage. The average pairwise corr

Graham L. Giller
arXiv · arXiv · 2023

Retail Demand Forecasting: A Comparative Study for Multivariate Time Series

Accurate demand forecasting in the retail industry is a critical determinant of financial performance and supply chain efficiency. As global markets become increasingly interconnected, businesses are turning towards advanced prediction models to gain a competitive edge. However, existing literature mostly focuses on historical sales data and ignores the vital influence of macroeconomic conditions on consumer spending

Md Sabbirul Haque, Md Shahedul Amin, Jonayet Miah
arXiv · arXiv · 2022

Using Knowledge Distillation to improve interpretable models in a retail banking context

This article sets forth a review of knowledge distillation techniques with a focus on their applicability to retail banking contexts. Predictive machine learning algorithms used in banking environments, especially in risk and control functions, are generally subject to regulatory and technical constraints limiting their complexity. Knowledge distillation gives the opportunity to improve the performances of simple mod

Maxime Biehler, Mohamed Guermazi, Célim Starck
arXiv · arXiv q-fin · 2025

Improving DeFi Accessibility through Efficient Liquidity Provisioning with Deep Reinforcement Learning

This paper applies deep reinforcement learning (DRL) to optimize liquidity provisioning in Uniswap v3, a decentralized finance (DeFi) protocol implementing an automated market maker (AMM) model with concentrated liquidity. We model the liquidity provision task as a Markov Decision Process (MDP) and train an active liquidity provider (LP) agent using the Proximal Policy Optimization (PPO) algorithm. The agent dynamica

Haonan Xu, Alessio Brini
arXiv · arXiv q-fin · 2026

Three-Currency HJM for Brazilian Credit Markets

This paper develops a three-currency Heath-Jarrow-Morton framework in which corporate credit is treated as a separate economy, connected to the nominal and real economies through synthetic inflation and credit exchange rates. The framework produces a testable identity. Under joint no-arbitrage, the credit spread of an issuer expressed over the inflation-rateindexed risk-free curve equals the same issuer's credit spre

Raphael Coelho
arXiv · arXiv q-fin · 2025

Sources and Nonlinearity of High Volume Return Premium: An Empirical Study on the Differential Effects of Investor Identity versus Trading Intensity (2020-2024)

Chae and Kang (2019, \textit{Pacific-Basin Finance Journal}) documented a puzzling Low Volume Return Premium (LVRP) in Korea -- contradicting global High Volume Return Premium (HVRP) evidence. We resolve this puzzle. Using Korean market data (2020-2024), we demonstrate that HVRP exists in Korea but is masked by (1) pooling heterogeneous investor types and (2) using inappropriate intensity normalization. When institut

Sungwoo Kang
arXiv · arXiv q-fin · 2024

am-AMM: An Auction-Managed Automated Market Maker

Automated market makers (AMMs) have emerged as the dominant market mechanism for trading on decentralized exchanges implemented on blockchains. This paper presents a single mechanism that targets two important unsolved problems for AMMs: reducing losses to informed orderflow, and maximizing revenue from uninformed orderflow. The ``auction-managed AMM'' works by running a censorship-resistant onchain auction for the r

Austin Adams, Ciamac C. Moallemi, Sara Reynolds, Dan Robinson
arXiv · arXiv q-fin · 2026

Public Opinion as an Option: Leveraging Prediction Markets to Hedge Exposure to Spot Crypto Volatility

This paper proposes an investment strategy through resource allocation into Kalshi Crypto Event Contracts in order to effectively hedge exposure to spot asset volatility. Using Bitcoin as a proof of concept, we treat corresponding Kalshi markets on the asset's future price as option contracts, and through construction of different portfolio allocations present a framework for which event contracts can be effectively

Prashanth Bhaskara, Aadit Jerfy
arXiv · arXiv q-fin · 2023

Construct sparse portfolio with mutual fund's favourite stocks in China A share market

Unlike developed market, some emerging markets are dominated by retail and unprofessional trading. China A share market is a good and fitting example in last 20 years. Meanwhile, lots of research show professional investor in China A share market continuously generate excess return compare with total market index. Specifically, this excess return mostly come from stock selectivity ability instead of market timing. Ho

Ke Zhang
arXiv · arXiv q-fin · 2023

Abnormal Trading Detection in the NFT Market

The Non-Fungible-Token (NFT) market has experienced explosive growth in recent years. According to DappRadar, the total transaction volume on OpenSea, the largest NFT marketplace, reached 34.7 billion dollars in February 2023. However, the NFT market is mostly unregulated and there are significant concerns about money laundering, fraud and wash trading. The lack of industry-wide regulations, and the fact that amateur

Mingxiao Song, Yunsong Liu, Agam Shah, Sudheer Chava
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