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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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295988117 · Jun 202019922001200920172026
48 results for individual investors

Social media reduces individual investors' disposition effect through negative information.

problem The disposition effect in individual investors selling profitable assets too early and holding onto losing assets for too long.
method Analysis of post data and trading data from Xueqiu.com.
result Social media information significantly reduces the disposition effect.

We study the cross-correlation matrix CijC_{ij} of inventory variations of the most active individual and institutional investors in an emerging market to understand the dynamics of inventory variations. We find that the distribution of cross-correlation coefficient CijC_{ij} has a power-law form in the bulk followed by …

2012-01-02abs ↗pdf ↗

Study on stock portfolio concentration among Finnish households and investors.

problem Understanding the concentration of stock portfolios owned by Finnish households and investors.
method Analysis of stock portfolios using Herfindahl-Hirschman index over 20 years.
result High portfolio concentration observed in Finnish retail investors, similar to institutional investors.

Study shows investor sentiment boosts intraday trading in Chinese markets.

problem Impact of investor sentiment on intraday overtrading in Chinese A-share markets.
method High-frequency sentiment indices from social media analyzed for intraday overtrading in CSI 300 and CSI 500 constituents.
result Investor sentiment significantly increases intraday overtrading, especially among institutional investors.

Study finds key investing characteristics for success in equity markets.

problem Understanding what traits lead to financial success in equity markets.
method Exploratory factor analysis and multiple linear regression on 403 respondents' data.
result Investing characteristics significantly impact individual investors' excess return.

Study uses FDA to analyze discount functions of different temperaments.

problem Traditional finance models fail to capture individual differences in investment choices.
method Functional Data Analysis (FDA) to investigate temporal discounting behaviors.
result Heterogeneity within each temperament revealed, suggesting diverse investor profiles.

Investors prioritize ESG in crypto-assets, showing higher exposure than traditional assets.

problem Understanding ESG preferences in crypto-assets and their investment behavior.
method A representative household finance survey in Austria to examine ESG preferences and crypto-investment exposure.
result ESG-conscious investors have higher exposure to crypto-assets compared to traditional asset classes.

Investor flows in Korean equity market transmit shared information, not private signals.

problem Whether investor flows transmit private information or only public signals.
method Transfer Entropy networks constructed from investor-type flows over umNDates{} trading days.
result Investor flows transmit shared information, not private signals.

Wealth inequality is an important matter for economic theory and policy. Ongoing debates have been discussing recent rise in wealth inequality in connection with recent development of active financial markets around the world. Existing literature on wealth distribution connects the origins of wealth inequality with a v…

2018-09-23abs ↗pdf ↗

Study shows how algorithmic prediction affects US housing market, reducing racial wealth disparities.

problem Impact of algorithmic prediction on housing market and racial wealth disparities.
method Natural experiment using digitization of housing records to study entry, allocation, and prices.
result Digitization leads to increased sale prices for minority-owned homes, reducing racial wealth disparities.

Study reveals how investor flows impact stock prices, especially during herding episodes.

problem Understanding how information transmits through prices and why it breaks down.
method Combining regularized deconvolution with Hawkes process analysis.
result Institutional price impact deteriorates sharply during herding episodes in small-cap stocks, while large-cap stocks maintain resilience.

Researchers adaptively analyze market regimes to reveal investor behavior shifts.

problem Market relationships shift across different regimes, affecting investor behavior.
method Combining Kalman filtering, Markov-switching, and asymmetric response estimation.
result Foreign investors' predictive power increases during crises, while individual investors react more strongly to positive shocks.

New model recommends stocks considering individual preferences and diversification.

problem Inaccurate stock price predictions and ignoring investment theories.
method Portfolio Temporal Graph Network Recommender (PfoTGNRec) incorporating diversification-enhancing sampling.
result PfoTGNRec outperforms state-of-the-art models in real-world data.

When investors have heterogeneous attitudes towards risk, it is reasonable to assume that each investor has a pricing kernel, and that these individual pricing kernels are aggregated to form a market pricing kernel. The various investors are then buyers or sellers depending on how their individual pricing kernels compa…

2013-01-14abs ↗pdf ↗

Retail investors set interest rates for P2P loans based on borrower characteristics.

problem Understanding how individual investors price credit risk in online consumer loan auctions.
method Reverse auction framework, analyzing interest rate variance and borrower characteristics.
result Retail investors exhibit strong predictability in pricing, with gender and marital status influencing interest rates.

Covid lockdown increased interest in Italian stock market, leading to new investors.

problem Impact of Covid lockdown on Italian stock market investors.
method Analysis of trading activity and investor demographics before and during lockdown.
result New investors during lockdown were more skilled traders than pre-lockdown investors.

Corporate transparency reduces investors' disposition effect by increasing confidence in holding profitable and losing stocks.

problem Irrational disposition effect in investors selling profitable assets too soon and holding onto losing assets for too long.
method Examined the impact of corporate transparency on individual investors' disposition effect.
result Increased corporate transparency significantly reduces the disposition effect.

Study uses LLMs to generate investor briefs from company reports and SEC filings.

problem Improving data analysis for individual investors.
method Preprocessed data, used gpt-4o model in RAG regime, evaluated by investors.
result LLMs can generate useful investor briefs from company reports and SEC filings.

The average portfolio structure of institutional investors is shown to have properties which account for transaction costs in an optimal way. This implies that financial institutions unknowingly display collective rationality, or Wisdom of the Crowd. Individual deviations from the rational benchmark are ample, which il…

2017-03-06abs ↗pdf ↗

We quantify the benefit of collectivised investment funds, in which the assets of members who die are shared among the survivors. For our model, with realistic parameter choices, an annuity or individual fund requires approximately 20\% more initial capital to provide as good an outcome as a collectivised investment fu…

2019-09-27abs ↗pdf ↗

Investors optimize liquid staking decisions in LSP and AMM protocols.

problem Optimal timing and allocation in liquid staking protocols.
method Derive optimal allocation strategy and model optimal exit timing using Laplace transforms and free-boundary techniques.
result Optimal stop-loss strategy maximizes expected payoff, influenced by fees and opportunity gains.

This paper conducts an empirically study on the trade package composed of a sequence of consecutive purchases or sales of 23 stocks in Chinese stock market. We investigate the probability distributions of the execution time, the number of trades and the total trading volume of trade packages, and analyze the possible s…

2011-03-08abs ↗pdf ↗

This paper explores portfolio management strategies to maximize alpha and minimize beta.

problem Maximizing returns while minimizing risk in investment portfolios.
method Examines asset allocation, diversification, active management, and risk management strategies.
result Combining these strategies optimizes portfolio performance.

In complex systems like financial market, risk tolerance of individuals is crucial for system resilience.The single-security price limit, designed as risk tolerance to protect investors by avoiding sharp price fluctuation, is blamed for feeding market panic in times of crash.The relationship between the critical market…

2019-08-20abs ↗pdf ↗

Study models human investors' sub-rational behavior in financial markets.

problem Lack of a comprehensive model for human sub-rationality in financial markets.
method Flexible reinforcement learning model incorporating five human sub-rational aspects.
result Model accurately reproduces human behavior and reveals insights into market dynamics.

New framework models stock relationships and investor expectations for better financial market predictions.

problem Limited by predefined stock relationships and immediate effects, current financial market analysis methods need improvement.
method Jointly models investor expectations and automatically mines latent stock relationships.
result Annual return exceeds 10%, surpassing existing benchmarks.

Statistical fields model explains capital allocation and accumulation among firms and investors.

problem Understanding capital allocation and accumulation dynamics among firms and investors.
method Applied statistical fields formalism to heterogeneous agents divided into firms and investors.
result Capital accumulation depends on various factors including long-term returns, competition, and stock price volatility.

The paper translates economic models into a field formalism to study capital accumulation and its fluctuations.

problem Understanding capital accumulation and its fluctuations in a complex economic system.
method Developed a field formalism to preserve interactions and microeconomic features, applying it to a microeconomic framework of investors and firms.
result Capital accumulation patterns can emerge at the macro-scale and affect neighboring sectors, leading to permanent fluctuations.

Game-theoretic model captures investor interactions for stock price forecasting.

problem Complex market dynamics driving stock price movements.
method Game-theoretic modeling of heterogeneous investor interactions in a dynamic graph structure.
result Our method outperforms state-of-the-art stock price forecasting methods.

Cryptocurrency forecasting model considers macro, sentiment, and technical indicators.

problem High price volatility in cryptocurrency markets.
method Dual-prediction mechanism incorporating macroeconomic fluctuations, technical indicators, and individual cryptocurrency price changes.
result The proposed model outperforms ten comparison methods in short-term cryptocurrency forecasting.

Investors use various asset allocation strategies to meet financial goals.

problem Finding the optimal asset allocation for individual investors is challenging.
method Conducted a benchmark study comparing traditional and machine learning approaches.
result Deep reinforcement learning models outperformed traditional methods in both bullish and bearish markets.

Collectivistic countries influence Bitcoin returns more than individualistic ones during the pandemic.

problem The impact of public attention to COVID-19 on Bitcoin returns.
method Rolling and recursive-evolving algorithms to account for timing and estimation bias.
result Collectivistic countries have stronger causal impacts on Bitcoin returns.

Online reviews are feedback voluntarily posted by consumers about their consumption experiences. This feedback indicates customer attitudes such as affection, awareness and faith towards a brand or a firm and demonstrates inherent connections with a company's future sales, cash flow and stock pricing. However, the pred…

2019-04-30abs ↗pdf ↗

This study interprets AMM fees as implied volatility, validating their relevance in digital asset markets.

problem Understanding the volatility of fees in decentralized exchange systems.
method Reinterpreting AMM fees as implied volatility and applying fixed-for-floating swaps to quote and validate these volatilities.
result The implied volatilities of digital assets can be accurately quoted using AMM fees, validating the approach.