Study shows cryptocurrency investor base affects volatility.
problem Investor base changes impact cryptocurrency volatility.
method Proxying investor base with subreddit follower changes, analyzed idiosyncratic volatility.
result Changes in cryptocurrency investor base significantly increase idiosyncratic volatility.
Study shows adding similar investors can either increase or decrease profits, depending on their strategy.
problem Investors argue conflictingly about the impact of adding similar investors on their profits.
method Built an agent-based financial market model with additional agents and investigated their earnings.
result Adding similar fundamental agents stabilizes market prices and decreases profits, while adding similar technical agents makes prices unstable and increases profits.
Simulation reveals relationships in stock market pyramid schemes.
problem Understanding pyramid scheme behavior in stock markets.
method Agent-based simulation with four investor types and parameters.
result Relationships between main fund's rate of return and trend investors' proportion.
We describe how the market-based average and volatility of the "actual" return, which the investors gain within their market sales, depend on the statistical moments, volatilities, and correlations of the current and past market trade values. We describe three successive approximations. First, we derive the dependence …
Geometric approach combines asset returns and investor views for better portfolio optimization.
problem Optimizing portfolios with investor-specific views.
method Generalized Wasserstein barycenter (GWB) to integrate statistical asset returns and investor views.
result The geometric approach offers more flexibility and rewards for correct investor views.
Enhances traditional MV model for socially responsible investors.
problem Traditional MV models ignore ESG scores relevant to socially responsible investors.
method Implemented an amended MV model considering ESG scores.
result SR investors can achieve competitive SR portfolios with a trade-off between Sharpe Ratio and ESG scores.
Modeling investor behavior from financial advisor notes using NLP.
problem Identifying behavioral coaching opportunities for financial advisors.
method Topic modeling and supervised classification model.
result Predicting investor needs during adverse market conditions.
We introduce a reinforcement learning framework for retail robo-advising. The robo-advisor does not know the investor's risk preference, but learns it over time by observing her portfolio choices in different market environments. We develop an exploration-exploitation algorithm which trades off costly solicitations of …
Investors trade based on shifting prices, leading to market inefficiencies.
problem Market inefficiencies due to trading behavior and financial dynamics.
method Analyzes trading strategies and market dynamics.
result Arbitrage opportunities arise from concentrated ownership and low collateral requirements.
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.
Investors suffer welfare loss despite having better information.
problem Welfare loss among investors with absolute information advantages.
method Examined financial markets with heterogenous investors and objective measures of welfare.
result Investors incur welfare loss even with better information, revealing a double loss phenomenon.
Study proposes a machine learning method to predict stock price crashes based on investor sentiment.
problem Predicting stock price crashes due to investor sentiment.
method Minimum covariance determinant methodology and cross-sectional regression analysis.
result The proposed method effectively captures stock price crash risk and is robust across different firm sizes.
The complex networks approach has been gaining popularity in analysing investor behaviour and stock markets, but within this approach, initial public offerings (IPO) have barely been explored. We fill this gap in the literature by analysing investor clusters in the first two years after the IPO filing in the Helsinki S…
Multilayer networks are attracting growing attention in many fields, including finance. In this paper, we develop a new tractable procedure for multilayer aggregation based on statistical validation, which we apply to investor networks. Moreover, we propose two other improvements to their analysis: transaction bootstra…
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.
TechRank ranks companies and technologies based on investor preferences.
problem Estimating influence and ranking companies and technologies.
method Recursive algorithm based on a bi-partite graph with weighted nodes, incorporating investor preferences.
result Provides investors with a quantitative ranking of technologies for optimal portfolio design.
We study the cross-correlation matrix Cij 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 Cij has a power-law form in the bulk followed by …
Game theory models storage investment to balance market competition and profits.
problem Strategic storage investment impacts electricity market prices and revenues.
method Formulated a non-cooperative game between investors to model strategic storage decisions.
result Increasing storage capacity reduces individual profits but increases total investment.
Paper uses agent-based simulation to identify investor types in financial markets.
problem Identifying investor types in real financial markets.
method Computational adaptation of PCA with agent-based simulation.
result A reduced set of investor models can approximate financial time series.
Paper proposes a GRU model to detect spoofing in retail investors.
problem Spoofing in unregulated markets with retail investors.
method GRU-based detection model using market variables.
result Model performs well in early detection of spoofing attempts.
We investigate the trading behavior of Finnish individual investors trading the stocks selected to compute the OMXH25 index in 2003 by tracking the individual daily investment decisions. We verify that the set of investors is a highly heterogeneous system under many aspects. We introduce a correlation based method that…
Behavioral Finance has become a challenge to the scientific community. Based on the assumption that behavioral aspects of investors may explain some features of the Stock Market, we propose an agent based model to study quantitatively this relationship. In order to approximate the simulated market to the complexity of …
The paper uses a novel framework to learn option prices by imitating principal investor behavior.
problem Challenges in modeling stock price changes and decision making in equity markets.
method Non-deterministic Markov decision process, Bayesian deep neural network, reinforcement learning.
result Optimal option prices learned through imitation of principal investor behavior.
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.
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 …
Study shows mutual funds add little value for uninformed investors.
problem Understanding the performance of actively managed equity mutual funds for uninformed investors.
method Constructed a reference portfolio using prices and supply information, analyzed various subsets of funds, and compared to market index.
result Mutual funds provide insignificant alpha for uninformed investors, with negative and significant alpha when compared to the market index.
New methods evaluate stock market anomalies for prospect investors.
problem Determining if new securities or investment changes improve prospect investors' opportunities.
method Developed and implemented a new testing procedure for prospect spanning using subsampling and Linear Programming.
result Many well-known anomalies expand prospect investors' opportunity sets, indicating real economic value.
Study investor attention using search volume data before and after mobile device popularity.
problem Accurately measure investor attention in a fast-paced market.
method Compare investor attention using search volume data before and after mobile device popularization.
result Investor attention measured using search volume data is more accurate and faster after mobile device popularization.
Model predicts trading strategies based on latent demand and price impact.
problem Predicting strategic trading behavior of investors with private targets.
method Equilibrium model of dynamic trading, learning, and pricing by strategic investors.
result Trading strategies are a combination of target following, liquidity provision, and front-running based on latent demand and price pressure.
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.
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.
Investor optimizes investment and consumption under uncertain market conditions with constraints.
problem Investor optimizes investment and consumption in a stochastic environment with model uncertainty and constraints.
method Robust control problem solved using stochastic Hamilton-Jacobi-Bellman-Isaacs equations, backward stochastic differential equations, and bounded mean oscillation martingale theory.
result Investor incurs utility loss when ignoring model uncertainty, and constraints impact optimal strategy and value function.
Study proposes DRL for investor-specific portfolio optimization considering asset volatility.
problem Dynamic allocation of funds balancing risk and return under market conditions.
method Volatility-guided Deep Reinforcement Learning (DRL) framework.
result Proposed DRL portfolios outperform baseline strategies.
We construct continuous-time equilibrium models based on a finite number of exponential utility investors. The investors' income rates as well as the stock's dividend rate are governed by discontinuous Levy processes. Our main result provides the equilibrium (i.e., bond and stock price dynamics) in closed-form. As an a…
We seek to utilize the nonextensive statistics to the microscopic modeling of the interacting many-investor dynamics that drive the price changes in a market. The statistics of price changes are known to be fit well by the Students-T and power-law distributions of the nonextensive statistics. We therefore derive models…
Investor-driven information diffusion affects excess comovement in China and the U.S. markets.
problem Investor-driven information diffusion and its impact on excess comovement.
method Cross-sectional analysis of 4,533 Chinese and 4,517 U.S. stocks from 2010 to 2022.
result Retail-driven information diffusion significantly drives excess comovement in China, while institution-driven diffusion is the primary driver in the U.S.
New approach for uninformed investors to optimize execution costs.
problem Optimizing execution costs for new investors with imperfect initial knowledge.
method Iterative derivation of OLS estimates of market parameters.
result Dynamic adjustment of trading strategies based on evolving market parameters.
Value adjustment of uncollateralized trades is determined within a risk-neutral pricing framework. When hedging such trades, investors cannot freely trade protection on their own name, thus facing an incomplete market. This fact is reflected in the non-uniqueness of the pricing measure, which is only constrained by the…
We study a financial model with a non-trivial price impact effect. In this model we consider the interaction of a large investor trading in an illiquid security, and a market maker who is quoting prices for this security. We assume that the market maker quotes the prices such that by taking the other side of the invest…
In this paper, we consider the problem of optimization of a portfolio consisting of securities. An investor with an initial capital, is interested in constructing a portfolio of securities. If the prices of securities change, the investor shall decide on reallocation of the portfolio. At each moment of time, the prices…
Investor sentiment improves model accuracy but complexity doesn't always boost predictive power.
problem Determining the optimal complexity of investor sentiment measures in asset pricing models.
method Comprehensive review of 71 papers from 2000-2021, analyzing various sentiment measures and models.
result Higher complexity of sentiment measures does not necessarily improve predictive power.
Research tackles investor confusion in ESG rankings, offering tailored strategies.
problem Widespread confusion among investors regarding ESG rankings.
method Developed ESG ensemble strategies, integrated ESG scores into RL model, proposed Double-Mean-Variance model, introduced ESG-adjusted CAPMs.
result Optimized portfolios that balance financial returns and ESG-focused outcomes.
To achieve the ambitious aims of the Paris climate agreement, the majority of fossil-fuel reserves needs to remain underground. As current national government commitments to mitigate greenhouse gas emissions are insufficient by far, actors such as institutional and private investors and the social movement on divestmen…
This paper compares token and equity financing for startups.
problem Understanding differences in return rates between token and equity financing.
method Developed a three-period model to analyze liquidity and return differences.
result Entrepreneurs can achieve higher payoffs by issuing tokens, especially for risk-averse investors with liquidity needs.
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.
Investor skill levels affect optimal portfolio size, study shows.
problem Optimal portfolio size for different skill levels of investors.
method Mathematical methods to study annual and continuous portfolio diversification, regression analysis.
result Strong investors should hold concentrated portfolios, poor investors should hold diversified portfolios.
Young investors, especially students, dominate Indonesian stock exchanges.
problem Investment behavior of young and rookie investors in the stock market.
method Qualitative approach with descriptive analysis and interviews.
result Perception of behavioral control influences investment decisions.
The paper analyzes how behavioral investors make portfolio decisions using Markowitz Stochastic Dominance criteria.
problem Understanding how behavioral investors make portfolio decisions.
method Developed stochastic optimization problems and MILP models to capture subjective decision weights and probability weighting functions.
result The developed models can be used to formulate computationally tractable portfolio analysis problems.