ArXiv
Finance
Realistic Limit Order Book Simulation: The MDQR model, an advanced Queue-Reactive model, uses neural networks to understand complex market dependencies, making it useful for practical applications like strategy creation. (2025-01-15, shares: 16)
Liquidity Spread Estimation: The article introduces a model that uses option theory to calculate liquidity spreads for corporate bonds, focusing on Italy's debt, and offers a method for pricing illiquid bonds. (2025-01-20, shares: 7)
Dynamic Portfolio Choice: The Pontryagin-Guided Direct Policy Optimization (PG-DPO) method has been developed to expand dynamic portfolio choice to tens of thousands of assets, exceeding the traditional six-asset limit. (2025-01-22, shares: 3)
Rebate Design in Auction Markets: The research proposes an effective rebate policy in auction markets, demonstrating that ideal transaction fees and rebate structures enhance market efficiency and guarantee a minimum profit for market makers. (2025-01-22, shares: 6)
Optimal Transport for Correction: The article presents a method that eliminates arbitrage opportunities in option prices, designed for regulatory stress-tests, and proves to be more effective than existing methods. (2025-01-21, shares: 6)
Penalised Estimation: A new objective function has been proposed for estimating all quantiles in dynamic quantiles models, providing a more robust and flexible approach to handling multiple dynamic quantiles in time-series data. (2025-01-17, shares: 3)
Option Price Data Cleaning: The article addresses three common issues in recorded option price datasets and suggests solutions to ensure the reliability of analyses based on these datasets. (2025-01-19, shares: 2)
Portfolio Optimization with Clustering: The article presents a new method for improving portfolio performance using clustering-based segmentation and Sharpe ratio-based optimization, tested with historical data from various asset classes. (2025-01-21, shares: 9)
Economics
Economics of AI Models: The article explores the economic reasons behind for-profit companies open sourcing their large language models, highlighting a balance between technological advancement and immediate profit. (2025-01-20, shares: 8)
Evolution of Skill Returns: The study disputes the common view that wage inequality in the US is due to unobserved skills, instead attributing it to increasing skill volatility. (2025-01-17, shares: 7)
Historical Trending
Neural Networks for Insurance Pricing: The article discusses the application of deep learning in insurance pricing, comparing different models and offering a method to interpret neural network insights through generalized linear models. (2023-10-19, shares: 27)
Semantic Consistency in Political Text Analysis: The article repeats the use of the MDQR model, a neural network-based extension of the Queue-Reactive model, for understanding complex market conditions and its application in strategy development. (2025-01-15, shares: 16)
Factors Influencing Stock Market Volatility in China: The research compares Word2Vec and BERT for political science text analysis, concluding that BERT offers better semantic stability and is ideal for tasks needing semantic consistency. (2024-12-03, shares: 13)
SSRN
Recently Published
Quantitative
Mutual Funds Analysis: The research assesses the performance of two key FinTech mutual funds in India, highlighting the importance of selecting profitable funds for investment. (2025-01-21, shares: 10.0)
Macroeconomic Models: The article reviews the influence of heterogeneity on macroeconomic modeling, especially in monetary and fiscal policy, and evaluates methods to solve these models. (2025-01-21, shares: 397.0)
Stock Market Volatility: The paper studies the volatility performance between the Nifty index and Sector index, emphasizing the role of the stock market in economic growth and the potential harm of market instability. (2025-01-21, shares: 10.0)
Weibull Distribution Investment: The research investigates the effectiveness of different optimization techniques for estimating Weibull distribution parameters, finding that metaheuristic algorithms outperform traditional methods. (2025-01-21, shares: 16.0)
Variational Inequality Finance: The paper discusses various variational inequality models in finance, which outline optimal strategies in derivatives pricing, portfolio selection, and corporate finance. (2025-01-21, shares: 11.0)
LLMVaR Risk Forecasting: The research introduces new methods for forecasting financial risk using large language models, finding these models effective for short-term but traditional models superior for long-term financial risk management. (2025-01-20, shares: 26.0)
Granular Option Info & Stock Returns: The research indicates that granular option variables can predict individual stock returns, with machine learning techniques improving this prediction. (2025-01-20, shares: 4.0)
Financial
Quadratic Model for Oil Options Market: The study uses the quadratic normal model to improve oil options pricing and hedging, incorporating fat-tailed distributions and testing its efficiency over 25 years. (2025-01-17, shares: 13.0)
Portfolio Gyrations in Mutual Funds Analysis: The research explores what influences portfolio changes in emerging market equity mutual funds, highlighting firm size, investment features, and stock attributes as key factors, with their significance changing based on market conditions and investment strategies. (2025-01-20, shares: 3.0)
Seasonal SEC Disclosures and Halloween Effect: A study reveals a seasonal trend in SEC regulatory disclosures, with a spike in winter, mirroring the Sell in May and Go Away effect, a pattern also seen in European markets. (2025-01-17, shares: 5.0)
Anomalies and Market Return Predictability: A link between cross-sectional anomalies and timeseries market return predictability in an international context has been found, leading to the creation of three new market efficiency measures. (2025-01-17, shares: 3.0)
Recently Updated
Quantitative
Energy Market Calibration: The article proposes a model to align historical correlations of futures contracts with implied volatility smiles using two specific mathematical models. (2025-01-12, shares: 233.0)
Bank Distress Prediction: The paper presents a machine learning-based early warning system to predict distress in large European banks, with the random forest model performing best. (2025-01-15, shares: 23.0)
Geopolitical Risk Relationship: The paper finds a significant influence of increased geopolitical risk on financial stress. (2025-01-15, shares: 19.0)
Financial Development Volatility: The article reveals a potential negative impact of excessive finance on growth volatility. (2025-01-15, shares: 11.0)
Portfolio Selection with Herd Behavior Index: The article introduces a method to create optimal portfolios using the Herd Behavior Index (HIX), which measures the synchronicity of stock price movements. (2025-01-15, shares: 14.0)
TwoStage Portfolio Optimization with Ensemble Learning: The study introduces a method that merges ensemble learning and genetic algorithms to optimize stock portfolios and predict asset returns in the Chinese Ashare market. (2025-01-15, shares: 8.0)
Combining Realized Volatility Estimators: The article suggests a forecast combination scheme using time-varying weights, which improves economic performance compared to existing methods. (2025-01-09, shares: 12.0)
Financial
Geometric Topological Data Analysis: The article analyzes geometric and topological data analysis methods, presenting a neural architecture that combines geometric convolutions with persistence-based features for improved data analysis. (2025-01-04, shares: 31.0)
Climate-Linked Bonds: The paper discusses the potential of climate-linked bonds in achieving a net-zero economy, suggesting that about three percent of government debt in major economies could be converted into such bonds. (2025-01-10, shares: 8.0)
Aggregated Equity Risk Premium: The article suggests a new method for predicting the equity risk premium by aggregating firm-level return predictions from neural networks, showing significant economic benefits in trading strategies. (2024-12-11, shares: 15.0)
News Sentiment Analysis Limitations: The paper explores the difficulties of using news sentiment analysis to predict next-day stock returns, proposing a multilevel approach that incorporates sentiment analysis across individual stocks, industries, and the overall economy. (2024-11-12, shares: 2.0)
Index Fund Costs: The composition changes in the stock market cause costs for index funds, negatively affecting returns due to a rebalancing strategy that buys high and sells low. (2025-01-02, shares: 3.0)
Geopolitical Risk and Mutual Funds: Geopolitical shocks like export controls impact the U.S. asset management industry, but active funds can mitigate this by selling stocks of affected U.S. firms. (2025-01-09, shares: 3.0)
Inflation and Asset Prices: Expected inflation changes influence firm-level credit spreads and equity returns, with good inflation reducing corporate credit spreads and increasing equity valuations. (2025-01-13, shares: 7.0)
SHAP Location Value: Machine learning and explainable artificial intelligence can estimate combined location value, separating it from structure value in apartment rents. (2025-01-09, shares: 8.0)
Insider Trading Strategy: A portfolio strategy using Monte Carlo simulations and insider trading transactions consistently performs better than the S&P 500 across various performance metrics. (2024-12-24, shares: 3.0)
Asset Co-Movement Conflicts: There is a positive correlation between the monthly returns of bonds and equities, with less stakeholder conflict leading to a higher degree of comovement between these financial instruments. (2025-01-05, shares: 3.0)
ArXiv ML
Recently Published
Physics of Skill Learning: The study proposes three models - Geometry, Resource, and Domino - to understand the physics of skill learning in neural networks, offering insights into neural scaling laws and learning dynamics. (2025-01-21, shares: 260)
Force-informed Dexterous Manipulation: DexForce, a new method for capturing demonstrations of complex manipulation, uses contact forces to compute actions for policy learning, achieving a 76% success rate. (2025-01-17, shares: 10)
Efficient Sparse Fourier Transform: GFast, a new algorithm, efficiently calculates the Fourier transform of functions over generalized q-ary sequences, outperforming existing algorithms in speed and sample usage. (2025-01-21, shares: 10)
RePec
Finance
Private Assets in Portfolio Approach: The Total Portfolio Approach (TPA) enhances investment returns by diversifying risk factors, particularly beneficial in private markets. (2025-01-23, shares: 28.0)
Factor Model for Equity Risk: A new model using instrumented principal component analysis (IPCA) predicts country equity risk premia better than other models, especially in emerging markets. (2025-01-23, shares: 21.0)
Feature Importance in Financial Models: Machine Learning can produce misleading results in financial models that assume linearity, indicating the need for careful application. (2025-01-23, shares: 18.0)
Model Specification for Volatility Forecasting: The best model for forecasting asset price volatility should use the natural logarithmic form of the original volatility measure for efficient regression estimators. (2025-01-23, shares: 16.0)
Machine Learning
Determinants of Zero-Leverage: The study uses machine learning to identify factors influencing the zero-leverage phenomenon, including cash holdings, tangible assets, industry leverage-level, and firm size, and suggests a solution for sample imbalance. (2025-01-23, shares: 20.0)
Predicting Bond Returns: Machine learning models show strong bond return predictability, especially during high risk aversion and slow economic growth, emphasizing the importance of using both cross-sectional and time-series predictors. (2025-01-23, shares: 13.0)
Detecting Asset Price Bubbles using Deep Learning: The article discusses a deep learning algorithm designed to detect financial asset bubbles using observed call option prices. This algorithm was tested on tech stock market data and under different models. (2025-01-23, shares: 15.0)
Historical Trending
Foreign Portfolio Investment Impact on Country Index Crash Risk: The study finds that country index crash risk is significantly influenced by exchange rate volatility and investor sentiment, but not by net foreign portfolio investment. (2024-05-09, shares: 24.0)
Asymmetric Volatility in Crypto Currency and Stock Market: Research shows a cointegration between major cryptocurrencies and Indian stock market indices, with cryptocurrencies reacting to stock market shocks. (2024-11-14, shares: 15.0)
Portfolio Optimization and ESG Risk Scores: The paper reveals that optimal portfolio structures are influenced by ESG Risk Scores under the Mean-Semivariance Behavioral Hypothesis, but the impact is minimal. (2024-11-15, shares: 15.0)
Improving Location Analytics with Explainable AI: The paper presents the SHAP location score, a new data-based method for assessing real estate locations, enhancing traditional urban models and benefiting real estate stakeholders. (2024-03-12, shares: 12.0)
EuroStoxx 50 Futures: Persistence: The study suggests that EuroStoxx 50 futures prices are not always efficient, with potential for abnormal profits at intraday frequency. (2024-10-23, shares: 12.0)
GitHub
Finance
Genetic Algorithm Python: PyGAD is a Python 3 library used for developing genetic algorithms and training machine learning models like Keras and PyTorch. (2018-12-11, shares: 1946.0)
Kiln AI: This tool aids in fine-tuning LLM models, creating synthetic data, and facilitating dataset collaboration. (2024-07-23, shares: 756.0)
OpStrat Options Trading: The project provides implementations of popular options trading strategies with experimental features, with plans to become a library in the future. (2019-06-29, shares: 21.0)
Trending
Open Source Gemini Research: The article presents an open-source AI tool that rivals Gemini Deep Research by generating reports from search results. (2024-12-24, shares: 231.0)
The Scikit-Learn Sidekick: The article discusses scikitlearn sidekick, a tool designed to assist in machine learning processes. (2024-06-17, shares: 239.0)
Python Stats Package: The article details a Python-based statistical package that utilizes the Pandas library. (2018-04-01, shares: 1668.0)
Simple Concurrent Python: The article provides a simplified explanation of concurrent programming in Python. (2024-05-22, shares: 675.0)
Twitter
Quantitative
Survey Paper on Crypto Trading Strategies: The article provides an in-depth analysis of cryptocurrency, including trading strategies, portfolio building, volatility forecasting, and data sources, along with a comprehensive list of references for further study. (2025-01-23, shares: 6)
Recap of Latest Research on Investing: The article recaps recent research on investment, covering topics like short interest and predictability, intraday oil futures patterns, banking stocks drivers, and forecasting FOMC decisions. (2025-01-21, shares: 1)
MOVE Index and VIX Predict Stock Returns: The article explores a new study that reveals a significant prediction of stock returns based on the divergence between the MOVE index and the VIX. (2025-01-17, shares: 1)
Miscellaneous
Postearnings Drift: Republican vs. Democratic Presidencies: The study shows that investors tend to overestimate expected tax cuts during Republican presidencies, leading to a notable difference in post-earnings announcement drift. (2025-01-22, shares: 0)
Beyond Momentum: Alternative Signals in Crypto Markets: Recent studies indicate that trend and breakout signals, not just momentum, are widely used in cryptocurrency markets. (2025-01-20, shares: 0)
Quantum Computing Breakthrough: Error Reduction Discovery: A recent breakthrough aims to drastically decrease errors in quantum computing, marking a significant advancement towards practical Quantum Computing. (2025-01-18, shares: 0)