ArXiv
Finance
RL Agents in Market Simulation: The research introduces a market simulation framework using reinforcement learning agents that can mimic real-world market dynamics and adapt to major market events. (2024-03-28, shares: 2)
Curb Appeal with Deep Learning: Incorporating image data into econometric models through deep learning enhances the accuracy of residential real estate price predictions. (2024-03-29, shares: 4)
Optimal Rebalancing in AMMs: A new method for optimally rebalancing asset ratios in Dynamic Automated Market Maker pools could potentially increase pool profit and loss by about 25% for a BTC-ETH-DAI pool from July 2022 to June 2023. (2024-03-27, shares: 4)
Revisiting String Models of Interest Rates: A revised model of the forward interest rate curve, considering market forces and return correlation, accurately replicates the curve's correlation structure from 1994-2023 with less than 2% error, confirming that perceived time in interest rate markets is a sub-linear function of real time. (2024-03-26, shares: 3)
Neural Networks for Finance: The study investigates the use of supervised autoencoders in improving financial forecasting through precise parameter tuning. (2024-04-02, shares: 3)
SSRN
Recently Published
Quantitative
Enhanced Equity Market Strategy: The article introduces a novel stock market strategy that enhances performance by merging a financial stress indicator with sentiment analysis. (2024-04-02, shares: 29.0)
Extending Financial Portfolio Methods with Deep RL: The paper suggests that deep reinforcement learning can potentially improve traditional portfolio allocation strategies by incorporating contextual data and future rewards. (2024-04-01, shares: 2.0)
Aggregating Autoencoders for Persistent Access Threats: The article presents AEAPT, a deep learning method for detecting and isolating long-term, undetected cyberattacks. (2024-04-02, shares: 6.0)
Uncertainty in Sentiment Analysis: The study explores the uncertainty in sentiment scores derived from text using advanced language processing models, finding moderate uncertainty in the results. (2024-04-01, shares: 14.0)
Portfolio Replication Insights: The paper introduces a new method for decoding investment portfolio strategies using Dynamic Bayesian Graphical Models, resulting in better portfolio allocation decisions and adaptability to various market conditions. (2024-04-01, shares: 12.0)
Financial
Forecasting Trading Costs: The research analyzes trading costs, revealing that large, complex trades can be executed affordably and that trade risk value and complexity extend trade horizons. (2024-04-02, shares: 17.0)
Pricing Liquidity Risk: The research investigates the pricing of liquidity factors in the US stock market, demonstrating that models with a liquidity factor outperform those with a size factor. (2024-03-30, shares: 5.0)
Extreme Liquidity: The article proposes a crypto asset portfolio model that adjusts for liquidity to improve effectiveness and reduce discontinuity. (2024-03-30, shares: 2.0)
US Treasury Yield Forecast: The study introduces a forecasting model for predicting the 10-Year US Treasury Yield based on variables like exchange rates and crude oil prices. (2024-04-01, shares: 7.0)
Intellectual Capital Growth Modeling: The paper discusses a new funding mechanism that uses intellectual capital money to stimulate the generation and exploitation of intellectual capital. (2024-03-31, shares: 3.0)
Market Clearing: The article investigates the role of firms in providing shares to passive investors, particularly in response to index funds' buying. (2024-03-29, shares: 6.0)
Recently Updated
Quantitative
Equity Premium Forecasting: Machine learning techniques, while effective in predicting equity premium within sample, struggle to beat the historical average in out-of-sample predictions. (2023-08-06, shares: 3.0)
China’s Inflation Rate Forecasting: Eight machine learning models, notably the gradient boost decision tree and forecast combination model, excel in predicting China's inflation rate over the autoregressive benchmark. (2024-03-24, shares: 4.0)
Predicting Beta: Machine Learning algorithms enhance the precision of estimating equity betas for private or nontraded assets, particularly for smaller, younger firms with unique capital structures. (2024-01-01, shares: 2.0)
Deep News Sentiment for Finance: The article discusses the use of neural networks to extract hidden economic factors from large news analytics data, showing superior performance in GDP growth forecasting and asset return analysis. (2023-09-12, shares: 2.0)
Behavioral Diversification in Portfolios: The article introduces a new simulation of a diversified portfolio based on consumer products, using linear regression and Monte Carlo Simulation, advocating for a consumer-behavior approach in portfolio structuring. (2023-08-07, shares: 2.0)
Comparative Study of Portfolio Risk Management: The article suggests a new method for portfolio risk management and capital allocation, combining value-at-risk with other statistical measures, proving its effectiveness in reducing potential portfolio losses. (2023-11-01, shares: 2.0)
Arbitrage Risk in MAX Effect: In the Korean stock market, the MAX effect, or the highest daily return from the previous month, is only significant in overpriced stock groups. (2022-05-20, shares: 28.0)
Financial
Global US Stock Integration: The research finds that US stocks with less global integration can improve portfolio diversification and match international index portfolios in risk-adjusted returns and tail risk. (2023-08-03, shares: 86.0)
Asymmetric Info in Asset Markets: The study suggests that reducing information asymmetry in secondary asset markets could potentially harm economic welfare. (2022-08-19, shares: 152.0)
PL Attribution Options: The paper disputes the belief that the gap between implied and realized volatility is the main factor in profit and loss for delta-hedged options, proposing a new formula for understanding this difference. (2023-07-07, shares: 169.0)
Strategic Mutual Fund Convergence: The research finds a trend towards similar allocation strategies in equity mutual funds globally, especially among funds managed by large financial institutions. (2022-04-29, shares: 89.0)
Forecasting TSEC Volatility: The study compares GARCH family models and EWMA models to identify the best algorithm for predicting volatility in Taiwan's stock market, using data from 1997 to 2023. (2023-12-31, shares: 2.0)
Issues with Implied Volatilities: OptionMetrics records stock options prices at 359 p.m., not 400 p.m., causing changes in implied volatility spreads and affecting stock comovement, especially during the COVID-19 pandemic. (2022-03-22, shares: 2.0)
Improved Volatility Strategy: An enhanced strategy for volatility-managed portfolios, based on Moreira and Muir 2017's formation, results in significant real-time performance improvement, including 148 Sharpe ratio increases and 165 positive abnormal returns. (2023-08-25, shares: 2.0)
Domain Influence on Diversification: A study of 251 US retail investors found diversification errors in the gain domain but not in the loss domain, supporting a loss-attention hypothesis. (2021-08-27, shares: 2.0)
False Discoveries in Currency Analysis: A new method, robust to data dependence and estimation errors, is developed to assess predictive models' performance, when applied to currency technical trading rules, it yields a Sharpe ratio around one for about 50 years. (2024-03-06, shares: 2.0)
Media Sentiment and Asset Allocation: US media sentiment about foreign countries affects domestic investors' international asset allocation, with negative media coverage leading to reduced flows to international mutual funds targeting the country. (2023-05-09, shares: 2.0)
ArXiv ML
Recently Published
Rashomon Partitions: Estimating Heterogeneity: The study introduces Rashomon Partition Sets, a new method for partitioning covariate space in statistical analyses, which includes all partitions with posterior values near the maximum, allowing for more robust conclusions. (2024-04-02, shares: 8)
Gecko: Compact Text Embeddings: Gecko is a new text embedding model that improves knowledge extraction from large language models, surpassing other models in the Massive Text Embedding Benchmark. (2024-03-29, shares: 172)
Historical Trending
LightGaussian Compression: LightGaussian is a new method that converts 3D Gaussians into a more compact format, enhancing efficiency in real-time neural rendering and reducing storage needs. (2023-11-28, shares: 519)
Longform Factuality: The Search-Augmented Factuality Evaluator (SAFE) method uses large language models to assess the accuracy of long-form factual content, achieving superior rating performance. (2024-03-27, shares: 323)
FP Deep Learning Quantization: A study finds that FP8 data formats are superior to INT8 in post-training quantization, offering better workload coverage, model accuracy, and versatility across various network architectures. (2023-09-26, shares: 100)
Visual LVLM Grounding: The Rephrase, Augment and Reason (RepARe) framework enhances the performance of large vision-language models in zero-shot tasks by rephrasing questions and extracting image details. (2023-10-09, shares: 127)
Unsupervised Diffusion Segmentation: A new method using self-attention layers in stable diffusion models achieves superior zero-shot segmentation without annotations, outperforming previous methods on the COCO-Stuff-27 dataset. (2023-08-24, shares: 107)
Riemannian Laplace Approximation: A recent improvement to the Laplace Approximation, which uses a Gaussian distribution to approximate a target density, corrects previous biases and narrow approximations, leading to practical improvements in experiments. (2023-11-05, shares: 75)
RePec
Finance
Global Impact on Volatility Persistence: Global factors significantly influence the local volatility persistence in equity indices of 17 developed economies. (2024-04-03, shares: 24.0)
Insider Trading Strategies: Seyhun's 1986 study indicates that insider buying often leads to positive future returns, while insider selling slightly hints at negative returns, possibly due to liquidity needs. (2024-04-03, shares: 12.0)
Accruals-Cash Flow Evaluation: This research clarifies misconceptions about the role of accruals in informative earnings, introducing a new analysis that recognizes non-cash accruals as parts of earnings that do not involve cash flows. (2024-04-03, shares: 9.0)
Forecasting CPI: The study enhances the precision and promptness of Consumer Price Index (CPI) forecasts by using a large Chinese news corpus and Internet search data, and combining penalized regression and mixed-frequency data sampling methods. (2024-04-03, shares: 9.0)
GitHub
Finance
Unified Time Series Forecasting Transformers: The piece investigates a combined training approach for universal time series forecasting transformers. (2024-02-07, shares: 283.0)
PyTorch Implementation for StockFormer: The article showcases a PyTorch implementation of the StockFormer paper, which studies hybrid trading machines using predictive coding. (2023-07-30, shares: 62.0)
Lightweight LLM Evaluation Suite: The article presents LightEval, a lightweight evaluation suite for LLM, used by Hugging Face along with the new LLM data processing library datatrove and LLM training library nanotron. (2024-01-26, shares: 267.0)
Python Package for TradingView Screeners: The piece explores a Python package that enables users to develop TradingView screeners. (2022-05-30, shares: 112.0)
Python Library for Nasdaq Data Links API: The article talks about a Python library that enables access to Nasdaq Data Links' RESTful API. (2021-11-02, shares: 379.0)
Trending
Python QuestDB InfluxDB Client: A Python client has been created for QuestDB's InfluxDB Line Protocol. (2022-06-13, shares: 47.0)
Rust Market Simulation Library: A Rust-based market simulation library with a Python API has been developed. (2024-02-20, shares: 13.0)
Local and API Model Experiments: Local and API-available models are being used in ongoing experiments. (2024-01-13, shares: 601.0)
LinkedIn
Trending
New Publication on Predictability: A new publication focusing on predictability and robustness for a special issue of Econometrics and Statistics has been released, featuring contributions from Lorenzo Camponovo and Fabio Trojani. (2024-04-03, shares: 2.0)
Fair Value Option Model: Thomas Feng from Graham Capital Management lectured at Columbia University on creating an option model for fair value determination across volatility term structures, useful for trading strategies. (2024-04-03, shares: 2.0)
Synthetic Data in Finance: The use of synthetic data is growing in quantitative finance due to its ability to improve modeling, analysis, and testing, while overcoming real-world financial data limitations. (2024-04-03, shares: 2.0)
Ilia Bouchouev Virtual Barrels Talk: Commodities trader Ilia Bouchouev will discuss his new book Virtual Barrels: Quantitative Trading in the Oil Market at a Thalesians Ltd event in London. (2024-04-02, shares: 2.0)
Risk Management in Trading: Will McBride and Dmitry Pargamanik emphasize the significance of risk management tools in option trading, following their webinar on using an options profit calculator. (2024-03-28, shares: 4)
Traders Use Weather Derivatives: Increased extreme climate events are causing a rise in weather trading. (2024-04-02, shares: 3)
Twitter
Quantitative
Turing Institute Report on Language Models in Finance: The report from the Alan Turning Institute explores the application of large language models in finance. (2024-04-02, shares: 0)
Machine Learning for Merger Arbitrage: A recent study utilizes machine learning to enhance the success and potential returns of merger arbitrage trades. (2024-03-29, shares: 8)
Using Option Market Data to Predict ETF Returns: The research paper proposes a novel trading strategy, suggesting that alterations in the implied volatility of ETF options can forecast returns on the underlying ETF. (2024-04-01, shares: 7)
Weekly Recap of New Research in Finance: The latest weekly summary emphasizes new research in fields like asset pricing, machine learning, market microstructure, and options. (2024-04-02, shares: 6)
Machine Learning and Data Science Notes: Ott Toomet from the University of Washington shares extensive lecture notes on machine learning and data science. (2024-04-01, shares: 5)
Equity Risk Premium Update: Aswath Damodaran's 2024 paper update explores the elements affecting the equity risk premium and ways to calculate it. (2024-04-01, shares: 2)
Miscellaneous
ML DL, AI in Asset Management: Article 1: The article explores the use of Machine Learning, Deep Learning, and AI in the field of Asset Management. (2024-04-02, shares: 1)
Mathematics of Neural Networks: Article 2: Bart Smets of Eindhoven University shares lecture notes on the mathematical aspects of Neural Networks for advanced students. (2024-03-30, shares: 1)
Momentum Goes Vertical: Article 3: The article reports on a notable surge in momentum. (2024-04-03, shares: 0)
Generative AI Language Model Market Map: The article introduces the fast-expanding Generative AI Large Language Model Infrastructure Stack and its market landscape. (2024-04-02, shares: 0)
Info for Traders: The article provides useful information for individuals involved in trading. (2024-03-30, shares: 0)
Linear Algebra Review: The article provides a comprehensive review of the subject of linear algebra. (2024-03-29, shares: 0)