Dynamic Market Maker for Automated Trading
The article introduces a Dynamic Function Market Maker protocol for decentralized automated market makers, providing a fully automated and robust solution.
4 sharesSource ↗
Quant LetterNo. 9
July 2023, Week 4
96 items across 6 sections, as sent to readers on 26 July 2023. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 96
- Papers
- 64
- Sections
- 6
- Issue
- No. 9
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
18 items
Finance7
Carbon Tax Propagation in Credit Portfolio
The study examines the impact of carbon taxes on firm value and credit risk measures in a closed economy, offering a method to calculate risk measures evolution based on a climate transition scenario.
4 shares2 citations todaySource ↗
Market Correlation Memory Effects
The study highlights the importance of considering the memory effect in market correlations for improving the accuracy of forecasting models and aiding in portfolio selection.
3 shares9 citations todaySource ↗
Adaptive RL for VWAP Tracking
The research introduces a reinforcement learning strategy that accurately tracks the daily volume-weighted average price of stocks, using a dual-level architecture for better results.
3 shares6 citations todaySource ↗
Mean Field Games for Portfolio Optimization
The paper discusses the use of the Mean Field Game framework for portfolio optimization, outlining optimal investment and consumption strategies.
3 sharesSource ↗
Transfer Learning for Portfolio Optimization
The study presents the concept of transfer risk in transfer learning techniques for financial portfolio optimization, showing its potential to improve the efficiency of the transfer learning approach.
3 shares2 citations todaySource ↗
Deep RL for Wealth Management
The paper suggests a new approach for goal-based wealth management using deep reinforcement learning, proving its effectiveness over several benchmarks on both simulated and historical market data.
3 shares1 citation todaySource ↗
Risk Engineering3
Optimal Bubble Riding with Price-dependent Entry
The paper improves the optimal bubble riding model by allowing price-dependent entry times, resulting in a mean field game of controls with common noise and random entry time.
4 shares6 citations todaySource ↗
Volatility Trading System for Stock Forecasting
The article presents a new stock market trading strategy using machine learning and statistical analysis to predict trends, proven effective through backtesting.
8 shares8 citations todaySource ↗
Adversarial Deep Hedging for Derivatives
The study introduces adversarial deep hedging, a new method for derivative hedging in incomplete markets, performing well across various real market data without explicit modeling.
8 shares9 citations todaySource ↗
Economics3
AI Predicting Human Decision-Making
A study reveals that only the GPT-4 chatbot could predict human decisions in a game, but it overestimated altruistic actions, impacting AI development.
2 shares7 citations todaySource ↗
Social Media's Impact on ESG Reputation Risk
The paper examines the influence of social media on shareholders' reactions to Environmental, Social, and Governance-related reputational risks, revealing a significant decrease in abnormal returns after an ESG-risk event.
2 shares106 citations todaySource ↗
Document Analytics for Banking Efficiency
The research investigates the use of advanced document analytics, such as LayoutXLM, in banking to analyze diverse documents efficiently and accurately, enhancing operational efficiency.
3 shares12 citations todaySource ↗
Historical Trending5
Price Discovery of Derivatives
The research proposes a theory on price discovery in derivative markets, focusing on insider trading and suggesting option strategies for trading.
36 shares1 citation todaySource ↗
Free Boundary Problem for Defaultable Bonds
The paper presents a pricing model for a corporate bond with credit rating migration risk, proving the solution's existence, uniqueness, and regularity.
13 shares3 citations todaySource ↗
Nonparametric Estimator of Tail Dependence
The study provides a theoretical expression for the mean squared error of a nonparametric estimator of the tail dependence coefficient and suggests a new method for optimal threshold selection.
13 shares4 citations todaySource ↗
Optimal Consumption-Investment Problems with Alternative Data
The research presents a new duality theory for optimal consumption-investment problem, incorporating alternative data like social media commentary and COVID-19 data, and suggests a consumption-investment strategy using these data.
9 shares2 citations todaySource ↗
FinGPT: Democratizing Internet-scale Data for Financial Large
Democratizing Internet-scale Data for Financial Large: The paper presents FinGPT, an open-source, data-centric framework that automates the gathering and curation of real-time financial data from various online sources, aiming to democratize financial data for large language models.
8 shares124 citations todaySource ↗
SSRN
Working papers in finance and economics from SSRN.
31 items
Financial10
Asset Pricing Outliers
The article discusses how using a Minimum Covariance Determinant estimator improves the performance of stochastic discount factor models by handling multivariate outliers effectively.
5 sharesSource ↗
Ambiguity Attitude and Risk-Return Tradeoff
The research shows that the link between the conditional equity premium and market volatility is influenced by the agent's ambiguity attitude, and market volatility doesn't significantly forecast returns.
4 sharesSource ↗
CDS Volatility as Economic Uncertainty Indicator
The article suggests that the fluctuation of sovereign credit default swaps can indicate economic uncertainty, aligning with economic policy uncertainty indices.
2 shares7 citations todaySource ↗
Retail vs Secondary Market Arbitrage
The study explores the link between product features and arbitrage returns in retail and secondary markets, creating a model to predict arbitrage return at product launch.
2 sharesSource ↗
Anomaly Predictability in Portfolios
Discussed above - the study suggests that past pricing errors can predict future anomaly returns, indicating that cross-sectional models should include price information to track return dynamics over time.
7 sharesSource ↗
ETF Pricing Dynamics
Policymakers are exploring swing pricing, a method that adjusts a mutual fund's value based on investor activity, to mitigate financial risks from open-end mutual funds.
88 sharesSource ↗
Market Fragmentation
A rise in market fragmentation, the spread of market trading across various platforms, results in a greater price impact of equity trading, especially for smaller stocks.
108 sharesSource ↗
Bond Fund Herding
The study reveals that collective behavior of mutual funds, known as fund herding, can sway a company's decision to issue new bonds, particularly in uncertain times.
69 sharesSource ↗
Hedge Fund Evaluation with Machine Learning
Bayesian Additive Regression Trees (BART), a Bayesian machine learning method, is more effective in assessing hedge fund performance than traditional models.
2 sharesSource ↗
Fractional Trading's Impact on Order Book Dynamics
The implementation of fractional trading in stock markets has significantly affected price levels and order book dynamics, potentially changing the investment habits of nonprofessional investors.
2 sharesSource ↗
Governance7
Accounting Quality and Fund Fire Sales
The study indicates that high accounting quality is linked to smaller fire-sale discounts, implying that good accounting practices can reduce undervaluation caused by mutual fund fire sales.
4 sharesSource ↗
Corporate Policy Extraction using ChatGPT
The research uses ChatGPT to interpret managerial expectations from corporate disclosures, predicting future capital expenditure and intangible and R&D investments.
3 shares60 citations todaySource ↗
Generative AI and Investment Advisory via ChatGPT
The article shows that AI like ChatGPT can generate portfolio recommendations based on policy announcements, potentially outperforming markets unlike traditional textual analysis.
3 shares11 citations todaySource ↗
Machine Learning for Monitoring Review and Testing at Financial Institutions
The article investigates the use of machine learning for automating Volcker Rule compliance testing, a neglected area in risk management.
3 sharesSource ↗
Trade Credit Provision and Finance Subsidiaries
The research shows that larger, more active captive finance subsidiaries positively impact the parent company's trade credit provision and lower default rates.
5 sharesSource ↗
PE and Corporate Borrowing Constraints
Private equity buyouts help firms increase their leverage by borrowing against cash flows, with PE sponsors providing equity and stability during distress.
2 sharesSource ↗
Machine Learning in Mortality Forecasting
The article introduces a new machine learning approach for long-term mortality forecasting, enhancing prediction accuracy and addressing the issue of diminishing patterns in long-term forecasts.
2 sharesSource ↗
Derivatives4
Quantifying Volatility Smile
The article examines the impact of maximal trading speed at the start and end of equity markets on backtesting quantitative strategies.
4 sharesSource ↗
Option Pricing with Costs and Volatility
The research uses a specific model to solve a complex equation related to option pricing, but finds discrepancies suggesting potential risks in the model.
4 sharesSource ↗
Pricing Pseudo-Swaps with Pseudo-Statistics
The article introduces a method for pricing different types of swaps using pseudostatistics, and compares it to an existing model.
2 sharesSource ↗
Volatility Curve Stationarity Testing
The paper introduces a test for stability of hidden volatility curves over time using high-frequency financial data, revealing nonstationary variation in intraday volatility pattern over time in SP 500 futures data.
2 shares2 citations todaySource ↗
Miscellaneous3
NLP for SQL Query Generation
The paper explores the creation of systems for generating SQL queries using natural language processing, discussing challenges, methods, and future research.
6 shares3 citations todaySource ↗
Auto ML Technique Analysis
The paper reviews Auto Machine Learning (AutoML), its pros and cons, and potential future research, highlighting its role in enhancing model accuracy and minimizing human intervention.
2 sharesSource ↗
Modeling Shanghai Composite Index Opening Spread
The research uses hybrid models to predict the opening price difference rate of the Shanghai Stock Exchange Composite Index, suggesting implications for stock market forecasting and investment decisions.
3 sharesSource ↗
Quantitative3
Dynamic Function Market Maker
The article suggests a new protocol for efficient asset pricing and risk management in decentralized automated market makers, combining a data aggregator and order routing.
9 sharesSource ↗
Optimization of Trading Strategies with MACD Indicator
The article explores the use of the Moving Average Convergence Divergence indicator for optimizing trading strategies, enabled by increased computational power and data availability.
2 shares1 citation todaySource ↗
Augmented HAR for Volatility Forecasting
The Augmented HAR algorithm, combined with artificial neural networks, enhances forecast accuracy for stocks with less than seven years of data.
2 shares6 citations todaySource ↗
Risk Engineering4
Decomposing Downside Investment Risk: CES
CES: The paper suggests using Centred Expected Shortfall (CES) instead of Expected Shortfall (ES) for a more precise evaluation of portfolio risk.
2 sharesSource ↗
Liquidity Premium for Crypto Assets
The research introduces new liquidity premium Beta measures for crypto assets and portfolios, enhancing predictability and performance in situations of high liquidity.
2 sharesSource ↗
Political Uncertainty and VIX Futures
The research identifies a link between the 2020 U.S. presidential election and the VIX futures term structure, with political uncertainty heightening investors' worries about anticipated market uncertainty.
49 sharesSource ↗
Zero-Day Options Trading and Asset Volatility
The surge in ZeroDaytoExpiry (0DTE) options trading from 2011 to 2022 has led to increased volatility in the underlying asset.
2 sharesSource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
15 items
Finance6
Factor portfolio optimization
The article discusses a model that uses machine learning and market predictors to reduce noise in historical data, enhancing portfolio optimization.
23 sharesSource ↗
Fama-French Model vs. Machine Learning
The piece highlights a seven-factor model that improves the average R-squared by 7% in the A-share market, with SVM and random forests being the most effective machine learning algorithms.
20 sharesSource ↗
Forecasting VaR and ES in portfolios
The article presents two new procedures for estimating Value-at-Risk and Expected Shortfall in large portfolios, which outperform existing methods based on backtesting and scoring results.
19 sharesSource ↗
Algorithmic Trading & Block Ownership: Investor Impact
Investor Impact: Algorithmic trading discourages sophisticated investors from gathering information, thus reducing the chances of block ownership initiation in U.S. public companies.
17 sharesSource ↗
Factor Models for Incomplete Data: Unknown Group Structure
Unknown Group Structure: A new method that combines two algorithms accurately estimates missing data and identifies group structures in large economic databases.
14 sharesSource ↗
External Debt & Exchange Rate Volatility in South Asia
External debt significantly increases exchange rate volatility in South Asian Countries, as per data from the World Development Indicators from 1980-2020.
13 sharesSource ↗
Statistical2
Machine Learning for Inflation Forecasting
The article discusses the use of machine learning to enhance inflation prediction in Brazil, emphasizing the role of non-linear factors in inflation trends.
13 sharesSource ↗
Robust Monitoring Machine for R2-Hacking
The research introduces a method using collective machine learning to prevent data manipulation in test samples, enhancing the accuracy and consistency of stock return predictions and preventing R^2-hacking issues.
12 sharesSource ↗
Machine Learning3
Herding Effect & Market Volatility in Chinese Stock Market
The research investigates the predictive power of market herding effect on Chinese stock market volatility, revealing improved prediction accuracy with machine learning algorithms.
15 sharesSource ↗
Facial Characteristics & Returns in Economics
The paper applies computer vision and machine learning to identify facial traits of college football coaches, suggesting a salary bias against attractiveness and favoring aggressiveness.
13 sharesSource ↗
Explainable ML Methods for Actuarial Problems
The article discusses the use of explainable artificial intelligence in solving insurance problems, highlighting the need for accurate and understandable machine learning models.
24 sharesSource ↗
Historical Trending4
Asset Volatility & Capital Structure in Corporate Mergers
The research indicates that changes in asset volatility after corporate acquisitions can predict changes in leverage and cash holdings, highlighting the role of firm risk.
20 sharesSource ↗
Default Risk Prediction of Enterprises using CNN
The study introduces a metric model based on machine learning to choose the best balance ratio and feature selection, enhancing the performance of neural networks in predicting default risk.
17 sharesSource ↗
Mean Expected-Shortfall Strategies: 'Cut Losses, Ride Gains'
'Cut Losses, Ride Gains': A new trading strategy is suggested that focuses on left tail risk, yielding an annualized alpha of 180 bps over five years, unlike the traditional contrarian mean-variance strategy.
15 sharesSource ↗
Adaptive Data Clustering Method Based on Density Peaks
A new data clustering method, AMDPC, based on density peaks, improves clustering accuracy by 22.58% to 28.03% across various datasets compared to traditional algorithms.
14 sharesSource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
5 items
Trending3
MetaTransformer: Unified Multimodal Learning
Unified Multimodal Learning: The piece explores multimodal learning, a method that develops models capable of processing and connecting information from different sources.
155 shares
TOAST: Transfer Learning with Attention Steering
Transfer Learning with Attention Steering: The article presents TOAST, a novel transfer learning algorithm that focuses on task-relevant features to enhance attention to task-specific features.
124 shares
AI for Science in Quantum Systems
The article underscores the impact of artificial intelligence advancements on new discoveries in the field of natural sciences.
146 shares
Rising2
ChatGPTs' Changing Behavior
The performance and behavior of AI models GPT3.5 and GPT4 can vary greatly over time.
89 shares
Evaluation for Long Context Language Models
The article explores the growing trend of enhancing instruction-following models to handle longer single-turn inputs such as detailed conversations and paper summaries.
53 shares
GitHub
Repositories the letter featured.
8 items
Finance3
Codebase Trials: Reinforcement Learning for Pair Trading
Reinforcement Learning for Pair Trading: The code presents a new pair trading model using hierarchical reinforcement learning, with code and tests on actual stock data.
28 shares
Sarimadashboard: Time Series Analysis using sARIMA Models
Time Series Analysis using sARIMA Models: The code showcases a Dash web app designed to analyze time series datasets using sARIMA models.
25 shares
Binance API in C
The code explains the process of implementing the Binance API using the C programming language.
177 shares
Trending5
Trex: Intelligent Unstructured Data Transformation
Intelligent Unstructured Data Transformation: The code outlines techniques for smartly transforming unstructured data into structured data.
123 shares
Pydantic: Data Validation with Python Type Hints
Data Validation with Python Type Hints: The code provides a guide on using Python type hints for data validation.
14,880 shares
Apps with LLMs
The code outlines the method of creating apps using the Low-Level Virtual Machine (LLVM) via composability.
55,960 shares
UNIX Find Command: Breadthfirst
Breadthfirst: This code introduces a breadth-first version of the UNIX find command, presenting a new search method.
791 shares
Llama2
The code details the process of implementing Inference Llama 2 using a single C programming language file.
3,065 shares
News
Industry news: funds, hiring, markets and regulation.
19 items
Quantitative4
Man Group Embraces Data Revolution in EM -> Man Group Embraces Data Revolution
Man Group's quantitative division is embracing the data revolution in developing markets.
4 shares
Quantitative Investment Market Growth -> Quantitative Investment Growth
The quantitative investment sector is witnessing substantial business expansion and industry evolution.
4 shares
Wright Research Launches Quantbased Portfolio Management -> Wright Research Launches Portfolio Management
Wright Research has launched a new portfolio management system based on quantitative analysis.
2 shares
New Programming Language Rivals C -> New Programming Language Rivals C
The article explores a crucial asset that is advantageous to understand.
1 shares
Twitter4
LongNet: GPTs for the Entire Internet
GPTs for the Entire Internet: Article 1: Microsoft has created LongNet, a transformer capable of processing the entire Internet as one long sequence.
0 shares
Reducing Risk: Crash Prevention
Crash Prevention: Article 2: The article explores methods to minimize the impact of sudden downturns in the financial market.
0 shares
Enhancing Equity Strategy Performance with VIX Scaling
The article proposes that the VIX can improve equity strategies' performance by accounting for volatility scaling and transaction costs.
3 shares
The Dangers of Overextrapolating Growth in Market Valuations
The article, citing a visualization by @ckaiwu, argues that a successful company doesn't necessarily make a good investment, especially when markets overvalue potential growth in times of euphoria.
0 shares
Videos3
ABFR Webinar
The seminar explores the potential impact of Large Language Models on the labor market, with insights from AI and big data experts in economics and finance.
1 shares
Easiest LLAMAv2 Finetuning
The tutorial video teaches how to fine-tune llamav2 on a personal computer for a custom dataset with autotrainadvanced.
30 shares
Fastest Chat UI
The tutorial video shows a fast way to create a chatbot interface using gradio.
32 shares
Blogs3
LSTM Neural Network Indicators
The first article explores the creation of a trading strategy using a LSTM neural network that is trained with technical analysis metrics.
8 shares
Man Group CEO Luke Ellis on Hedge Funds (podcast)
Under CEO Luke Ellis, Man Group's assets under management have nearly doubled to approximately $145 billion.
5 shares
Reddit5
Software Engineer & Quant Dev Resources
A junior engineer in a quant fund is looking for advanced resources on Delta One products to better understand their pricing, trading, and execution.
20 shares
Fixed Income Quant Start
The post discusses how quantitative analysts frequently begin their careers or work in the fixed income sector.
29 shares
HFT Shop Founders' Life Lessons
The author is interested in learning about life lessons from others' experiences.
21 shares
Leveraged ETF Portfolio Drawbacks
The post explores potential disadvantages of portfolio construction using futures and leveraged ETFs, including tax implications and expense ratios.
14 shares
Investment Choices of Quants
The author is contemplating an unspecified question that they have frequently considered.
60 shares