Lead-Lag Relationships in Time Series Detection
A new technique using dynamic time warping has been created to identify lead-lag relationships in multivariate time series systems, demonstrated in financial markets.
6 shares5 citations todaySource ↗
Quant LetterNo. 16
September 2023, Week 3
104 items across 10 sections, as sent to readers on 21 September 2023. Paper titles open their ML-Quant page; ↗ goes to the source.
- Items
- 104
- Papers
- 63
- Sections
- 10
- Issue
- No. 16
arXiv
Quantitative-finance and ML-for-finance preprints from arXiv.
19 items
Finance6
Deep Learning for Credit Portfolio Sensitivity Quantification
A unique method using Variational Autoencoders has been suggested to measure credit portfolio Value-at-Risk sensitivity to asset correlations, providing a clearer latent space representation.
6 shares5 citations todaySource ↗
VIX Index Model and Futures/Options Pricing Empirics
A new model for the VIX index has been proposed, using a continuous-time Markov process to model its dynamics and offering a solution for pricing VIX futures and call options.
5 sharesSource ↗
Sizing Strategies for Algorithmic Trading in Volatility
The article investigates various models of sizing in financial trading and backtesting during high volatility situations, showing how crisis events can be handled using short and long positional size.
4 sharesSource ↗
Transformers vs LSTMs for Financial Time Series Prediction Comparison
A comparison study of LSTM-based and Transformer-based models for financial time series prediction found that LSTM-based models perform better in difference sequence prediction, despite Transformer-based models having limited advantages in absolute price sequence prediction.
3 shares33 citations todaySource ↗
Sparse Grid Interpolation for Option Pricing
The first article introduces a new method for pricing American options with multiple assets, combining dynamic programming and sparse grid-based polynomial interpolation.
7 shares4 citations todaySource ↗
Economics4
Rationality Testing with P-GMM Estimation
The article examines the use of P-GMM moment selection procedure in estimating and testing forecast rationality, using data from the Federal Reserve Bank of Philadelphia's Survey of Professional Forecasters.
5 sharesSource ↗
Competitive Equilibrium with Substitutes
The study presents new findings on the existence and uniqueness of a general nonparametric and nonseparable competitive equilibrium with substitutes, offering an algorithm to calculate the unique competitive equilibrium.
2 shares1 citation todaySource ↗
Ticket Allocation with Marginal Price Auctions
A proposed ticketing protocol uses a marginal price auction system to allocate tickets to the highest bidders, with the final price set by the lowest winning bid, aiming to enhance efficiency and fairness.
2 shares1 citation todaySource ↗
Chaotic Price Adjustment in Exchange Economy
A study investigates the conditions needed for topological chaos in a standard exchange economy model, utilizing a recent finding about the existence of topological chaos for a unimodal interval map.
2 sharesSource ↗
Crypto & Blockchain5
Ethereum's Proof of Stake Sustainability Doubt
Doubts are raised about the sustainability and security of Ethereum's shift to Proof of Stake, with concerns about how competition with other smart contract platforms could affect Ether's price.
8 shares3 citations todaySource ↗
Predictable Wealth Dynamics in DeFi
The study outlines the wealth dynamics of strategic liquidity providers in constant product markets, proposes an optimal liquidity provision strategy, and uses Uniswap v3 data to show its effectiveness.
6 shares47 citations todaySource ↗
Crypto Skeptics and the Supreme Court
The article explores the debate on the classification of crypto assets as commodities or securities, and the potential impact of the Supreme Court's final decision on this matter.
14 sharesSource ↗
Liquidity Math in Uniswap v3: Concentrated Liquidity Understanding
Concentrated Liquidity Understanding: The technical note explains the mathematical correlation between a position's liquidity, the assets in that position, and its price range in Uniswap v3, the largest decentralized exchange, providing equations not covered in the whitepaper.
3 shares12 citations todaySource ↗
Wealth Management Democratization: Hedged Fund Blockchain
Hedged Fund Blockchain: The paper proposes innovations to adapt traditional investment fund practices to blockchain, including regular fund price updates, performance fees, and measures to counteract trading-related slippage costs.
2 sharesSource ↗
Historical Trending4
Lead-Lag Detection in Multi-Factor Models
A new method for detecting lead-lag relationships in multivariate time series systems, applicable to fields like finance and environment, has been developed.
122 shares5 citations todaySource ↗
Investment in Pension Schemes
The article proposes an optimal investment strategy for defined contribution pension scheme workers that adapts to environmental changes while maintaining time-consistency.
46 shares7 citations todaySource ↗
Equity Auction Price Impact
The research identifies statistical patterns in equity auctions at the Paris stock exchange, focusing on the influence of new market orders or cancellifications at auction time.
35 shares5 citations todaySource ↗
Ensemble Forecasting for Insurance Loss Reserving
The paper introduces a framework for combining multiple stochastic loss reserving models, which performs better than traditional strategies and equally weighted ensembles, taking into account the full distributional properties of the ensemble.
33 shares6 citations todaySource ↗
SSRN
Working papers in finance and economics from SSRN.
28 items
Quantitative13
Transformers vs LSTMs in Electronic Trading
The research compares LSTM and Transformer models in financial prediction tasks, finding out if Transformer models can surpass LSTM in financial time series prediction.
70 sharesSource ↗
Forecasting Stock Market Volatility with Realized Volatility
The paper presents the REGARCH-CDJI model for predicting stock market volatility, which performs better than other models when applied to Shanghai Stock Exchange Composite index data.
2 sharesSource ↗
Product Market Competition's Impact on Mutual Funds' Portfolio Choices
The research shows that mutual funds hold less equity in companies facing increased product market competition, especially for firms more susceptible to competition and with greater agency problems.
2 sharesSource ↗
Graph Embedding for Sentiment Analysis
The research suggests a self-supervised method for Persian sentiment analysis using combined representation learning and Siamese Network, using a self-supervised approach to enhance feature vectors from graph-structured data.
2 sharesSource ↗
Leverage Cycles
The study presents a framework for understanding leverage cycles and asset bubbles in a production economy, indicating that an asset bubble can either promote or impede long-term growth, and can lead to various dynamic equilibria, including endogenous boom-bust cycles.
3 sharesSource ↗
Decentralized Market Liquidity Provision
The study examines how liquidity providers in decentralized exchanges decide to add liquidity, finding that it often occurs when price volatility or return is within a certain range, as evidenced by Uniswap token pools data.
2 sharesSource ↗
Media Sentiment and Conflict
Using machine learning and natural language processing, the research finds a significant link between conflictual sentiment in media reports and future conflict events, indicating sentiment analysis can improve our understanding of conflict dynamics.
2 shares3 citations todaySource ↗
Time-Varying Volatility Interactions
The paper introduces a new volatility model that accounts for changes in codependence, simplifying the estimation process and offering a new test for constancy codependence volatility, with Monte Carlo experiments supporting its empirical properties.
2 sharesSource ↗
Efficient Deep Hedging: No-Transaction Band Network
No-Transaction Band Network: The research introduces a neural network model that allows quick and accurate assessment of optimal hedging strategies for a broad range of utilities and derivatives, including exotic ones.
2 sharesSource ↗
Bayesian Modeling of Dynamic Parameters
The paper introduces a nonparametric time-varying parameter (TVP) model using Bayesian additive regression trees (BART) for macroeconomic models, providing flexibility in parameter change and easy inference.
2 sharesSource ↗
Enhanced Block Rearrangement Algorithm
The article discusses improving the block rearrangement algorithm (BRA) used in finance and operations research by refining block submatrix sizes using a Beta distribution.
2 sharesSource ↗
Data-driven Investors: Trade-off of Data Technologies
Trade-off of Data Technologies: Venture capitalists using data technologies tend to invest in familiar businesses and avoid failures, but are less likely to back startups with potential for major success, indicating these technologies favor businesses with historical data.
2 sharesSource ↗
Responsible Investing: Potential and Protection
Potential and Protection: The research indicates that responsible investors with highly rated processes can achieve both enhanced upside potential and protection from downside risks, unlike mere Principles for Responsible Investment (PRI) members.
2 sharesSource ↗
Financial15
ML Models for Stock Crash Prediction
The paper suggests a machine learning framework that predicts stock market crashes by combining market data, graph data, and sentiment analysis, with LightGBM showing superior accuracy.
2 shares1 citation todaySource ↗
Hedge Funds Exploiting Nonpublic Bankruptcy Info
The article reveals that hedge funds use nonpublic information to profit from trades in securities of firms linked to a bankrupt company they serve on the unsecured creditors committee.
2 shares1 citation todaySource ↗
Loss Function for Investment Strategies
The article introduces a new Mean Absolute Directional Loss function to enhance the efficiency of machine learning models used in financial forecasting.
2 sharesSource ↗
Course in Financial Risk Management
The University of Paris-Saclay offers an advanced course in financial risk management, covering topics like market risk, credit risk, operational risk, liquidity risk, model risk, and stress testing.
3 sharesSource ↗
Efficient Pricing of Low-Risk Bonds
The research indicates that low-risk corporate bonds yield high returns due to leverage-constrained investors 'reaching for yield', and presents new systematic volatility measures for all bonds.
3 sharesSource ↗
Private Equity, Debt, and Infrastructure for Pension Investments
Large institutional asset owners are increasingly incorporating private market assets into their core investment strategies, moving away from viewing them as 'alternatives'.
5 sharesSource ↗
Total Return and Active Management of Option Portfolios
The total return concept for options and option portfolios can be used to assess the performance of an options portfolio, extending the total return concept from traditional investment portfolios.
2 sharesSource ↗
Ensembling ARIMAX Model for Investment Strategies
ARIMAX/ARIMAX-Garch models are ineffective for making buy or sell decisions for selected commodity baskets, as per a study on four Invesco ETF funds.
2 shares1 citation todaySource ↗
ETF Rebalancing & Hedge Fund Trades
Hedge funds are manipulating ETF rebalancing to their advantage, causing price distortions and forcing ETFs to make unfavorable trades.
587 sharesSource ↗
Sparse International Portfolio Optimization
A study shows that a regularized joint optimization approach for multicurrency asset allocation surpasses traditional strategies, enhancing portfolio performance and currency risk management.
2 sharesSource ↗
Risk Budgeting with Diversity Index
The article proposes a new risk diversification method based on a 2012 diversity index, arguing that equal budgeting can be inefficient when assets are correlated.
22 sharesSource ↗
Cross-Sectional Test for Missing Factors
The paper argues that traditional multifactor models like CAPM are incomplete, while the ZCAPM model seems to cover all factors and explains CAPM alphas over time.
41 sharesSource ↗
Explainable ML Models for Cost of Capital
The article introduces a machine learning model to evaluate the influence of financial and nonfinancial factors on a company's cost of capital, emphasizing the role of environmental performance and governance practices.
2 sharesSource ↗
CDS Trading and Credit Risk Reallocation
A study suggests that Credit Default Swaps (CDS) are mainly used for speculation, increasing overall default risks, rather than for hedging or arbitrage.
2 sharesSource ↗
Managerial Capital Gains Taxes and Risk
A study on the American Taxpayer Relief Act 2012 suggests that mutual fund managers with large co-investment stakes may prioritize their own tax interests, leading to poor fund performance.
2 sharesSource ↗
RePEc
Economics working papers from RePEc's NEP field reports.
16 items
Finance8
Comparing Cryptocurrency and Stock Market Volatility Forecasts
The article finds that HAR models are more accurate than GARÑH models in predicting the volatility of Bitcoin and E-mini S&P 500 futures.
26 sharesSource ↗
Spillovers of Return and Volatility in Stock Portfolios by Size
The study suggests that restricting fund managers to specific size categories could lead to suboptimal performance, based on an analysis of return and volatility spillovers among Saudi indices.
22 sharesSource ↗
Enhancing Short-term Futures Trading with Deep Learning Indicator Model
The study finds that using artificial intelligence to determine exact RSI indicators can help day traders achieve higher profits in short-term stock index prediction.
19 sharesSource ↗
High-Frequency Data in Finance
The research explores how market volatility and skewness risks affect stock returns, noting differences in information and pricing between call and put options.
16 sharesSource ↗
Sharpe Ratio and Mean-Variance Optimization
The article recognizes Harry Markowitz’s 1952 paper on Portfolio Selection as the basis of quantitative investment strategy.
19 sharesSource ↗
Post Analysis
The study reviews literature on the use of high-frequency data in finance, highlighting key journals, articles, and authors.
17 sharesSource ↗
Solving Trading Problems
The paper finds a strong correlation between the U.S. economic policy uncertainty index and the volatility of bond returns in emerging markets.
16 sharesSource ↗
Trading Framework
The article discusses the importance of counterfactuals, optimal trading oracles, and concludes with a final note.
15 sharesSource ↗
Machine Learning3
High-Frequency Arbitrage on Cross-Listed Stocks: Info Latency Effects
Info Latency Effects: The research proposes a new strategy for high-frequency arbitrage on cross-listed stocks, capitalizing on price deviations, and generating an annual net profit of about US$6 million.
28 sharesSource ↗
Geopolitical Risks & Stock Market Volatility: ML Insights
ML Insights: The study uses machine learning to predict US stock market volatility based on geopolitical risks, finding military actions significantly impact forecasts, which can yield financial benefits.
36 sharesSource ↗
Leveraging Return Prediction for Improved VaR Estimation
The article explores the use of Value at Risk (VaR) and machine learning for estimating potential portfolio losses and comparing different metrics for VaR estimation.
25 sharesSource ↗
Historical Trending5
Enhancing Reliability Estimation for Numeric Predictions: ML Approach
ML Approach: The article presents a machine learning method to enhance the accuracy of individual predictions in numerical predictive modeling, showing notable improvements in complex predictive scenarios.
20 sharesSource ↗
Herding Behavior in Islamic Bank Market: Gulf Region Evidence
Gulf Region Evidence: The study investigates herding behavior in Islamic bank equity markets under different conditions, revealing that herding is common in all Gulf countries regardless of market conditions, but unaffected by oil price fluctuations.
8 sharesSource ↗
Portfolio Decision Analysis: Friction and Decision Rules
Friction and Decision Rules: The research suggests that the traditional method of maximizing expected utility in portfolio decision analysis may not always be the best approach, highlighting the need for further studies on friction.
6 sharesSource ↗
Scoring Market Consensus Against Probability Forecasts
The paper proposes a new probability scoring rule that incentivizes forecasters to gather superior information and discourages them from following the crowd.
2 sharesSource ↗
Stochastic Control with Exit Time: Policy Gradient Learning
Policy Gradient Learning: The research shows that policy gradient methods for stochastic control with exit time outperform other techniques in share repurchase pricing and can adapt to realistic market conditions.
2 sharesSource ↗
Papers with code
Papers that shipped their code, from the Papers with Code feed (2023-25).
7 items
Trending4
Enhanced TTS using Neural Transducers
Neural HMMs are a novel technology that enhances sequence-to-sequence modelling in text-to-speech systems.
17,149 shares
Open LLMs for NLP Tasks
Large language models excel in natural language tasks with little instruction, lessening the requirement for comprehensive feature engineering.
1,934 shares
ALA with LLMs
Recent progress in large language models enables the development of autonomous language agents that can interact with humans and environments through natural language interfaces.
363 shares
Survey: LLMB Agents
LLMB Agents: The quest for artificial intelligence matching human intelligence continues, with AI agents viewed as a potential method to reach this objective.
112 shares
Rising3
Assessing Neural Network Representations with Data Diffusion
There has been a noticeable rise in DSMI in relation to the class label over time.
91 shares
projectnuwa LayoutNUWA Unveiling Hidden Layout Expertise
The field of graphic layout generation is growing, significantly affecting user engagement and the way information is perceived.
45 shares
sherdencooper GPTFUZZER Red Teaming LLMs
Even with less than ideal seed templates, fuzzer effectively attacks ChatGPT and Llama2 models, maintaining a high success rate.
40 shares
GitHub
Repositories the letter featured.
7 items
Finance4
Python Stock Prediction Examples
The article demonstrates the use of Python-based neural networks and machine learning for predicting stock market trends.
115 shares
Bayesian Econometrics Slides
The article shares lecture slides on Bayesian Vector Autoregressions from a University of Melbourne course.
2 shares
Automated Backtesting
The article explores the automation of backtesting investment portfolios using different datasets.
50 shares
Substrait: Data Transformation
Data Transformation: The article explores a cross-platform method for expressing data transformation, relational algebra, and standardized record expression.
827 shares
Trending3
OpenAI: Human Interaction Function Calls
Human Interaction Function Calls: OpenAI has launched a feature that allows for responses that mimic human interaction.
960 shares
Instagraph: Text/URL to Knowledge Graph Conversion
Text/URL to Knowledge Graph Conversion: The tool converts text or URL into a visual knowledge graph.
1,459 shares
Scalaz: Functional Programming in Scala
Functional Programming in Scala: The principles of functional programming in the Scala language are explored in the article.
4,628 shares
News
Industry news: funds, hiring, markets and regulation.
1 items
Quantitative1
China investigates quant strategies
Chinese regulators are investigating hedge funds and brokerages for their quantitative trading strategies amid criticism of sectors profiting from share price falls and market volatility.
7 shares
Podcasts
Episodes on markets, quant methods and economics.
8 items
Quantitative5
Liquidity in Pension Funds with Elizabeth Burton
Elizabeth Burton, a managing director at Goldman Sachs Asset Management, discusses her career and role in advising institutional clients on investment strategies in an interview with Bloomberg Radio host Barry Ritholtz.
14 shares
Mechanisms of the Federal Reserve Explored
Former Federal Reserve advisor Daniel DiMartino Booth and trader Joseph Wang discuss the Federal Reserve's impact on the bond market, credit spreads implications, and the potential economic effects of a rising dollar.
9 shares
Firm's Data Product Creation Process
David Sharratt, global head of data product commercialization at Standard Chartered, talks about the challenges of data monetization, including geographical boundaries and the importance of use cases.
8 shares
Demand Forecasting for Executives & Professionals
Authors of Demand Forecasting for Executives and Professionals discuss the role of forecasting in business decisions, the influence of AI and machine learning, and common obstacles in assessing forecast quality.
4 shares
Discerene: Long-Term Value Investing with a Contrarian Approach
Long-Term Value Investing with a Contrarian Approach: Soo Chuen Tan, Founder & President of Discerene Group, shares his investment philosophy, lessons learned from Seth Klarman at Baupost, and the ideal structure for an investment firm.
3 shares
Related3
Rising Emerging Market Equities
Kevin Daly of Goldman Sachs Research forecasts a substantial growth in emerging market capital markets in the future.
2 shares
Phil Suttle on US Recession and AI Impact
The podcast features Phil from Suttle Economics discussing potential recession triggers, his perspective on the Euroarea and UK, and other economic insights.
1 shares
Market Huddle with Pinecone Macro
The Market Huddle podcast features Chase Taylor discussing commodity charts including cotton, sugar, copper, cannabis, homebuilders, and bitcoin.
1 shares
Blogs
Posts from quant and economics blogs and newsletters.
7 items
Quantitative4
Range-Based Volatility Estimators Overview
The article explores the role of volatility estimation in finance, particularly range-based estimators using an asset's highest and lowest prices.
13 shares
Range-Based Volatility Estimators Usage Examples
The piece discusses the importance of volatility estimation in finance, especially in portfolio allocation, and the use of range-based estimators.
13 shares
Volatility Estimation Importance in Finance
The article emphasizes the importance of volatility estimation in finance, focusing on Parkinson's range-based volatility estimators.
13 shares
Parkinson's Volatility Estimator
The write-up highlights the significance of volatility estimation in finance, exploring range-based estimators based on an asset's price range.
13 shares
Related3
Eurozone Economy Under Scrutiny
Our recent publication examines the Eurozone economy's state as policy support decreases.
2 shares
Carbon Intensity in Two Sigma's Compute Environment
Two Sigma's Sustainability Science team is developing ways to precisely calculate our compute environment's carbon footprint, focusing on server-level power usage.
0 shares
Overnight Risk: The Unknown Unknown
The Unknown Unknown: The fear of what is unknown is more intense than the fear of what is known.
0 shares
X / Twitter
Posts from quant researchers on X.
7 items
Quantitative3
Short-Term Reversal Effect in Stock Returns Weakens
A recent study indicates that while the typical short-term reversal effect in stock returns has lessened, reversals adjusted for industry exposure and FamaFrench factors are still strong, especially for low volatility, low liquidity stocks without news.
3 shares
Optimized BlackLitterman Model Beats Classical Approaches
A new study introduces a version of the BlackLitterman model that uses machine learning to optimize the view generation and portfolio allocation processes, which has proven to be more effective than traditional methods when used on 14 liquid ETFs.
2 shares
Asset Management's Generative AI Models
A new study explores the application of Generative AI models in Asset Management.
1 shares
Miscellaneous4
Stocks Fall on Inflation Shocks
Article: Research shows stocks typically decline following positive inflation shocks, half due to reduced future real cashflows and half due to increased equity risk premium.
1 shares
LLMs vs Econometric CPI Forecasts
Article: The piece compares the effectiveness of LLMs and Econometric TimeSeries in predicting the Consumer Price Index, according to a St. Louis Fed paper.
0 shares
Option Market Manipulation on Triple Witching Day
Article: The piece explores the possibility of option markets being manipulated on triple-witching day, citing a related research paper.
0 shares
Linking Two Research Papers
Article: The article shares a link to an unspecified topic or research.
0 shares
Threads from r/quant, r/algotrading and friends.
4 items