Leveraging LLMs for Human Aversion
The TRIBE model simulates human-like decision-making in trading, showing that large language models can enhance client agency and reveal new market behaviors.
18 shares2 citations todaySource ↗
Quant LetterNo. 87
180 items across 9 sections, as sent to readers on 5 March 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
28 items
The TRIBE model simulates human-like decision-making in trading, showing that large language models can enhance client agency and reveal new market behaviors.
18 shares2 citations todaySource ↗
A review of deep learning in financial asset management identifies trends like explainable AI and deep reinforcement learning, suggesting deep learning can enhance portfolio performance and price forecasting.
18 shares3 citations todaySource ↗
A new volatility forecasting model, combining the heterogeneous autoregressive model with path-dependent volatility models, shows improved forecasting accuracy in the Chinese stock market.
16 shares1 citation todaySource ↗
A new class of short-rate models exhibiting a higher for longer phenomenon provides explicit pricing for zero-coupon bonds and interest rate derivatives, and outlines conditions for various endpoints.
14 sharesSource ↗
The Volterra Stein-Stein model with stochastic interest rates unifies various models while maintaining analytical tractability for pricing and hedging financial derivatives, capturing key empirical features for cap options.
14 shares3 citations todaySource ↗
A new method for predicting long-term electricity prices, which combines forecasts and extrapolates price series, has improved accuracy by 3% to 15% in German and Spanish power markets.
13 shares10 citations todaySource ↗
The article introduces signature perturbations as a way to explain the success of signature-based classification in commodities markets, with convenience yield volatility as a key factor.
12 sharesSource ↗
The study shows that AI ETFs and clean energy transmit risk, while AI tokens and green bonds receive risk, with diverse portfolios effectively reducing AI token investment risk.
11 sharesSource ↗
The paper proposes using reinforcement learning methods to manage stochastic trade flows, offering an alternative to traditional grid-based numerical PDE techniques.
11 shares2 citations todaySource ↗
A new method for estimating Value-at-Risk (VaR) and Expected Shortfall (ES) models allows for tail risk forecasting and can be applied to any data or model where the VaR and ES relationship remains constant.
11 sharesSource ↗
Research shows that zonal pricing boosts solar energy investments in Germany, while fixed pricing discourages it, and regional solar availability significantly influences rooftop solar panel investments.
15 shares2 citations todaySource ↗
A new theoretical model introduces an asset beta concept for nature, potentially enabling the conversion of natural resources into monetary terms to assist in resource allocation decisions.
14 sharesSource ↗
A study found that a 1% rise in working from home during the COVID-19 pandemic in the US resulted in a 1.8% decrease in daily average transportation emissions per person.
12 shares3 citations todaySource ↗
Research indicates Hungary's transition to low-carbon electricity is too slow to achieve climate neutrality by 2050 due to a 'lock-in' effect.
12 shares2 citations todaySource ↗
A new model with a unique variation-free parameterization of factor loadings shows adaptability and scalability in both small and large asset return environments.
11 shares1 citation todaySource ↗
A study on 19th-century Denmark reveals that railway expansion significantly boosted population growth and triggered institutional and cultural changes.
11 sharesSource ↗
A study on Chinese companies shows that employee health and education significantly affect productivity, but further health improvements may yield diminishing returns for highly educated individuals.
11 shares2 citations todaySource ↗
The article presents Agentic RAG, a new method for topic modeling with large language models, offering a more efficient and reliable alternative for AI-based qualitative research.
17 shares6 citations todaySource ↗
The study shows that artificial agents, powered by large language models, can speed up social contagion due to their lower adoption thresholds, potentially accelerating societal behavioral changes.
17 shares2 citations todaySource ↗
The research disputes the common belief that Rawlsian policies lower average social welfare, showing that under specific conditions, they can surpass utilitarian policies in the long term, highlighting the need for long-term planning in policy design.
15 shares3 citations todaySource ↗
The article introduces Seeded Poisson Factorization (SPF), a new topic modeling method that uses seed words to enhance interpretability and efficiency in large datasets.
13 shares3 citations todaySource ↗
The paper compares the effectiveness of deep learning methods like BERT, FinBERT, and ULMFiT in sentiment analysis of financial transcripts, offering insights for practical financial decision-making.
13 shares2 citations todaySource ↗
The article explores the impact of Google's update from manifest version 2 to 3 on ad blockers, concluding that the update does not significantly affect ad-blocking or anti-tracking capabilities.
13 sharesSource ↗
The study analyzes the effect of Google's shift from manifest version 2 to 3 on ad blockers, finding that the update does not notably diminish their ad and tracker blocking abilities.
13 sharesSource ↗
The Supra blockchain network introduces a mechanism that boosts market efficiency and liquidity by using idle network resources and exploiting arbitrage opportunities.
18 shares1 citation todaySource ↗
Cryptocurrency Masterminds: Perseus, a new detection system, has been created to identify and track the orchestrators of cryptocurrency fraud schemes, aiding regulators in preventing such activities.
16 shares5 citations todaySource ↗
A new method for Volume Weighted Average Price (VWAP) execution has been suggested, using a single neural network across multiple assets, providing a more scalable and effective solution than traditional asset-specific models.
11 shares1 citation todaySource ↗
The article discusses a model of investment in innovation, proposing that the ideal search for innovation should persist until success is reached, though there is a small possibility of never achieving it.
20 sharesSource ↗
Working papers in finance and economics from SSRN.
59 items
The article reviews different time series models used in finance, discussing their use in asset price prediction, risk management, and portfolio optimization, as well as their limitations.
14 sharesSource ↗
A new deep learning-based framework for financial stress testing is introduced, combining financial indicators to improve risk prediction accuracy and reduce financial risks.
31 shares15 citations todaySource ↗
The paper presents a framework that treats large language models as reinforcement learning agents in token space, offering theoretical insights for more effective language models.
81 sharesSource ↗
The study analyzes the performance of spot bitcoin ETFs in their first trading year, shedding light on the complexities of U.S. regulatory decisions.
32 sharesSource ↗
The article provides new insights into the factors affecting bond credit spreads in China, with a focus on wealth management products and central bank policies.
12 sharesSource ↗
The article discusses gaming bonds and specialized hedge funds as a new high-risk financial instrument with potential for significant profits.
18 sharesSource ↗
The paper introduces a method for analyzing the relationship between stock market volatility and output growth, using a bivariate Markov switching model on a selection of developed countries.
28 sharesSource ↗
Hedge funds perform better when their managers have a wider network of executive connections.
23 sharesSource ↗
SnowflakeDB's new framework enhances machine learning pipelines, effectively handling big data and scaling tasks.
5 sharesSource ↗
The Top10 South African Fine Wine Index can improve portfolio diversification and risk-adjusted returns, making fine wine a viable asset class.
10 sharesSource ↗
Investor flow shocks in prime money market funds can greatly affect commercial paper's primary market pricing and issuance.
30 sharesSource ↗
Improvements to the Physics-Informed Neural Networks (PINN) method optimize model performance by focusing on hyperparameter tuning.
19 sharesSource ↗
Capital risks significantly impact the financial performance of banks listed on the Bahrain Bourse.
8 shares1 citation todaySource ↗
A new portfolio selection model minimizes estimation errors and overdiversification, with an efficient algorithm developed for its solution.
16 sharesSource ↗
The article introduces a predictive network for corporate bond issuers using estimated volatilities in credit spread differences for better portfolio management.
229 sharesSource ↗
The paper discusses common time series models in finance, their uses, challenges, and limitations, and proposes areas for future research.
14 sharesSource ↗
The research investigates the ethical aspects of data governance models in companies, identifies bias sources, and proposes ways to minimize these biases.
43 sharesSource ↗
The study reveals a U-shaped correlation between corporate financial asset allocation and audit fees, influenced by various financial effects and constraints.
26 sharesSource ↗
The article presents a new method for classifying bond price risk using machine learning, based on financial metric fluctuations over a business cycle.
22 sharesSource ↗
The study delves into the ethical concerns of data governance frameworks in organizations, pinpoints bias origins, and recommends measures to lessen these biases.
37 sharesSource ↗
Tech and Policy: The paper suggests treating data as a rival good in many situations, taking into account privacy protection, statistical validity, and the risk of overuse leading to overfitting.
14 sharesSource ↗
Research using FinBERT language models in a RAG pipeline shows that market sentiment analysis can enhance decision-making processes when combined with other financial indicators, despite its limited power in predicting next-day stock prices.
32 sharesSource ↗
A new deep learning-based framework for financial stress testing improves risk prediction accuracy by integrating quantitative and qualitative financial indicators, significantly reducing training and testing loss.
31 shares15 citations todaySource ↗
The s1 model improves the efficiency and accuracy of Large Language Models (LLMs) by using a compact dataset of high-quality reasoning examples and an inference-time budget forcing mechanism.
286 sharesSource ↗
Research shows that an increase in wealth management products reduces bond credit spreads in China, mainly by reducing liquidity risk, and this impact is enhanced by loose monetary policy.
12 sharesSource ↗
A paper suggests viewing Large Language Models (LLMs) as reinforcement learning (RL) agents operating in token space, providing new theoretical insights and potential for more effective language models.
81 sharesSource ↗
A study on the performance of spot bitcoin ETFs during their first year of trading reveals complexities and inconsistencies in U.S. regulatory decision-making.
32 sharesSource ↗
Research using Alipay data shows that digital wealth management can improve financial inclusion and mitigate the impact of uncertainty shocks on consumption, particularly among residents with lower wealth and less access to conventional finance.
24 sharesSource ↗
A Chinese Financial Turbulence Index (FTI) developed using textual analysis and AI of news articles can negatively predict market returns, and a hedging framework incorporating firm characteristics related to financial resilience can effectively hedge against financial turbulence risk.
17 sharesSource ↗
The article introduces a new framework that merges sparse synthetic control and copula-based dependence modeling to enhance adaptability and risk management in pairs trading strategies.
123 sharesSource ↗
The authors suggest a structural default model for portfolio-wide valuation adjustments, using a deep BSDE approach to handle each layer sequentially, making the computation manageable.
75 sharesSource ↗
The paper explores the pricing and hedging of counterparty credit risk and funding when hedging the jump to default is impossible, using local risk-minimization to find the best strategy.
107 sharesSource ↗
The authors suggest a modified version of the Constant Product Market Maker (CPMM) to improve liquidity and maintain competitive transaction costs in trading of SME stocks.
57 sharesSource ↗
ADE Portfolio: The article introduces a new framework to exploit asset pricing anomalies without depending on traditional long-short portfolio construction, showing high efficiency in cross-sectional pricing.
59 sharesSource ↗
Econometrics ML: The paper reviews the shift from econometrics to machine learning in empirical asset pricing, suggesting a unified framework that combines machine learning while maintaining economic interpretability.
11 sharesSource ↗
The authors suggest a modified generalized smooth-transition (MGST) function to estimate pair-specific convergence risk in statistical arbitrage, showing higher cumulative return and Sharpe Ratio net of transaction costs.
23 sharesSource ↗
Nonbank financial institutions tend to sell domestic currency when portfolio returns are low, causing G10 currencies to depreciate against the USD.
48 sharesSource ↗
Despite volatility and regulatory risks, US state governments are contemplating investing in Bitcoin and other cryptocurrencies.
32 sharesSource ↗
Aggressive short selling by market makers in Korea's single-stock futures market has improved liquidity, reduced volatility, and increased price efficiency.
35 sharesSource ↗
Cognitive biases like overconfidence and anchoring cause systematic mispricing in financial markets, which can be factored into asset pricing models.
20 sharesSource ↗
In China, positive sentiment beta significantly predicts stock returns, while negative sentiment beta has a negligible effect.
24 sharesSource ↗
The net-zero alignment strength (NZAS) metric, based on corporate GHG emissions and reduction rate, can aid socially responsible investors in portfolio selection.
18 sharesSource ↗
Financial accounting-focused news articles result in higher trading volume and abnormal returns, particularly when stock prices are volatile and analyst forecasts vary.
53 sharesSource ↗
Highlighting fees on online investment platforms diverts attention from past performance graphs and increases focus on fees, leading to more investment in lower-fee funds.
52 sharesSource ↗
The article presents a new framework that merges sparse synthetic control and copula-based dependence modeling to enhance risk management in pairs trading strategies.
123 sharesSource ↗
The study indicates that firm embeddings, extracted from US corporate bond holdings, can offer more precise and timely data for fixed income markets than traditional credit ratings.
40 sharesSource ↗
The research investigates the correlation between liquidity and volatility in cryptocurrency markets, using a model to evaluate the effect of market volatility on liquidity.
35 sharesSource ↗
The paper introduces a structural default model for portfolio-wide valuation adjustments, utilizing an iterative deep BSDE method to manage the computational complexity of the issue.
75 sharesSource ↗
The study reveals that longer trade durations are associated with a lower chance of short-term reversals and a higher likelihood of momentum, with factors like institutional investors, lower market volatility, and positive sentiment boosting momentum predictability.
91 sharesSource ↗
The research uses local risk-minimization to determine the best strategy for pricing and hedging counterparty credit risk and funding in scenarios where hedging the jump to default is not possible.
107 sharesSource ↗
The article suggests a modified version of the Constant Product Market Maker (CPMM) from Decentralised Finance (DeFi) to improve liquidity and maintain competitive transaction costs in trading of SME stocks.
57 sharesSource ↗
The article introduces a new framework for capitalizing on asset pricing anomalies, which surpasses traditional long-short portfolio strategies by using all deciles and volatility timing for a balanced risk-return tradeoff.
59 sharesSource ↗
The article discusses how big data and machine learning have transformed empirical asset pricing, outlining the strengths and limitations of both traditional multifactor models and machine learning methods.
11 sharesSource ↗
The article suggests a modified generalized smooth-transition function to estimate pair-specific convergence risk in statistical arbitrage, which performs better than three benchmark arbitrage portfolios in terms of cumulative return and Sharpe Ratio.
23 sharesSource ↗
The article reveals that firms with large, persistent government spending contracts earn abnormal returns and gain market share, resulting in increased profitability and rising industry status.
231 sharesSource ↗
The article presents the BKMN model for financial institutions to conduct climate stress tests, connecting temperature change and CO2 prices to macro, sector, and financial market impacts.
116 sharesSource ↗
The article identifies four factors that provide robust return premia in the cross-section of U.S. corporate bonds, proposing a five-factor model that most robustly prices these bonds after considering transaction costs.
66 shares3 citations todaySource ↗
The article combines normalizing flows with traditional portfolio optimization methods to capture nonlinear asset relationships while ensuring scalability and effective risk management.
51 sharesSource ↗
The article investigates the relationship between currency-hedged investments of nonbank financial institutions, global return, and exchange rates, discovering that lower portfolio return prompts investors to sell domestic currency, causing the depreciation of G10 currencies against USD.
48 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
30 items
The rise of algorithmic trading and passive investing can cause issues during market downturns, but a new Automated Adaptive Trading System could help stabilize emerging markets in turbulent times.
27 sharesSource ↗
Machine learning has been used to pinpoint assets causing downward trends in the Pakistan Stock Exchange, suggesting a portfolio optimization plan for efficient asset allocation.
25 sharesSource ↗
Using expected shortfall as the risk measure in risk parity portfolio optimization can lessen sensitivity to volatility shocks, decrease portfolio turnover in market turmoil, and enhance risk-adjusted returns considering fat-tailed returns.
16 sharesSource ↗
The research finds that trading strategies based on the Sharpe Ratio are more profitable than the buy-and-hold strategy in global markets, supporting the Adaptive Market Hypothesis.
15 sharesSource ↗
The study introduces a new window analysis method for assessing decision-making units' efficiency, using the Whale Optimization Algorithm, and applies it to forex investment strategies and utility firms in the Ho Chi Minh City Stock Exchange.
11 sharesSource ↗
The paper uses a new data augmentation technique to study poverty in the Middle East and North Africa, specifically Lebanon, using alternative data sources when traditional income data is scarce or unavailable.
10 sharesSource ↗
The blockwise reduced modeling (BRM) method is a new approach for analyzing incomplete data, using ensemble models to reduce data imputation and improve predictive performance.
20 sharesSource ↗
The momentum-determined indicator-switching (N-MDIS) strategy uses machine learning to improve equity premium prediction accuracy, outperforming previous MDIS and N-MDIS strategies.
19 sharesSource ↗
A study shows that increased product market competition leads firms to adopt zero-leverage policies, particularly those with high earnings volatility, emphasizing the impact of earnings volatility on the relationship between competition and financial behavior.
18 sharesSource ↗
The research adapts Stochastic Gradient Boosting for Data Envelopment Analysis to estimate production possibility sets, reducing overfitting and satisfying shape constraints, as proven by simulations and a PISA example.
16 sharesSource ↗
The research reassesses the effect of news sentiment on stock return volatility, finding that both positive and negative firm-specific and macroeconomic news significantly impact intraday stock return volatility, with GPT-4 potentially outperforming RavenPack in classification accuracy.
16 sharesSource ↗
The study enhances the prediction performance of the expected goal model in football analytics by integrating data from various sources and using a supervised machine learning approach, resulting in significant improvements in sensitivity, F1 metrics, and AUC metric.
10 sharesSource ↗
Machine learning models are more effective than traditional methods in predicting Chinese corporate merger and acquisition activities.
28 sharesSource ↗
Two new deep learning frameworks have been proposed for estimating financial risk measures, which are more efficient than existing methods.
27 sharesSource ↗
Machine learning methods can accurately predict Chinese stock market volatility using the volatility of long-term treasury bond contracts.
24 sharesSource ↗
The article proposes a new algorithm and machine learning model to improve the efficiency and accuracy of the Lot Streaming and Scheduling Problem with stochastic product arrival times.
16 sharesSource ↗
The paper introduces a new machine learning technique for decomposing and modeling complex time series, providing a potential alternative to the Box-Jenkins method in financial modeling.
13 sharesSource ↗
The study uses machine learning to analyze the impact of a monetary policy frictions index on commercial banks' nonperforming loans, advocating for more transparency in monetary policy transmission.
12 sharesSource ↗
The research uses machine learning and quantile connectedness models to study the international housing market, emphasizing the significant influence of the US housing market and its interest rates.
10 sharesSource ↗
Machine Learning vs Deep Learning: The study reveals that deep learning methods, particularly the long short-term memory approach, are more effective than machine learning methods like the support vector machine in predicting oil prices, especially during crises.
31 sharesSource ↗
The article discusses a machine learning study that predicts the CBOE Volatility Index using weekly jobless claim data.
23 sharesSource ↗
The study reveals that traditional machine learning models outperform deep learning models in predicting Eurozone banking sector stock prices.
13 sharesSource ↗
The research indicates that AI capability directly affects firm performance, with a data-driven culture and AI infrastructure playing key roles.
5 sharesSource ↗
The study uses machine learning to analyze social media discussions on climate change, advocating for diverse policies and a comprehensive approach to achieve net-zero targets.
4 sharesSource ↗
The review examines the link between e-governance initiatives and citizen participation, identifying success factors and emphasizing the need for interdisciplinary research.
2 sharesSource ↗
The paper explores the use of artificial intelligence in improving resource management in cloud environments for better DevOps workflows.
2 sharesSource ↗
The article discusses the problem of dark patterns in retail investment and the potential of AI and behavioral sciences in enhancing regulation.
2 sharesSource ↗
The study profiles young informal workers in the EU27, aiming to understand the impact of Covid-19 on youth labor market informality.
2 sharesSource ↗
The paper suggests new research areas in understanding banks' performance, focusing on digital transformation, AI, and the effects of COVID-19.
1 sharesSource ↗
The study investigates the relevance of the Work Need Satisfaction Scale for online gig workers, proposing modifications to better suit online platform work.
1 sharesSource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
11 items
Time Series Library: The article introduces Merlion, a new open-source library for machine learning in time series analysis.
4,105 shares
Loyalty Training: The piece discusses the challenges in developing open-source models that are accessible and governed by the community.
3,071 shares
RLHF Framework: The article describes how traditional Reinforcement Learning (RL) can be represented as a dataflow with nodes and edges symbolizing neural network computations and data dependencies respectively.
840 shares
Markov LLM Scaling: The Atom of Thoughts (AoT) model is introduced, which breaks down each reasoning state transition into a dependency-based directed acyclic graph.
289 shares
ZeroShot TextToSpeech System: The article presents IndexTTS, a large language model-based text-to-speech system known for its natural sound and zero-shot voice cloning features.
226 shares
The first article explores the difficulties in creating a universal sparse attention that improves the speed and efficiency of different models.
181 shares
The second article demonstrates through experiments that data augmentation can significantly improve robustness.
142 shares
The third article conducts a thorough examination of how different depth normalization strategies impact pseudolabel distillation.
122 shares
Audiolanguage Models: AudioFLAN is a versatile audio language model capable of comprehension and generation tasks across different audio domains without needing specific training.
103 shares
Speech Interaction Framework: A proposed two-stage pretraining strategy aims to enhance audio modeling and preserve language understanding, avoiding intelligence loss during pretraining.
71 shares
Finetuning Effects: A study was carried out where a model was discreetly manipulated to generate insecure code unbeknownst to the user.
69 shares
Repositories the letter featured.
10 items
PrimoGPT Finance is a financial application that integrates reinforcement learning and natural language processing for improved functionality.
150 shares
Pure Mojo is used to develop a new machine learning framework from the ground up.
443 shares
A new quantitative finance framework is introduced, leveraging the capabilities of Python.
766 shares
The official repository for TLOB, a unique transformer model using dual attention for stock price trend prediction with limit order book data, is unveiled.
5 shares
PIXIU is an open-source platform that introduces the first large financial language models, offering tuning data and evaluation benchmarks to enhance financial AI development.
647 shares
The article explores how NVIDIA GPUs or Apple Silicon can enhance the performance of large language model inference.
1,426 shares
The piece presents a new model designed to generate conversational speech.
2,539 shares
The article informs about the official Python SDK for Model Context Protocol servers and clients.
2,265 shares
The piece describes DeepSeek R1, an AI research assistant that integrates search engines, web scraping, and large language models.
1,148 shares
The article provides a beginner's guide to using Phi Models, Microsoft's open-source AI models.
2,854 shares
Industry news: funds, hiring, markets and regulation.
20 items
Anders Holst, ex-partner at Lynx Asset Management, has been named Senior Portfolio Manager at Tidan Capital.
9 shares
A Citco report suggests that private credit has become a lucrative investment sector, with innovative firms partnering with specialist fund administrators to overcome entry barriers.
6 shares
Alex Abagian, formerly of Morgan Stanley, is set to join Ghisallo Capital Management in a senior position.
5 shares
Sylebra Capital, under Dan Gibson, saw a significant downturn in 2024, ending the year with a 7.8% gain after an initial 27.2% surge by April.
5 shares
Bloomberg and General Index have broadened their partnership to offer Bloomberg Terminal users enhanced access to voluntary carbon market data.
4 shares
The MFA and AIMA, representing major hedge funds, are opposing global regulators' plans to limit borrowing for trades, arguing that it is not the cause of recent market instability.
4 shares
Cisu Capital, a London-based hedge fund, has successfully launched a commingled fund with a large endowment, led by former Elliott Management portfolio manager Mark Wills.
4 shares
Abu Dhabi Global Market, the city's financial hub, experienced a 32% increase in company registrations last year, largely due to an influx of hedge funds and investment firms.
4 shares
Don Wilson's trading firm has announced the appointment of a new operations chief.
3 shares
BNP Paribas' THEAM Quant fund range has launched a nuclear energy UCITS fund, citing increasing global electricity demand and energy security concerns as long-term investment opportunities.
3 shares
Engaged Capital, an activist hedge fund with an 8.6% stake in Portillo’s, is advocating for significant changes at the fast-casual chain.
3 shares
Dubai is setting up a dedicated workspace at the Dublin International Finance Centre to attract hedge fund startups seeking to establish a foothold in the region.
3 shares
Digital asset investment products saw $508m in outflows last week due to uncertainties over trade tariffs, inflation, and monetary policy.
2 shares
A growing number of investors, including Mount Lucas Management, are betting against the US dollar due to fears of a slowing US economy and potential trade war repercussions.
2 shares
The article explores the advantages and disadvantages of pursuing a PhD.
2 shares
CME Group and DTCC aim to broaden their cross-margining agreement by December 2025.
2 shares
Despite past failures, Nicholas Maounis' Verition Fund Management has expanded from 1bn to nearly 12bn since 2019.
2 shares
SocGen has recruited a new data specialist from Deutsche Bank.
2 shares
GResearch is looking to expand its operations in America.
1 shares
An experienced high-frequency trader recommends not using node-based containers.
1 shares
Episodes on markets, quant methods and economics.
10 items
Alex Shahidi encourages investors to rethink traditional asset allocation and diversification strategies, highlighting risk parity and innovative ETFs.
15 shares
Mark Longo and Matt Amberson discuss the rise in long straddles, macro volatility effects, and record-breaking options trading volumes.
14 shares
Peter Oppenheimer explains how changes in macroeconomic factors, geopolitics, and social attitudes influence secular super cycles and investor returns.
11 shares
Jonny Goulden and Saad Siddiqui discuss the impact of recent market developments on the EM fixed income asset class in a 2025 podcast.
9 shares
Howard Chan advocates for the use of covered call strategies to generate extra returns and manage risks, especially for cash flow-focused investors.
8 shares
Capstone's CEO, Paul Britton, talks about the changes in the derivatives market, risk management strategies, and the impact of a low VIX in a volatile economic environment.
7 shares
A podcast discusses Yale University's successful endowment investment strategies and introduces the Endowment ETF, aimed at providing access to advanced investment strategies to all.
7 shares
Jay Barry and Meera Chandan analyze the recent US economic moderation, upcoming tariff announcements, and their potential effects on US rates and the dollar.
5 shares
Francis Diamond and Phoebe White share their perspectives on global inflation markets following a significant narrowing of breakeven over the past month.
5 shares
Ben Bennett discusses the possible effects of Germany's parliamentary election on its debt brake, the surge in Chinese tech stocks, and the influence of political polarization on US inflation predictions.
3 shares
Posts from quant researchers on X.
6 items
Independent trader Scott Phillips shares insights on navigating the complexities of crypto markets.
1 shares
A new study explores economic regimes for factor timing, using historical performance to inform investment positions.
0 shares
The article highlights the crucial need to comprehend the connection between Artificial General Intelligence and the US Government.
0 shares
The recent investment research explores areas like commodity return predictions, stock return predictability, factor investing, volatility forecasting, and various related blogs, repositories, and podcasts.
0 shares
The article emphasizes that robustness is a characteristic of causality, rather than complexity or simplicity.
0 shares
Threads from r/quant, r/algotrading and friends.
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