Quant LetterNo. 89
182 items across 9 sections, as sent to readers on 20 March 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
26 items
The article explores conditions for no-arbitrage in one-dimensional diffusion markets, highlighting unexpected outcomes like the absence of unlimited profit with limited risk under certain conditions.
20 shares2 citations todaySource ↗
The research simplifies the dual problem in the symmetric case under the dispersion assumption, aiming to find a reliable, no-arbitrage limit on the price of a Bermudan option with two potential exercise dates.
19 sharesSource ↗
The paper introduces a 'deep hedging' approach using machine learning to develop hedging strategies in power markets, specifically for Green Power Purchase Agreements, which are subject to price and weather risks.
17 shares1 citation todaySource ↗
The study presents the two-factor Quintic Ornstein-Uhlenbeck model, showing its effectiveness in capturing the volatility surfaces of SPX and VIX and aligning with the skew-stickiness ratio across different maturities.
15 sharesSource ↗
The SVSDU, a new financial model, is introduced to track winning and losing streaks in financial markets, using a deep neural network to solve the related complex equation.
13 sharesSource ↗
The research investigates the use of hybrid quantum-classical methods for predicting financial trends, introducing a Quantum Neural Network (QNN) regressor and two hybrid optimization strategies.
13 shares34 citations todaySource ↗
A new method for portfolio optimization is presented, utilizing hierarchical graph structures and the Schur complement method to decrease computational complexity while maintaining full covariance data.
12 sharesSource ↗
The article offers a detailed overview of derivative pricing adjustments, including XVA, within an Ito SDE/parabolic PDE framework, and explores certain meta-adjustments beyond XVA.
12 shares1 citation todaySource ↗
The study introduces a new model that applies machine learning for regime modeling in tactical asset allocation, showing significant enhancements in portfolio performance.
11 shares3 citations todaySource ↗
The research finds that the GLS estimator remains reliable in multivariate regression even with heteroskedastic and autocorrelated errors.
16 shares2 citations todaySource ↗
The study reveals that extreme temperatures significantly decrease the asset value of businesses, with state-owned and foreign-funded firms being more resilient.
15 shares1 citation todaySource ↗
Extreme temperatures negatively affect business asset values, but state-owned and foreign-funded firms are less impacted due to their resources and efficiency, according to the study.
15 shares1 citation todaySource ↗
The study finds that Deep Reinforcement Learning algorithms are more effective in identifying collusion risks in pricing strategies, performing better than Tabular Q-learning.
15 shares6 citations todaySource ↗
Research shows environmental liability insurance can lower industrial carbon emissions, especially in developed industrial regions.
14 sharesSource ↗
The same study confirms that environmental liability insurance can significantly cut down industrial carbon emissions in industrially advanced areas.
14 sharesSource ↗
Brazilian study reveals police blitzes lead to a 35% drop in violent crime, with effects lasting 2-3 days post-blitz.
14 shares2 citations todaySource ↗
Adoption of artificial intelligence boosts trade volumes in Southeast Asia, especially in areas with advanced tech infrastructure and supportive regulations.
14 shares2 citations todaySource ↗
The article presents a new method for predicting financial asset volatility using multiple sources of data, which performs better than models using only target data or combined source and target data.
16 sharesSource ↗
The paper introduces a new method for approximating complex mathematical equations, which proves to be more reliable than the standard method, even under challenging conditions.
15 shares6 citations todaySource ↗
The study presents an improved version of the Light Graph Convolutional Network that learns over time, enhancing its performance in time-sensitive applications, especially in recommending financial products.
13 shares2 citations todaySource ↗
The emergence of Artificial General Intelligence (AGI) could disrupt economic and political structures, necessitating a new economic framework to ensure fair distribution of AGI-driven wealth.
16 shares1 citation todaySource ↗
Solo Ethereum stakers are more affected by changes in staking rewards than those using centralized exchanges, implying that reducing issuance could favor centralized entities.
11 shares5 citations todaySource ↗
Research on vote delegation in Decentralized Autonomous Organizations (DAOs) indicates that those with fewer votes and ties to venture capital firm a16z receive more vote delegations, suggesting reputation-based governance in DAOs.
11 shares4 citations todaySource ↗
A new econophysics model unifies several empirical laws, including the square-root law of price impact, and shows that price dynamics remain diffusive under this law, with volatility having a long memory.
248 shares3 citations todaySource ↗
A deep learning framework with methods for adjusting label imbalance has been effectively used to predict high-frequency returns in the Chinese futures market.
20 sharesSource ↗
Research on Germany's 2023 Heating Law found that providing detailed information about the policy didn't significantly influence adoption decisions or policy support, indicating that opposition to climate policy is due to fundamental preference differences, not information gaps.
16 shares1 citation todaySource ↗
Working papers in finance and economics from SSRN.
60 items
Research indicates a long-term link between Bitcoin prices and the MSCI World Index, suggesting Bitcoin can boost global stock portfolio performance.
5 sharesSource ↗
A machine learning model is introduced in a paper that enhances tactical asset allocation by predicting future regimes and optimizing portfolio distributions.
3 sharesSource ↗
A data-driven method for pricing blockchain transaction fee derivatives is proposed in a study, offering better fee volatility capture than other models.
4 sharesSource ↗
ViTSGMM, an image recognition network, is presented in a paper, improving performance on limited labeled data and addressing a data leakage issue in the STL10 dataset.
7 sharesSource ↗
A study reveals that liquidity constraints and inventory dynamics impact monetary policy transmission, with firms having tighter liquidity constraints adjusting their inventory-to-sales ratio less.
3 sharesSource ↗
Research shows that Quantum Machine Learning provides better financial forecasting accuracy and cybersecurity resilience than traditional models.
2 sharesSource ↗
A new methodology for financial sentiment analysis using large language models is proposed in a study, with the GPT-3-based OPT model outperforming others in predicting stock market returns.
2 sharesSource ↗
The article proposes a solution that uses optimization and machine learning to fix disrupted airline crew schedules, considering aircraft recovery plans and passenger disruption costs.
3 sharesSource ↗
The research uses transformations to create a new set of eigenstates for the Hopfield Hamiltonian, using the direct product of two types of elementary excitations' Fock states.
4 sharesSource ↗
The study uses a data analytics framework and machine learning to identify the best cricket players from the T20 World Cup 2022, improving decision-making in cricket analytics.
2 shares3 citations todaySource ↗
The research develops predictive solutions using machine learning to forecast electricity prices, focusing on affordability and the influence of economic policies.
2 shares2 citations todaySource ↗
The study finds that investor uncertainty overreaction is more pronounced in put options and during economic recessions in intraindustry information diffusion processes.
2 sharesSource ↗
The paper reveals that the chairman’s alumni network can increase financial leverage and contribute to firm value in China.
2 sharesSource ↗
The research shows that building height affects the natural frequency in predicting buildings' dynamic properties using machine learning, with taller buildings having a lower frequency.
2 sharesSource ↗
The study suggests that combining charitable remainder unitrusts with tax-aware strategies can help investors diversify low-basis stock and increase after-tax wealth, integrating philanthropy and investment management.
3 sharesSource ↗
The article discusses how the growth of large tech stocks can affect smart beta factor indices, but these effects can be lessened with diversified strategies and risk control.
228 sharesSource ↗
The piece examines the intricate relationship between inflation and the value of gold and treasury bonds, influenced by factors such as market sentiment and monetary policy.
57 sharesSource ↗
The article points out common errors in using Pearson's correlation in risk management, offering counterexamples and R code for clarity.
81 sharesSource ↗
The paper suggests an event-driven Limit Order Book model using a Neural Hawkes process to understand the dynamic relationships in financial markets.
26 sharesSource ↗
The article introduces a new method to calculate bid-ask prices of European knock-in barrier options, taking into account market liquidity.
17 sharesSource ↗
The study investigates the role of trade-credit default in the transmission of macro shocks, introducing two new mechanisms - a markup effect and an insurance effect.
20 sharesSource ↗
The paper presents a method that combines semiparametric partially additive time series models with technical indicators to enhance the prediction of stock returns.
26 sharesSource ↗
A study using machine learning reveals that corruption greatly hampers innovation and economic growth by reducing profits and devaluing patents.
13 sharesSource ↗
A new study suggests using a Graph Neural Network model to detect fake reviews on ecommerce platforms, improving detection accuracy by about 10%.
42 sharesSource ↗
Using individual accounting earnings from corporate financial reports can provide more accurate GDP forecasts, according to a new micro-forecasting approach.
22 shares1 citation todaySource ↗
President Trump's reciprocal tariffs policy could disrupt India's export sectors, increase consumer costs, and affect financial markets, potentially harming US-India trade relations.
51 sharesSource ↗
A study by Li, Tibay, and Wang suggests that investor flows in prime money market funds can significantly impact the pricing and issuance in the primary markets for commercial paper.
30 sharesSource ↗
Traditional load balancing methods have limitations in adjusting to fluctuating workloads and unexpected system failures, affecting performance in real-time financial analytics.
15 sharesSource ↗
AI roles demand more complementary skills like resilience, agility, and analytical thinking, which command a significant wage premium, as per an analysis of 12 million US online job vacancies.
97 sharesSource ↗
A new model links two types of bubbles to an equity's risk premium, showing that both bubbles are significant and crucial in understanding equity risk premium.
27 sharesSource ↗
Investment funds' rise in the corporate bond market has led to more index-driven bond trading, improving liquidity during index closing times.
3 sharesSource ↗
XTREND, a proposed cross-asset trend factor, uses machine learning to predict corporate bond returns using equity market data, showing resilience in various market conditions.
4 sharesSource ↗
The Capital Asset Pricing Model (CAPM) is being challenged, with alternative models suggested for emerging economies and smaller companies to enhance financial market valuation and risk investments.
3 sharesSource ↗
The Wealth Attraction Law posits that wealth acquisition is not just through effort or capital but also personal ability, scarcity, and social recognition, as shown by successful entrepreneurs' case studies.
3 sharesSource ↗
Hedge fund returns are strongly influenced by the covariation between fund returns and equity capital ratio shocks of key financial intermediaries, with high-exposure portfolios outperforming low-exposure ones.
3 sharesSource ↗
The gain of capital concept, accounting for biases in forecasting, investor perceptions, and firm characteristics, is introduced to enhance traditional discounted cash flow models and better determine firm valuations.
3 sharesSource ↗
The Alaali WACC model refines the traditional Weighted Average Cost of Capital by including firm-specific risk factors, industry leverage constraints, and macroeconomic volatility adjustments, offering a more accurate approach to corporate financial planning.
2 sharesSource ↗
The LASSO method effectively predicts European sovereign bond market returns, except for German bonds.
3 sharesSource ↗
Violent conflicts reduce cross-border lending but increase financing for military and dual-use industries.
4 sharesSource ↗
Stock indices with maximal sample selection provide more accurate future economic predictions than randomly selected stocks.
3 sharesSource ↗
The ACCM offers a dynamic, multifactor approach to estimating capital costs, improving on traditional models.
2 sharesSource ↗
A credit market competition model suggests that Big Data screening can reduce bank profits and increase consumer surplus.
2 sharesSource ↗
Inflation and exchange rate fluctuations significantly affect gold prices and electricity rates, while geopolitical risks have a minor direct impact.
3 sharesSource ↗
The paper explores the challenges and potential solutions for implementing 24-hour trading on major exchanges.
2 sharesSource ↗
The paper examines methods for estimating the discount rate for an income approach to value, highlighting the usefulness of asset pricing models.
2 sharesSource ↗
Companies using anti-short selling language in their filings are more likely to have insider sales, which often precede stock price drops and future accounting restatements.
107 sharesSource ↗
Incorporating machine learning into empirical asset pricing can enhance understanding of financial markets and improve predictive performance.
11 sharesSource ↗
Companies frequently awarded government contracts experience large abnormal returns and steady market share growth, leading to increased profitability and industry prominence.
231 sharesSource ↗
Uniswap v4 protocol's new feature, a hook, allows for more customized liquidity pool designs but also imposes certain implementation constraints.
90 sharesSource ↗
A proposed bill might permit stablecoins to be offered without federal deposit insurance protections, potentially heightening the risk of systemic crises during a stablecoin run.
184 sharesSource ↗
The new Corporate Deforestation Exposure metric shows that companies with high deforestation risk significantly underperform and suffer negative returns after the EU Deforestation Regulation agreement.
60 sharesSource ↗
Banks demand lower haircuts from hedge funds with more bargaining power in secured lending, potentially increasing the risk of insufficient haircuts based on standard value-at-risk models.
17 sharesSource ↗
The 2025 Bybit hack highlights the need for better security measures in the cryptocurrency industry due to ongoing vulnerabilities.
46 sharesSource ↗
Eye-tracking technology study suggests that highlighting investment fees can shift investor focus from past performance to lower-fee funds.
52 sharesSource ↗
A new evaluation method shows that many factor models fail to consistently price their factors, except for the Fama-French 5-factor model.
21 sharesSource ↗
Spanned factors, previously considered redundant, are found to be significant in explaining equity risk premiums, challenging the prevailing view.
20 sharesSource ↗
Interruptions in international information flow can harm domestic market liquidity and fairness, making stocks more prone to manipulative trading.
11 sharesSource ↗
The emergence of meme coins poses risks such as market manipulation and regulatory arbitrage, and may be used for financial exploitation without stricter regulation.
16 sharesSource ↗
The 2025 Bybit hack has led to increased scrutiny of cryptocurrency platforms, especially DeFi projects, due to governance and structural risks.
26 sharesSource ↗
A reinforcement learning model for asset allocation surpasses both Modern Portfolio Theory and an equally-weighted portfolio in terms of total return and Sharpe ratio.
2 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
30 items
The rise of algorithmic trading and passive investing has caused issues during market downturns like the COVID-19 pandemic and Russia-Ukraine conflict, but a new Automated Adaptive Trading System could stabilize emerging markets in such times.
27 sharesSource ↗
Machine learning has been used to pinpoint the assets causing downward trends in the Pakistan Stock Exchange, with a proposed scheme aiming to optimally allocate these assets in a portfolio.
25 sharesSource ↗
Risk parity portfolio optimization using expected shortfall as a risk measure is less affected by volatility shocks when considering fat-tailed returns, potentially improving risk-adjusted returns and reducing drawdowns during market stress.
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 method for assessing decision-making units' efficiency over time, 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 introduced for analyzing incomplete data sets, showing improved predictive performance for both linear and nonlinear models.
20 sharesSource ↗
A new machine learning strategy, momentum-determined indicator-switching (N-MDIS), is proposed for better equity premium prediction, outperforming existing strategies.
19 sharesSource ↗
The study suggests that firms are more likely to adopt zero-leverage policies as product market competition increases, especially those with higher earnings volatility.
18 sharesSource ↗
The impact of both negative and positive news sentiment on stock return volatility is reevaluated, showing significant effects on intraday stock return volatility.
16 sharesSource ↗
A version of Stochastic Gradient Boosting is proposed for estimating production possibility sets in Data Envelopment Analysis (DEA), reducing overfitting and showing competitive performance.
16 sharesSource ↗
A study found that machine learning models are more effective than traditional methods in predicting Chinese corporate merger and acquisition activities using 60 variables.
28 sharesSource ↗
New probabilistic deep learning frameworks have been proposed for estimating financial risk measures, outperforming existing methods and aiding in more effective capital allocation.
27 sharesSource ↗
Machine learning methods can enhance the prediction accuracy of Chinese stock market volatility using the volatility of long-term treasury bond contracts, especially those with a 10-year maturity.
24 sharesSource ↗
The article proposes a new algorithm and machine learning model to enhance efficiency and accuracy in the Lot Streaming and Scheduling Problem (LSSP) with unpredictable product arrival times.
16 sharesSource ↗
The paper introduces a new machine learning technique for decomposing and analyzing 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 global influence of the US housing market and its interest rates, emphasizing their significant impact on international housing market spillovers.
10 sharesSource ↗
Machine Learning vs. Deep Learning: Research shows deep learning methods outperform traditional machine learning in predicting oil prices, especially during crises.
31 sharesSource ↗
The newly introduced MFF-CPPM model in China has demonstrated higher accuracy and flexibility in predicting carbon trading prices compared to current models.
10 sharesSource ↗
The article discusses a study that uses machine learning to predict the CBOE Volatility Index, highlighting weekly jobless claim data as a significant factor.
23 sharesSource ↗
The paper concludes that traditional machine learning models outperform deep learning models in predicting Eurozone banking sector stock prices.
13 sharesSource ↗
The study indicates that AI capability directly affects firm performance, with a data-driven culture and AI infrastructure playing key roles.
5 sharesSource ↗
The research stresses the need for communication and a comprehensive approach to address climate change, using machine learning to analyze climate change discussions on social media.
4 sharesSource ↗
The article investigates the issue of dark patterns in retail investment, focusing on the use of behavioral sciences and AI to improve regulation and safeguard investors.
2 sharesSource ↗
The study profiles young informal workers in the EU27 pre-pandemic, aiming to inform future research on Covid-19's impact on youth labor market informality.
2 sharesSource ↗
The paper discusses how artificial intelligence can improve resource management in cloud environments, boosting DevOps workflows' performance and efficiency.
2 sharesSource ↗
The review investigates the link between e-governance initiatives and citizen participation, highlighting e-governance evolution and knowledge gaps, especially in terms of sustainability and impact.
2 sharesSource ↗
The paper analyzes literature on factors affecting banks' performance, suggesting new research areas, particularly around digital transformation, artificial intelligence, and FinTechs.
1 sharesSource ↗
The study explores the Work Need Satisfaction Scale's factor structure among online gig workers, indicating a need to modify the scale to better reflect online work nuances and inform interventions and platform designs.
1 sharesSource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
13 items
The article presents Attentive Reasoning Queries (ARQs), a new method that improves instruction-following in Large Language Models through the use of specific reasoning blueprints.
1,843 shares
The article highlights the need for large language models to effectively gather external knowledge and up-to-date information for better reasoning and text generation.
1,086 shares
The article explores the difficulties in enhancing reasoning in Large Multimodal Models due to the intricate relationship between visual perception and logical reasoning, particularly in compact 3B-parameter structures.
532 shares
The LightR1 series proves the efficiency of training longCOT models from scratch, showcasing excellence in SFT data and releasing top-notch models from RL.
441 shares
Recent progress in genomic language models underscores their capability in decoding DNA sequences.
372 shares
A novel technique is presented for creating neural fields, enabling points to be queried with an adjustable Gaussian PSF, guaranteeing accurate antialiasing at any chosen output resolution.
301 shares
Diffusion language models offer advantages such as parallelized generation and controllability, but face challenges with likelihood modeling and are limited to fixed-length generation.
298 shares
The complexity of Large Language Models (LLMs) and lack of effective visualization tools make their reasoning processes hard to analyze.
280 shares
Algorithm Design Platform: LLM4AD is a newly developed Python platform specifically designed for algorithm design using large language models.
250 shares
The world's first chatbot's entire stack, compatible with Unix-like operating systems, is now open source and was developed on the first timesharing system.
220 shares
Reinforcement learning has been shown to improve the reasoning abilities of large language models and is increasingly used in visual multimodal tasks.
143 shares
The updated model architecture and training recipe provide enhanced training stability and per-token efficiency.
138 shares
Reduce Context Memory: For Whisper models and similar encoder-decoder transformers, slim attention reduces context memory by 8x, accelerating token generation by 5x for a batch size of 64.
110 shares
Repositories the letter featured.
10 items
A new ETL framework has been created to index data for AI systems like RAG, with features such as real-time updates and custom logic support.
288 shares
The OrderBook Heatmap project uses live data from the Binance WS API to visualize the limit order book and time sales log, but needs more development for all market conditions.
414 shares
Researchagent LLMs can be trained independently on custom data using reinforcement learning and self-verification techniques.
430 shares
A beginner's guide to quantitative investment has been compiled, including an open-source tutorial on multi-factor stock quantitative framework.
484 shares
Trading automation scripts are being planned for release in the year 2025.
9 shares
The article emphasizes the need for proper documentation in the development of general artificial intelligence.
23,974 shares
The piece introduces Pydoll, a Python-supporting library for automating chromium-based browsers and web scraping.
2,849 shares
The article previews a discussion on the VGGT Visual Geometry Grounded Transformer at the upcoming CVPR 2025 conference.
1,905 shares
The article provides a review of The Startup CTO's Handbook, a guide for software engineering team leaders on leadership, management, and technical aspects.
12,828 shares
The piece highlights an AI agent that can manage engineering tasks from beginning to end, integrating with developers' tools and refining until successful outcomes are reached.
1,822 shares
Industry news: funds, hiring, markets and regulation.
20 items
BizTech Magazine explores the debate on the effectiveness of machine learning versus human analysts in quantitative strategies.
10 shares
Boundary Creek Advisors, a New York hedge fund, returns part of its capital to investors following three years of losses, according to Bloomberg.
8 shares
Russian President Putin allows US hedge fund 683 Capital Partners to buy Russian corporate securities from select foreign investors, a rare move amid geopolitical tensions, reports Reuters.
5 shares
FalconX executes the first block trade of CME Group's Solana futures product with StoneX, marking a milestone in cryptocurrency derivatives trading.
5 shares
Winton, a London-based quant hedge fund, launches a new fund combining systematic trend-following and passive equity exposure, reports CityWire.
5 shares
Richard Perry, a veteran hedge fund manager, is rejoining the industry as a partner at Olympus Peak Management, a distressed credit specialist firm, after closing Perry Capital nearly ten years ago.
4 shares
Polymer Capital Management, a Hong Kong-based hedge fund with $4bn in assets, plans to launch two Japan-focused funds this year to cater to increasing investor demand.
4 shares
The recent market downturn that pushed the S&P 500 into correction territory was not due to hedge funds exiting equity positions, as per a Barclays client note cited by MarketWatch.
4 shares
Hedge fund analysis firm HFR has launched an expanded strategy classification system for hedge funds and alternative investment products in the cryptocurrency and blockchain sector, featuring 11 specialised substrategies.
4 shares
Regents Gate Capital, co-founded by Joshua White, Yi-Sung Y, and Dane Vrabac, has incorporated artificial intelligence into a traditional market-neutral approach, offering a unique investment proposition in the hedge fund industry.
3 shares
Hedge funds have potentially earned $16.2bn from Tesla's 50% stock price drop in the past three months.
3 shares
Digital asset investment products saw a fifth week of outflows, totaling $1.7bn and bringing the total to $6.4bn.
3 shares
TT International has launched the TT Credit Opportunities Strategy on its Irish UCITS platform after a merger from a Luxembourg UCITS.
3 shares
Rio Tinto has asked shareholders to reject Palliser Capital's proposal to review its listings, maintaining its commitment to a dual-listed structure.
2 shares
The number of hedge funds in Dubai increased by 50% in 2024, with 75 funds now based in the city.
2 shares
Bridgewater Associates' Pure Alpha II fund has grown by 11.3% this year, attributed to market instability from Trump's trade policies.
2 shares
Participation in quant competitions could lead to profitable side jobs or internships at Jane Street.
2 shares
UBS Group AG is closing its outsourced trading desk, a major Wall Street entity, to refocus its global markets strategy.
2 shares
Robeco Active Quant is targeting predictable outcomes in institutional investing.
2 shares
Court documents show FTX liquidated $1.53bn of Three Arrows Capital's assets two weeks before its 2022 collapse, contradicting claims that market conditions caused the failure.
2 shares
Episodes on markets, quant methods and economics.
10 items
Apple data scientist Rami Krispin shares his experiences in forecasting and data science, his contributions to the field, and the future of time series forecasting in a podcast.
12 shares
In a March 2025 podcast, Tom Liu, Founder of Ideate Capital, talks about the increasing use of alternative data in the corporate sector and its growing relationship with AI.
11 shares
Brian Cullinan, a consultant at Capital Markets Recruitment, offers advice on creating an effective resume for quant finance professionals in a webinar.
9 shares
Meb Faber, founder of Cambria Investment Management, discusses the current state of the US stock market and introduces Cambria's endowment-style ETF E&DW in a podcast.
8 shares
In a March 2025 podcast, Srini Ramaswamy and Ipek Ozil discuss the latest trends in US rates markets.
7 shares
Justin Wang Ngai Yeung explores how network science and machine learning can help law enforcement identify key figures in criminal organizations and improve intervention strategies.
7 shares
Lotfi Karoui discusses the increasing yield in corporate bonds and its impact on the economic outlook and global credit market opportunities.
6 shares
Jay Hatfield shares income-focused investing strategies that can endure economic uncertainty, challenges conventional wisdom on tariffs, and predicts a drop in the 10-year Treasury.
6 shares
Thanos, of ABP Invest, shares his career experiences and insights on the Russia-Ukraine conflict, Trump vs EU, and US-China relations.
5 shares
Kevin and Peter Haynes discuss the changing landscape of index rebalancing and its effects on hedge funds, including significant losses due to prepositioning before index events.
5 shares
Posts from quant researchers on X.
7 items
Recent investment research focuses on areas including cryptocurrency, overnight stock returns, factor exposures, quantile regressions, and the impact of macro regimes on asset allocation.
2 shares
Winton has introduced a new UCITS product, MSCI World Trend, with a standard fee of 0.8.
2 shares
Trend following and commodities are the most effective hedges against inflation, according to recent surveys.
2 shares
The ReSolve team has published new research comparing multiasset carry in Liquid and Extended trading universes.
1 shares
Threads from r/quant, r/algotrading and friends.
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