Liquidity Spread Estimation
The article introduces a model that uses option theory to calculate liquidity spreads for corporate bonds, focusing on Italy's debt, and offers a method for pricing illiquid bonds.
7 sharesSource ↗
Quant LetterNo. 83
181 items across 10 sections, as sent to readers on 23 January 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
28 items
The article introduces a model that uses option theory to calculate liquidity spreads for corporate bonds, focusing on Italy's debt, and offers a method for pricing illiquid bonds.
7 sharesSource ↗
The research proposes an effective rebate policy in auction markets, demonstrating that ideal transaction fees and rebate structures enhance market efficiency and guarantee a minimum profit for market makers.
6 shares3 citations todaySource ↗
The article presents a method that eliminates arbitrage opportunities in option prices, designed for regulatory stress-tests, and proves to be more effective than existing methods.
6 sharesSource ↗
The paper presents a market equilibrium formula that combines informational imperfections and investor beliefs about assets, deriving the market portfolio and examining the sensitivities of each asset's extra excess returns.
3 sharesSource ↗
The Pontryagin-Guided Direct Policy Optimization (PG-DPO) method has been developed to expand dynamic portfolio choice to tens of thousands of assets, exceeding the traditional six-asset limit.
3 shares2 citations todaySource ↗
A new objective function has been proposed for estimating all quantiles in dynamic quantiles models, providing a more robust and flexible approach to handling multiple dynamic quantiles in time-series data.
3 sharesSource ↗
The article addresses three common issues in recorded option price datasets and suggests solutions to ensure the reliability of analyses based on these datasets.
2 shares1 citation todaySource ↗
The article examines the impact of foreign direct investment (FDI) on the development of host countries, indicating that FDI is only beneficial in the early stages of a country's development.
2 shares1 citation todaySource ↗
The article explores the challenges and opportunities in risk assessment and mitigation for loss of earning capacity insurance in Denmark, highlighting the need for innovative actuarial approaches.
2 shares1 citation todaySource ↗
The article explores the economic reasons behind for-profit companies open sourcing their large language models, highlighting a balance between technological advancement and immediate profit.
8 shares3 citations todaySource ↗
The study disputes the common view that wage inequality in the US is due to unobserved skills, instead attributing it to increasing skill volatility.
7 shares2 citations todaySource ↗
The research uses machine learning to study the effects of Indonesia's conditional cash transfer scheme on maternal health care, finding significant variations based on supply-side factors and poverty indicators.
6 shares5 citations todaySource ↗
The paper investigates the link between sovereign debt default and environmental factors, concluding that climate risk does not significantly affect the decision to default in developing and low-income countries.
6 shares1 citation todaySource ↗
The article highlights the role of digital financial services in promoting financial responsibility in five East Central European countries.
6 shares11 citations todaySource ↗
The study shows that educating consumers about animal welfare-friendly products can positively influence their behavior and support sustainable food systems.
6 shares4 citations todaySource ↗
The paper suggests that dollarization in Latin American countries can guard against inflation, but domestic policies and government action are more crucial for economic stability.
6 shares2 citations todaySource ↗
The study reveals that China continues to benefit from a demographic dividend despite an aging population and increased pension costs, largely due to the high employment rate among young people.
6 sharesSource ↗
The article presents a new method for improving portfolio performance using clustering-based segmentation and Sharpe ratio-based optimization, tested with historical data from various asset classes.
9 shares1 citation todaySource ↗
The paper uses a normalized L1 distance to evaluate changes in Airbnb booking lead times from 2018 to 2022, highlighting changes in travel planning during the COVID-19 pandemic overlooked by conventional metrics.
5 shares14 citations todaySource ↗
The study introduces a novel technique using normalized L1 distance to examine shifts in Airbnb booking lead times during the COVID-19 pandemic, offering useful insights for better demand prediction and pricing in the travel sector.
5 shares14 citations todaySource ↗
The new ASIG activation function improves credit scoring by adjusting to imbalanced datasets, outperforming traditional methods in the financial industry.
3 shares2 citations todaySource ↗
ASIG, an optimized activation function, enhances credit scoring by adapting to dataset imbalances, providing a competitive edge in the financial sector.
3 shares2 citations todaySource ↗
A new framework that combines dataset distillation techniques with pretrained models improves credit scoring technologies, expanding the use of large models in finance.
2 sharesSource ↗
The study examines the impact of Bitcoin's growing integration with traditional financial markets, especially U.S. equity indices, on its correlations with the Nasdaq 100 and the S&P 500. It suggests that Bitcoin is transitioning from an alternative asset to a more mainstream financial instrument.
3 shares4 citations todaySource ↗
The article discusses the application of deep learning in insurance pricing, comparing different models and offering a method to interpret neural network insights through generalized linear models.
27 shares16 citations todaySource ↗
The MDQR model, an advanced Queue-Reactive model, uses neural networks to understand complex market dependencies, making it useful for practical applications like strategy creation.
16 shares4 citations todaySource ↗
The article repeats the use of the MDQR model, a neural network-based extension of the Queue-Reactive model, for understanding complex market conditions and its application in strategy development.
16 shares4 citations todaySource ↗
The research compares Word2Vec and BERT for political science text analysis, concluding that BERT offers better semantic stability and is ideal for tasks needing semantic consistency.
13 shares3 citations todaySource ↗
Working papers in finance and economics from SSRN.
52 items
The research assesses the performance of two key FinTech mutual funds in India, highlighting the importance of selecting profitable funds for investment.
10 sharesSource ↗
The article reviews the influence of heterogeneity on macroeconomic modeling, especially in monetary and fiscal policy, and evaluates methods to solve these models.
397 sharesSource ↗
The paper studies the volatility performance between the Nifty index and Sector index, emphasizing the role of the stock market in economic growth and the potential harm of market instability.
10 shares2 citations todaySource ↗
The research investigates the effectiveness of different optimization techniques for estimating Weibull distribution parameters, finding that metaheuristic algorithms outperform traditional methods.
16 sharesSource ↗
The study examines the effect of disclosing alternative data on corporate tax avoidance, revealing that tax avoidance decreases with such disclosure, especially for firms with high information opacity and low stock liquidity.
11 sharesSource ↗
The paper discusses various variational inequality models in finance, which outline optimal strategies in derivatives pricing, portfolio selection, and corporate finance.
11 sharesSource ↗
The research introduces new methods for forecasting financial risk using large language models, finding these models effective for short-term but traditional models superior for long-term financial risk management.
26 sharesSource ↗
The research indicates that granular option variables can predict individual stock returns, with machine learning techniques improving this prediction.
4 sharesSource ↗
Regulatory Forbearance & Zombie Firms: The study shows that during a crisis, India's banking system's asset quality forbearance negatively affects credit efficiency, with state-owned banks lending more to insolvent firms.
8 sharesSource ↗
A new fatigue life prediction model, combining physical constraints and machine learning, outperforms other models.
4 sharesSource ↗
The article reviews key architectures by Jürgen Schmidhuber, emphasizing his significant contributions to deep learning and artificial intelligence.
23 sharesSource ↗
The study introduces a hybrid machine learning model for predicting coalbed methane production, which provides more accurate predictions.
3 sharesSource ↗
The research suggests that competition from U.S. money market mutual funds could affect the availability of bank loans.
13 sharesSource ↗
The research proposes a new framework for inspecting telecommunication towers using drones with LiDAR sensors.
4 sharesSource ↗
The study finds that China's new asset management regulations significantly reduce the risk of intercompany contagion.
10 sharesSource ↗
The article proposes a model to align historical correlations of futures contracts with implied volatility smiles using two specific mathematical models.
233 sharesSource ↗
The paper presents a machine learning-based early warning system to predict distress in large European banks, with the random forest model performing best.
23 shares1 citation todaySource ↗
The article introduces a framework for applying normalizing flows to credit risk modeling, using invertible neural networks to combine two different approaches.
28 sharesSource ↗
The paper finds a significant influence of increased geopolitical risk on financial stress.
19 sharesSource ↗
The article reveals a potential negative impact of excessive finance on growth volatility.
11 sharesSource ↗
The paper offers a technical analysis of NVIDIA's Cosmos World Foundation Model Platform for Physical AI, highlighting its architecture, training methods, and performance.
45 sharesSource ↗
The study finds that financially independent corporations in China tend to prefer financial investments due to high agency costs and reduced financial risk.
15 sharesSource ↗
The article introduces a method to create optimal portfolios using the Herd Behavior Index (HIX), which measures the synchronicity of stock price movements.
14 sharesSource ↗
The research examines the positive effect of banking regulations on liquidity risk and financial stability in the European banking sector.
10 sharesSource ↗
The study introduces a method that merges ensemble learning and genetic algorithms to optimize stock portfolios and predict asset returns in the Chinese Ashare market.
8 sharesSource ↗
The research finds a positive link between corporate diversification and Ponzi finance in China's Ashare-listed nonfinancial firms.
6 sharesSource ↗
The article suggests a forecast combination scheme using time-varying weights, which improves economic performance compared to existing methods.
12 sharesSource ↗
The article highlights the importance of machine learning in evaluating financial management in big data and IoT in the credit industry, improving creditworthiness accuracy.
5 shares27 citations todaySource ↗
The research examines the lead-lag relationships between different maturity stock index futures contracts in the Chinese financial futures market, uncovering a consistent price discovery pattern.
6 sharesSource ↗
The study investigates the low regularity Cauchy data for nonlinear dispersive PDEs using modulation spaces, proving local well-posedness under certain conditions.
4 sharesSource ↗
The study uses the quadratic normal model to improve oil options pricing and hedging, incorporating fat-tailed distributions and testing its efficiency over 25 years.
13 sharesSource ↗
The research explores what influences portfolio changes in emerging market equity mutual funds, highlighting firm size, investment features, and stock attributes as key factors, with their significance changing based on market conditions and investment strategies.
3 sharesSource ↗
The paper studies the investment behaviors of Development Finance Institutions in venture capital, revealing their goals to develop VC ecosystems, encourage entrepreneurship, stimulate innovation, and advocate sustainability, with differing levels of success in developed and developing economies.
2 sharesSource ↗
A study reveals a seasonal trend in SEC regulatory disclosures, with a spike in winter, mirroring the Sell in May and Go Away effect, a pattern also seen in European markets.
5 sharesSource ↗
The risk of a cyberattack is heightened during stressed financial conditions, as evidenced during the COVID-19 pandemic, necessitating policy solutions tailored for such adverse conditions.
14 sharesSource ↗
A link between cross-sectional anomalies and timeseries market return predictability in an international context has been found, leading to the creation of three new market efficiency measures.
3 sharesSource ↗
Following the implementation of stricter flood standards, an unexpected rise in home valuations has been noted, with changes in appraisers' practices suggesting a behavioral shift rather than market mispricing.
2 sharesSource ↗
The article introduces a mathematical model that combines five major generative modeling paradigms, using optimal transport theory, stochastic differential equations, and information geometry.
26 sharesSource ↗
The study reveals that digital platforms enhance financial knowledge, increase stock market participation, and improve investment behavior, especially among older, less wealthy, and inexperienced households.
16 sharesSource ↗
The article extends the FeynmanKac formula to nonMarkovian settings, providing a mathematical model for complex memory effects in stochastic processes and financial derivatives pricing.
24 sharesSource ↗
The article analyzes geometric and topological data analysis methods, presenting a neural architecture that combines geometric convolutions with persistence-based features for improved data analysis.
31 sharesSource ↗
The paper discusses the potential of climate-linked bonds in achieving a net-zero economy, suggesting that about three percent of government debt in major economies could be converted into such bonds.
8 shares3 citations todaySource ↗
The article suggests a new method for predicting the equity risk premium by aggregating firm-level return predictions from neural networks, showing significant economic benefits in trading strategies.
15 sharesSource ↗
The paper explores the difficulties of using news sentiment analysis to predict next-day stock returns, proposing a multilevel approach that incorporates sentiment analysis across individual stocks, industries, and the overall economy.
2 sharesSource ↗
The composition changes in the stock market cause costs for index funds, negatively affecting returns due to a rebalancing strategy that buys high and sells low.
3 sharesSource ↗
The demand shifts for U.S. Treasuries impact foreign exchange and bond markets, causing the U.S. dollar to depreciate against G9 currencies when demand is high.
23 sharesSource ↗
Equity portfolios that are diversified based on risk and sector significantly lower the chances of extreme losses without greatly affecting portfolio performance.
4 sharesSource ↗
Geopolitical shocks like export controls impact the U.S. asset management industry, but active funds can mitigate this by selling stocks of affected U.S. firms.
3 sharesSource ↗
Expected inflation changes influence firm-level credit spreads and equity returns, with good inflation reducing corporate credit spreads and increasing equity valuations.
7 sharesSource ↗
Machine learning and explainable artificial intelligence can estimate combined location value, separating it from structure value in apartment rents.
8 sharesSource ↗
A portfolio strategy using Monte Carlo simulations and insider trading transactions consistently performs better than the S&P 500 across various performance metrics.
3 sharesSource ↗
There is a positive correlation between the monthly returns of bonds and equities, with less stakeholder conflict leading to a higher degree of comovement between these financial instruments.
3 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
30 items
The Total Portfolio Approach (TPA) enhances investment returns by diversifying risk factors, particularly beneficial in private markets.
28 sharesSource ↗
A new model using instrumented principal component analysis (IPCA) predicts country equity risk premia better than other models, especially in emerging markets.
21 sharesSource ↗
Machine Learning can produce misleading results in financial models that assume linearity, indicating the need for careful application.
18 sharesSource ↗
The best model for forecasting asset price volatility should use the natural logarithmic form of the original volatility measure for efficient regression estimators.
16 sharesSource ↗
High-performing US tech stocks, like FAANG, can offer diversification and act as safe havens for cryptocurrency investors.
16 sharesSource ↗
In a complete market, using Value-at-Risk (VaR) increases losses while Expected Shortfall (ES) reduces losses during market downturns.
14 sharesSource ↗
A portfolio optimization framework accounting for systemic and individual risk reveals potential inefficiencies in portfolio structures, indicating a risk trade-off.
14 sharesSource ↗
The study identifies factors affecting stock price volatility in BRICS countries during crises using data analysis, with the Random Tree method proving most effective.
14 sharesSource ↗
The paper finds that asset price declines are more consistent in extreme market conditions, based on an exploration of dependencies among commodity futures, stock markets, and ESG bond markets.
14 sharesSource ↗
The research reveals that the COVID-19 pandemic significantly impacted the dynamic connectedness between volatility indexes and worldwide ESG leaders’ equity markets.
13 sharesSource ↗
The paper finds that green inclusive bonds showed stronger resilience to the Russia-Ukraine conflict compared to standard green bonds.
13 sharesSource ↗
The study finds that ETF asset managers became the major long-side participants following the introduction of the ProShares bitcoin strategy ETF.
13 sharesSource ↗
The research reveals that volatility spillovers in dual financial systems form as intersectoral clusters affected by their own volatility.
11 sharesSource ↗
The paper introduces a model-free lattice model that can describe the complete price evolution of an asset and re-price all of its European options simultaneously.
10 sharesSource ↗
The study finds that the spillover effect of economic policy uncertainty on real effective exchange rate volatility is stronger in emerging markets than in developed markets.
10 sharesSource ↗
The study uses machine learning to identify factors influencing the zero-leverage phenomenon, including cash holdings, tangible assets, industry leverage-level, and firm size, and suggests a solution for sample imbalance.
20 sharesSource ↗
Machine learning models show strong bond return predictability, especially during high risk aversion and slow economic growth, emphasizing the importance of using both cross-sectional and time-series predictors.
13 sharesSource ↗
The paper introduces new optimization models for Support Vector Machine for classification tasks, using robust optimization techniques to guard against data perturbations, and demonstrates the benefits through real-world datasets.
12 sharesSource ↗
The paper suggests a Prescriptive Analytics approach for data-driven dynamic inventory control of large product portfolios, using a 'global learning' model that outperforms 'local learning' strategies, and highlights the importance of contextual information.
11 sharesSource ↗
The article discusses a deep learning algorithm designed to detect financial asset bubbles using observed call option prices. This algorithm was tested on tech stock market data and under different models.
15 sharesSource ↗
The study finds that country index crash risk is significantly influenced by exchange rate volatility and investor sentiment, but not by net foreign portfolio investment.
24 sharesSource ↗
Research shows a cointegration between major cryptocurrencies and Indian stock market indices, with cryptocurrencies reacting to stock market shocks.
15 sharesSource ↗
The paper reveals that optimal portfolio structures are influenced by ESG Risk Scores under the Mean-Semivariance Behavioral Hypothesis, but the impact is minimal.
15 sharesSource ↗
The study uses Partial Dependence Plots to analyze real estate features in Szczecin, Poland, highlighting its effectiveness in understanding complex property price relationships.
14 sharesSource ↗
The paper presents the SHAP location score, a new data-based method for assessing real estate locations, enhancing traditional urban models and benefiting real estate stakeholders.
12 sharesSource ↗
Persistence: The study suggests that EuroStoxx 50 futures prices are not always efficient, with potential for abnormal profits at intraday frequency.
12 sharesSource ↗
The research indicates that the $1/N$ rule is best in high-dimensionality but can be improved by combining it with other rules or machine learning portfolios.
10 sharesSource ↗
The article explores the benefits and risks of using artificial intelligence in asset management, including improved research and decision-making but potential biases.
10 sharesSource ↗
The study finds that demographics, not income, are the key predictors of social welfare and inequality in Madrid's neighbourhoods.
9 sharesSource ↗
The paper introduces the Decision Discovery Framework (DDF) for creating decision discovery algorithms, and suggests future research on decision modeling and processing unstructured data.
9 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
18 items
The study proposes three models - Geometry, Resource, and Domino - to understand the physics of skill learning in neural networks, offering insights into neural scaling laws and learning dynamics.
260 shares8 citations todaySource ↗
The research uses GPS tags in photo metadata to train models that generate images based on location, improving the estimated 3D structure and capturing the unique appearance of different locations.
52 shares8 citations todaySource ↗
The paper presents CUT3R, a unified framework that uses a recurrent model to generate metric-scale pointmaps from a stream of images, enabling dense scene reconstruction that updates with new images.
45 shares593 citations todaySource ↗
The study introduces a method for segmenting objects in videos based on motion, using long-term point trajectories to complement optical flow, improving motion-based segmentation.
30 shares14 citations todaySource ↗
The research proposes a method for scene flow prediction that estimates geometry and motion, offers a solution to scene flow data scarcity, and introduces a natural parameterization for scene flow prediction, enhancing scene flow prediction in-the-wild.
14 shares22 citations todaySource ↗
A study shows that while AI tools can assist in artistic creation, professional artists still produce more creative and accurate work, though the difference is slight.
13 shares7 citations todaySource ↗
GSTAR, a new method for photo-realistic rendering and 3D tracking of dynamic scenes, has been introduced, enabling a variety of applications.
11 shares17 citations todaySource ↗
DexForce, a new method for capturing demonstrations of complex manipulation, uses contact forces to compute actions for policy learning, achieving a 76% success rate.
10 shares55 citations todaySource ↗
GFast, a new algorithm, efficiently calculates the Fourier transform of functions over generalized q-ary sequences, outperforming existing algorithms in speed and sample usage.
10 shares2 citations todaySource ↗
HAC++, a new 3D Gaussian Splatting compression technique, uses relationships between unorganized anchors and a structured hash grid to achieve a size reduction of over 100X while improving fidelity.
10 shares70 citations todaySource ↗
The research shows that increasing computation during inference-time can enhance the quality of samples produced by diffusion models, especially in image generation.
175 shares256 citations todaySource ↗
The article discusses advancements in Large Language Models (LLMs) reasoning, emphasizing the use of reinforcement learning and thought simulation for complex reasoning, and the potential of scaling during training and testing.
107 shares250 citations todaySource ↗
Machine Writing Expansion: OmniThink, a machine writing framework that mimics learner cognition, is introduced to improve the knowledge density of machine-written articles, addressing the limitations of retrieval-augmented generation.
52 shares26 citations todaySource ↗
The study reveals that scaling the decoder in auto-encoders, specifically the VisionTransformer architecture for Tokenization (ViTok), improves reconstruction performance and sets new standards for class-conditional video generation when combined with Diffusion Transformers.
31 shares33 citations todaySource ↗
A study using a dataset of over 48,000 Jupyter notebook edits from GitHub reveals the complexity of machine learning maintenance tasks and the potential of large language models in predicting code edits.
30 shares3 citations todaySource ↗
Text-to-Video Benchmark: TV-CompBench, a new benchmark for evaluating text-to-video generative models, shows that current models struggle with composing various elements into a video.
28 shares183 citations todaySource ↗
Learning Neuroimaging Reports: Neuradicon, a new natural language processing framework, has been developed for analyzing neuroradiological reports, showing excellent adaptability across different time periods and healthcare institutions.
26 shares3 citations todaySource ↗
A new tokenization scheme, Frequency-space Action Sequence Tokenization (FAST), has been proposed for robot actions, facilitating the training of vision-language action policies for complex and high-frequency tasks.
24 shares673 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
1 items
The article discusses self-adaptive large language models (LLMs) which are designed to tackle the issues of high computational intensity and inflexibility in managing diverse tasks, common problems with traditional fine-tuning methods.
665 shares
Repositories the letter featured.
10 items
PyGAD is a Python 3 library used for developing genetic algorithms and training machine learning models like Keras and PyTorch.
1,946 shares
The toolkit is intended for the development and comparison of various reinforcement learning algorithms.
35,183 shares
This tool aids in fine-tuning LLM models, creating synthetic data, and facilitating dataset collaboration.
756 shares
The project provides implementations of popular options trading strategies with experimental features, with plans to become a library in the future.
21 shares
The article presents an open-source AI tool that rivals Gemini Deep Research by generating reports from search results.
231 shares
The article discusses scikitlearn sidekick, a tool designed to assist in machine learning processes.
239 shares
The article details a Python-based statistical package that utilizes the Pandas library.
1,668 shares
The article provides a simplified explanation of concurrent programming in Python.
675 shares
The article unveils AppAgent, a framework that uses LLM-based technology to operate smartphone apps.
5,403 shares
Industry news: funds, hiring, markets and regulation.
20 items
Former Millennium manager, Robert BonteFriedheim, is launching a London-based hedge fund, Scarlet Macaw Capital, with a starting capital of 200m in Q2.
7 shares
Nalmont Capital, a Montreal-based asset manager, has named Alexandre Hocquard as its new Managing Partner and Lead Portfolio Manager.
6 shares
LSEG Business, Acadia, has appointed Xabier Anduaga as a Partner in its Quantitative Services team.
6 shares
Saba Capital's bid to revamp the UK's closed-ended investment trust sector was blocked as Herald Investment Trust shareholders rejected its board replacement proposal.
5 shares
Edinburgh Worldwide Investment Trust (EWIT) is urging investors to resist Saba Capital's plan to replace its board, labeling it a significant threat.
5 shares
Code Willing and Exchange Data International have partnered to launch CWIQ Platform, aimed at enhancing research workflows for hedge funds and asset management firms.
4 shares
Chinese hedge fund managers are launching products similar to Bridgewater Associates’ “All Weather” strategy to cope with potential volatility under Trump's second presidency.
4 shares
Hudson Bay Capital Management, Sona Asset Management, and Centiva Capital are expanding their presence in Hong Kong, enhancing the city's status as a top financial centre in Asia.
3 shares
Hedge fund trends: Hedge funds are at a crossroads due to global uncertainty, high interest rates, and market dispersion, potentially heralding a new golden era for active management.
3 shares
Simmons & Simmons law firm has updated LaunchPlus, a tool designed to assist new fund managers in navigating the complexities of establishing a hedge fund in the UK.
3 shares
PhD quants are potentially losing their unique appeal in the US market.
3 shares
Broadridge Financial Solutions has added an AI analytics feature to its platform to enhance posttrade processing and operational reporting.
2 shares
Billionaire Alex Gerko's firm, XTX, intends to build a €1 billion data hub, investing in machine learning.
2 shares
In 024, Brazilian hedge funds saw a record level of withdrawals due to increasing interest rates and market volatility.
2 shares
A top quant researcher from Two Sigma is leaving to join Cubist, as reported by MSN.
2 shares
Hedge Fund: Hedge funds are increasing their market positions and betting on the dollar's rise in anticipation of Trump's potential second term, reaching the highest borrowing levels since 2010.
2 shares
Fasanara Capital has launched its first tokenised Money Market Fund, the Fasanara MMF Token, on the Polygon PoS public blockchain.
2 shares
European credit manager, Chepstow Lane Capital, reported net returns of 13.24% in 2024, as per an investor letter cited by Bloomberg News.
2 shares
Baupost Group, a former leading hedge fund, has experienced a $7bn client withdrawal over the past three years due to poor returns, according to Bloomberg.
1 shares
Lombard Odier Investment Managers has introduced DOM Global Macro, a new liquid diversified absolute-return UCITs strategy, expanding its Alternatives franchise.
1 shares
Episodes on markets, quant methods and economics.
10 items
Michael Gayed and Jeff Sarti emphasize the need for diversification in investments, the potential of private credit markets, and the influence of behavioral finance on investment decisions.
17 shares
Jay Hatfield discusses the effects of deregulation on inflation, the advantages of active management in fixed income markets, and how small and large firms differ in responding to market changes.
10 shares
David Lebowitz and Jared Gross provide a macroeconomic update and discuss asset allocation strategies for 2025, including equities, fixed income, real assets, and financial alternatives.
10 shares
Jonny Goulden and Saad Siddiqui discuss recent market developments and their impact on the EM fixed income asset class, with a strict rule against sharing the discussed research without J.P. Morgan's consent.
8 shares
Timothy Sykes shares his transition from tennis to stock trading, his strategies for dealing with volatile stocks, the importance of understanding market sentiment, and his philanthropic activities funded by his trading profits.
7 shares
Wendy Li of Ivy Invest shares her strategies for risk management and alternative asset investment, aiming to make endowment-style investing available to individual investors.
6 shares
Former Wall Street manager, Nomi Prins, explores the intricate relationship between central banks, their growing gold reserves, and the effect on the global monetary system.
5 shares
Jonathan Fine and George Cole of Goldman Sachs discuss the recent fluctuations in global bond yields and what it means for the economy and investors.
4 shares
Jeff Cullen and Cathy Howse from Schafer Cullen emphasize the role of dividends in a portfolio's total return and discuss the future of the ETF market.
4 shares
Arindam Sandilya, Junya Tanase, James Nelligan, and Patrick Locke discuss the FX outlook ahead of the US Presidential inauguration, highlighting the need for confidentiality when using J.P. Morgan Data in AI systems.
4 shares
Posts from quant researchers on X.
6 items
The article provides an in-depth analysis of cryptocurrency, including trading strategies, portfolio building, volatility forecasting, and data sources, along with a comprehensive list of references for further study.
6 shares
The article recaps recent research on investment, covering topics like short interest and predictability, intraday oil futures patterns, banking stocks drivers, and forecasting FOMC decisions.
1 shares
The article explores a new study that reveals a significant prediction of stock returns based on the divergence between the MOVE index and the VIX.
1 shares
Republican vs. Democratic Presidencies: The study shows that investors tend to overestimate expected tax cuts during Republican presidencies, leading to a notable difference in post-earnings announcement drift.
0 shares
Alternative Signals in Crypto Markets: Recent studies indicate that trend and breakout signals, not just momentum, are widely used in cryptocurrency markets.
0 shares
Error Reduction Discovery: A recent breakthrough aims to drastically decrease errors in quantum computing, marking a significant advancement towards practical Quantum Computing.
0 shares
Threads from r/quant, r/algotrading and friends.
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