Quant LetterNo. 80
170 items across 10 sections, as sent to readers on 1 January 2025. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
27 items
The OPT model, a large language model, has proven superior in predicting stock market returns using sentiment analysis of U.S. financial news, outdoing traditional methods like the Loughran-McDonald dictionary model.
46 shares107 citations todaySource ↗
A new portfolio selection model is proposed to minimize estimation errors and over-diversification, with an algorithm developed to establish a direct link between the risk-aversion coefficient and robustness level.
6 sharesSource ↗
TradingAgents, a new stock trading framework, employs large language models to simulate real-world trading dynamics, enhancing trading performance.
5 shares220 citations todaySource ↗
A novel model is presented to address a stochastic control issue in optimal liquidation with dark pools, using a system of backward stochastic differential equations with jumps and singular terminal values.
5 shares5 citations todaySource ↗
The research shows brokers in a mediated market have a strategic edge over traders who only use prices for information, and that brokers can gain economic value from leaked information.
5 shares2 citations todaySource ↗
The paper presents a method for jointly lifting a Brownian motion and a low-regularity adapted stochastic rough path, useful for modeling rough volatility.
5 shares6 citations todaySource ↗
The article introduces the Adaptive Learning Policy Engine, a new approach to mid-price forecasting using NASDAQ data, which outperforms other machine learning models.
4 sharesSource ↗
The research proposes new BASEL 2 and 3 compliant techniques for credit scoring in banks, demonstrating improved performance and default capture rate with Gradient Boosting Machines.
3 shares6 citations todaySource ↗
The study introduces Choquet Expected Shortfall, a new class of risk measures, and provides optimization algorithms and examples using financial data.
2 shares2 citations todaySource ↗
The study outlines a three-step pivoting framework for B2B platform business models in manufacturing, using an energy sector case study.
18 shares31 citations todaySource ↗
The paper shows that AI has increased demand for complementary skills and decreased demand for substitute skills in the U.S. economy.
11 shares27 citations todaySource ↗
The research creates an index system to assess the development of new infrastructure investment and digital transformation in 31 Chinese provinces and cities from 2014 to 2021.
7 sharesSource ↗
The study reveals that gig work platforms in Japan have expanded the market and are more variable in efficiency than the public employment platform.
6 shares4 citations todaySource ↗
The article discusses how US sanctions on Venezuela could lead to an increase in migration, potentially causing an additional one million Venezuelans to emigrate over the next five years.
6 shares2 citations todaySource ↗
The study reveals that China's economic growth has eradicated absolute poverty but has also increased income inequality and relative poverty.
6 sharesSource ↗
The paper highlights the growth of gig work platforms in Japan, showing they have more variability in efficiency and higher elasticity than public employment platforms.
6 shares4 citations todaySource ↗
The research shows that China's economic growth, while eradicating absolute poverty, has also worsened income inequality and relative poverty.
6 sharesSource ↗
The study assesses the accuracy of Large Language Models like OpenAI's ChatGPT and Google's Gemini in giving financial advice, finding a 70% accuracy rate but limitations with complex queries.
7 shares17 citations todaySource ↗
The paper examines the use of a second-order differential operator in the Black-Scholes framework, leading to a variant of the Harry Dym equation for potential use in studying financial-market volatility.
6 sharesSource ↗
The research explores the application of the Hidformer model, a Transformer-based neural network, in stock price forecasting, combining technical analysis and advanced machine learning for improved accuracy.
3 shares6 citations todaySource ↗
The paper discusses the application of text mining and natural language processing in finance, emphasizing the need to improve data quality and model understanding for better financial predictions.
11 shares1 citation todaySource ↗
The study reveals a lack of research on the challenges oracles present in incorporating blockchain technology into accounting systems, despite numerous articles on the topic.
8 shares8 citations todaySource ↗
The research highlights a gap in studies addressing the constraints of oracles in the implementation of blockchain technology in accounting systems, despite abundant literature on the subject.
8 shares8 citations todaySource ↗
The article proposes a strategy to manage cryptocurrency risks during crises like the new crown outbreak, after analyzing how risks spread among cryptocurrencies during such extreme events.
2 sharesSource ↗
The research reveals a decrease in job and worker finding rates in Japan from 1972 to 2024, with a greater mismatch in occupations than in regions.
11 sharesSource ↗
An experiment on an Asian short-video platform found that AI-generated titles boosted content consumption, but were inferior in quality to those created by humans, emphasizing the value of human-AI collaboration.
9 shares6 citations todaySource ↗
A study using the DICE model with variable discount rates shows that current climate change mitigation cost decisions lead to intergenerational inequality, suggesting a revised optimization for better fairness.
8 shares2 citations todaySource ↗
Working papers in finance and economics from SSRN.
59 items
The article presents a mathematical proof showing the similarity between decision trees and artificial neural networks, hinting at new combined machine learning methods.
37 sharesSource ↗
The research assesses the impact of Machine Learning in finance, emphasizing its potential in personal finance optimization, but also noting issues like data privacy and algorithmic biases.
30 sharesSource ↗
The paper mathematically compares Kolmogov-Arnold-Networks and traditional Artificial Neural Networks, showing a balance between expressivity and computational complexity.
81 sharesSource ↗
A new deep learning method is introduced for predicting Chinese futures market movements, demonstrating superior predictability compared to existing benchmarks.
4 sharesSource ↗
Large Language Models are utilized to interpret China's industrial policies from 2000 to 2022, extracting structured data from 3 million government documents.
31 shares15 citations todaySource ↗
The study criticizes post hoc causal interpretations in social sciences, advocating for machine learning as a supplementary tool for causal inference, not a standalone solution.
7 sharesSource ↗
A new semiparametric volatility model is introduced for estimating inflation volatility, outperforming standard models and offering a new measure to explain the fluctuating asymmetric inflation level-volatility relationship.
2 sharesSource ↗
Forensic accounting is being revolutionized by AI and Big Data analytics, improving fraud detection and investigation, but adoption is hindered by high costs, privacy issues, and a lack of technical expertise.
3 sharesSource ↗
A new framework combining Machine Learning and Dynamic Mode Decomposition has been introduced to enhance flow prediction and control in vortex-induced vibration systems.
5 sharesSource ↗
Financial fraud detection is being transformed by big data analytics, machine learning, and natural language processing, which can identify patterns and anomalies often missed by traditional systems.
2 sharesSource ↗
A proposed alloy design strategy combines orthogonal experiments, machine learning, and Pareto analysis to address the challenge of using data-driven methods with limited sample data.
2 sharesSource ↗
The use of stochastic neural networks and uncertainty estimation is proposed to improve the quality and speed of dataset distillation.
5 sharesSource ↗
A new online algorithm, OS2ISVM, has been introduced to enhance the efficiency of SVMs in online semi-supervised learning scenarios.
2 sharesSource ↗
The study reveals a dynamic link between green bonds, ESG ETFs, and energy-efficient cryptocurrencies, influenced by market sentiment and risks.
2 sharesSource ↗
The paper shows that stock crash risk can significantly predict future volatility of the SP 500 index, providing unique predictive insights separate from macroeconomic variables.
2 sharesSource ↗
The study reviews sentiment analysis methods in Natural Language Processing, covering data collection, preprocessing, feature extraction, and classification.
64 shares2 citations todaySource ↗
The review discusses the use of Artificial Intelligence in financial markets, including trading, fraud detection, and credit scoring, and addresses data privacy and regulatory issues.
10 sharesSource ↗
The paper provides a detailed exploration of Generalized Linear Models (GLMs), including likelihood functions, estimation methods, and theoretical properties.
157 sharesSource ↗
The paper analyzes the integration of Transformer architectures with Reinforcement Learning, offering a mathematical framework, a new taxonomy, and a review of real-world applications.
62 sharesSource ↗
The study introduces a Reinforcement Learning-based algorithm for hedging European call option payoffs, proving its effectiveness against the standard delta hedging strategy.
9 sharesSource ↗
The study uses machine learning models to predict the accuracy of corporate takeover rumors, emphasizing the effectiveness of TabNet and the need for data imbalance and dimensionality reduction.
8 sharesSource ↗
The paper analyzes three types of agents in computational systems, exploring their integration and the convergence of different agent architectures.
77 sharesSource ↗
The article discusses the use of machine learning techniques like topic modeling and LDA for sentiment analysis, and their role in data-driven decision making.
2 sharesSource ↗
The article analyzes the effect of the Robin Hood tax on the Spanish stock market, suggesting it lowered volatility without impacting trading or liquidity.
11 sharesSource ↗
The article reveals that brokers in a broker-mediated market have a strategic advantage and can profit from information leakage in client trading.
15 sharesSource ↗
The article studies the ability of mutual fund managers to generate positive alpha around FOMC meetings, and its impact on investor flows and fund performance.
6 sharesSource ↗
The article talks about the integration of PySpark and machine learning models on Databricks to improve predictive analytics, and offers optimization strategies.
2 sharesSource ↗
The article shows a positive correlation between hedge fund leverage and prime brokers' stock price crash risk, based on data from 2001-2021.
11 sharesSource ↗
Value vs Speculation: The article presents a theoretical model of Bitcoin's market price volatility, attributing it to the interaction between fundamentalists and speculators.
15 sharesSource ↗
The article discusses different architectures for distributed machine learning systems, their scalability potential, and design principles for enhanced scalability.
2 sharesSource ↗
The study suggests that contractionary monetary policy can cause equity outflows from mutual funds, which are then absorbed by banks charging a premium for market making.
3 sharesSource ↗
The research indicates that adding commodities to an equity-bond portfolio can enhance diversification during climate stress, but it also increases tracking error and reduces risk-adjusted performance.
2 sharesSource ↗
The paper reveals that risk transfer among U.S. investors is minimal, challenging macrofinance models that forecast a larger risk transfer due to varying equity premiums.
5 sharesSource ↗
The study presents a general equilibrium model where investors aim for multiple stochastic investment goals, suggesting that unique bonds issued by Brazil in 2023 could be seen as Goals-based Arrow Debreu securities.
3 sharesSource ↗
The research warns that using a target volatility level for portfolio choice can lead to poor decisions when market conditions change or when faced with a high-performing active portfolio.
2 sharesSource ↗
The study presents a new method for calculating transaction costs in the infrequently traded corporate bond market, emphasizing the significant impact of delay costs in illiquid securities.
2 sharesSource ↗
The paper introduces a new algorithmic execution model that combines interbank limit and market orders with internal liquidity, aiming to reduce market impact and enhance execution efficiency.
3 sharesSource ↗
The study confirms that risk premiums are directly influenced by risk, with risk prices backed by separate risk and risk premium structures.
2 sharesSource ↗
AI enhances investment performance, but it benefits those with greater financial expertise more, potentially increasing existing performance disparities.
3 sharesSource ↗
The efficient market hypothesis is not applicable to South-Eastern Mediterranean capital markets due to inefficiencies and predictable outcomes, possibly due to lack of institutions, regulations, and information.
3 sharesSource ↗
The value of UK companies operating in Latin America in the 19th and early 20th centuries was more affected by the location of their headquarters than their operations.
3 sharesSource ↗
Stock market performance tends to drop when Congress is in session, likely due to high disapproval ratings and media-induced behavioral biases.
2 sharesSource ↗
The termination of the CRSP tape in 2025 will alter 9.62% of monthly returns, but these changes will not significantly impact time-series average premia or their significance.
3 sharesSource ↗
Chinese public companies increase their WeChat posts after environmental and social crises, which can help mitigate potential negative effects on the capital market.
2 sharesSource ↗
The article introduces a multivariate version of the Rough Fractional Stochastic Volatility model for analyzing logvolatilities, providing an estimator and confirming its theory through simulation.
12 shares4 citations todaySource ↗
The study shows that active exchange-traded funds (AETFs) help investors remove underperforming managers, leading to improved sector efficiency and price informativeness.
9 sharesSource ↗
The research presents a dynamic portfolio optimization framework that includes individual financial health metrics in the investment decision-making process, balancing risk and return.
2 sharesSource ↗
The paper introduces automated market-making algorithms for cryptocurrency perpetual contracts, showing the Bar Portion alpha signal's superiority over a baseline MACD signal in live trading.
4 sharesSource ↗
The article reveals that foreign economic policy uncertainty significantly predicts excess U.S. stock returns, primarily affecting equity prices through cash flow news.
10 sharesSource ↗
The research explores the macroeconomic effects of the Russian invasion of Ukraine on Central and Eastern European economies, indicating increased inflation and decreased GDP.
16 sharesSource ↗
The study investigates the impact of valuation adjustments on systemic US banks' derivatives portfolios, providing insights into how banks manage these adjustments and their effects on balance sheets.
4 sharesSource ↗
The cost of hedging can be greatly affected by monetary policy decisions, as seen during the height of the pandemic crisis in March 2020.
2 sharesSource ↗
Advanced AI-powered deepfake technology threatens financial markets by manipulating market sentiment, disrupting trading systems, and exploiting retail investors.
2 sharesSource ↗
Rates and Currency Risk: The currency risk premium links the neutral interest rates of two countries, with global interest rates showing strong correlations across foreign countries.
8 sharesSource ↗
Dealers use sponsored repo when balance sheet space is limited, with factors like money market fund assets and end-of-month dates affecting sponsored repo spreads.
10 sharesSource ↗
Portfolio selection can be improved by combining risky assets with a market fund, rather than adding more capital.
2 sharesSource ↗
Sustainable finance needs a shift from maximizing financial value to integrated value balancing, which includes financial, social, and environmental value.
3 sharesSource ↗
The demand for safe assets, auction bidding strategies, and post-auction price dynamics are determined by differences in investment horizons.
10 sharesSource ↗
Asset allocation mandates affect stock price reactions to new information, with stocks with higher rebalancing fund ownership showing smaller price reactions to earnings surprises.
2 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
22 items
The article finds that traditional sample covariance matrix performs better in portfolio selection than both naive allocation and advanced covariance estimators, challenging previous equity-focused studies.
21 sharesSource ↗
The article introduces a new continuous-time insider trading model, showing that a higher correlation coefficient makes the equilibrium price more informative, reducing trading intensity and the insider's expected payoff.
15 sharesSource ↗
The article introduces a new online portfolio selection strategy that considers transaction costs and uses an adaptive scheme for sequential parameter decision, yielding higher cumulative returns and competitive Sharpe ratios than existing strategies.
10 sharesSource ↗
The study presents mathematical models to compute the capital valuation adjustment using market theory and suggests numerical methods for solving the related partial differential equations.
9 sharesSource ↗
The research introduces measures of stochastic non-dominance to analyze scenarios where stochastic dominance rules are not applicable, using the Wasserstein distance as the measure.
8 sharesSource ↗
The paper suggests a new eigenvalue ratio criterion to determine the number of factors in static approximate factor models, validating its effectiveness through a Monte Carlo study.
6 sharesSource ↗
The study introduces a new method to solve Markov reward games using matrix norms, which considers all stages and actions at once, unlike traditional methods.
1 sharesSource ↗
The research shows that Large Language Models (LLMs) can improve clustering accuracy in consumer segmentation for marketing research and can simulate consumer preferences.
1 sharesSource ↗
The paper presents a new method for forecasting loss given default (LGD) by dividing features into groups, building individual models, and combining the results.
1 sharesSource ↗
The article finds that while both ChatGPT and Bing Chat can detect the truthfulness of political information, ChatGPT performs better and provides more nuanced responses across different languages.
0 sharesSource ↗
The article suggests a new method for assessing the significance of product features and their effect on customer satisfaction. This method uses online reviews and mathematical programming to aid businesses in creating investment strategies for product enhancement.
7 sharesSource ↗
The article reviews the progress of geometric shape recognition research since the 1970s, emphasizing the effectiveness of the Hough transform method, but points out its drawback of discretising its parameter space because of high computational cost.
2 sharesSource ↗
Research indicates that machine learning credit scoring models may unintentionally favor individuals with more accessible data, leading to potential algorithmic bias.
43 sharesSource ↗
Machine learning methods often fail to predict the equity premium better than the historical average due to small datasets and low signal-to-noise ratios, despite strong forecasting abilities.
28 sharesSource ↗
Machine learning clustering techniques can greatly improve stock market research and investment strategies, but require careful selection and human oversight.
27 sharesSource ↗
A study on algorithmic trading strategies for Futures CopperMainContinuous in the Shanghai Futures Exchange found no successful strategies, underlining the difficulty of finding profitable strategies in the volatile futures market.
24 sharesSource ↗
A study found that combining the random forest and LASSO methods in machine learning models provided the best forecasting performance for stock market volatility.
24 sharesSource ↗
The XGBoost machine learning algorithm is the best at predicting African stock market crises, with stock prices and exchange rates being key factors.
22 sharesSource ↗
Indonesian retail bond investors' decisions are heavily influenced by the comparative return performance against other investments.
21 sharesSource ↗
The hybrid CNN-LSTM model, combined with sentiment scores, is the most accurate at predicting salmon spot prices.
19 sharesSource ↗
A combined approach using financial and macroeconomic variables is the most effective for forecasting exchange rate volatility, especially when using wavelet analysis.
19 sharesSource ↗
Wealthier Northern European countries yield higher returns on sin stocks, with familiarity with gambling stocks reducing rejection, indicating human behavior's role in financial markets.
16 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
20 items
The study introduces a new framework for language models that enhances inference-time decoding procedures, leading to significant improvements over previous methods.
18 shares35 citations todaySource ↗
The research shows that the VADER machine learning algorithm performs best in sentiment analysis of Twitter data on imported food in Trinidad and Tobago.
12 sharesSource ↗
The paper uses machine learning to explore flat metrics of Fermat Calabi-Yau n-folds, revealing new properties and achieving significant reductions in Ricci curvature.
9 shares11 citations todaySource ↗
The study finds that Large Language Models can provide accurate financial advice about 70% of the time, but struggle with complex financial queries.
8 shares17 citations todaySource ↗
The paper introduces IMAGINE, a compute-in-memory SRAM for processing convolutional neural networks, which offers high energy efficiency and competitive accuracies on MNIST and CIFAR-10.
8 shares2 citations todaySource ↗
The article introduces a new adaptive batch size schedule for large-scale model training, which optimizes memory usage and performs better than constant batch sizes, especially in pretraining smaller models.
8 shares5 citations todaySource ↗
The study explores the use of tensor networks in evolutionary optimization algorithms, concluding that better generative models don't always improve optimization performance and suggests adding a mutation operator for better results.
8 shares2 citations todaySource ↗
Locally Adaptive Nonparametric Regression: The paper presents LASER, a new nonparametric regression method that adapts to the local Hölder exponent of the regression function, outperforming other locally adaptive methods in various experiments.
7 sharesSource ↗
The authors introduce SWE-Gym, the first training environment for software engineering agents, featuring real-world Python tasks and showing significant improvements in task resolution rates.
6 shares315 citations todaySource ↗
The research studies the effect of AI on skill demand and compensation in the U.S., finding increased demand for AI-complementary skills and decreased demand for substitute skills, indicating AI's transformative impact on workforce skills.
5 shares27 citations todaySource ↗
Research suggests AI safety benchmarks often align with general capabilities and training compute, leading to potential safetywashing, and recommends a stricter framework for AI safety research.
178 shares85 citations todaySource ↗
Google introduces SpeechSSM, a speech language model for generating long-form audio, along with new metrics and a benchmark for long-form speech processing and generation.
21 shares27 citations todaySource ↗
A novel bootstrapping method is suggested to reduce bias in the empirical entropic risk estimator, a tool used in high-stakes decision making, and is applied to insurance contract design.
18 shares1 citation todaySource ↗
A proposed GameFi ecosystem integrates advanced AI agents into gaming platforms, improving player engagement and economic interaction within gaming ecosystems.
13 shares3 citations todaySource ↗
A new algorithm for Gaussian graphical model selection is presented, offering theoretical guarantees on computational and statistical complexity when data is sampled according to the Glauber dynamics.
12 shares2 citations todaySource ↗
KAMIM is a new method that enhances vision transformers' performance by using patch-wise weighting from keypoint features, showing improved accuracy on the ImageNet-1K dataset.
12 shares1 citation todaySource ↗
Efficient Language Model: YuLan-Mini, a 2.42B parameter base model, delivers top-tier performance among similar models through a sophisticated data pipeline, robust optimization method, and effective annealing approach.
11 shares7 citations todaySource ↗
The MetamorphASM benchmark is designed to assess Large Language Models' ability to generate and analyze obfuscated assembly code, potentially threatening anti-virus engines.
11 shares18 citations todaySource ↗
A new computational technique has been introduced for modeling the evolution of dynamical systems, specifically targeting the complex problem of modeling partially-observed partial differential equations on high-dimensional non-uniform grids.
11 shares4 citations todaySource ↗
Attention Control in Video Generation: DiTCtrl is a new training-free method for multi-prompt video generation under MM-DiT architectures, allowing for mask-guided precise semantic control across different prompts.
10 shares81 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
8 items
DeepSeekV3 is a robust language model with 671B parameters, 37B of which are used for each token.
10,160 shares
People are increasingly engaging with digital devices via graphical user interfaces.
296 shares
Large Language Models are proving useful in addressing some issues in the semiconductor industry.
253 shares
The workflow with Large Language Models can become complex and difficult to handle as task complexity rises.
207 shares
The article introduces a medical verifier to check the precision of model outputs for medical issues.
177 shares
The article highlights the difficulties in pretraining large language models due to resource and technical complexities.
85 shares
The article introduces CoMCTS, a tool used to develop Mulberry260k, a dataset with a detailed reasoning tree for each question.
81 shares
The article discusses the increasing interest in story visualization in the artificial intelligence field.
78 shares
Repositories the letter featured.
10 items
The article offers a guide on creating a trading strategy for the Freqtrade cryptocurrency bot.
2,104 shares
The piece explores a deep reinforcement learning framework for developing alpha factors for quantitative investment using GFlowNet and PythonPyTorch.
27 shares
This article discusses the Chinese version of the book Machine Learning Systems Design and Implementation.
4,144 shares
The article demonstrates how the Charting Library can be combined with other libraries, frameworks, and data transports.
1,476 shares
The article introduces a large-scale multimodal dataset of astronomical data.
312 shares
The article discusses a unique terminal-based platform created for testing AI Software Engineering, separate from the GPT-Engineer.
52,756 shares
The piece introduces the official Python library made for interfacing with the OpenAI API.
23,754 shares
The article presents a detailed toolkit for managing an AI agent service, built using LangGraph FastAPI and Streamlit.
641 shares
The article talks about AutoJobsApplierAIAgent, an AI tool developed to streamline job searching by automating the application process.
23,896 shares
The piece describes a plotting library specifically created for use in IPython/Jupyter notebooks.
3,641 shares
Industry news: funds, hiring, markets and regulation.
8 items
AIMA urges for measures to tackle systemic obstacles hindering cryptocurrency hedge fund managers from accessing banking services.
4 shares
Edinburgh Worldwide Investment Trust strengthens its resistance against a takeover bid by Saba Capital Management, offering shareholders an opportunity to invest in SpaceX.
3 shares
South Africa's rand may recover following a significant sell-off of long rand-dollar futures instigated by hedge funds, marking a major positioning reversal.
3 shares
Despite Citadel founder Ken Griffin's assertion, a Bloomberg report indicates that the multistrategy hedge fund boom is still ongoing.
2 shares
Hedge funds are consistently supporting MicroStrategy's weekly bitcoin acquisitions for the eighth consecutive week.
2 shares
Hedge fund manager Crispin Odey is filing a libel lawsuit against the Financial Times, demanding at least £79m in compensation.
1 shares
Another Managing Director leaves the company just before the bonus season starts.
0 shares
Episodes on markets, quant methods and economics.
8 items
Axel Merk discusses his shift from tech to gold investments, emphasizing risk management, balanced portfolios, and gold as a hedge during economic instability.
15 shares
Seth Cogswell talks about the differences between fiduciary advisors and asset gatherers, the need for a disciplined sell strategy, and achieving growth amidst market and economic changes.
12 shares
Meb Faber shares insights on ETF fund strategies and tax-efficient investing, discussing the transition from mutual funds to ETFs, shareholder yield, buybacks, and the potential of 351 exchanges for tax optimization.
11 shares
Robin Wigglesworth examines the bond market dynamics, volatility in U.S. Treasury yields, the bond and equity markets relationship, and potential impacts of a second Trump administration on global markets.
11 shares
Bloomberg's CTO, Shawn Edwards, shares his views on tech innovation, product strategy, and the shift towards cloud, mobile, and API-first technologies in a podcast.
2 shares
In a MacroVoices podcast, hosts Erik Townsend and Patrick Ceresna discuss nuclear fuels and fuel cycles with Thomas Jam Pedersen, focusing on the economics of Thorium-based nuclear power versus traditional Uranium reactors.
1 shares
Professor John Skrentny talks about the current state of STEM education, its impact on the future workforce, and the link between technology policy and societal needs in a podcast.
0 shares
The podcast episode recaps the top episodes of 2024, featuring interviews with notable figures such as Aswath Damodaran, Brad Gerstner, Cliff Asness, Hendrik Bessembinder, and Kenneth French.
0 shares
Posts from quant researchers on X.
2 items
The article compiles popular research papers from 2024, discussing topics like alternative data commodities, equities, machine learning, and trading.
8 shares
The article discusses Tobias Wiest's comprehensive review on different momentum strategies such as cross-sectional timeseries, residual volatility-scaled, industry factor momentum, and their theoretical justifications.
0 shares
Threads from r/quant, r/algotrading and friends.
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