GCNLSTM Forecasting
A new predictive model using a multi-channel Graph Convolutional Network and Long Short-Term Memory network is proposed for forecasting E-mini S&P 500 and CBOE Volatility Index futures.
7 sharesSource ↗
Quant LetterNo. 61
160 items across 10 sections, as sent to readers on 15 August 2024. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
21 items
A new predictive model using a multi-channel Graph Convolutional Network and Long Short-Term Memory network is proposed for forecasting E-mini S&P 500 and CBOE Volatility Index futures.
7 sharesSource ↗
An insurance company uses neural networks to find the best reinsurance strategy to manage its financial risk and control its terminal wealth and ruin probability.
5 sharesSource ↗
The Efficient Tail Hypothesis (ETH), a theory about the extreme behavior of the market, is rejected in a study of China's futures market, revealing potential profitable investment opportunities.
4 shares7 citations todaySource ↗
The thesis explores the use of Stochastic Calculus in financial models, using techniques like Monte-Carlo Simulation and machine learning, and suggests future research directions.
3 sharesSource ↗
The paper introduces a method to enhance the signal to noise ratio in financial data using auto-encoders, offering a new way to discover regularities in financial time-series.
3 shares2 citations todaySource ↗
The study highlights the need to consider group structures in financial datasets when using explainable machine learning methods, advocating for group versions of the Shapley value for consistent explanations.
3 shares2 citations todaySource ↗
The paper introduces a multilevel stochastic approximation algorithm that adaptively selects the number of inner samples to compute the value-at-risk of a financial loss, improving the previous scheme's complexity.
3 shares5 citations todaySource ↗
A new recession indicator using job vacancy and unemployment data suggests a 40% chance the US is currently in a recession, improving on the existing Sahm rule.
16 shares4 citations todaySource ↗
A new proposal characterizes a utilitarian social welfare relation on lotteries over welfare distributions for infinite populations, meeting several key axioms.
2 sharesSource ↗
The DEA method suggests that a tax system could control fishing capacity and boost efficiency in Chinese inshore fleets, provided the tax rate isn't too low.
2 sharesSource ↗
The environmental performance of China's marine economy in coastal provinces was assessed using data envelopment analysis, offering insights for a healthier local economy.
2 shares1 citation todaySource ↗
The article presents a method for monitoring coastal environmental health, combining static and dynamic methods with DEA and efficiency theory, to balance marine pollution control and coastal economic growth.
2 sharesSource ↗
The research disputes prior claims that decision sequences are influenced by scheduling, using data from randomly timed law school oral exams, and advises caution in applying previous studies to policy-making.
2 sharesSource ↗
The study uses a mathematical model to compare two water trading systems, demonstrating that the 'common pool' system is significantly more efficient than the improved pair-wise trading system.
2 shares6 citations todaySource ↗
The article questions the belief that democracy automatically results in positive outcomes, suggesting that any perceived benefits may be due to preferential treatment of democracies by powerful democratic countries and international bodies.
2 sharesSource ↗
Q&A Systems for Financial Data: HybridRAG, a new method combining Knowledge Graphs and VectorRAG techniques, improves question-answer systems for extracting information from financial documents, offering better accuracy and answer generation.
150 shares231 citations todaySource ↗
A new forward differential deep learning-based algorithm has been created to solve complex nonlinear backward stochastic differential equations, proving more efficient in accuracy and computation time.
6 sharesSource ↗
The study explores Explainable Case-Based Reasoning methods to clarify the results of black-box machine learning algorithms, using a technique to extract the learned distance metric from Random Forests, and assesses their explanatory power.
4 shares5 citations todaySource ↗
LLMs for Organizational Evaluations: Large Language Models, particularly GPT-4, are a dependable substitute for human raters in assessing knowledge-based performance, showing higher consistency and reliability, but are susceptible to contextual biases like the halo effect.
2 shares8 citations todaySource ↗
The Concentration Risk Indicator (CRI) is a new tool designed to assess risks associated with concentrated portfolios, useful in areas such as insurance risk and product portfolio mixes, especially where wealth is concentrated in few tokens.
4 shares3 citations todaySource ↗
A new portfolio management model based on Reinforcement Learning has been created for high-risk environments, combining a new environmental formulation with a Profit and Loss-based reward function, proving effective in managing risk and maintaining profitability in volatile markets like cryptocurrency.
4 sharesSource ↗
Working papers in finance and economics from SSRN.
30 items
The research develops a model using inflation and central bank interest rates to predict US consumption growth and explain stock and bond market characteristics.
10 sharesSource ↗
The project uses sentiment analysis of Tesla-related tweets and an optimized Long Short-Term Memory network to accurately predict Tesla's stock closing price.
4 sharesSource ↗
The study finds that financial influencers significantly impact their followers' investment decisions in four Nordic countries, especially under certain conditions.
5 sharesSource ↗
The paper explores the use of TinyML for estimating battery State of Charge on low-powered devices, emphasizing the need to understand dataset features and data stationarity.
2 sharesSource ↗
The article underscores the role of capital market reforms in fostering economic stability, enhancing investor confidence, and mitigating systemic risks.
3 sharesSource ↗
The research shows that audit fees increase when corporate financial asset allocation reaches a certain level due to the crowding-out effect.
2 sharesSource ↗
The study indicates that risk factors, particularly regulatory governance risk, significantly influence pricing in short-term rental markets.
6 sharesSource ↗
The research finds that Vietnamese postgraduate students frequently use modal verbs as a way to hedge in academic writing.
2 sharesSource ↗
The study demonstrates that Bitcoin and Ethereum returns have similar statistical characteristics to other financial returns, with the two-component GJR model being the most accurate for predicting future volatility.
3 sharesSource ↗
The article proposes a comparative analysis of deep learning techniques for financial market analysis, emphasizing the need for more detailed research in this field.
2 sharesSource ↗
A novel investment strategy that adapts to interest rate fluctuations could enhance the sustainability of retirement funds, ensuring more dependable post-retirement support.
3 sharesSource ↗
Machine learning is revolutionizing smart search and data discovery, with uses in voice search, predictive analytics, etc., but issues persist in data training, domain expertise, and ethical aspects.
2 sharesSource ↗
Machine learning and deep learning are propelling the progress of generative AI models, enhancing human-machine interaction and language understanding.
2 sharesSource ↗
Private equity firms are increasingly buying life insurance companies and investing in riskier assets, sparking worries about potential failures akin to previous incidents.
2 sharesSource ↗
Implementing smart beta strategies to corporate bonds can boost returns and diversify portfolios, with value and momentum strategies demonstrating significant alpha in U.S. investment-grade and high-yield bonds.
2 sharesSource ↗
The study presents a method for identifying mispricing in implied volatility, which is a strong predictor for option returns and is unaffected by changes in liquidity and transaction costs.
2 sharesSource ↗
The article highlights the growing role of Sentiment Analysis in business, enabling companies to leverage customer feedback for expansion and improvement.
2 sharesSource ↗
The paper assesses various optimization algorithms for machine learning models, showing that Adam and RMSprop optimizers are effective for practical deep learning issues.
2 sharesSource ↗
The research investigates how central bank communications impact volatility in different markets, offering valuable information for investors and policy makers about the potential and limitations of monetary policy communications.
2 sharesSource ↗
The note introduces a straightforward measure of momentum and mean reversion effects in asset class returns, indicating that fixed income assets exhibit momentum effects while equities display short term momentum and long term mean reversion.
2 sharesSource ↗
Machine learning can predict the stocks held by successful mutual fund managers more accurately than other methods, with past ownership, market cap, and volume being key factors.
2 sharesSource ↗
Inflation impacts the liquidity of closed-end funds differently in the short and long term, with a confirmed rate showing a reverse relationship between the prime rate and liquidity, and between liquidity and CEFs discounts.
4 sharesSource ↗
A two-stage quantile neural network and spline interpolation method can accurately predict stock returns based on 194 stock characteristics and market variables, performing better than other models.
3 sharesSource ↗
Insurers are increasing corporate bond investments and reducing equity and cash holdings to enhance earnings, especially when parent companies barely meet or exceed quarterly earnings forecasts.
3 sharesSource ↗
Institutions and individuals provide more liquidity during price surges on the Taiwan Stock Exchange, with institutions more likely to do so during high inventory risk periods.
2 sharesSource ↗
Banks' positions regarding covered-interest parity deviations are affected by foreign safe asset scarcity, market power and segmentation, and demand concentration, as per a study using confidential supervisory data.
3 sharesSource ↗
A new metric, the Information Ratio Churn (IRC), indicates that a higher IRC leads to a lower realized Information Ratio, with 8% of assets under management invested in funds with an excessively high IRC.
2 sharesSource ↗
Research indicates that equity derivative traders in Kerala are significantly influenced by regret aversion, loss aversion, and mental accounting in their trading decisions, with variations seen among different age and education groups.
2 sharesSource ↗
Maturity and Liquidity: A study rejects standard corporate bond factor models in favor of a model featuring the global corporate bond market, a global maturity spread factor, and a global liquidity spread factor, although it doesn't price Japanese Yen bonds well.
2 sharesSource ↗
A new peer momentum strategy, based on firms co-searched by investors on the SEC EDGAR server, yields an annualized return alpha of 17, outperforming the shared-analyst peer momentum.
2 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
27 items
Fintech lenders are using alternative data and complex models to provide more loans to areas with high unemployment and business bankruptcy rates, aiding small businesses that struggle to get credit from traditional lenders.
22 sharesSource ↗
A new hedge strategy has been created to lessen carbon risk in diverse portfolios, enabling investors to decrease their carbon risk exposure without major losses in risk-adjusted returns, needing only an investment in one extra asset.
21 sharesSource ↗
Long-term straddle momentum, implied volatility, and illiquidity are identified as key predictors of cross-sectional FX options returns, making other characteristics insignificant after considering these three factors.
19 sharesSource ↗
The article discusses the use of PCA and LSTM machine learning methods for predicting Poland's yield curve, with LSTM providing the most accurate results.
16 sharesSource ↗
The study examines the effect of limit-to-arbitrage factors on the distress risk puzzle in Vietnam, revealing a negative correlation between distress risk and corporate profitability.
15 sharesSource ↗
The paper introduces a model for forecasting large realized covariance matrices of returns for the S&P 500 daily, improving forecasting precision and portfolio estimates.
14 sharesSource ↗
The research establishes arbitrage-free conditions for a parametric yield curve in the P-world and presents a bonds-portfolio optimization as a stochastic control problem.
14 sharesSource ↗
The research introduces a machine learning model that uses multicriteria optimization to reduce bias and enhance stability in data analysis.
25 sharesSource ↗
The research shows that simple machine learning methods like the KNN model, combined with PCA, can effectively predict bank failures.
20 sharesSource ↗
The study uses machine learning to examine the influence of personality traits and financial literacy on Private Pension System participation, highlighting significant factors like gender, age, and financial literacy.
15 sharesSource ↗
The research suggests a new framework using machine learning to predict the severity of marine accidents, with the Light Gradient Boosting Machine model showing the best results.
14 sharesSource ↗
The study reviews the use of Google Search Volume Index as an indicator for investor attention and stock market trends, finding a correlation between increased investor attention and market volatility and trading volume.
12 sharesSource ↗
A study reveals that machine learning models using unconventional data are more efficient in predicting credit losses and defaults, particularly during economic downturns.
30 sharesSource ↗
A stock-bond portfolio can gain significant diversification benefits by incorporating size- and momentum-based cryptocurrency factors, and these benefits can be amplified using machine-learning asset allocation strategies.
23 sharesSource ↗
An enhanced binary crayfish optimization algorithm (IBCOA) has been developed to improve feature selection in data mining and machine learning, which reduces dimensionality and increases classification accuracy.
19 sharesSource ↗
During the 2009-2015 Greek debt crisis, negative future narratives identified through text mining of newspaper articles influenced the spread of Greek bonds, indicating that perceived futures can affect investor behavior and lead to financial crises.
17 sharesSource ↗
The article advocates for the use of machine learning in international business research to enhance predictive accuracy and manage complexity, thereby aiding theory development.
16 sharesSource ↗
The study introduces a new method for creating property price indices using machine learning, which offers better prediction accuracy than linear models, but may have stability and bias issues in smaller samples.
15 sharesSource ↗
The paper suggests a model for flexible truck appointment systems at smart ports, using machine learning to process real-time data, predict disruptions, and manage port flows.
14 sharesSource ↗
The study introduces variable selection with random forests, a machine learning method, compares it with traditional linear models, and provides practical advice for its application.
14 sharesSource ↗
Long-term exposure to high market volatility can lead to underestimation of volatility, creating predictable stock returns; a strategy capitalizing on this can beat a standard index portfolio.
13 sharesSource ↗
Equity premium predictions for long-term country stocks based on a global factor model are more accurate than time-series models, resulting in substantial benefits in various developed equity markets.
10 sharesSource ↗
Insider trading can disclose information about the value of all securities held by the insider, indicating that even sales driven by liquidity and diversification can offer valuable insights into insider holdings.
8 sharesSource ↗
The article discusses the advantages of systematic investment strategies in syndicated leveraged loans, highlighting the success of short-term momentum and valuation styles.
6 sharesSource ↗
The paper investigates the effects of AI and digitalization on the macroeconomics of EU countries, including Romania, focusing on its relationship with GDP per capita, labor productivity, and IT employment.
1 sharesSource ↗
The study explores the impact of generational, gender, educational, and geographical differences on financial inclusion in Kenya, noting significant disparities among rural communities and women.
1 sharesSource ↗
The research looks into the impact of agency cost on auditor selection in Iranian nonfinancial firms, revealing a preference for lower-class auditors in high agency cost companies, unless financial experts are on the board.
1 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
20 items
The Body Transformer (BoT) architecture enhances robot learning by representing the robot's body as a sensor and actuator graph, proving more efficient than traditional transformers and multilayer perceptrons.
58 shares49 citations todaySource ↗
ECG-FM, a transformer-based model for ECG analysis, shows strong performance in predicting cardiac conditions, having been pretrained on 2.5 million samples.
55 shares121 citations todaySource ↗
A new framework improves 2D displacement estimation from Inertial Measurement Unit data by addressing the overlooked symmetry principle, proving effective on various datasets.
14 shares25 citations todaySource ↗
A new decoding method for Quantum Low-Density Parity-Check codes based on Graph Neural Networks outperforms conventional and neural-enhanced decoding algorithms in performance and complexity.
6 shares21 citations todaySource ↗
VisualAgentBench (VAB), a benchmark for training and evaluating Large Multimodal Models, showcases the significant yet evolving capabilities of these models across diverse scenarios.
5 shares97 citations todaySource ↗
The study suggests a Feedback-Aware Fine-Tuning (FAFT) method to improve Large Language Models' (LLMs) performance in real-world planning tasks by using both positive and negative feedback.
5 shares30 citations todaySource ↗
The paper presents Task Skill Localization and Consolidation (TaSL), a new framework for language models that enhances knowledge transfer and prevents forgetting, improving the balance between old and new knowledge.
4 shares11 citations todaySource ↗
The research introduces a new HCI-guided molecular design method that uses an unsupervised multimodal joint embedding to generate new molecules with similar phenotypic effects to a given image target.
4 shares10 citations todaySource ↗
The study introduces VizWiz-LF, a dataset of long-form answers to visual questions asked by blind and low vision users, and assesses the ability of vision language models to provide accurate and useful responses.
3 shares28 citations todaySource ↗
The paper presents OWL2Vec4OA, an improved ontology embedding system that uses edge confidence values from seed mappings to enhance the effectiveness of ontology alignment tasks.
2 shares9 citations todaySource ↗
The Self-Taught Evaluator approach enhances model evaluators using only synthetic training data, surpassing models like GPT-4.
410 shares68 citations todaySource ↗
RAGGED, a new framework, optimizes language models for document-based question answering by analyzing Retrieval-augmented generation configurations.
222 shares24 citations todaySource ↗
New quirky language models and datasets are developed to improve Eliciting Latent Knowledge research, aiding in extracting reliable knowledge from untrusted models.
176 shares63 citations todaySource ↗
A new study on abstention in large language models identifies areas for future work to enhance abstention abilities based on the query, the model, and human values.
99 shares148 citations todaySource ↗
The ReLU-KAN implementation simplifies the design of Kolmogorov-Arnold Networks and optimizes computation for efficient CUDA computing, achieving a 20x speedup.
46 shares53 citations todaySource ↗
A new method, instruction back-and-forth translation, is introduced for creating high-quality synthetic data to improve large language models, outperforming other datasets on AlpacaEval.
30 shares18 citations todaySource ↗
MCRank, a new benchmark for evaluating multi-conditional ranking in recommendation systems, is introduced, along with a decomposed reasoning method that boosts large language models' performance by 12%.
27 shares2 citations todaySource ↗
Machine Learning for Macrocycle Peptides: CREMP, a new dataset with over 36,000 unique macrocyclic peptides, is launched to support the development of machine learning models for peptide design and optimization in therapeutics.
23 shares23 citations todaySource ↗
A novel framework is proposed for reasoning on SHAP scores under unknown entity population distributions, enhancing feature scoring robustness in machine learning models.
20 shares3 citations todaySource ↗
Transformer Explainer, an interactive tool, is unveiled to help non-experts understand Transformers through the GPT-2 model, allowing real-time user input experimentation.
19 shares16 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
6 items
Recent models using automatic labeling have demonstrated better results than traditional manual labeling methods.
10,238 shares
RAG Foundry is a new open-source framework aimed at improving large language models for RAG applications.
292 shares
Software agents are proving to be useful in handling complex tasks in software engineering.
234 shares
Weight quantization is crucial for reducing memory usage of Language Learning Models on devices.
196 shares
Crab Benchmarkv0, a cross-platform benchmark with 100 tasks, was created for both desktop and mobile using Crab.
123 shares
Some online jailbreak prompt datasets can effectively attack Language Learning Models such as ChatGLM3, GPT3.5, and PaLM2.
89 shares
Repositories the letter featured.
10 items
The article offers a detailed list of machine learning and data science tools useful in different sectors, compiled by firmai.
7,173 shares
Backtesting: The piece presents a flexible, clear, and fast Python library created for backtesting quantitative strategies.
356 shares
Interpretability: The article explores the understandability and clarity of data and machine learning models.
1,579 shares
ML Containers: The article highlights the application of containers in machine learning.
7,590 shares
Jupyter Tool: The article showcases an AI-driven Jupyter Notebook capable of creating and modifying code cells, correcting errors, and interacting with data.
1,035 shares
An LLMbased Web Navigating Agent KDD24 presents a web navigating agent using LLM for efficient web browsing.
555 shares
WebApps in pure Python examines the creation and operation of web applications using Python.
567 shares
Real time face swap and oneclick video deepfake with only a single image uncensored explores a technology for real-time face swapping and deepfake videos using one image.
9,056 shares
Truly independent web browser discusses a web browser that functions independently from major tech companies.
14,174 shares
Infisical is the opensource secret management platform Sync secrets across your teaminfrastructure prevent secret leaks and manage internal PKI introduces Infisical, a platform for managing secrets and preventing leaks within a team.
14,062 shares
Industry news: funds, hiring, markets and regulation.
20 items
Cboe Global Markets is set to introduce options on its Volatility Index futures, subject to regulatory approval.
12 shares
Gabriel Trebilcock, co-founder of Ace Capital, has been named as the new head of local credit sales and trading at Banco Bradesco.
7 shares
A seasoned hedge fund professional is exploring the application of quant trading strategies in sports betting.
6 shares
Brevan Howard Asset Management has recruited Andrew Saxton and David Nash for its Asia credit team, after a 10% global staff cut.
5 shares
Hedge funds, pension funds, and retail traders faced billions in losses following a failed bet on stock market stability, triggered by a record intraday surge in the CBOE VIX index.
4 shares
Arini Capital's flagship fund recorded a 7% gain in July following a disappointing first half of 2022, as per Bloomberg.
4 shares
Reuters reports that hedge fund managers are cutting back on high-risk positions due to market instability, yen-funded trade unwinding, and potential US recession fears.
4 shares
Pershing Square Capital Management has invested in new companies, including Nike and Brookfield, for the first time in over a year in Q2 2024, according to Reuters.
4 shares
Repool's analysis reveals that New York tops the list in US hedge fund registrations with 12,732, followed by California and Connecticut.
4 shares
Citadel Securities is bolstering its team with experts from JPMorgan.
3 shares
Digital asset investment products saw inflows of $176m last week as investors took advantage of recent price drops, according to CoinShares' report.
3 shares
Hedge fund managers are favoring Amazon and Microsoft over Netflix and Meta, as per Jefferies' recent data.
3 shares
US hedge fund Whitebox Advisors backs a new restructuring plan for German battery manufacturer Varta, potentially allowing shareholders to inject new capital.
3 shares
Simon Robertshaw has been appointed as Chief Technology Officer for front office trading at Broadridge Financial Solutions.
3 shares
Liquidators for the bankrupt crypto hedge fund Three Arrows Capital are seeking $1.3bn from TerraForm Labs due to losses from the 2022 collapse of TerraForms TerraUSD and Luna tokens.
2 shares
Howard Hughes Holdings is contemplating a takeover bid from Bill Ackman's hedge fund, Perishing Square Capital Management.
2 shares
Employee departures are increasing at Segantii.
2 shares
Under Elliott Investment Management's pressure, Starbucks has appointed Brian Niccol, formerly of Chipotle Mexican Grill, as its new CEO, replacing Laxman Narasimhan.
2 shares
Starboard Value, a New York hedge fund, has acquired a stake in Starbucks, joining Elliott Investment Management as an investor in the coffee company.
2 shares
Episodes on markets, quant methods and economics.
10 items
The article features an interview with Stan Uryasev, the author of the Conditional Value at Risk paper, discussing his journey in quantitative finance and his wife's mathematical art.
11 shares
In a podcast recorded on August 14, 2024, Srini Ramaswamy and Ipek Ozil discuss the dynamics of the upcoming Treasury futures roll cycle.
10 shares
Jonny Goulden and Saad Siddiqui discuss the impact of extreme global market volatility on Emerging Market assets in a podcast recorded on August 8, 2024.
10 shares
Hager Radi discusses her work in biodiversity monitoring, the challenges she encounters, and the machine learning tools she uses for predicting species distributions with limited data.
8 shares
Lyn Alden discusses the Yen Carry trade, market dynamics, the US dollar system, and the impact of various central banks' policies on financial stability.
8 shares
Patrick and Brent Kochuba discuss market volatility, gamma, and the dispersion trade in the Huddle podcast.
7 shares
Michael Mauboussin talks about market concentration, equity issuance, stock buybacks, and the relationship between boom-bust cycles and AI in his latest research.
5 shares
Liang discusses the potential impact of Fed rate cuts on global equity markets and the state of the Chinese economy in a podcast hosted by Mirza Baig.
5 shares
Weston Nakamura discusses the global margin call, the strength of the yen, and its impact on global finance, comparing it to Japan's post-1990s bubble burst and the 2008 financial crisis.
5 shares
Arindam Sandilya and Patrick Locke discuss the current state of the FX carry trade and the outlooks for JPY, USD, CNY, and FX volatility in their latest podcast.
5 shares
Posts from quant and economics blogs and newsletters.
8 items
The Bank of Japan increased its interest rate to 0.25 due to a weak yen, causing a surge in the currency and concerns about a yen carry trade unwind.
1 shares
The Bank of Japan's interest rate hike to 0.25 led to a stronger yen and fears of a potential yen carry trade unwind.
1 shares
The Bank of Japan raised its interest rate to 0.25 due to a weak yen, leading to a stronger yen and concerns about a yen carry trade unwind.
1 shares
The Bank of Japan's interest rate increase to 0.25 caused the yen to strengthen and led to concerns about a yen carry trade unwind.
1 shares
The Bank of Japan increased its benchmark interest rate to 0.25% due to a weak yen, causing market concerns about a yen carry trade unwind.
1 shares
The Bank of Japan raised its benchmark interest rate to 0.25% due to a weak yen, leading to market fears of a yen carry trade unwind.
1 shares
The Bank of Japan increased its benchmark interest rate from 0 to 0.25%, causing the yen to strengthen and sparking market fears of a yen carry trade unwind.
1 shares
The Bank of Japan raised its benchmark interest rate to 0.25% due to a weak yen, resulting in a stronger yen and market concerns about a yen carry trade unwind.
1 shares
Posts from quant researchers on X.
8 items
Goodacre and Schlagman compare algorithmic trading in finance and sports betting, suggesting sports trading could be a new asset class.
9 shares
Griffin and Kruger's paper reviews research on financial market misconduct like market manipulation and insider trading.
2 shares
Recent studies highlight the potential of large language models in sentiment-driven trading strategies.
1 shares
Sestovic's paper offers simple formulas for the marginal Sharpe ratio, supported by numerical examples.
1 shares
Michaillat and Saez have created a recession indicator using vacancy rates, indicating a possible ongoing U.S. recession.
0 shares
Christoph Molnar explores the idea of interpretable machine learning in his discussion.
0 shares
Jiang and his team discovered that the skewness of investors' interest rate expectations can notably forecast market returns.
0 shares
The article suggests a potential downturn in the advancement of AI technology.
0 shares