Price-Aware AMM: Advanced Models
Advanced Models: The article presents models for improving quotes in automated market making platforms, considering complex price changes and demand fluctuations.
4 shares8 citations todaySource ↗
Quant LetterNo. 48
164 items across 11 sections, as sent to readers on 8 May 2024. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
7 items
Advanced Models: The article presents models for improving quotes in automated market making platforms, considering complex price changes and demand fluctuations.
4 shares8 citations todaySource ↗
The research investigates the Fourier-Laplace transforms of different volatility models, links them to the solution of a specific equation, and creates a numerical method for solving these equations for pricing options and volatility swaps.
4 shares8 citations todaySource ↗
Surrender Option Analysis: The paper analyzes Variable Annuities, particularly the holder's right to early termination, and introduces a new method for non-monotone stopping boundaries.
2 shares4 citations todaySource ↗
The study shows that improving financial literacy in Japan does not necessarily lead to more involvement in financial investments or retirement planning, indicating other strategies may be needed to encourage these financial activities.
3 shares2 citations todaySource ↗
The article introduces an ε-policy gradient algorithm for online pricing learning tasks. This algorithm merges model-based and model-free reinforcement learning methods, and optimizes regret by balancing exploration and exploitation costs. It is expected to achieve a regret of order √T over T trials.
3 shares1 citation todaySource ↗
The study introduces algorithms for adjusting model parameters in credit rating transition models, using different methods for high and low-default portfolios, with tests indicating precise outcomes.
3 sharesSource ↗
The research suggests a new method for estimating the potential risk of financial loss using limited data, which is resilient and provides superior statistical properties, surpassing traditional estimators in various loss distributions.
3 shares1 citation todaySource ↗
Working papers in finance and economics from SSRN.
39 items
The article explores how machine learning can identify design patterns in Object-Oriented Programming, potentially simplifying software maintenance.
3 sharesSource ↗
The paper suggests a machine learning method for optimizing the structure of 3D frames under seismic loads, surpassing traditional methods.
6 sharesSource ↗
The research looks into how central banks' quantitative easing can reduce debt costs for banks' equity holders, especially during the COVID-19 crisis.
2 sharesSource ↗
The article discusses the use of machine learning in health insurance for anomaly detection and predictive modeling, emphasizing the effectiveness of decision tree regression and random forest regressor.
2 shares1 citation todaySource ↗
The study investigates the influence of Bitcoin investors' sentiments on global stock market volatility and the relationship between Bitcoin and other financial assets.
2 shares1 citation todaySource ↗
The study explores permutation-invariant neural networks, which can process various data formats and generate results unaffected by the input data's sequence.
4 sharesSource ↗
The paper examines the risks in the banking industry and the different risk management strategies, based on data from secondary sources.
2 sharesSource ↗
The suggested model uses an explainable variational autoencoder to detect anomalies in multivariate time series data, overcoming issues of large data size, unknown anomalies, and unclear deep learning detection methods.
2 sharesSource ↗
The research shows that private equity buyouts can harm the retirement welfare of target firms' defined benefit plan participants, as these plans are often frozen, terminated, or replaced with inadequate substitutes.
2 sharesSource ↗
The article explores the challenges and opportunities of recent advancements in computing and data engineering, proposing Secure Vector Databases and Secure Vector Computation as potential solutions for machine learning applications using post-quantum cryptographic techniques.
2 sharesSource ↗
Gold is a valuable asset for hedging, with its prices predicting stock returns positively, contradicting common academic views, once the bias from expected dividend growth rate is considered.
45 sharesSource ↗
Mutual funds investing in the same stocks underperform by 1.4% annually compared to passive benchmark funds, due to high demand for liquidity and the related discount for owning liquid stocks.
66 sharesSource ↗
The combination of big data and machine learning in the defence sector improves intelligence, strategic decision-making, and operational efficiency, but also brings up issues about data privacy, ethical implications, and potential misuse.
2 sharesSource ↗
Using GPT-4 and a BERT model for sentiment analysis reveals that emoji sentiment on social media significantly impacts cryptocurrency market trends and can be utilized to create trading strategies.
2 sharesSource ↗
Stablecoins, digital assets tied to stable currencies, do not always deliver on their promise of stability, with volatility varying based on analysis frequency.
2 sharesSource ↗
The research paper investigates the creation of efficient AI models for autonomous decision-making in dynamic information systems, emphasizing data analysis, algorithm optimization, and sensor integration.
2 sharesSource ↗
A new study applies extreme value statistics to independent data with varying distributions, introducing a new asymptotic theory and its applications to the lifespan of identical twins and global earthquake energies.
3 shares3 citations todaySource ↗
The paper explores the challenges and implications of AI supply chains, which are networks of datasets, models, and tools used in the development and deployment of machine learning products.
2 sharesSource ↗
The study finds that startup founders, while valuing partnerships with ESG-focused venture capitalists, often prioritize profit-driven investors due to financial concerns, particularly among profit-driven, smaller startups, Republican founders, and high-emission industries.
2 sharesSource ↗
The article explores the vice premium concept in investments, where businesses deemed socially unacceptable yield higher returns, and its impact on startup governance and economy.
40 sharesSource ↗
The article reveals that the use of Treasury futures by mutual funds varies significantly over time and across funds, influencing the variation in aggregate Treasury futures open interest.
2 shares3 citations todaySource ↗
The article examines the differences in cryptocurrency pricing across 80 global exchanges, emphasizing the influence of exchange features and regulatory environments on arbitrage opportunities.
4 shares1 citation todaySource ↗
The article investigates the Fourier-Laplace transforms of various polynomial Ornstein-Uhlenbeck volatility models, linking it with the solution of an infinite dimensional Riccati equation.
11 shares8 citations todaySource ↗
The article highlights the significant growth of equity crowdfunding campaigns for small firms during the COVID-19 pandemic, indicating a shift towards equity as the primary funding choice.
2 shares1 citation todaySource ↗
Research indicates that large dealers can manipulate prices and increase costs in the foreign exchange market through coordinated trading and information sharing.
2 sharesSource ↗
Economic policy uncertainty and stock market volatility negatively affect the interconnectedness of clean energy, electric vehicles, and rare earths stock markets, according to a study.
2 sharesSource ↗
A study finds that retail investors favor a market where index providers have significant control over passive funds.
2 sharesSource ↗
The study reveals an asymmetric relationship between the returns of the S&P 500 index and its constituents during high market volatility, especially for stocks with lower dividends and higher return volatilities.
3 sharesSource ↗
Research on the Indian economy indicates a positive link between Foreign Direct Investment (FDI) and trading, suggesting that increased FDI will enhance GDP.
2 sharesSource ↗
The article suggests that analyst cash flow predictions are swayed by price changes not related to cash flow news, using a model that aligns subjective beliefs data with asset pricing models.
394 sharesSource ↗
The authors share risk management challenges in the crypto field and offer risk mitigation strategies based on their trading desk experiences.
296 sharesSource ↗
The study explores the impact of disagreement between retail and institutional investors on stock liquidity, efficiency, and returns, concluding that increased liquidity may decrease informational efficiency.
294 sharesSource ↗
The research examines various algorithm models used in stock trading in the last five years, revealing their primary use for prediction and their potential to enhance portfolio strategy accuracy.
8 sharesSource ↗
The paper introduces a dynamic model of the implied volatility surface and its underlying asset, showcasing its utility as a risk management tool and its capability to accurately predict the VIX distribution.
2 sharesSource ↗
The research shows that stock returns are influenced by how much a company's actual leverage deviates from its target, especially during economic growth periods, introducing a new risk factor called VDOL.
85 sharesSource ↗
The paper suggests using cointegration-based pair trading in Forex markets to improve reliability and objectivity, offering profitable strategies and contributing to algorithmic financial market frameworks.
2 sharesSource ↗
The article highlights the difficulties in allocating assets to private markets due to unique cashflow dynamics and portfolio variations, indicating the need for dynamic cash management strategies in portfolio optimization.
2 sharesSource ↗
The research develops a new uncertainty index using machine learning, showing its strong predictability of stock market returns, especially during periods of high uncertainty and sentiment.
2 sharesSource ↗
The study employs a machine learning approach to develop a new macroeconomic index for predicting stock returns, showing its significant predictive power and economic value in asset allocation, and its complementary relationship with investor sentiment.
2 sharesSource ↗
Economics working papers from RePEc's NEP field reports.
29 items
The article highlights the significant role of big data and AI in revolutionizing the finance industry, stressing the need for financial expertise combined with data analytics skills.
26 sharesSource ↗
The study investigates the effect of feedback trading on India's market volatility during the COVID-19 pandemic, revealing that foreign institutional investors' positive feedback trading results in negative autocorrelation in market returns.
23 sharesSource ↗
The research uncovers recurring volatility and volume patterns in Bitcoin and Ether across various exchanges, indicating that price formation primarily happens on centralized exchanges, while price adjustments on decentralized exchanges are slower.
19 sharesSource ↗
The paper examines the link between the Indian stock market and the top four global economies pre and post-COVID-19, discovering significant volatility spillover from these markets to India, which investors and policymakers should take into account.
18 sharesSource ↗
The study examines the characteristics of kinks in efficient frontiers, demonstrating the absence of tangency in some ranges and the consistent presence of kinks in portfolio choices.
16 sharesSource ↗
A comprehensive review of 2022 papers on Explainable AI in Finance shows extensive research in risk management and portfolio optimization, but a lack of study in anti-money laundering.
16 sharesSource ↗
The paper suggests that the level of network connection in financial networks can either stabilize or intensify market fluctuations, based on the degree of network connectivity.
14 sharesSource ↗
The study applies factor investing strategies to the cryptocurrency market, introducing a weekly rebalancing method and using the Newey–West standard error approach to tackle the market's high volatility and continuous trading.
13 sharesSource ↗
The research introduces a memory-enhanced momentum strategy for commodity futures markets, using variance ratios to predict the persistence of past winners and losers, surpassing traditional momentum strategies.
12 sharesSource ↗
Machine learning study on Chinese data from 1993-2016 reveals credit is a better output predictor than money, but its effectiveness has decreased since 2007 due to financial development, indicating a need for market reforms and better non-monetary asset classification.
28 sharesSource ↗
The article presents the ddml package for double/debiased machine learning in Stata, supporting estimators of causal parameters for five econometric models, and suggests its use with stacking estimation, supported by Monte Carlo evidence.
20 sharesSource ↗
The research proposes two control function approaches to adjust machine learning when training and prediction samples differ on unobserved dimensions, showing that ignoring such selection can result in higher predicted vote shares for incumbents in gubernatorial elections.
17 sharesSource ↗
A machine learning study predicting stock price changes found the LSTM classifier to be superior to RF and SVM, and these data-driven methods outperform a random choice strategy, challenging the random walk and efficient market hypotheses.
17 sharesSource ↗
A machine learning model has been created to enhance the selection process for social safety net programs, featuring a mobile app for applications and results, with the random forest-based algorithm proving most accurate.
16 sharesSource ↗
A machine learning-based credit risk assessment model for Micro Small and Medium-sized Enterprises (MSMEs) has been launched, classifying borrowers based on credit and transaction data, achieving a balanced accuracy of 92%.
14 sharesSource ↗
A multi-output regression model has been suggested for hierarchical forecasting in supply chains, using variables from different hierarchical levels to produce reliable forecasts, especially during deep promotional discounts.
13 sharesSource ↗
A machine learning model using XGBoost has been developed to enhance the accuracy of project cost forecasting, providing consistent and accurate estimates throughout project execution.
12 sharesSource ↗
A study using machine learning methods revealed that equity anomalies do not predict overall market returns, questioning the belief that anomalies collectively provide useful information for forecasting market risk premia.
11 sharesSource ↗
The article suggests a machine learning approach to create big data-based macroeconomic fan charts, capable of managing non-Gaussian asymmetric heavy-tailed data and their non-linear interactions, beneficial for public policy decision making.
16 sharesSource ↗
The article explores the application of machine learning in the COLIEE competition, using data augmentation techniques to address the lack of annotated data in legal text analysis, and a cutting-edge language model to enhance legal information extraction and entailment predictions.
13 sharesSource ↗
Research shows that multifactor models are generally effective in pricing sustainable equity portfolios in the Pakistan Stock Exchange–Karachi Meezan Index (PSX–KMI).
16 sharesSource ↗
Asset valuation models are significantly affected by both market-level and stock-level investor sentiments, with the latter having a greater impact.
8 sharesSource ↗
A study is being conducted to identify the factors influencing gold prices in Malaysia, using macroeconomic indicators like GDP, inflation rate, interest rate, unemployment rate, and exchange rate.
7 sharesSource ↗
An International Financial Conditions Index for South American economies is proposed to evaluate financial conditions over time, focusing on the effects of the Russian invasion of Ukraine and commodity prices.
7 sharesSource ↗
The article suggests a new investment strategy for endowments and foundations, recommending two optimized long/short funds to outperform the traditional stock/bond split and maintain value in volatile markets.
7 sharesSource ↗
The study finds a significant change in international consumer price index inflation comovement in 2008, with global factors having a greater influence on national inflation rates, especially the noncommodity global factor.
6 sharesSource ↗
The article presents a new method for creating robust portfolios using the Chance Constrained Data Envelopment Analysis model, which minimizes systematic risk and maximizes returns during market downturns, especially for risk-averse investors.
6 sharesSource ↗
The research uses a dynamic factor model to analyze house price movements, suggesting a possible national bubble in the US housing market as the national factor has been disconnected from identified macroeconomic shocks since 2014.
5 sharesSource ↗
The article proposes a new accounting tool for early fraud detection and prevention, testing the importance of certain financial statement positions and creating a new financial statement fraud detection model.
5 sharesSource ↗
The general machine-learning papers the letter carried in 2023-25.
19 items
Prometheus 2 is a new open-source language model evaluator that aligns more closely with human and GPT-4 judgements and can process both direct assessment and pairwise ranking formats.
361 shares541 citations todaySource ↗
Pair Customization is a new method for art reinterpretation that learns stylistic differences from a single image pair and applies the style to the generation process, preventing overfitting.
91 shares51 citations todaySource ↗
A new method for sparse view synthesis without camera poses uses the 3D Gaussian splatting method and introduces an expected surface concept, resulting in significantly better quality than other methods.
29 shares49 citations todaySource ↗
The research combines mirror descent-based variational inference with Gaussian process for few-shot classification, enhancing accuracy, uncertainty measurement, and faster convergence.
15 shares2 citations todaySource ↗
The authors suggest a sparse-matrix factorization technique for calculating latent query and item embeddings, enhancing recall and speed in cross-encoder models and reducing computational needs.
14 shares4 citations todaySource ↗
The paper presents a framework for post-processing machine learning models to ensure multi-group fairness in predictions, applicable in image segmentation, hierarchical classification, and text generation.
12 shares15 citations todaySource ↗
The research proposes a factuality-aware alignment process for large language models, reducing false facts generation and enhancing the model's instruction-following accuracy.
8 shares62 citations todaySource ↗
The paper introduces Plan-Seq-Learn, a method that uses motion planning to connect abstract language and learned low-level control for solving long-horizon robotics tasks, achieving top-tier results.
8 shares105 citations todaySource ↗
Large language models may not be truly reasoning but overfitting to specific datasets, as shown by decreased accuracy on new benchmarks.
1,161 shares238 citations todaySource ↗
Med-Gemini, an AI model for medical applications, outperforms previous models and human experts in medical benchmarks, indicating potential for real-world medical use.
1,114 shares446 citations todaySource ↗
Wanda, a new method, efficiently prunes weights in Large Language Models without retraining, offering a more efficient approach to inducing sparsity in pretrained models.
721 shares981 citations todaySource ↗
CLoRA, a new method, prevents catastrophic forgetting in text-to-image models when introducing new concepts, achieving top performance in continual learning settings for image classification.
192 shares175 citations todaySource ↗
The article introduces Diffusive Gibbs Sampling (DiGS), a new method for sampling from multi-modal distributions, which performs better in tasks like Bayesian neural networks and molecular dynamics.
171 shares24 citations todaySource ↗
The paper presents a new method to enhance the quality of relevance labels in search systems using large language models, proving to be more efficient and cost-effective than third-party labellers.
149 shares297 citations todaySource ↗
The study introduces geo-FNO, a new framework for solving partial differential equations on any geometry, proving to be faster and more accurate than standard and machine learning-based solvers.
126 shares727 citations todaySource ↗
The report summarizes the latest techniques for reconstructing models of dynamic, non-rigidly moving scenes, discussing potential applications and future research directions.
68 shares49 citations todaySource ↗
LLM-Generated Dialogues: The article introduces LUCID, an automated data generation system that creates realistic dialogues, aiming to enhance the dialogue capabilities of virtual assistants by addressing the lack of high-quality data.
37 shares11 citations todaySource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
12 items
A new framework has been created to automatically enhance deep learning models for specific tensor computations.
9,577 shares
The efficiency of Large Language Models (LLMs) in tasks like extended conversations and document analysis is limited due to restricted context windows.
9,235 shares
Kolmogorov-Arnold Networks (KANs), based on the Kolmogorov-Arnold theorem, are suggested as possible replacements for MultiLayer Perceptrons (MLPs).
4,923 shares
The success of large language models has greatly improved the development of visual language models.
478 shares
Deepfake detection faces challenges in generalization, particularly when the training and testing data sets are not similar.
293 shares
A collaborative prompting method enhances the performance of a single language model, enabling it to function as both a conductor and a group of specialists in different tasks.
227 shares
WavCraft is a novel system that employs large language models to connect diverse task-specific models for audio content production and modification.
189 shares
GPT4, a proprietary language model, is frequently utilized to assess the performance of different language models.
131 shares
The article presents the first conversational agent that allows extensive hybrid data access to large knowledge databases through a new language named SUQL.
126 shares
Despite advancements in Natural Language Processing (NLP) through Large Language Models (LLMs), challenges such as hallucination and the requirement for domain-specific knowledge persist.
76 shares
Highly trained Gaussian fields can be memory-intensive, requiring up to three million Gaussian primitives and over 700 MB of memory.
48 shares
The article presents Score-based Iterative Reconstruction (SIR), a new algorithm for efficient 3D generation using a multiview score-based diffusion model.
46 shares
Repositories the letter featured.
10 items
The article explores the use of machine learning techniques in managing financial assets.
16 shares
The piece reviews a library for pricing financial instruments like bonds and derivatives, featuring risk sensitivity tools.
71 shares
The article presents a Python library for backtesting trading strategies.
13,080 shares
The article investigates the application of Python Notebooks in investment finance research.
784 shares
The article provides instructions on operating IBKR GatewayTWS within a Docker container.
142 shares
The article presents Penpot, an open-source tool that enhances collaboration between designers and coders.
27,874 shares
The article explores a fast, customizable vulnerability scanner that uses a simple YAML-based DSL.
17,310 shares
The article evaluates a multilingual text-to-speech library from MyShell.ai, supporting several languages including English, Spanish, French, Chinese, Japanese, and Korean.
3,567 shares
The article details how pyinfra, a Python tool, can automate infrastructure tasks, execute commands, manage configurations, and deploy services.
3,186 shares
Industry news: funds, hiring, markets and regulation.
19 items
Farre Quantitative Strategies -> Finance: Farre Quantitative Strategies: Farre Quantitative is exploring innovative quantitative trading strategies that could revolutionize the financial sector.
10 shares
Ai For Alpha has introduced its CTA Flows Oracle technology, which uses AI to forecast managed futures funds flows across various asset classes.
9 shares
Gerald Chua, formerly of Lauro Asset Management, has taken up a new role as a Portfolio Manager at Kamet Capital, according to Citywire Asia.
7 shares
MFA has proposed to the Commodity Futures Trading Commission to incorporate the use of artificial intelligence tools in derivatives markets.
6 shares
Activist hedge fund TOMS Capital Investment Management has bought a significant stake in Kellanova, previously known as Kellogg Company.
6 shares
The Securities and Future Commission in Hong Kong has started insider trading criminal proceedings against Segantii Capital Management Founder, Simon Sadler, and ex-trader Daniel La Rocca.
6 shares
Tabula Capital plans to sell its parent European ETF business, Tabula Investment Management, to global asset manager Janus Henderson Group.
5 shares
BlueCrest Capital intends to expand its trading teams by 10% by year-end due to high returns.
5 shares
Hedge funds experienced growth in April as equities fell, with macro strategies leading and the HFRI Macro Asset Weighted Index rising 2.6%.
4 shares
LMR Partners has grown its commodities team to capitalize on a new oil-based investment strategy introduced earlier this year.
4 shares
South Korea's financial regulator has found $156m worth of alleged illegal trading by nine global investment banks during a short selling investigation.
4 shares
Beryl Capital Management has named Michael Callahan as Managing Director Head of Investor Relations, responsible for client service, capital formation, marketing, and business strategy.
3 shares
Citadel is hiring more quantitative analysts, also known as quants.
3 shares
Hedge funds have shown increased optimism towards consumer stocks in the week ending 3 May, influenced by a weakening US labour market and potential interest cuts hinted by Federal Reserve Chair Jerome Powell.
3 shares
Financial services firm Clear Street has hired several senior-level employees in its prime brokerage business to expand its institutional division.
2 shares
Jeffrey Cantafio has been appointed as Vice President of Business Consulting at Fidelity Prime Services, reporting to James Coughlin.
1 shares
Hedge fund Exodus Point reportedly gained around 2% in Q1 due to a bond market basis trade, which has raised regulatory concerns.
1 shares
The article debates whether Figgie could be considered as Pit the younger.
0 shares
The article explores the possibility of executives manipulating sentiment engines and deceiving LLM's Risk.
0 shares
Episodes on markets, quant methods and economics.
10 items
Well Being: Dr. Meir Statman discusses his book A Wealth of Well Being and his research on behavioral finance and investment decisions in a podcast.
13 shares
Srini Ramaswamy and Ipek Ozil explore the link between US swap spreads and a type of term premium in a podcast.
9 shares
Jonny Goulden and Saad Siddiqui discuss the impact of recent market developments on the EM fixed income asset class in a podcast.
8 shares
West Africa Cocoa: Tracey Allen and Gbolahan S Taiwo delve into global commodities research in a podcast.
7 shares
Real Estate Success: Clint Murphy shares his knowledge on property investments, personal growth, and team development in a podcast episode.
7 shares
Hendrik Bessembinder highlights the significance of diversification and retaining successful stocks for long-term returns in his research.
7 shares
Despite robust US growth and persistent inflation, Jay Powell is cautious about interest rate adjustments, while the Hang Seng index and Brent crude oil prices show positive and negative trends respectively.
6 shares
Nelligan, Gupta, and Lund share their perspectives on the economic, rate, and FX scenarios in Sweden and Norway, in anticipation of central bank meetings.
5 shares
Francesca Trivellato's book debunks the myth that Jews created the credit instruments known as bills of exchange, tracing its roots and effects in early modern Europe.
5 shares
Barry and Chandan examine the potential impact of the FOMC meeting and April employment report on US rates and FX markets, including possible effects on USDJPY and EURUSD.
5 shares
Posts from quant and economics blogs and newsletters.
7 items
The article shares useful AUDJPY trading strategies, emphasizing on diversifying strategies and managing risks.
7 shares
The article provides insights on trading the AUDUSD currency pair in forex, highlighting its complexity and potential for profit.
5 shares
The article compares paper trading and live trading, underlining their significance in successful trading.
4 shares
The article advises against constant full investment with maximum leverage.
3 shares
The article supports the use of complex models for market timing due to their ability to detect nonlinear relationships.
2 shares
The article delves into the life and influence of Edward Thorp, a mathematician who transformed gambling and financial trading.
0 shares
The author recounts a personal experience of skipping their graduation ceremony at the University of Southampton.
0 shares
Talks, lectures and tutorials.
5 items
The author revisits a 2017 video about job types in quantitative finance, suggesting a more specific title would have been beneficial.
5 shares
Will Cong presented a data-driven approach to corporate finance and AI-guided decisions at an ABFR seminar.
0 shares
A raw screen recording from the Workshop on AI in Finance at Texas State University San Marcos is accessible on GitHub.
5 shares
The article explores Christina Qi's journey towards choosing a career in finance.
7 shares
The article recommends candidates to be ready to discuss their projects and experiences in depth during interviews.
0 shares
Posts from quant researchers on X.
7 items
Lasse Pedersen from Copenhagen Business School provides a detailed course on Big Data Asset Pricing, discussing empirical asset pricing, multiple testing problems, and machine learning.
8 shares
A study by Erb and Harvey investigates the elements affecting gold prices, such as ETFs, China, Costco buyers, and the difficulty of obtaining trustworthy data.
2 shares
A recent paper examines carry strategies and their possible advantages for portfolio diversification.
2 shares
The article explores the use of 1-minute intraday data to identify systemic risk in financial systems.
1 shares
The article reviews an AQR white paper discussing the advantages of using complex models for return predictions.
0 shares
The article investigates different algorithms for predicting building energy use, emphasizing the superior predictive power of memory-based models.
0 shares
The article presents an Earnings Conference Call Analyzer, a tool designed for financial analysis.
0 shares