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Quant LetterNo. 28

December 2023, Week 1

73 items across 9 sections, as sent to readers on 6 December 2023. Paper titles open their ML-Quant page; ↗ goes to the source.

arXiv

Quantitative-finance and ML-for-finance preprints from arXiv.

14 items

Finance6

01

Stock return distribution

A new model suggests that financial markets often underreact to small events and overreact to major ones, with a stronger reaction to positive events.

5 shares4 citations todaySource ↗

02

Monotonic risk measures

Monotonic mean-deviation measures have been characterized from a general model, providing new examples of consistent risk measures and establishing the consistency and normality of the natural estimators of the measures.

4 shares3 citations todaySource ↗

03

Rough Volatility: Range Volatility Estimators

Range Volatility Estimators: The study further analyzes volatility dynamics using range-based proxies, confirming that log-volatility behaves like fractional Brownian motion and the rough fractional stochastic volatility model predicts better.

7 shares3 citations todaySource ↗

04

FinMem: LLM Trading Agent

LLM Trading Agent: The article presents FinMem, a new Large Language Model-based system designed to improve financial decision-making by retaining crucial information beyond human capabilities.

27 shares253 citations todaySource ↗

05

ESG Raw Scores vs Aggregated Scores

The paper compares the predictive power of raw and aggregated Environmental, Social, and Governance (ESG) scores on company stock returns and volatility, with raw ESG data proving most predictive.

5 shares1 citation todaySource ↗

Crypto & Blockchain5

01

DeFi: Protocols, Risks, Governance

Protocols, Risks, Governance: The article discusses the benefits of decentralized finance (DeFi) over traditional finance, the function of smart contracts, and the associated risks, highlighting the need for more research on scalability and auditing.

7 shares22 citations todaySource ↗

02

DeFi Market Misconduct Analysis

The paper investigates the rise of blockchain and DeFi, potential market misconduct, and the challenges of creating a DeFi regulatory framework, suggesting possible regulation strategies.

7 shares3 citations todaySource ↗

04

Uniswap Daily Transaction Indices

The study explores the effect of Layer 2 solutions on DeFi by analyzing millions of transactions from Uniswap, offering insights into adoption, scalability, and decentralization in the DeFi sector.

5 shares24 citations todaySource ↗

05

Cryptocurrency Tail Risk and Systemic Risk Estimation

The paper introduces an expectile-based approach to assess the tail risk of cryptocurrencies, presenting the Marginal Expected Shortfall as a tool to measure the impact of a single cryptocurrency on the market's systemic risk.

5 shares3 citations todaySource ↗

Historical Trending3

02

Theory and Stock Return Predictions

The research indicates that the predictability of cross-sectional return predictors decreases by half in post-sample scenarios, implying that theoretical models don't improve predictions and peer-review often misinterprets mispricing as risk.

48 shares5 citations todaySource ↗

03

Optimal Stopping with Neural Networks

The article highlights the benefits of using randomized neural networks to approximate solutions for optimal stopping problems, proving they are more efficient and faster than other machine learning methods.

38 shares49 citations todaySource ↗

SSRN

Working papers in finance and economics from SSRN.

13 items

Quantitative9

02

Machine Learning for Portfolio Performance

The study introduces a method to determine the impact of individual factors on portfolio performance, providing insights into the economic value of return predictability in machine learning models.

2 sharesSource ↗

07

Machine Learning Framework for Portfolio Choice

The paper presents a computational framework for solving dynamic portfolio choice problems with multiple risky assets and transaction costs, suggesting that having more assets can mitigate some illiquidity caused by transaction costs.

2 sharesSource ↗

Financial4

01

Competition between ETFs and Mutual Funds

The research indicates that less transparent active ETFs do not affect mutual fund investor flows, instead, the reputation of the cloned mutual funds helps the new ETFs attract more flows.

2 shares1 citation todaySource ↗

RePEc

Economics working papers from RePEc's NEP field reports.

7 items

Finance4

02

Bond Selection

The chapter discusses the challenges of bond selection and the use of traditional optimization techniques, highlighting the need for thorough analysis in portfolio construction.

20 sharesSource ↗

04

Forecasting Parameters in SABR Model

Two methods for predicting parameters in the SABR model, the vector autoregressive moving-average model and epsilon-support vector regression, both provide accurate fits, with the SABR model yielding superior pricing results.

15 sharesSource ↗

Statistical3

01

Real Estate Appraisals: ML vs Traditional Methods

ML vs Traditional Methods: Research indicates that machine learning, particularly XGBoost, offers the most precise predictions in Automated Valuation Models for residential properties, suggesting a need for regulators to consider various methods.

31 sharesSource ↗

02

Bitcoin Futures Forecasting with ML

Machine learning algorithms have proven to be more effective than traditional models in predicting Bitcoin futures prices, maintaining an average classification accuracy consistently over 50%.

18 sharesSource ↗

Machine learning

The general machine-learning papers the letter carried in 2023-25.

5 items

Recently Published3

01

Training Data Extraction from Language Models

The study shows that large amounts of training data can be extracted from different machine learning models, highlighting that current techniques do not prevent data memorization.

115 shares619 citations todaySource ↗

02

Benefits of Overparameterization in ML

The paper supports the theory that larger model size, more data, and more computation enhance performance in random feature regression, similar to shallow networks with only the last layer trained.

66 shares23 citations todaySource ↗

Historical Trending2

01

Universalizing Weak Supervision for Any Label Type

The article introduces a universal technique for weak supervision frameworks that can be applied to any label type, demonstrating improvements in various settings including learning-to-rank and regression problems.

71 shares36 citations todaySource ↗

02

Edge Directionality in Heterophilic Graphs

The study presents Directed Graph Neural Network (Dir-GNN), a new deep learning framework for directed graphs that surpasses traditional models in heterophilic benchmarks.

186 shares148 citations todaySource ↗

GitHub

Repositories the letter featured.

5 items

Finance5

01

Statistical ML Discovery

The article explores a machine learning package designed for accurate scientific discovery through statistical analysis.

113 shares

02

Advanced Sentiment Trading App

The piece presents a new web app for trading and investment research, featuring real-time sentiment analysis.

146 shares

03

Scalable Realtime Datastore

The piece examines a scalable datastore specifically created for metrics events and real-time analytics.

26,787 shares

04

Koopa Learning for Time Dynamics

The article announces the launch of a code for learning nonstationary time series dynamics using Koopman Predictors, set for NeurIPS 2023.

83 shares

Podcasts

Episodes on markets, quant methods and economics.

4 items

Quantitative4

01

Market States and Recession Prediction

The podcast explores the influence of AI in finance, potential recession indicators, and the effect of market volatility, featuring insights from industry expert Michael Khouw.

14 shares

02

The Quant Finance LIE

The podcast debunks the idea of a full stack quant in finance, suggesting individuals to focus on one primary area instead.

13 shares

03

Embracing Reality: Debunking AGI Hype

Debunking AGI Hype: Filip Piekniewski, an AI expert, debunks hype about artificial general intelligence and the singularity, focusing on real AI advancements.

8 shares

04

24 Interest Rate Derivatives Forecast

Srini Ramaswamy and Ipek Ozil predict the state of interest rate derivatives markets in 2024 in a podcast recorded in December 2023.

6 shares

Videos

Talks, lectures and tutorials.

4 items

Quantitative4

01

Language to SQL Generator with LLM

Rami Krispin explains how LLM models can be used to convert language into code, specifically developing a language to SQL translator via the OpenAI API.

0 shares

02

The Biggest LIE in Quant Finance

Krispin delves into the use of LLM models for translating language into code, focusing on the creation of a language to SQL translator through the OpenAI API.

9 shares

03

Yield Farming: Costs, Returns, and Risks

Costs, Returns, and Risks: The article debates the concept of a 'full stack quant' in quantitative finance, arguing that while such professionals exist, they typically specialize in a particular area rather than mastering all aspects.

68 shares

04

Covariance Matrix and Shrinkage

The article explores the problems of unstable covariance matrix in contemporary statistics and suggests a practical solution through statistical shrinkage.

8 shares

X / Twitter

Posts from quant researchers on X.

12 items

Quantitative7

Miscellaneous5

01

Obfuscation: More Sinister?

More Sinister?: The article explores the idea of effective obfuscation, questioning if it's a real accelerationism or a disguise for something darker.

0 shares

02

GenAI in Financial Services

The article shares a report by Oliver Wyman about the impact of GenAI in the financial services sector.

0 shares

03

Analyst Disagreement and Future Returns

The article reviews studies showing a negative link between analyst disagreement and future returns, emphasizing the importance of proxy choice in empirical results.

0 shares

Reddit

Threads from r/quant, r/algotrading and friends.

9 items

Quantitative5

Rising4

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