Quant LetterNo. 17
83 items across 8 sections, as sent to readers on 28 September 2023. Paper titles open their ML-Quant page; ↗ goes to the source.
Quantitative-finance and ML-for-finance preprints from arXiv.
21 items
The study suggests a new method for hedging risky asset portfolios using ensemble algorithmic investment strategies, finding Bitcoin-based AIS to be the best diversifier for S&P 500 index-based AIS.
8 shares7 citations todaySource ↗
The research introduces a simple method for managing and hedging cross-asset portfolio risk using quadratic programming, emphasizing the link between economic ideas and their mathematical expressions.
7 shares1 citation todaySource ↗
The paper offers quantitative error limits for deep neural networks approximating option prices on a risky asset, demonstrating that DNNs can learn option prices with minimal error without the curse of dimensionality.
6 shares6 citations todaySource ↗
The paper presents a Markovian approximation of the ADO-Heston model, challenging previous beliefs that such approximation cannot replicate the behavior of the vanilla implied skew at small T.
4 sharesSource ↗
The study uses Arbitrage Pricing Theory and Quantile Regression to analyze the risk and return of crude oil stocks, identifying key risk factors and the impact of changes in West Texas Intermediate returns.
4 sharesSource ↗
The paper compares three portfolio design strategies using historical stock prices from the National Stock Exchange of India, identifying the highest return yielding portfolio for each sector.
3 sharesSource ↗
A new deep learning model can predict the success of startups at Series B and C investment stages, using data like funding metrics and founder characteristics.
8 shares10 citations todaySource ↗
A new machine learning framework can identify critical changes in complex systems and calculate the likelihood of rare events, using detailed spatiotemporal data.
6 shares2 citations todaySource ↗
An Investigation: The study investigates the reliability of scientific explanations when using explainable machine learning methods on science-based machine learning models, showing varying results based on the type of monotonicity.
6 shares2 citations todaySource ↗
A study has shown that a gray-box method can significantly reduce the profits of a Deep Reinforcement Learning-based trading agent, highlighting the need for stronger automated trading systems.
3 shares5 citations todaySource ↗
Research indicates that recommendation algorithms on e-commerce platforms can affect the dynamics of AI-based pricing algorithms, with profit-based systems promoting collusion and demand-based systems encouraging competition.
2 shares3 citations todaySource ↗
The newly proposed FaSTMAN framework improves the detection of suspicious money flows in large-scale transaction data by efficiently constructing a temporal graph of sequential transactions, surpassing two leading solutions.
2 shares13 citations todaySource ↗
The study suggests a combined approach to decrease Maximal Extractable Value in decentralized systems, indicating that neither fair ordering nor economic mechanisms alone can mitigate MEV effectively.
4 shares5 citations todaySource ↗
Efficiency and Slippage Analysis: The research analyzes the costs of trading on a decentralized exchange, showing that costs vary based on trade characteristics, and proposes that DEXs could be a trustworthy alternative to centralized exchanges for trading digital assets.
3 shares20 citations todaySource ↗
The research introduces a model for assessing a vulnerable derivative with bilateral cash flows, taking into account funding, credit, and wrong-way risks.
29 sharesSource ↗
The research demonstrates a mean-field control problem in portfolio liquidation models, showing that the value function follows a linear-quadratic form.
14 shares10 citations todaySource ↗
The paper compares Constraint Programming and Quantum Annealing for optimising rolling stock assignment, with both methods yielding similar results.
13 shares13 citations todaySource ↗
The article suggests a machine learning method to enhance the accuracy of individual predictions in numerical predictive modeling, compatible with any prediction model and not needing distributional assumptions.
20 sharesSource ↗
The paper introduces new policy gradient methods for stochastic control with exit time, showing they perform better than traditional methods and can adapt to realistic market conditions.
2 sharesSource ↗
The paper presents a probability scoring rule that evaluates a forecaster's economic performance against market consensus, promoting better information gathering and discouraging groupthink.
2 sharesSource ↗
The study presents a novel method for frontier estimation in econometrics, merging Data Envelopment Analysis and Stochastic Frontier Analysis via Bayesian artificial neural networks, tested on a dataset of large US banks.
16 sharesSource ↗
Working papers in finance and economics from SSRN.
31 items
The FSDA method combines feature selection and data augmentation to enhance the accuracy of machine learning models in predicting rare events in imbalanced financial data.
2 sharesSource ↗
Deep reinforcement learning (DRL) surpasses traditional methods in portfolio management, offering better risk-adjusted return and Sharpe ratio.
18 sharesSource ↗
The article presents a new toolkit that uses AI and yield curve modelling to detect potential risks in bank balance sheets, illustrated with two hypothetical banks.
15 sharesSource ↗
The research introduces a new method for assessing volatility spillovers in asymmetric realized covariance, proving its effectiveness with high-frequency data from major ETFs.
4 sharesSource ↗
The research investigates the progression of systemic risk in China's financial market using a new multiscale decomposition method, uncovering varying network characteristics in high and low volatility spillover networks.
4 sharesSource ↗
The article explores the link between option-implied volatility spreads and option-implied borrow rate in Chinese SSE 50 ETF options, discovering a significant negative correlation and nonlinearity.
2 sharesSource ↗
The article discusses the application of Large Language Models (LLMs) and machine learning in assessing trademarks for registration, showing how an LLM can help identify issues and prepare data for machine learning algorithms.
2 shares2 citations todaySource ↗
News Analysis: A new system using news coverage and machine learning can accurately detect financial fraud in Chinese companies from 2001 to 2022.
236 sharesSource ↗
A paper suggests the contextual effects model as a better method for handling nested data in research, over fixed effects and multilevel models.
2 sharesSource ↗
Egyptian investors' decisions are significantly influenced by the reliability of cybersecurity risk management, according to research.
2 shares2 citations todaySource ↗
Government interventions that increase interest rates enhance risk sharing efficiency, while those that lower rates promote inefficient risk-taking, a study suggests.
2 sharesSource ↗
A higher level of idiosyncratic volatility predicts lower stock returns, especially in central industries more exposed to such shocks.
3 sharesSource ↗
Legal Singularity Ahead: The idea of legal singularity, where law becomes entirely comprehensive and predictable, could be achieved through AI and new technologies in tax law.
2 sharesSource ↗
A study comparing four models for forecasting volatility in emerging markets found the HAR model best for long-term volatility and realised GARCH models for volatility clustering and persistence.
3 shares13 citations todaySource ↗
The European Market Infrastructure Regulation (EMIR) requires non-EU central counterparties to get approval from the European Commission to provide clearing services in EU financial markets.
22 sharesSource ↗
Research indicates that BlackRock, Vanguard, and State Street, the three largest asset managers, have limited capacity for active ownership due to their engagement targets and resource constraints.
34 sharesSource ↗
Tax-aware long-short factor strategies can lead to net capital losses exceeding 100% of the initial investment within three years, due to deferred capital gains, not increased capital losses.
4 shares3 citations todaySource ↗
According to the research, firms with more unused credit lines have higher returns due to greater liquidity needs, but are also more vulnerable to economic shocks.
2 sharesSource ↗
The research reveals that defaulted U.S. corporate bonds are traded to dealers with prior expertise in the bond, improving recovery rates and emphasizing the importance of dealer expertise.
3 sharesSource ↗
A study emphasizes the need to measure risk-adjusted returns in investments and trading, highlighting metrics like the Sortino Ratio, Calmar Ratio, and Pareschi Ratio.
20 shares4 citations todaySource ↗
A paper suggests using a simulation approach with mortality-linked securities and stochastic mortality rates to manage capital risk in the insurance industry and meet regulatory capital requirements.
2 shares5 citations todaySource ↗
A study suggests that high-frequency traders' use of low-latency trading algorithms for arbitrage opportunities increases execution costs for other market participants, proposing batch auctions as a solution.
4 sharesSource ↗
From 2002-2019, active investment-grade corporate bond mutual funds saw significant positive returns, largely due to underpriced new bond offerings to funds with strong underwriting relationships.
121 sharesSource ↗
Data breaches at banks lead to a loss of insured and brokered deposits and negatively impact stock returns, but do not affect long-term operations; banks often increase lending after a breach, likely due to CEO compensation incentives.
74 sharesSource ↗
Current pricing models for SP 500 and VIX options are insufficient, but a new model controlling higher-order moments of risk-neutral return distribution outperforms alternatives and reconciles the two markets.
155 sharesSource ↗
A dynamic model reveals that the predictability of noise trading flows influences return predictability at both individual asset and factor levels, potentially causing asset price bubbles when flows show excessive momentum.
234 sharesSource ↗
Firms diversify investments into various industries to mitigate risks, but this can result in decreased growth, equity value, and financial constraint, leading to inefficient resource allocation and a drop in overall productivity.
8 sharesSource ↗
Including defined benefit pension funds in an asset pricing model enhances its performance in matching historical equity premium and riskless rate, and offers significant risk sharing benefits.
124 sharesSource ↗
The process of creating an index, particularly in less active stock markets, greatly influences the index and its statistical characteristics, as shown by a historical Finnish stock market database.
73 sharesSource ↗
The Barndorff-Nielsen Shephard volatility model is expanded to include a jump Ornstein-Uhlenbeck equation with a non-zero stochastic mean-reversion level, offering insights into variance swap pricing.
86 sharesSource ↗
The performance and volatility of sustainable indices are influenced by regime-switching, with positive shocks impacting volatility differently than negative ones, as demonstrated by a study of major sustainable indices from 2009 to 2017.
2 sharesSource ↗
Papers that shipped their code, from the Papers with Code feed (2023-25).
5 items
Generation Quality Unleashed: The paper explores the untapped potential of diffusion UNet in enhancing generation quality.
633 shares
LongLoRA uses LLaMA2 7B or LLaMA2 70B to broaden context on a single 8x A100 machine.
353 shares
The article explores a hypothesized failure in logical deduction caused by the Reversal Curse.
86 shares
Multimodal Comprehension and Creation: The article presents DreamLLM, a learning framework that improves Multimodal Large Language Models by combining multimodal comprehension and creation.
65 shares
The article explains how COCO DEViT outperforms the current state-of-the-art open-vocabulary by 6.9 AP50 and reaches 50 AP50 in new categories.
48 shares
Repositories the letter featured.
10 items
Temporal Data Engineering and Augmentation: Temporian is a Python tool that improves and expands time-based data for machine learning uses.
140 shares
Limit Order Book Data Visualization and Analysis: R package is a tool for examining, visualizing, and rebuilding limit order book data.
140 shares
Quantitative Trading Platform Development: An open-source structure is available for creating quantitative trading platforms using Python.
43 shares
Programmatic Quantitative Trading: QUANT is a software designed for quantitative and algorithmic trading.
31 shares
Efficient Longcontext Finetuning for LongQA: Efficient longcontext finetuning is a technique for guided finetuning of the LongQA dataset.
361 shares
GPT4 Autonomy: The article explores an open-source project that aims to make GPT4 fully self-sufficient.
149,153 shares
Metatrader4MetaTrader5 as Web Socket Client: The piece provides a guide on transforming MetaTrader4/5 into a web socket client.
47 shares
The article presents kani カニ, a microframework for chat-based language models with customizable tool usage.
359 shares
The article offers a tutorial on creating type-safe code from SQL.
9,104 shares
Programming Language for Literate Programming Law Specification: The piece introduces a new programming language designed for literate programming law specification.
1,754 shares
Episodes on markets, quant methods and economics.
2 items
ML in Quant Finance Conf Pt 02: The second part of the Machine Learning in Quant Finance Conference is available to watch, featuring discussions on the application of machine learning in quantitative finance.
12 shares
ML in Quant Finance Conf Pt 01: The first part of the Machine Learning in Quant Finance Conference is available for viewing, focusing on the integration of machine learning in the financial sector.
12 shares
Posts from quant and economics blogs and newsletters.
2 items
Quantifiedstrategies.com is providing 200 complimentary trading strategies for active traders.
2 shares
Posts from quant researchers on X.
9 items
The article suggests that equity factors and raw returns usually perform better in bear markets due to the slow correction of mispricing.
4 shares
The new paper offers a detailed list of potential data sources across various fields including finance, medicine, retail, etc.
2 shares
The article explores the process of modeling liquidity in decentralized finance (DeFi) exchanges.
2 shares
The article analyzes the existence of a low-risk anomaly in the corporate bond market.
1 shares
The article investigates the role of technology in fostering new creative processes.
0 shares
The article explores the use of long-term pricing effects in understanding short-term price fluctuations.
0 shares
The article shares HBR's research on how AI is affecting knowledge-based professions.
0 shares
The article delves into the increasing interest in systematic corporate bond strategies, their limitations, and the effects of high-turnover strategies.
0 shares
Threads from r/quant, r/algotrading and friends.
3 items