Quant Letter: June 2024, Week-1

Weekly (49th Edition)

ArXiv

Finance

Efficiency of Dutch Auctions on Blockchains: The study by Milionis et al. (2023) explores the expected losses and time-to-fill in Dutch auctions in decentralized finance. It considers factors such as starting price, volatility, decay rate, and average interblock time, and examines the balance between execution speed and quality. (2024-05-31, shares: 3)

Miscellaneous

Distributional Forecasting with DRN: The article introduces the Distributional Refinement Network (DRN), a model that enhances predictive performance and interpretability in actuarial modelling by merging a baseline model with a flexible neural network. (2024-06-03, shares: 3)

Historical Trending

Debt Recycling: A study finds the success of debt recycling, a strategy involving a second loan to pay off a mortgage faster, depends on factors like the initial mortgage-to-equity ratio and economic conditions. (2024-05-29, shares: 7)

Limit Order Book Forecast: A new deep learning model, HLOB, has been developed for predicting Limit Order Book mid-price changes, outperforming nine other models and offering new insights into information distribution in Limit Order Books. (2024-05-29, shares: 6)

Broker Performance Optimization: A new method for assessing the efficiency of broker execution algorithms in reducing execution costs for large orders has been introduced, offering a robust framework for choosing the most cost-effective brokers. (2024-05-29, shares: 6)

Language Models as Cognitive Models: Researchers have found that Large Language Models (LLMs) pretrained on relevant arithmetic datasets can predict human behavior more accurately than many existing cognitive models. (2024-05-29, shares: 5)

Tickby-Tick Liquidity Provisioning: Early findings suggest that programmable automated market makers with concentrated liquidity capabilities are not most effective when focused solely on the current price. (2024-05-29, shares: 5)

Queue-Reactive Models with Order Sizes: The queue-reactive model has been expanded to include order sizes, types, and arrival rates, creating simulated markets that closely mirror real markets and exhibit similar volatility. (2024-05-28, shares: 3)

Worst-cases of Distortion Riskmetrics: The paper explores the worst-case scenarios of distortion risk metrics for general distributions with limited information, with applications for entropies, weighted entropies, and risk measures. (2024-05-29, shares: 2)

SSRN

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