A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Exchange improves liquidity by using different bid and ask tick sizes.
Study compares market microstructure between two South African exchanges.
PRIME models cryptocurrency exchange market impact.
Paper establishes MLE consistency for market microstructure models.
We investigate the relative information efficiency of financial markets by measuring the entropy of the time series of high frequency data. Our tool to measure efficiency is the Shannon entropy, applied to 2-symbol and 3-symbol discretisations of the data. Analysing 1-minute and 5-minute price time series of 55 Exchang…
Stablecoins are unstable, but some are more stable than others.
In this paper, we provide non-parametric statistical tools to test stationarity of microstructure noise in general hidden Ito semimartingales, and discuss how to measure liquidity risk using high frequency financial data. In particular, we investigate the impact of non-stationary microstructure noise on some volatility…
A market fix serves as a benchmark for foreign exchange (FX) execution, and is employed by many institutional investors to establish an exact reference at which execution takes place. The currently most popular FX fix is the World Market Reuters (WM/R) 4pm fix. Execution at the WM/R 4pm fix is a service offered by FX b…
Financial markets can be described on several time scales. We use data from the limit order book of the London Stock Exchange (LSE) to compare how the fluctuation dominated microstructure crosses over to a more systematic global behavior.
Blockchain-based exchanges adopt based on token pair volatility and personal use.
Quantitative finance has had a long tradition of a bottom-up approach to complex systems inference via multi-agent systems (MAS). These statistical tools are based on modelling agents trading via a centralised order book, in order to emulate complex and diverse market phenomena. These past financial models have all rel…
We analyze realized volatilities constructed using high-frequency stock data on the Tokyo Stock Exchange. In order to avoid non-trading hours issue in volatility calculations we define two realized volatilities calculated separately in the two trading sessions of the Tokyo Stock Exchange, i.e. morning and afternoon ses…
In this work, we study the problem of learning the volatility under market microstructure noise. Specifically, we consider noisy discrete time observations from a stochastic differential equation and develop a novel computational method to learn the diffusion coefficient of the equation. We take a nonparametric Bayesia…
Study shows changes in information sharing between Bitcoin markets during 2017 crash.
Study on CFMMs pricing and hedging, developing models for LP and derivatives valuation.
Neural Hawkes method estimates cryptocurrency market microstructure and causality.
Microstructure of market dynamics is studied through analysis of tick price data. Linear trend is introduced as a tool for such analysis. Trend arbitrage inequality is developed and tested. The inequality sets limiting relationship between trend, bid-ask spread, market reaction and average update frequency of price inf…
Centralized exchanges influence staking behavior and decentralization in Proof of Stake blockchain ecosystems.
We calculate realized volatility of the Nikkei Stock Average (Nikkei225) Index on the Tokyo Stock Exchange and investigate the return dynamics. To avoid the bias on the realized volatility from the non-trading hours issue we calculate realized volatility separately in the two trading sessions, i.e. morning and afternoo…
This research compiles knowledge on decentralized exchanges with AMM protocols.
SHIFT simulates realistic financial markets for research and industry.
Novel method reconstructs liquidity data for CLMMs, optimizing dynamic liquidity strategies.
Enhances topology optimization with multiclass microstructures using latent variable Gaussian process.
A key problem in computational material science deals with understanding the effect of material distribution (i.e., microstructure) on material performance. The challenge is to synthesize microstructures, given a finite number of microstructure images, and/or some physical invariances that the microstructure exhibits. …
Paper uses MBO data for high-frequency price forecasting.
BBE simulates betting exchanges to generate synthetic data for AI research.
AIMM-X monitors markets for suspicious behavior using transparent scoring.
We present a novel approach to describing the microstructure of high frequency trading using two key elements. First we introduce a new notion of informed trader which we starkly contrast to current informed trader models. We describe the exact nature of the `superior information' high frequency traders have access to,…
Deep learning predicts stock price changes in Limit Order Books.
The tick value is a crucial component of market design and is often considered the most suitable tool to mitigate the effects of high frequency trading. The goal of this paper is to demonstrate that the approach introduced in Dayri and Rosenbaum (2015) allows for an ex ante assessment of the consequences of a tick valu…
A tick size is the smallest increment of a security price. It is clear that at the shortest time scale on which individual orders are placed the tick size has a major role which affects where limit orders can be placed, the bid-ask spread, etc. This is the realm of market microstructure and there is a vast literature o…
A new framework assesses liquidity risk in perpetual futures exchanges.
A VAE model predicts material properties and microstructures.
Polymarket-v1 Database tracks 1.2B trades across 1.3M markets with 100% ground-truth direction.
Establishes a microstructural foundation for a rough log-normal volatility model.
Framework automates microstructure image analysis for materials science.
Paper clusters microstructure measures for better stock return prediction.
Market Microstructure is the investigation of the process and protocols that govern the exchange of assets with the objective of reducing frictions that can impede the transfer. In financial markets, where there is an abundance of recorded information, this translates to the study of the dynamic relationships between o…
Optimizes natural frequencies of cellular composites with various microstructures.
Microstructures of a material form the bridge linking processing conditions - which can be controlled, to the material property - which is the primary interest in engineering applications. Thus a critical task in material design is establishing the processing-structure relationship, which requires domain expertise and …
This paper proposes a parametric approach for stochastic modeling of limit order markets. The models are obtained by augmenting classical perfectly liquid market models by few additional risk factors that describe liquidity properties of the order book. The resulting models are easy to calibrate and to analyze using st…
Adaptive market maker curves minimize arbitrage losses in DeFi.
We present a simple microstructure model of financial returns that combines (i) the well-known ARFIMA process applied to tick-by-tick returns, (ii) the bid-ask bounce effect, (iii) the fat tail structure of the distribution of returns and (iv) the non-Poissonian statistics of inter-trade intervals. This model allows us…
Two models incorporate market microstructure noise into asset pricing and option valuation.
Cryptocurrency patterns stable across market caps, validated by microstructure theory.
A new model prices assets considering market microstructure effects.
In this work, we provide a framework linking microstructural properties of an asset to the tick value of the exchange. In particular, we bring to light a quantity, referred to as implicit spread, playing the role of spread for large tick assets, for which the effective spread is almost always equal to one tick. The rel…
The study finds a liquidity premium in stock returns, but only after correcting for microstructure noise.