arXiv research

An open market is a subset of an entire equity market composed of a certain fixed number of top capitalization stocks. Though the number of stocks in the open market is fixed, the constituents of the market change over time as each company's rank by its market capitalization fluctuates. When one is allowed to invest al…

This study reviews decentralized prediction markets, identifying key design variants and open problems.

Unified approach to equity markets with open and hybrid Jacobi models.

Open AI models affect bond yields differently than closed ones.

The financial market entropy is modeled using open quantum systems.

Model financial markets using open quantum systems to understand market imperfections.

Financial markets show a number of non-stationarities, ranging from volatility fluctuations over ever changing technical and regulatory market conditions to seasonalities. On the other hand, financial markets show various stylized facts which are remarkably stable. It is thus an intriguing question to find out how thes…

Proposes overnight volatility model for better market dynamics.

The study evaluates nine machine learning regressors for predicting NASDAQ stock opening prices.

Survey of AI in finance covering models, strategies, and knowledge systems.

In a stock market, the numeraire portfolio, if it exists, is the portfolio with the highest expected logarithmic growth rate at all times. A numeraire market is a stock market for which the market portfolio is the numeraire portfolio. We study open markets, markets comprising the higher capitalization stocks within a b…

Study finds discrepancies in open interest reporting for Bitcoin perpetual swaps.

In a model independent discrete time financial market, we discuss the richness of the family of martingale measures in relation to different notions of Arbitrage, generated by a class $\mathcal{S}$ of significant sets, which we call Arbitrage de la classe $\mathcal{S}$. The choice of $\mathcal{S}$ reflects into the int…

Study analyzes order transitions in high, medium, and low market cap stocks using Markov chains.

In this paper, we study a time-inconsistent consumption-investment problem with random endowments in a possibly incomplete market under general discount functions. We provide a necessary condition and a verification theorem for an open-loop equilibrium consumption-investment pair in terms of a coupled forward-backward …

It is believed by the majority today that the efficient market hypothesis is imperfect because of market irrationality. Using the physical concepts and mathematical structures of quantum mechanics, we construct an econophysics framework for the stock market, based on which we analogously map massive numbers of single s…

Study analyzes price change patterns across different market capitalizations using Markov chains.

PCA reveals a market factor in S&P500 implied volatilities.

The capitalization-weighted total relative variation $\sum_{i=1}^d \int_0^\cdot μ_i (t) \mathrm{d} \langle \log μ_i \rangle (t)$ in an equity market consisting of a fixed number $d$ of assets with capitalization weights $μ_i (\cdot)$ is an observable and nondecreasing function of time. If this observable of the market …

Email messages have been an important mode of communication, not only for work, but also for social interactions and marketing. When messages have time sensitive information, it becomes relevant for the sender to know what is the expected time within which the email will be read by the recipient. In this paper we use a…

Constant and symmetric price impact functions, most commonly used in agent-based market modelling, are shown to give rise to paradoxical and inconsistent outcomes in the simplest case of arbitrage exploitation when open-hold-close actions are considered. The solution of the paradox lies in the non-constant nature of re…

Investor attention predicts global equity market volatility during Ukraine invasion.

Study uses Open Banking data to estimate customer value, showing potential 21% increase.

Paper introduces a specialized text classification system for French Open Banking transactions.

Paper uses SAC RL to optimize market-making strategies.

Automates detection of fast-ramped flexibility events for DSOs.

EmTract extracts emotions from financial social media text.

We study a continuous-time version of the intermediation model of Grossman and Miller (1988). To wit, we solve for the competitive equilibrium prices at which liquidity takers' demands are absorbed by dealers with quadratic inventory costs, who can in turn gradually transfer these positions to an exogenous open market …

The increasing richness in volume, and especially types of data in the financial domain provides unprecedented opportunities to understand the stock market more comprehensively and makes the price prediction more accurate than before. However, they also bring challenges to classic statistic approaches since those model…

Study predicts customer data sharing in Open Banking and explains key factors.

Crashes have fascinated and baffled many canny observers of financial markets. In the strict orthodoxy of the efficient market theory, crashes must be due to sudden changes of the fundamental valuation of assets. However, detailed empirical studies suggest that large price jumps cannot be explained by news and are the …

Study macroscopic equity market properties affecting active strategies.

The aim of this paper is to identify the determinants of international stock markets integration. Intuitively we selected a great number of factors linked to financial integration. Then, we developed an international asset-pricing model with time-varying degree of integration. This model is estimated for 30 countries (…

Agent-based simulation assesses tradable credit schemes for congestion reduction.

Visualizes futures markets using particle physics tools.

The multi dimensional string objects are introduced as a new alternative for an application of string models for time series forecasting in trading on financial markets. The objects are represented by open string with 2-endpoints and D2-brane, which are continuous enhancement of 1-endpoint open string model. We show ho…

The paper analyzes binary option markets with exogenous information and price sensitivity.

We use the expectation of the range of an arithmetic Brownian motion and the method of moments on the daily high, low, opening and closing prices to estimate the volatility of the stock price. The daily price jump at the opening is considered to be the result of the unobserved evolution of an after-hours virtual tradin…

Order matching systems form the backbone of modern equity exchanges, used by millions of investors daily. Thus, their operation is strictly controlled through numerous regulatory directives to ensure that markets are fair and transparent. Despite these efforts, market manipulation remains an open problem. In this work,…

Large financial dataset tracks FOMC communications and their impact.

This paper describes the design, implementation, and successful use of the Bristol Stock Exchange (BSE), a novel minimal simulation of a centralised financial market, based on a Limit Order Book (LOB) such as is common in major stock exchanges. Construction of BSE was motivated by the fact that most of the world's majo…

Study finds key investing characteristics for success in equity markets.

Study shows marketable order routing to wholesalers benefits all traders, leading to lower market depth and price volatility.

We exploit a continuous time random walk description of stock prices to obtain a fast and accurate evaluation of their volatility from intraday data. We show that financial markets are usefully described as open physical systems. Indeed we find that the process determining market volatility is not stationary while the …

LLMs simulate financial markets, revealing consistent trading strategies and market dynamics.

AI agents in experimental markets exhibit behavioral patterns that aggregate into market dynamics.

Quarter-hour market bursts predict algorithmic trading and returns in crypto futures.

New LSTM model predicts stock market prices with improved accuracy.