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arXiv research

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.

168,742 papers · 148 categories

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3773110146 · May 202619922001200920172026
48 results for market propagation

Study extends Lévy models to capture market propagation delays.

problem Capturing sudden events in related markets with stochastic delays.
method Extend multivariate Lévy models using self-decomposability and multivariate subordination.
result Derived closed-form expressions for characteristic function and implemented Monte Carlo scheme.

A key aspect of word of mouth marketing are emotions. Emotions in texts help propagating messages in conventional advertising. In word of mouth scenarios, emotions help to engage consumers and incite to propagate the message further. While the function of emotions in offline marketing in general and word of mouth marke…

2014-09-16abs ↗pdf ↗

Paper uses AI to predict stock market volatility with neural networks and genetic algorithms.

problem Traditional methods for predicting stock market volatility have high errors.
method Back-propagation neural network and genetic algorithm integrated model.
result The model predicts future volatility with low errors and high accuracy.

Investor flows in Korean equity market transmit shared information, not private signals.

problem Whether investor flows transmit private information or only public signals.
method Transfer Entropy networks constructed from investor-type flows over umNDates{} trading days.
result Investor flows transmit shared information, not private signals.

We analyze a proprietary dataset of trades by a single asset manager, comparing their price impact with that of the trades of the rest of the market. In the context of a linear propagator model we find no significant difference between the two, suggesting that both the magnitude and time dependence of impact are univer…

2017-02-26abs ↗pdf ↗

Using a rolling windows analysis of filtered and aligned stock index returns from 40 countries during the period 2006-2014, we construct Granger causality networks and investigate the ensuing structure of the relationships by studying network properties and fitting spatial probit models. We provide evidence that stock …

2015-07-22abs ↗pdf ↗

Study extends Gai-Kapadia framework to assess systemic risk in global equity markets.

problem Systemic risk and default cascades in global equity markets.
method Network analysis, threshold filtering, Monte Carlo simulations, tail risk assessment.
result System exhibits strong global resilience with negligible probability of large-scale failure.

A self-organized model with social percolation process is proposed to describe the propagations of information for different trading ways across a social system and the automatic formation of various groups within market traders. Based on the market structure of this model, some stylized observations of real market can…

2000-04-18abs ↗pdf ↗

The paper analyzes arbitrage opportunities in a large investor market with common stock noises.

problem Identifying arbitrage opportunities in a market with many competitive investors.
method Stochastic differential games and mean-field systems to study market dynamics and optimal arbitrage.
result Optimal arbitrage is characterized by a solution to a Cauchy PDE involving volatility terms.

A growing body of studies on systemic risk in financial markets has emphasized the key importance of taking into consideration the complex interconnections among financial institutions. Much effort has been put in modeling the contagion dynamics of financial shocks, and to assess the resilience of specific financial ma…

2018-05-11abs ↗pdf ↗

Study finds a phase transition in flash crashes involving large and liquid stocks.

problem Systemic risk and propagation of shocks in high frequency trading.
method In-depth investigation of co-crashes in high frequency trading.
result Large co-crashes involve mostly illiquid stocks, while small crashes involve a mix of liquid and illiquid stocks.

A statistical generalization is made of microeconomics in the spirit of going from classical to statistical mechanics. The price and quantity of every commodity1 traded in the market, at each instant of time, is considered to be an independent random variable: all prices and quantities are considered to be stochastic p…

2012-11-30abs ↗pdf ↗

We show how bad and good volatility propagate through forex markets, i.e., we provide evidence for asymmetric volatility connectedness on forex markets. Using high-frequency, intra-day data of the most actively traded currencies over 2007 - 2015 we document the dominating asymmetries in spillovers that are due to bad r…

2016-07-27abs ↗pdf ↗

One of the shortcomings of the Black and Scholes model on option pricing is the assumption that trading of the underlying asset does not affect the price of that asset. This assumption can be fulfilled only in perfectly liquid markets. Since most markets are illquid, this assumption might be too restrictive. Thus, taki…

2013-04-17abs ↗pdf ↗

Study shows publicly available news impacts financial markets.

problem Impact of publicly available news on financial markets.
method Extracted news from Common Crawl, identified relevant companies, used sentiment analysis and information theory.
result Publicly available news has significant impact on financial markets.

We provide some theoretical extensions and a calibration protocol for our former dynamic optimal execution model. The Hawkes parameters and the propagator are estimated independently on financial data from stocks of the CAC40. Interestingly, the propagator exhibits a smoothly decaying form with one or two dominant time…

2015-06-29abs ↗pdf ↗

We provide a microfoundation for linear price impact models in a stationary market.

problem Deriving linear price impact models in a stationary market with asymmetric information.
method Deriving linear price impact models as the equilibrium of an agent-based system.
result The model shows compatibility with universal price diffusion at small times and non-universal mean-reversion at larger times.

The vast majority of market impact studies assess each product individually, and the interactions between the different order flows are disregarded. This strong approximation may lead to an underestimation of trading costs and possible contagion effects. Transactions in fact mediate a significant part of the correlatio…

2016-09-08abs ↗pdf ↗

Optimal trading strategy under market resistance and concave price impact model.

problem Optimal trading in a market with endogenous resistance and concave price impact.
method Modeling market resistance, deriving a stochastic Fredholm equation, proving existence and uniqueness, proposing an iterative scheme.
result Existence and uniqueness of optimal control under certain conditions, exponential convergence of iterative scheme.

We present a study of price impact in the over-the-counter credit index market, where no limit order book is used. Contracts are traded via dealers, that compete for the orders of clients. Despite this distinct microstructure, we successfully apply the propagator technique to estimate the price impact of individual tra…

2016-09-15abs ↗pdf ↗

The paper analyzes how news sentiment of companies can affect market movements.

problem Understanding how news sentiment impacts market performance and volatility.
method Applied NLP techniques to analyze news sentiment of 87 companies over 7 years.
result Strong media sentiment towards one company can indicate significant changes in sentiment towards related companies.

This work develops an agent-based model for the study of how the leverage through the use of repurchase agreements can function as a mechanism for the propagation and amplification of financial shocks in a financial system. Based on the analysis of financial intermediaries in the repo and interbank lending markets duri…

2017-03-22abs ↗pdf ↗

Due to the extremely volatile nature of financial markets, it is commonly accepted that stock price prediction is a task full of challenge. However in order to make profits or understand the essence of equity market, numerous market participants or researchers try to forecast stock price using various statistical, econ…

2018-05-29abs ↗pdf ↗

Improved ABFMs capture market complexities, aiding policy decisions.

problem Limited usefulness of current ABFMs due to missing microstructure and agent behaviors.
method Developed ABMMS with realistic market structure, communication, and auction mechanisms; populated with adaptive agents.
result Generated data from ABMMS more accurately reflects real market phenomena.

REST framework predicts stock trends by considering stock-specific and related-stock events.

problem Predicting stock trends using event information from news, social media, and discussion boards.
method REST framework addresses two main shortcomings of existing event-driven methods: stock-specific event influence and related-stock event influence.
result REST framework achieves higher investment returns compared to baselines.

Develops a new model to better estimate cryptocurrency and stock volatility.

problem Misrepresentation of volatility and co-movement in traditional models.
method Introduces liquidity-sensitive multivariate volatility framework with novel liquidity measures.
result Liquidity-adjusted models yield more stable and interpretable risk structures.

High-speed computerized trading, often called "high-frequency trading" (HFT), has increased dramatically in financial markets over the last decade. In the US and Europe, it now accounts for nearly one-half of all trades. Although evidence suggests that HFT contributes to the efficiency of markets, there are concerns it…

2012-11-08abs ↗pdf ↗

This paper explores integration and contagion among US metropolitan housing markets. The analysis applies Federal Housing Finance Agency (FHFA) house price repeat sales indexes from 384 metropolitan areas to estimate a multi-factor model of U.S. housing market integration. It then identifies statistical jumps in metrop…

2011-10-18abs ↗pdf ↗

Study finds market inefficiencies vary by time scale, with news uncertainty key.

problem Evaluating scale-dependent informational efficiency of stock markets.
method Tensor-eigenvalue-based Financial Chaos Index, Granger causality, network analysis.
result Semi-strong form of EMH rejected at daily frequency, but not at monthly.

Study examines oil and US stock market interactions during coronavirus crisis.

problem Understanding the impact of coronavirus on oil and stock markets.
method Wavelet analysis of daily data from February 18, 2020 to August 15, 2020.
result Oil prices lead US stock prices at 3-5-day cycles during the first and second parts of March and April 2020.

Study compares information flow between Chinese and US stock sectors.

problem Analyzing how information flows between sectors in Chinese and US stock markets.
method Daily sector indices, transfer entropy of daily returns, comparing 2000-2017.
result Most active sectors in information exchange differ between China and US, reflecting market dynamics.