Bid-ask spread is taken as an important measure of the financial market liquidity. In this article, we study the dynamics of the spread return and the spread volatility of four liquid stocks in the Chinese stock market, including the memory effect and the multifractal nature. By investigating the autocorrelation functi…
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48 results for “spread dynamics”
Algorithm reconstructs spreading model parameters from incomplete data.
problem Reconstructing unknown transmission probabilities from partial observation data.
method Dynamic message-passing algorithm for incomplete spreading data.
result Efficient algorithm reconstructs parameters of spreading models.
Estimating Dynamic Conditional Spread Densities to Optimise Daily Storage Trading of Electricitystat.AP
The paper optimizes daily storage trading of electricity using dynamic spread densities.
problem Optimizing daily storage trading of electricity based on price spreads.
method Formulated dynamic density functions based on skewed-t representations to model hourly electricity price spreads. Selected the best specification for each spread using the Pinball Loss function and calculated risk associated with spread arbitrages.
result Optimal daily operation of a battery storage facility determined from spread densities.
Model predicts bid and ask price dynamics with spread-dependent intensities.
problem Predicting bid and ask price dynamics in high-frequency stock markets.
method Extended Hawkes process with zero intensities, spread-dependent intensities, and negative excitement.
result Spread-narrowing tendency, excitations caused by previous events, impact of flash crashes, and different market participant features.
A new model predicts bid-ask spread dynamics in financial markets.
problem Capturing the self-exciting nature of bid-ask spread changes.
method State-dependent Spread Hawkes model (SDSH) incorporating various spread jump sizes and current state impact.
result The SDSH model accurately forecasts spread values at short-term horizons.
The study examines order flow patterns in NASDAQ stocks, finding that limit order placement inside the spread is influenced by spread dynamics.
problem Understanding the dynamics of order flow in NASDAQ stocks.
method Analysis of order flow data for different NASDAQ stocks, focusing on limit orders, market orders, and their placement.
result Limit order placement inside the spread is strongly influenced by spread dynamics, while most orders are placed outside the spread.
Study of influenza A virus spread using mathematical equations.
problem Understanding the spread of influenza A virus infection.
method Mathematical model and analysis of dynamical system.
result Surface trajectories and asymptotic behavior of the system.
A new model explains relative spreads between economies using dynamic Nelson-Siegel and functional regression.
problem Analyzing and predicting relative spreads between economies in fixed income markets.
method State-space functional regression model incorporating dynamic Nelson-Siegel model and kernel PCA.
result The new model outperforms the dynamic Nelson-Siegel model in explaining relative spreads.
Paper models and forecasts intra-day electricity price spreads.
problem Forecasting intra-day price spreads for electricity traders and operators.
method Dynamic density functions based on skewed-t distributions, conditional on exogenous drivers.
result Best fitting and forecasting specifications selected using Pinball Loss function.
We derive the price of a spread option based on two assets which follow a bivariate volatility modulated Volterra process dynamics. Such a price dynamics is particularly relevant in energy markets, modelling for example the spot price of power and gas. Volatility modulated Volterra processes are in general not semimart…
Study of volume dynamics at market spread in Bitcoin/USD.
problem Understanding the statistical properties of order volumes in financial markets.
method Examined the dynamical properties of volume available at the spread, focusing on mean reversion, asymmetry, and clustering.
result Evidence of mean reverting volume changes and strong asymmetries in sell and buy orders.
Healthy... Distress... Defaultq-fin.PR
Model predicts stock returns from CDS spreads, useful for trading.
problem Predicting stock returns from market sentiment.
method Simple model with regime switching, analytically tractable.
result Extracts expected returns from CDS spreads, useful for statistical arbitrage.
Method estimates parameters for disease spread models robustly.
problem Estimating parameters for disease spread models.
method Statistical Learning applied to Approximate Bayesian Computation.
result Qualitative properties of disease evolution can be assessed.
The paper prices energy spread options using a complex stochastic model.
problem Pricing energy spread options with specific stochastic dynamics.
method Uses an exponential Ornstein-Uhlenbeck process driven by variance gamma processes, applying the Esscher transform and FFT method.
result Derives an analytical formula for pricing forwards and spread options.
Trend arbitrage, bid-ask spread and market dynamicsphysics.data-an
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…
The paper uses moment matching method for pricing spread options under Lévy models.
problem Pricing spread options under Lévy models with mean-variance mixture.
method Moment matching method applied to Lévy models with mean-variance mixture.
result Obtains semi-closed form formulas for spread option prices.
Efficient algorithm learns Independent Cascade model from partial network observations.
problem Learning accurate spreading models from limited network data.
method Scalable dynamic message-passing approach for parameter learning.
result Improved prediction of marginal probabilities compared to original model.
Quantifying the impact of COVID-19 on the US stock market: An analysis from multi-source informationq-fin.ST
Study quantifies how COVID-19 spread affects US stock markets.
problem Impact of COVID-19 on US stock market during pandemic.
method Developed a novel temporal complex network approach using econometric and ML models.
result Local spread of COVID-19 and Google searches impact abnormal stock prices.
In the top-down approach to multi-name credit modeling, calculation of singe name sensitivities appears possible, at least in principle, within the so-called random thinning (RT) procedure which dissects the portfolio risk into individual contributions. We make an attempt to construct a practical RT framework that enab…
Limit Order Book Dynamics in Matching Markets: Microstructure, Spread, and Execution Slippageq-fin.TR
The paper models market dynamics using a limit order book system to explain slippage and inefficiency.
problem Inefficiency in matching markets due to structural liquidity constraints and slippage.
method Introduces a market microstructure framework with a latent preference state matrix and a dynamic discrete choice execution model.
result Persistent slippage and regional invariance of preference orderings are explained by liquidity thresholds.
We derive a continuous time model for the joint evolution of the mid price and the bid-ask spread from a multiscale analysis of the whole limit order book (LOB) dynamics. We model the LOB as a multiclass queueing system and perform our asymptotic analysis using stylized features observed empirically. We argue that in t…
We develop a model for the dynamic evolution of default-free and defaultable interest rates in a LIBOR framework. Utilizing the class of affine processes, this model produces positive LIBOR rates and spreads, while the dynamics are analytically tractable under defaultable forward measures. This leads to explicit formul…
Paper compares GRU and LSTM for predicting wildfire spread direction.
problem Predicting wildfire spread direction with limited data.
method Comparison of Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM) networks.
result GRU performs better for longer time series than LSTM.
We study the relaxation dynamics of the bid-ask spread and of the midprice after a sudden, large variation of the spread, corresponding to a temporary crisis of liquidity in a double auction financial market. We find that the spread decays very slowly to its normal value as a consequence of the strategic limit order pl…
We analyze the counterparty risk embedded in CDS contracts, in presence of a bilateral margin agreement. First, we investigate the pricing of collateralized counterparty risk and we derive the bilateral Credit Valuation Adjustment (CVA), unilateral Credit Valuation Adjustment (UCVA) and Debt Valuation Adjustment (DVA).…
Large tick assets, i.e. assets where one tick movement is a significant fraction of the price and bid-ask spread is almost always equal to one tick, display a dynamics in which price changes and spread are strongly coupled. We introduce a Markov-switching modeling approach for price change, where the latent Markov proc…
Study on order book dynamics with uniform catastrophes, explaining volatility and trends.
problem Understanding volatility and trends in financial markets with different types of liquidity.
method Stochastic models and population processes with uniform catastrophes.
result Law of large numbers, central limit theorem, and large deviations proved for the model.
Neural networks model COVID-19 spread with partial isolation data.
problem Modeling the spread of COVID-19 with limited data.
method Semi-supervised neural networks solving inverse problems.
result Estimates optimal conditions for virus spread and passive population.
Quantum theory explains price dynamics in financial markets, capturing bid-ask spread and ergodicity.
problem Nature of price formation in financial markets and bid-ask spread dynamics.
method Developed a quantum coupled-wave theory using a 2x2 price operator with eigenvalues representing bid and ask prices.
result The theory adequately models bid-ask spread and directional price movement due to quantum-chaotic interaction.
Beyond the Bid-Ask: Strategic Insights into Spread Prediction and the Global Mid-Price Phenomenonq-fin.TR
Study examines new financial metrics and their implications for trading and risk management.
problem Liquidity and price dynamics in financial markets.
method High-frequency trading data, ARMA(1,1)-GARCH(1,1) model, normal inverse Gaussian distribution, option pricing model, Rachev ratio.
result New financial metrics (TMOBBAS, GMP) have heavy-tailed distributions and significant deviations from normality.
Optimal Liquidity Provisionq-fin.TR
A small investor provides liquidity at the best bid and ask prices of a limit order market. For small spreads and frequent orders of other market participants, we explicitly determine the investor's optimal policy and welfare. In doing so, we allow for general dynamics of the mid price, the spread, and the order flow, …
We show that the statistics of spreads in real order books is characterized by an intrinsic asymmetry due to discreteness effects for even or odd values of the spread. An analysis of data from the NYSE order book points out that traders' strategies contribute to this asymmetry. We also investigate this phenomenon in th…
Study uses epidemiological models to analyze financial contagion risks.
problem Analyzing and controlling contagion risks in the global financial network.
method Formulated an optimal control problem based on infection spread models.
result The approach effectively describes the world economy's financial contagion.
Optimal timing strategy for mean-reverting price spreads.
problem Trading price spreads with mean-reverting characteristics.
method Sequential optimal stopping framework with refined signature method.
result Precise entry and exit timings that maximize gains.
Study optimal semi-static hedging for illiquid markets using dynamic cash and static quoted derivatives.
problem Optimal pricing of exotic derivatives in illiquid markets with bid-ask spreads.
method Use Galerkin method and integration quadratures to approximate hedging problem as convex optimization, solved by interior point method.
result Semi-static hedging improves pricing and reduces transaction costs compared to static or dynamic trading alone.
Study optimal investment and consumption in financial markets using Ornstein-Uhlenbeck process.
problem Optimal consumption/investment problem in financial markets with logarithmic utility.
method Stochastic dynamical programming method and Hamilton-Jacobi-Bellman (HJB) equation.
result Explicit solution to the HJB equation and optimal financial strategies constructed.
Improved model predicts wildfire spread on slopes.
problem Accurate prediction of wildfire spread on slopes.
method Combines Rothermel model, Huygens' principle, and advanced techniques.
result More precise model of wildfire propagation.
We introduce a multiple curve framework that combines tractable dynamics and semi-analytic pricing formulas with positive interest rates and basis spreads. Negatives rates and positive spreads can also be accommodated in this framework. The dynamics of OIS and LIBOR rates are specified following the methodology of the …
The credit spread curve. I: Fundamental concepts, fitting, par-adjusted spread, and expected returnq-fin.PR
The paper explains how to construct a credit spread curve from bond prices.
problem The challenge of constructing a credit spread curve from bond prices.
method Fit parametrised survival curves to construct the curve, avoiding the Z-spread issue.
result A concise treatment of the high-dollar price bonds trading at higher yields is explained.
A simple model of price formationcond-mat.stat-mech
A simple Ising spin model which can describe the mechanism of price formation in financial markets is proposed. In contrast to other agent-based models, the influence does not flow inward from the surrounding neighbors to the center site, but spreads outward from the center to the neighbors. The model thus describes th…
This study examines lead-lag relationships in Chinese futures markets using high-frequency data.
problem Understanding high-frequency trading dynamics and information flow in futures markets.
method High-frequency tick-by-tick data analysis of lead-lag relationships between different maturity futures contracts.
result The near-month futures lead longer-dated contracts by one tick, with a negative feedback effect on the leading asset.
Enhances inference of spreading processes using neural-network priors.
problem Estimating initial states of graph processes from partial observations.
method Bayesian framework with single-layer perceptron neural network for initial states; hybrid BP-AMP algorithm.
result Model exhibits first-order phase transitions, creating a statistical-to-computational gap.
In order-driven markets, limit-order book (LOB) resiliency is an important microscopic indicator of market quality when the order book is hit by a liquidity shock and plays an essential role in the design of optimal submission strategies of large orders. However, the evolutionary behavior of LOB resilience around liqui…
We introduce, in continuous time, an axiomatic approach to assign to any financial position a dynamic ask (resp. bid) price process. Taking into account both transaction costs and liquidity risk this leads to the convexity (resp. concavity) of the ask (resp. bid) price. Time consistency is a crucial property for dynami…
Efficient reconstruction of transmission probabilities in a spreading process from partial observationsphysics.soc-ph
An important problem of reconstruction of diffusion network and transmission probabilities from the data has attracted a considerable attention in the past several years. A number of recent papers introduced efficient algorithms for the estimation of spreading parameters, based on the maximization of the likelihood of …
Develops Lagrange-Hamilton geometry for COVID-19 disease dynamics.
problem Modeling the spread of COVID-19 disease.
method Least squares variational method, nonlinear connections, d-torsions, Lagrangian Yang-Mills.
result Jacobi stability of the dynamical system.
Statistical arbitrage strategies, such as pairs trading and its generalizations, rely on the construction of mean-reverting spreads enjoying a certain degree of predictability. Gaussian linear state-space processes have recently been proposed as a model for such spreads under the assumption that the observed process is…
Paper uses Chebyshev Tensors for accurate dynamic sensitivities and ISDA SIMM computation.
problem Computing dynamic sensitivities and initial margin for financial instruments.
method Uses Chebyshev Tensors in Monte Carlo simulations to compute dynamic sensitivities and ISDA SIMM.
result High accuracy and computational gains for FX swaps and Spread Options.