Repo pricing model explains haircut and spread dynamics.
problem Characterize and explain repo pricing measures.
method Develops a haircut model to identify economic capital as the main driver of repo pricing.
result Empirically reproduces repo haircut hikes and explains differences in haircut and spread.
Model estimates LIBOR rates and finds COVID-19 spread spike due to credit risk.
problem Estimating LIBOR rates and understanding the factors affecting them.
method Developed a joint model for various LIBOR-related rates and used it to decompose spreads.
result Credit risk mainly caused the spike in LIBOR-OIS spread during the COVID-19 onset, with equal contributions from credit and funding-liquidity risks on average.
Repo rates are explained as a convexity effect from bond and derivative discount rates.
problem Explaining the observed basis between repo rates and bond prices.
method Using a Hull-White model, derived expressions for repo rates and extrapolation.
result Interpolated and extrapolated repo curves for bond-collateralised derivatives.
The general and special repo rates are related with the prices of the European call- and American put-options. The evaluation takes into account specific business models of the parties in the repo agreement and the law restrictions. Using the repo-option relation, an alternative to the Black-Scholes method of option pr…
The paper introduces a new approach to repo pricing by incorporating gap risk and economic capital.
problem The gap risk or hedging errors in derivatives businesses.
method Extends the Black-Scholes-Merton framework with a reserve capital approach to model gap risk and economic capital charge.
result Practical repo pricing formulae are derived showing the importance of economic capital charge.
Repo dealers' market power affects bond prices by up to 2 percentage points.
problem Market power of repo dealers impacts bond prices and liquidity.
method Proprietary data on repo and reverse-repo trades analyzed.
result Market power of repo dealers accounts for 0.5-1.3 percentage points of bond yield deviation.
The paper explains the fair basis in bond-CDS trading during financial crises.
problem Large basis trading losses during financial crises are not explained by reduced form models.
method Dynamic spread model with bond repo financing, economic capital approach.
result Unhedged and unhedgeable residual jump to default risk exists, affecting fair basis level.
Model simulates financial contagion through repo agreements.
problem Financial contagion through repo agreements.
method Agent-based model of financial intermediaries.
result Model accurately simulates financial contagion dynamics.
The paper develops a new discount rate for derivatives using imperfect securities as collateral.
problem Inconsistent and non-observable collateral rates in derivatives markets.
method Synthesizes effects of imperfect collateral into a new discount rate, employs break-even repo formulae, and uses linear programming for optimization.
result Liquidity value adjustment (LVA) can be significant for long-term derivatives portfolios.
Leverage is strongly related to liquidity in a market and lack of liquidity is considered a cause and/or consequence of the recent financial crisis. A repurchase agreement is a financial instrument where a security is sold simultaneously with an agreement to buy it back at a later date. Repurchase agreements (repos) ma…
We study the semilinear partial differential equation (PDE) associated with the non-linear BSDE characterizing buyer's and seller's XVA in a framework that allows for asymmetries in funding, repo and collateral rates, as well as for early contract termination due to counterparty credit risk. We show the existence of a …
The study calculates securities lending haircuts and indemnification costs.
problem Managing borrower default risk in securities markets.
method Repo haircut model applied to securities lending transactions; quantifies haircuts and indemnification costs.
result Computed borrower-dependent haircuts and indemnification costs for US Treasuries and equities.
Develops framework for XVA calculation with no-arbitrage constraints.
problem Calculating XVA with no-arbitrage constraints.
method Derives BSDEs and PDEs for XVA calculation, identifies no-arbitrage intervals.
result Provides explicit expressions for XVA under various funding conditions.
In this note we show how to replicate a stylized CDS with a repurchase agreement and an asset swap. The latter must be designed in such a way that, on default of the issuer, it is terminated with a zero close-out amount. This break clause can be priced using the well known unilateral credit/debit valuation adjustment f…
Study how network structure affects collateral dynamics in banking systems.
problem Effects of network structure on collateral volume and hoarding in banking systems.
method Simple model of bank interactions via repo contracts and rehypothecation.
result Network structures with concentrated collateral flows are more exposed to large hoarding cascades.
A neural network method for financial data nowcasting.
problem Financial data nowcasting, especially with variable grid nodes.
method Neural network architecture for variable grid nodes data.
result Outperforms interpolation benchmarks and outlier detection.
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.
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…
Study shows how liquidity and trading volume affect price spread in financial markets.
problem Understanding and optimizing price spread in financial markets.
method Analyzes the interplay between order liquidity and order impact, connects spread to microstructural parameters.
result Additional liquidity improves price accuracy and reduces spread up to a certain point, after which it deteriorates.
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.
We explain a persistent cost-of-carry spread in EUA market and suggest ECB policy change.
problem Persistent cost-of-carry spread in EUA market.
method Cointegration analysis of EUA spread with credit spread and risk-free rate.
result Cointegration found between EUA spread, credit spread, and risk-free rate.
We establish that, over certain ground fields, the set of osculating tangents of Cayley's ruled cubic surface gives rise to a (maximal partial) spread which is also a dual (maximal partial) spread. It is precisely the Betten-Walker spreads that allow for this construction. Every infinite Betten-Walker spread is not an …
The paper develops a comprehensive valuation method for OTC claims that considers credit and funding risks.
problem Valuation of Over-The-Counter (OTC) claims that incorporate credit and funding liquidity risks.
method Develops a holistic approach using nonlinear mathematical models (semilinear PDEs and FBSDEs) and provides an analytical solution for the benchmark claim.
result An analytical solution for the benchmark claim is derived and expressed in terms of the Black-Scholes formula with dividends.
The study compares how deletions and trades affect stock prices and spread changes.
problem Understanding the impact of deletions and trades on stock prices and spread changes.
method Examined the frequencies of relative amounts of price changing events due to trades, deletions, and order placements.
result Deletions of orders open the bid-ask spread more often than trades and have a similar effect on prices as trades.
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.
We introduce nonlinear higher-order label spreading for semi-supervised learning.
problem Efficient semi-supervised learning on graphs with complex label spreading.
method We add nonlinearity to label spreading through higher-order graph structures, proving convergence and demonstrating efficiency on various datasets.
result Our nonlinear higher-order label spreading algorithm converges to the global solution and performs favorably compared to classical methods.
The statistical properties of the bid-ask spread of a frequently traded Chinese stock listed on the Shenzhen Stock Exchange are investigated using the limit-order book data. Three different definitions of spread are considered based on the time right before transactions, the time whenever the highest buying price or th…
New approximations for Asian basket spread options using stochastic Taylor expansions.
problem Pricing Asian basket spread options under the Black-Scholes model.
method Stochastic Taylor expansion applied to a log-normal proxy model.
result Highly accurate approximations for Asian and spread options, without numerical integration.
Study analyzes price response and spread impact in foreign exchange markets.
problem Understanding deviations from Markovian behavior in foreign exchange markets.
method Detailed large-scale data analysis of price response functions for different years and time scales, using pip bid-ask spread definition.
result Large pip spreads significantly impact price response in foreign exchange markets.
Machine learning fails to improve recession prediction with yield spread.
problem Improving recession prediction using yield spread selection.
method Machine learning algorithm to identify best maturity pair and coefficients.
result Machine learning does not significantly improve prediction of recession.
Deep learning models predict COVID-19 spread.
problem Predicting the spread of COVID-19 to mitigate its impact.
method Proposed DSPM and NRM models trained on 19.53M cases.
result Superior prediction performance of proposed models.
New model predicts credit spreads using stochastic CIR++ intensities.
problem Lack of continuous stochastic credit spread models and limited term structure models.
method Stochastic CIR++ model for default intensities in risk-neutral space.
result Model produces realistic credit spread term structure curves and consistent diffusion over time.
The term structure of credit spreads is studied with an aim to predict its future movements. A completely new approach to tackle this problem is presented, which utilizes nonlinear parametric models. The Brain-Cousens regression model with five parameters is chosen to describe the term structure of credit spreads. Furt…
GPR models epidemic spread on logarithmic scale.
problem Modeling and predicting epidemic spread for policy decisions.
method Gaussian process regression (GPR) on logarithmic scale of infected cases.
result GPR predictions have high probability of being within 95% confidence interval for 94.29% of data.
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.
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.
Improved spread option pricing with a new approximation method.
problem Inaccuracies in the original Kirk's formula for high correlation cases.
method Developed a new approximation method for spread option pricing.
result The Modified Kirk's Approximation method is extremely accurate and improves upon Kirk's approach.
Paper uses reinforcement learning to optimize bid-ask spreads in OTC markets.
problem Optimizing bid-ask spreads in over-the-counter markets with dynamic order sizes.
method Reinforcement learning to solve high-dimensional stochastic control problem.
result Optimal bid-ask spreads follow a Gaussian distribution under certain conditions.
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 use high-frequency data of 1364 Chinese A-share stocks traded on the Shanghai Stock Exchange and Shenzhen Stock Exchange to investigate the intraday patterns in the bid-ask spreads. The daily periodicity in the spread time series is confirmed by Lomb analysis and the intraday bid-ask spreads are found to exhibit L…
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.
Paper forecasts recession indicators using yield spread models.
problem Forecasting the leading indicator of a recession using yield spread.
method Applied econometric time series and machine learning models to forecast yield spread.
result Parsimonious univariate ARIMA model outperforms richly parameterized VAR method.
Random forest predicts catastrophe bond spreads with 93% accuracy.
problem Predicting spreads in the primary catastrophe bond market.
method Random forest approach using all information in offering circulars.
result Random forest explains 93% of spread variability, significantly better than linear regression (47%).
Study optimal trading strategies for mean-reverting spreads using integral equations.
problem Optimal timing for trading mean-reverting price spreads.
method Utilized local time-space calculus and nonlinear integral equations of Volterra-type.
result Derived optimal boundaries for trading strategies.
The paper uses option theory to estimate corporate bond liquidity spreads.
problem Estimating liquidity spreads for corporate bonds.
method Option-theoretic approach considering risk-free rate volatility and credit risk.
result The model provides a robust tool for pricing illiquid bonds.
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.
Bayesian inference models disease spread on networks.
problem Understand disease spread mechanisms and predict outbreaks.
method Approximate Bayesian computation (ABC) for complex models.
result Inference scheme works well on heterogeneous network topologies.