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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.

169,341 papers · 148 categories

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326495127 · May 202619922001200920182026
48 results for Swaption calibration

Efficiently calibrates SABR/LIBOR models to real market caplets and swaptions data.

problem Calibration of stochastic volatility models to real market data.
method Proposes a parallelized simulated annealing algorithm for multi-GPUs.
result Numerical results show advantages of using multi-GPUs for SABR/LIBOR model calibration.

Proposes a method to fill in missing swaption volatility data using variational autoencoders.

problem Missing swaption volatility data due to market illiquidity.
method Variational autoencoders for learning latent volatility representations, Gibbs sampling for inference.
result Imputed missing volatilities are robust and close to SABR fits.

We derive semi-analytic approximation formulae for bond and swaption prices in a Black-Karasiński interest rate model. Approximations are obtained using a novel technique based on the Karhunen-Loève expansion. Formulas are easily computable and prove to be very accurate in numerical tests. This makes them useful for nu…

2015-06-01abs ↗pdf ↗

The Hull-White one factor model is used to price interest rate options. The parameters of the model are often calibrated to simple liquid instruments, in particular European swaptions. It is therefore very important to have very efficient pricing formula for simple instruments. Such a formula is proposed here for Europ…

2009-01-13abs ↗pdf ↗

The article introduces a new interest rate model using Bergomi stochastic volatility.

problem Developing a model for interest rate swaps and swaptions without requiring calibration.
method Forward variance modeling by L. Bergomi applied to co-terminal swap market model.
result The model provides simple PnL formulas and high flexibility in controlling model dynamics.

Paper presents a new model for derivatives pricing using zero-coupon rates.

problem Exact volatility calibration of swaption matrices and structured products pricing.
method Model uses a dual-term structure with long-term zero-coupon rates driven by Brownian motion.
result Numerical scheme developed for model implementation and examples provided.

Proposes efficient calibration method for LIBOR Market Model with stochastic volatility.

problem Calibrating LIBOR Market Model with stochastic volatility.
method Derives analytical gradient of swaptions prices for DDSVLMM and uses it for gradient-based optimization.
result Analytical gradient-based calibration is highly competitive and efficient for DDSVLMM.

We present a new model for credit index derivatives, in the top-down approach. This model has a dynamic loss intensity process with volatility and jumps and can include counterparty risk. It handles CDS, CDO tranches, Nth-to-default and index swaptions. Using properties of affine models, we derive closed formulas for t…

2009-11-09abs ↗pdf ↗

Proposes a new model for negative interest rates that fits market data closely.

problem Negative interest rates and their impact on financial models.
method Uses a deterministic-shift extension of two independent CIR processes with Gram-Charlier expansion for swaption pricing.
result The model produces close swaption prices to market data.

In this short note, using our geometric method introduced in a previous paper \cite{phl} and initiated by \cite{ave}, we derive an asymptotic swaption implied volatility at the first-order for a general stochastic volatility Libor Market Model. This formula is useful to quickly calibrate a model to a full swaption matr…

2006-02-15abs ↗pdf ↗

We develop a multi-factor stochastic volatility Libor model with displacement, where each individual forward Libor is driven by its own square-root stochastic volatility process. The main advantage of this approach is that, maturity-wise, each square-root process can be calibrated to the corresponding cap(let)vola-stri…

2012-04-25abs ↗pdf ↗

A new model uses a Levy-driven process to value credit index swaptions.

problem Valuation of credit index swaptions in financial markets.
method Proposes a Levy-driven Ornstein-Uhlenbeck process to model risk-free rate and default intensities.
result Derives formulas for characteristic function, moments, and stationary distribution.

Derives formulas for swaption prices in HJM model and uses nonparametric fit to identify arbitrage opportunities.

problem Deriving swaption prices in the HJM model and identifying arbitrage opportunities.
method Derives closed form formulas for swaption prices in HJM model and uses nonparametric fit of deterministic forward volatility.
result Demonstrates that the derived formulas and nonparametric fit work well and can identify arbitrage opportunities.

New SL algorithms improve Bermudan Swaption pricing efficiency.

problem Efficient pricing of Bermudan Swaptions using Monte Carlo methods.
method Supervised Learning algorithms linking Bermudan Swaption to European Swaptions and other financial quantities.
result SL algorithms (Ridge, ANN, Gradient Boosted Regression Tree) are reliable and fast, overcoming Monte Carlo computational bottleneck.

We enhance short-rate models to control implied volatility analytically.

problem Controlling implied volatility in short-rate models.
method Randomized Affine Diffusion (RAnD) method applied to Heath-Jarrow-Morton framework.
result Randomized short-rate models improve calibration and control implied volatility shapes.

Modified BFGS and LBFGS++ libraries boost performance for non-parallelizable functions.

problem Improving performance of non-parallelizable functions using SIMD and AAD.
method Modifications to BFGS and LBFGS++ libraries, utilizing SIMD and Automatic Differentiation (AAD).
result Up to 3.8 times faster for European Swaption curve calibration and 1.4 times faster for LMM model calibration.

Tensor Neural Networks improve pricing accuracy for interest rate derivatives.

problem Inaccurate pricing of Bermudan Swaptions using traditional methods.
method Leveraging Tensor Neural Networks to solve backward Stochastic Differential Equations.
result Tensor Neural Networks provide more accurate and robust prices than Dense Neural Networks.

Deep learning solves high-dimensional Bermudan swaption pricing and hedging efficiently.

problem Efficiently pricing and hedging Bermudan swaptions in Libor market model.
method Backward DNN solver for FBSDEs, demonstrating superior performance over Monte Carlo.
result Deep learning method effectively and efficiently solves high-dimensional Bermudan swaption pricing and hedging.

Paper presents a fast algorithm for pricing Bermudan swaptions under the two-factor Hull-White model.

problem Evaluating Bermudan swaption prices under the two-factor Hull-White model with high computational efficiency.
method Discretization of expected value calculation, Gaussian kernel sums, fast Gauss transform, grid rotation for stability.
result Significant reduction in computation time and improved stability for correlation close to -1.

Develops a diagnostic framework for interest rate model calibration, showing equivalence to Weighted Least Squares and revealing boundary-dominated leverage and local parameter instability.

problem Calibration of stochastic interest rate models
method Diagnostic framework using non-linear regression and analytical tractability of At-The-Money caps
result Reveals boundary-dominated leverage and local parameter instability

Proposes a new model to handle negative interest rates using CIR framework.

problem Negative interest rates and their impact on financial markets.
method Develops a new model based on Cox-Ingersoll-Ross (CIR) framework without shifting market rates.
result The model accurately reproduces market term structures and swaption prices.

Paper proposes a deep hedging method for Bermudan swaptions to manage residual profit and loss.

problem Real-world market conditions differ from ideal assumptions in traditional hedging methods, leading to residual profit and loss.
method Deep hedging framework applied to Bermudan swaptions, allowing flexible risk measures and hedge strategies.
result Effective residual profit and loss management demonstrated through numerical analysis.

We study a Markov-Functional (MF) interest-rate model with Uncertain Volatility Displaced Diffusion (UVDD) digital mapping, which is consistent with the volatility-smile phenomenon observed in the option market. We first check the impact of pricing Bermudan swaptions by the model. Next, we also investigate the future s…

2014-04-24abs ↗pdf ↗

A semi-static approach efficiently replicates and prices callable interest rate derivatives.

problem Efficiently replicating and pricing callable interest rate derivatives under dynamic market conditions.
method Proposes a semi-static hedging algorithm that updates the replication portfolio on a finite number of instances, rather than continuously.
result The hedging error can be made arbitrarily small with a sufficiently large replication portfolio, and closed-form error margins are determined.

The study models mortgage prepayment risk using stochastic housing market activity.

problem Modeling prepayment risk in mortgages under varying housing market conditions.
method Developed a stochastic model for prepayment option value, using swaption pricing formulas and non-standard actuarial hedging.
result Housing market covariance significantly impacts prepayment option prices.

Hedging strategies in bond markets are computed by martingale representation and the Clark-Ocone formula under the choice of a suitable of numeraire, in a model driven by the dynamics of bond prices. Applications are given to the hedging of swaptions and other interest rate derivatives, and our approach is compared to …

2013-04-23abs ↗pdf ↗

A heat kernel approach is proposed for the development of a general, flexible, and mathematically tractable asset pricing framework in finite time. The pricing kernel, giving rise to the price system in an incomplete market, is modelled by weighted heat kernels which are driven by multivariate Markov processes and whic…

2012-11-05abs ↗pdf ↗

The crisis that affected financial markets in the last years leaded market practitioners to revise well known basic concepts like the ones of discount factors and forward rates. A single yield curve is not sufficient any longer to describe the market of interest rate products. On the other hand, using different yield c…

2010-06-24abs ↗pdf ↗