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…
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48 results for “CDS swaptions”
We develop and test a fast and accurate semi-analytical formula for single-name default swaptions in the context of a shifted square root jump diffusion (SSRJD) default intensity model. The model can be calibrated to the CDS term structure and a few default swaptions, to price and hedge other credit derivatives consist…
Dirac Processes and Default Riskq-fin.PR
Introduces Dirac processes for financial derivative pricing.
problem High implied volatility for CDS swaptions in hazard rate setups.
method Uses Dirac delta functions to add spikes to short-rate models.
result Dirac processes enable high implied volatility for CDS swaptions.
Analyzes American swaption pricing in LR model, solving optimal stopping problem.
problem Analyzes American swaption pricing in LR model.
method Analyzes American swaption pricing in LR model, solving optimal stopping problem.
result Characterizes optimal stopping boundary and obtains arbitrage-free price.
Derives measure changes for pricing midcurve swaptions.
problem Pricing midcurve swaptions in a forward swap annuity measure.
method Derives measure change formulae and constructs linear and exponential terminal swap rate models.
result Captures midcurve swaption correlation skew.
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.
Berms without Calibrationq-fin.PR
A new model prices Bermudan swaptions without calibration.
problem Calibration of Bermudan swaptions models.
method Semi-analytical pricing model using swap rates and correlations.
result No product-specific calibration required.
Learning Bermudansq-fin.PR
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.
Proposes atomic swaptions for trustless cryptocurrency derivatives.
problem Lack of trustless derivatives for cryptocurrency exchanges.
method Extends atomic swap protocol to include derivatives without oracles.
result Atomic swaptions enable trustless exchange of derivative assets.
Simple model prices swaptions in multicurve interest rates.
problem Pricing swaptions in multicurve interest rate models.
method Three-parameter multicurve extension of Hull-White model.
result Simple closed formula for swaption pricing.
Accurate approximations for bond and swaption prices in a specific interest rate model.
problem Calibrate a specific interest rate model efficiently.
method Novel technique based on Karhunen-Loève expansion for semi-analytic approximations.
result Approximations are very accurate and useful for 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.
Learning to Hedge Swaptionsq-fin.RM
Paper uses RL for dynamic swaption hedging, outperforming traditional methods.
problem Dynamic hedging of swaptions using reinforcement learning.
method Design agents with three objective functions to adapt hedging strategies dynamically.
result Deep hedging strategies using two swaps outperform traditional methods, even with model misspecification.
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.
Pricing Bermudan swaptions with few exercise dates using analytic methods.
problem Pricing Bermudan swaptions with few exercise dates
method Analytic decomposition and backward induction under rolling forward measures
result Pricing formulas with decomposition and boundary linearity
Rough SABR Forward Market Modelq-fin.MF
Enhances swaption modeling with rough stochastic volatility.
problem Modeling swaption volatility in post-LIBOR markets.
method Introduces rough stochastic volatility into FMM and rigorously justifies the freezing approximation.
result Establishes a new framework connecting FMM to rough Bergomi for forward swap rates.
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.
Interpolation of Missing Swaption Volatility Data using Gibbs Sampling on Variational Autoencoderscs.LG
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.
The paper uses deep learning to efficiently price Bermudan swaptions.
problem Pricing Bermudan swaptions efficiently and accurately.
method Combines differential machine learning, Monte Carlo simulation, and joint learning.
result Improves efficiency and accuracy in pricing Bermudan swaptions.
A fast method for pricing swaptions in Gaussian models.
problem Pricing swaptions in multi-factor Gaussian term structure models efficiently.
method Approximating exercise boundary by a hyperplane and simplifying multi-dimensional integration.
result Our method is superior to previous methods in accuracy and speed.
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…
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.
Deep Hedging Bermudan Swaptionsq-fin.CP
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.
HJM Local Volatility Modelq-fin.PR
Improved LV model for interest rate swaptions and caplets.
problem Calibration of arbitrage-free LV models to European options.
method HJM interest rate model with Small Volatility Approximation.
result Deterministic and fast method with excellent calibration accuracy.
Develops a machine learning system to recommend swaption trades.
problem Derivative traders struggle with analyzing many possible trades daily.
method Pipeline of computing metrics, predicting returns, ranking trades.
result Linear regression with lasso regularization performs well.
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…
The study finds equivalent properties for CD inequalities with unbounded Laplacians.
problem Implying gradient estimates for laplace operator on graphs with unbounded Laplacians.
method Investigates equivalent properties of CD(K,∞) and CD(K,n) inequalities with unbounded Laplacians.
result Concludes equivalent properties of CD(K,∞) and CD(K,n) inequalities.
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.
Optimal maps exist in very strict spaces despite plan uniqueness issues.
problem Existence of optimal transport maps in very strict spaces.
method Introduced a more restrictive condition and showed existence of optimal maps.
result Existence of optimal maps in very strict spaces.
The study presents examples of spaces with varying dimensions and discusses the limitations of the condition.
problem Exploring the properties and limitations of spaces with varying dimensions.
method Generalizing results from previous work, presenting examples and analyzing the conditions under which the condition fails.
result The condition is not stable under measured Gromov-Hausdorff convergence and may fail in various ways.
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.
We present a generic framework for parallel coordinate descent (CD) algorithms that includes, as special cases, the original sequential algorithms Cyclic CD and Stochastic CD, as well as the recent parallel Shotgun algorithm. We introduce two novel parallel algorithms that are also special cases---Thread-Greedy CD and …
Paper offers a simple CDS approximation formula with high accuracy.
problem Lack of CDS levels for market appreciation of companies' default risk.
method Developed a global and transparent Equity-to-Credit (E2C) formula using random forest regression.
result Random forest regression with E2C formula achieves 87.3% out-of-sample accuracy in CDS approximations.
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…
A new algorithm, Weighted Contrastive Divergence (WCD), improves on Contrastive Divergence (CD) for learning Boltzmann architectures.
problem Computational infeasibility of exact gradient computation in Boltzmann architectures.
method Proposes Weighted Contrastive Divergence (WCD) as a modification of Contrastive Divergence (CD) with small modifications to the negative phase.
result Experimental results show significant improvement of WCD over standard CD and persistent CD with minimal additional computational cost.
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.
The paper proposes a machine learning method to estimate proxy CDS rates for illiquid counterparties.
problem Estimating counterparty default risks from illiquid CDS quotes for financial valuation and risk management.
method Constructing proxy CDS rates by associating illiquid counterparty liquid CDS Proxy using machine learning techniques.
result Some classifiers achieve highly satisfactory accuracy rates in constructing proxy CDS rates.
CD meets CATmath.DG
Study shows curvature bounds for CD and CAT spaces.
problem Understanding curvature bounds for CD and CAT spaces.
method Analyzes noncollapsed CD(K,n) spaces with curvature bounds.
result Establishes curvature bounds for CD and CAT spaces.
Given any K and N we show that there exists a compact geodesic metric measure space satisfying locally the CD(0,4) condition but failing CD(K,N) globally. The space with this property is a suitable non convex subset of R^2 equipped with the l^\infty-norm and the Lebesgue measure. Combining many such spaces gives a (non…
New methods improve prediction regions for high-dimensional data.
problem Creating effective prediction regions for high-dimensional data.
method CD-split and HPD-split methods that combine split method and data-driven partition.
result CD-split and HPD-split converge to oracle highest predictive density set and satisfy local and asymptotic conditional validity.
This paper uses SLT to ensure learning guarantees in CD detection.
problem Lack of learning guarantees in CD detection algorithms.
method Adapting SLT assumptions to CD scenarios to ensure learning guarantees.
result Ensured learning guarantees in CD detection algorithms.
Study uncovers CDS anomalies leading to arbitrage profits.
problem Identifying arbitrage opportunities in CDS term structures.
method Derive No-arbitrage conditions for CDS term structures, analyze extensive dataset.
result Presented 2,416 pairs of anomalous CDS contracts.
This paper is devoted to the analysis of metric measure spaces satisfying locally the curvature-dimension condition CD(K,N) introduced by the second author and also studied by Lott & Villani. We prove that the local version of CD(K,N) is equivalent to a global condition CD*(K,N), slightly weaker than the (usual, global…
Basel III introduces new capital charges for CVA. These charges, and the Basel 2.5 default capital charge can be mitigated by CDS. Therefore, to price in the capital relief that CDS contracts provide, we introduce a CDS pricing model with three legs: premium; default protection; and capital relief. If markets are compl…
Abstract shows entropy and convexity definitions of very strict spaces are equivalent.
problem Equivalence of definitions of very strict spaces.
method Showed equivalence of definitions using entropy functionals and full displacement convexity class.
result Equivalence of definitions of very strict spaces.
CDS market redesign makes financial networks more resilient to insolvency.
problem Managing systemic risk in financial networks during insolvency cascades.
method Designing a CDS market to rewire interbank exposures, adding systemic insurance surcharges based on network topology.
result A regulated CDS market makes financial systems more resilient to insolvency.
Quantum annealer speeds up RBM training for image classification.
problem Training RBM with contrastive divergence (CD) is slow and computationally expensive.
method Used D-Wave 2000Q quantum annealer to calculate model expectation of gradient learning for RBM.
result Quantum training yields similar classification performance to CD but faster.
Almost-Riemannian manifolds fail to meet a synthetic curvature condition.
problem Proving almost-Riemannian manifolds do not satisfy the condition.
method Developed a new strategy to contradict the 1-dimensional condition.
result 2D and strongly regular almost-Riemannian manifolds do not satisfy for any and .