Continuous tenor extension of affine LIBOR models for multiple curves, with applications to XVA calculations.
problem Modeling interest rates with multiple curves and arbitrage-free value adjustments.
method Introducing an interpolating function to extend discrete tenor models to continuous tenor models, deriving expressions for instantaneous forward rates and short rates.
result The continuous tenor model is arbitrage-free and analytically tractable under the spot martingale measure, allowing consistent computation of value adjustments.
Alternative method preserves positivity in interest rate interpolation.
problem Positivity issue in interest rate interpolation.
method Alternative method preserving Markovian properties and positivity.
result Guaranteed positivity of all interpolated rates.
Modeling interest rates for multiple tenors considering rollover risk.
problem Tackling the risk of borrowing at a shorter tenor and lending at a longer tenor.
method Constructing a stochastic model framework with endogenous frequency basis, incorporating credit and liquidity risks.
result The model can be calibrated to market data and used for pricing interest rate derivatives.
A new model for pricing ultra-short-term options with complex volatility patterns.
problem Complex pricing of ultra-short-term options due to oscillations in implied volatility.
method Edgeworth++ model with nonparametric stochastic volatility and deterministic shift extension.
result Fast and accurate closed-form option pricing for ultra-short-term options.
WATTNet models FX trading tenor selection using spatio-temporal data.
problem NDF tenor selection in FX trading with long-term planning.
method WaveATTentionNet (WATTNet) for spatio-temporal modeling of multivariate time series.
result Significant positive ROI in all NDF markets, outperforming baselines.
Develops optimal currency hedging strategy for fund managers considering liquidity risk.
problem Choosing optimal foreign exchange (FX) hedge tenors to maximize carry returns within liquidity constraints.
method Time-dispersing total hedge value into future time buckets, maximizing FX carry benefit while adhering to liquidity risk metric (CFaR).
result Hedging strategy operates within liquidity budget, demonstrating practical insights for fund managers.
The goal of this paper is to specify dynamic term structure models with discrete tenor structure for credit portfolios in a top-down setting driven by time-inhomogeneous Lévy processes. We provide a new framework, conditions for absence of arbitrage, explicit examples, an affine setup which includes contagion and prici…
Visualizes Treasury issuance strategy using cost and risk metrics.
problem Analyzing and visualizing tradeoffs in Treasury issuance strategy.
method Mapping issuance fractions to long-term portfolio implications for cost and risk.
result Identifies an efficient frontier and optimal tenor for Treasury issuance.
In the LIBOR market model, forward interest rates are log-normal under their respective forward measures. This note shows that their distributions under the other forward measures of the tenor structure have approximately log-normal tails.
We propose a unified structural credit risk model incorporating both insolvency and illiquidity risks, in order to investigate how a firm's default probability depends on the liquidity risk associated with its financing structure. We assume the firm finances its risky assets by mainly issuing short- and long-term debt.…
This study applies Benford's law to monitor CDS quotes, revealing discrepancies by country and tenor.
problem Monitoring sovereign CDS quotes for health and default probability using Benford's law.
method Applying Benford's law to daily changes in sovereign CDS spreads for 13 European countries over 2008-2015.
result Differences in CDS quotes by country and tenor, with Greece showing unique behavior.
A hybrid Convolutional VAE predicts crypto volatility surfaces, outperforming single-symbol approaches.
problem Predicting crypto volatility surfaces
method Convolutional VAE with hybrid predictor
result Model achieves 0.94-1.56 vol-point RMSE across BTC and ETH markets
Regulations impose idiosyncratic capital and funding costs for holding derivatives. Capital requirements are costly because derivatives desks are risky businesses; funding is costly in part because regulations increase the minimum funding tenor. Idiosyncratic costs mean no single measure makes derivatives martingales f…
Paper uses VAEs to model yield curves without arbitrage violations.
problem Forecasting yield curves across diverse macroeconomic regimes leads to arbitrage violations.
method Proposes a two-stage architecture with CVAEsT+LS and Neural SDEs penalized by No-Arbitrage PDE.
result Significantly reduces forecasting errors and overcomes HJM model limitations.
Revisits elastic string model to explain interest rate correlations.
problem Describing the forward interest rate curve using an elastic string model.
method Reinterprets Baaquie and Bouchaud's (2004) model to highlight market forces.
result Model accurately reproduces FRC correlation structure with minimal parameters.
Quantum computing speeds up interest rate derivative pricing using LMM.
problem Challenges in pricing interest rate derivatives, especially caps.
method Hybrid classical-quantum approach using quantum amplitude estimation.
result Quantum computing improves convergence in pricing interest rate derivatives.
A new method for pricing options with flexible volatility shapes.
problem Parameterizing risk-neutral distributions for accurate option pricing.
method Parsimonious and interpretable parameters for direct control over implied volatility curves.
result Accurate calibration across a large dataset of option curves.
Collateralization with daily margining has become a new standard in the post-crisis market. Although there appeared vast literature on a so-called multi-curve framework, a complete picture of a multi-currency setup with cross-currency basis can be rarely found since our initial attempts. This work gives its extension r…
We propose a general framework for modeling multiple yield curves which have emerged after the last financial crisis. In a general semimartingale setting, we provide an HJM approach to model the term structure of multiplicative spreads between FRA rates and simply compounded OIS risk-free forward rates. We derive an HJ…
We review the main changes in the interbank market after the financial crisis started in August 2007. In particular, we focus on the fixed income market and we analyse the most relevant empirical evidences regarding the divergence of the existing basis between interbank rates with different tenor, such as Libor and OIS…
The LIBOR market model is very popular for pricing interest rate derivatives, but is known to have several pitfalls. In addition, if the model is driven by a jump process, then the complexity of the drift term is growing exponentially fast (as a function of the tenor length). In this work, we consider a Lévy-driven LIB…
Paper proposes a new daily benchmark for post-GFC government bond CIP deviations.
problem Lack of a canonical daily benchmark for CIP deviations.
method Used G10 plus KRW currency-tenor panels to analyze three lagged public state variables.
result Three lagged public state variables deliver strong performance in daily regressions.
In the context of multi-curve modeling we consider a two-curve setup, with one curve for discounting (OIS swap curve) and one for generating future cash flows (LIBOR for a give tenor). Within this context we present an approach for the clean-valuation pricing of FRAs and CAPs (linear and nonlinear derivatives) with one…
Neural-SDE models improve option hedging with lower errors and robustness.
problem Improving option hedging strategies using machine learning.
method Derive sensitivity-based and minimum-variance-based hedging strategies using neural-SDE market models.
result Neural-SDE models achieve lower hedging errors and are more robust than traditional models.
New inflation model captures correlations and skew in interest rates.
problem Modeling inflation with market correlations and skew.
method Multi-factor volatility structure with parametric correlation calibration, leveraging single-factor Gaussian model.
result Captures market volatility skew with a single process, simplifying model calibration.
We orthogonalize the NSS model to condition and diagnose its ill-conditioned parameters.
problem The ill-conditioning of the NSS model's design matrix.
method Exact orthogonal reparametrization via QR decomposition.
result Orthogonalization isolates the conditioning structure and maintains fit uncertainty.
Model explains yield curve dynamics using order flow shocks.
problem Understanding the yield curve's fluctuations and their relation to order flows.
method Relates exogenous shocks to order flow surprises, creating a microstructural model that incorporates price and order flow dynamics.
result The model explains yield curve dynamics with fewer parameters and generates liquidity-dependent correlations.
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.
Develops a new model for interest rates allowing negative rates and superior calibration.
problem Current market environment with negative interest rates and poor calibration of existing models.
method Forward price process approach using time-inhomogeneous Lévy processes.
result The model allows for negative interest rates and superior calibration properties.
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.
The paper explains the concave shape of yield curves from trading perspectives.
problem Lack of explanation for the concavity of yield curves from economics theory.
method Explains the concavity of yield curves from trading perspectives.
result Offers an explanation for the concave shape of yield curves.
Once upon a time there was a classical financial world in which all the Libors were equal. Standard textbooks taught that simple relations held, such that, for example, a 6 months Libor Deposit was replicable with a 3 months Libor Deposits plus a 3x6 months Forward Rate Agreement (FRA), and that Libor was a good proxy …
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.
We revisit the problem of pricing and hedging plain vanilla single-currency interest rate derivatives using multiple distinct yield curves for market coherent estimation of discount factors and forward rates with different underlying rate tenors. Within such double-curve-single-currency framework, adopted by the market…
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.
Develops a novel SABR DNN for accurate volatility surface calibration.
problem Inaccurate SABR model approximation for high volatility, long maturities, and out-of-the-money options.
method A specialized Artificial Deep Neural Network (DNN) architecture trained on a large dataset of interest rate volatility surfaces.
result Arbitrage-free calibration of real market volatility surfaces and Cap/Floor prices for any maturity and strike.
We present a quantitative study of the markets and models evolution across the credit crunch crisis. In particular, we focus on the fixed income market and we analyze the most relevant empirical evidences regarding the divergences between Libor and OIS rates, the explosion of Basis Swaps spreads, and the diffusion of c…
The study proposes a new interest rate model that captures long-term periodicity in U.S. Treasury yields.
problem The conventional Hull-White model fails to adequately capture long-term economic cycles in interest rates.
method The study introduces a sinusoidal Hull-White model with a time-varying mean reversion speed.
result The proposed model improves bond pricing and interest rate derivative valuation, especially for longer maturities.
Develops a three-currency HJM framework for Brazilian credit markets, finding significant credit spread differences between indexed segments.
problem Identifies and quantifies differences in corporate credit spreads between two parallel segments of the Brazilian bond market.
method Uses a Heath-Jarrow-Morton framework to model corporate credit as a separate economy, linking it to nominal and real economies through synthetic rates.
result Empirically finds a 640 basis point average difference in credit spreads between CDI-indexed and IPCA-indexed segments, stable through market cycles.
The paper studies continuous submodular functions and their optimization.
problem Maximizing continuous submodular functions in poly. time.
method Characterization of continuous submodularity, operations preserving it, and algorithms for constrained maximization.
result Continuous submodularity is equivalent to a weak DR property, leading to continuous DR-submodular functions with the full DR property.
Solves complex Monge-Ampère equation with Hölder continuous boundary data.
problem Complex Monge-Ampère equation with Hölder continuous boundary data.
method Solves the Dirichlet problem for the complex Monge-Ampère equation.
result The solution is Hölder continuous if the boundary data is Hölder continuous.
Bilevel Continual Learning improves continual learning by transferring knowledge effectively.
problem Catastrophic forgetting and poor generalization in continual learning.
method Bilevel optimization and dual memory management strategies.
result BCL achieves effective knowledge transfer and alleviates catastrophic forgetting.
Defines continuous versions of combinatorial objects from lattice paths.
problem Lattice path enumeration and combinatorial identities.
method Continuous analog of lattice paths and binomials.
result Defines continuous versions of combinatorial objects.
Uniform Lipschitz continuity of isoperimetric profiles in evolving surfaces.
problem Uniform Lipschitz continuity of isoperimetric profiles in evolving surfaces.
method Normalized Ricci flow on compact surfaces.
result Uniform Lipschitz continuity of isoperimetric profiles under normalized Ricci flow.
The study proves unique continuation for biharmonic maps.
problem Unique continuation of biharmonic maps between manifolds.
method Proof of unique continuation results.
result Proves several unique continuation results for biharmonic maps.
CANDI solves the gap between continuous and discrete diffusion models for text generation.
problem Underperformance of continuous diffusion models in discrete data domains.
method Introduces token identifiability and a hybrid framework (CANDI) to decouple discrete and continuous corruption.
result CANDI successfully avoids temporal dissonance, enabling continuous diffusion benefits for discrete spaces.
Continuized Nesterov acceleration accelerates stochastic gradient descent and gossip algorithms.
problem Improving the convergence rate of stochastic gradient descent and gossip algorithms.
method Introducing a continuized variant of Nesterov acceleration, which mixes variables continuously and takes gradient steps at random times.
result The continuized Nesterov acceleration achieves convergence rates similar to Nesterov's original acceleration but with random parameters.
Faster policy learning via continuous-time gradients.
problem Efficiently estimating policy gradients for continuous-time systems.
method Approximating continuous-time gradients directly, using adaptive discretization.
result More efficient policy gradient estimator leads to faster learning.