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The present study deals with the analysis and mapping of Swiss franc interest rates. Interest rates depend on time and maturity, defining term structure of the interest rate curves (IRC). In the present study IRC are considered in a…

Statistical Finance · Quantitative Finance 2009-11-13 M. Kanevski , M. Maignan , A. Pozdnoukhov , V. Timonin

The Vasicek model is a commonly used interest rate model, and there exist many extensions and generalizations of it. However, most generalizations of the model are either univariate or assume the noise process to be Gaussian, or both. In…

The main purpose of this work is to derive a partial differential equation for the reserves of life insurance liabilities subject to stochastic interest rates where the benefits and premiums depend directly on changes in the interest rate…

Risk Management · Quantitative Finance 2021-01-01 David R. Baños

It is well known that the Cox-Ingersoll-Ross (CIR) stochastic model to study the term structure of interest rates, as introduced in 1985, is inadequate for modelling the current market environment with negative short interest rates.…

Computational Finance · Quantitative Finance 2018-06-12 Giuseppe Orlando , Rosa Maria Mininni , Michele Bufalo

In this paper, a new way to integrate volatility information for estimating value at risk (VaR) and conditional value at risk (CVaR) of a portfolio is suggested. The new method is developed from the perspective of Bayesian statistics and it…

Risk Management · Quantitative Finance 2022-05-04 Taras Bodnar , Vilhelm Niklasson , Erik Thorsén

In this paper, we study option pricing under Vasicek Model by a Hamiltonian approach. Since the interest rate changes with time, we split the time to maturity into infinite steps, and the matrix element during each step could be calculated…

Pricing of Securities · Quantitative Finance 2024-12-09 Chao Guo , Ning Yao

In this work, we consider the issue of pricing exchange options and spread options with stochastic interest rates. We provide the closed form solution for the exchange option price when interest rate is stochastic. Our result holds when…

Condensed Matter · Physics 2007-05-23 Craig Liu , D. F. Wang

To address the complexity of financial time series, this paper proposes a forecasting model combining sliding window and variational mode decomposition (VMD) methods. Historical stock prices and relevant market indicators are used to…

Machine Learning · Computer Science 2025-08-22 Luke Li

In this paper, we consider the problem of pricing discretely-sampled variance swaps based on a hybrid model of stochastic volatility and stochastic interest rate with regime-switching. Our modelling framework extends the Heston stochastic…

Mathematical Finance · Quantitative Finance 2016-03-29 Jiling Cao , Teh Raihana Nazirah Roslan , Wenjun Zhang

This paper explores the implications of producing forecast distributions that are optimized according to scoring rules that are relevant to financial risk management. We assess the predictive performance of optimal forecasts from…

Statistical Finance · Quantitative Finance 2023-03-06 Yuru Sun , Worapree Maneesoonthorn , Ruben Loaiza-Maya , Gael M. Martin

In the last two decades, a number of methods have been proposed for forecasting based on fuzzy time series. Most of the fuzzy time series methods are presented for forecasting of car road accidents. However, the forecasting accuracy rates…

Artificial Intelligence · Computer Science 2010-05-25 G. Arutchelvan , S. K. Srivatsa , R. Jagannathan

In the Vasicek credit portfolio model, tail risk is driven primarily by the asset-correlation parameter, yet empirically is subject to correlation risk. We propose a stochastic correlation extension of the Vasicek framework in which the…

Risk Management · Quantitative Finance 2026-03-06 Dhruv Bansal , Mayank Goud , Sourav Majumdar

A novel approach for dynamic modeling and forecasting of realized covariance matrices is proposed. Realized variances and realized correlation matrices are jointly estimated. The one-to-one relationship between a positive definite…

Methodology · Statistics 2019-02-18 Nicole Barthel , Claudia Czado , Yarema Okhrin

Partition-wise models offer a flexible approach for modeling complex and multidimensional data that are capable of producing interpretable results. They are based on partitioning the observed data into regions, each of which is modeled with…

Methodology · Statistics 2017-06-07 Rex C. Y. Cheung , Alexander Aue , Thomas C. M. Lee

We study the dynamics of the linear and non-linear serial dependencies in financial time series in a rolling window framework. In particular, we focus on the detection of episodes of statistically significant two- and three-point…

Statistical Finance · Quantitative Finance 2013-01-10 Milan Žukovič

Path integral techniques for the pricing of financial options are mostly based on models that can be recast in terms of a Fokker-Planck differential equation and that, consequently, neglect jumps and only describe drift and diffusion. We…

Pricing of Securities · Quantitative Finance 2010-11-08 L. Z. J. Liang , D. Lemmens , J. Tempere

In this paper we propose a semi-Markov modulated model of interest rates. We assume that the switching process is a semi-Markov process with finite state space E and the modulated process is a diffusive process. We derive recursive…

Pricing of Securities · Quantitative Finance 2012-10-12 Guglielmo D'Amico , Raimondo Manca , Giovanni Salvi

The discrete-time multifactor Vasi\v{c}ek model is a tractable Gaussian spot rate model. Typically, two- or three-factor versions allow one to capture the dependence structure between yields with different times to maturity in an…

Mathematical Finance · Quantitative Finance 2016-09-05 Philipp Harms , David Stefanovits , Josef Teichmann , Mario V. Wüthrich

We investigate the joint description of the interest-rate term stuctures of Italy and an AAA-rated European country by mean of a --here proposed-- correlated CIR-like bivariate model where one of the state variables is interpreted as a…

General Finance · Quantitative Finance 2008-12-02 L. Bertini , L. Passalacqua

Quantum computers are not yet up to the task of providing computational advantages for practical stochastic diffusion models commonly used by financial analysts. In this paper we introduce a class of stochastic processes that are both…

Quantum Physics · Physics 2023-11-03 Eric Ghysels , Jack Morgan , Hamed Mohammadbagherpoor
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