Academic literature on the topic 'Callable range accrual swap'

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Journal articles on the topic "Callable range accrual swap"

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BEVERIDGE, CHRISTOPHER, and MARK JOSHI. "THE EFFICIENT COMPUTATION OF PRICES AND GREEKS FOR CALLABLE RANGE ACCRUALS USING THE DISPLACED-DIFFUSION LMM." International Journal of Theoretical and Applied Finance 17, no. 01 (2014): 1450001. http://dx.doi.org/10.1142/s0219024914500010.

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We study the simulation of range accrual coupons when valuing callable range accruals in the displaced-diffusion LIBOR market model (DDLMM). We introduce a number of new improvements that lead to significant efficiency improvements, and explain how to apply the adjoint-improved pathwise method to calculate deltas and vegas under the new improvements, which was not previously possible for callable range accruals. One new improvement is based on using a Brownian-bridge-type approach for simulating the range accrual coupons. We consider a variety of examples, including when the reference rate is a LIBOR rate, when it is a spread between swap rates, and when the multiplier for the range accrual coupon is stochastic.
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JAIMUNGAL, SEBASTIAN, and VLADIMIR SURKOV. "VALUING EARLY-EXERCISE INTEREST-RATE OPTIONS WITH MULTI-FACTOR AFFINE MODELS." International Journal of Theoretical and Applied Finance 16, no. 06 (2013): 1350034. http://dx.doi.org/10.1142/s0219024913500349.

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Multi-factor interest-rate models are widely used. Contingent claims with early exercise features are often valued by resorting to trees, finite-difference schemes and Monte Carlo simulations. When jumps are present, however, these methods are less effective. In this work we develop an algorithm based on a sequence of measure changes coupled with Fourier transform solutions of the pricing partial integro-differential equation to solve the pricing problem. The new algorithm, which we call the irFST method, also neatly computes option sensitivities. Furthermore, we are also able to obtain closed-form formulae for accrual swaps and accrual range notes. We demonstrate the versatility and precision of the method through numerical experiments on European, Bermudan and callable bond options, accrual swaps and accrual range notes.
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Seong, Hanki, and Sang Bin Lee. "An Optimal Selection of the basis Functions for the Valuation of Interest Rate Structured Notes." Journal of Derivatives and Quantitative Studies 22, no. 4 (2014): 637–74. http://dx.doi.org/10.1108/jdqs-04-2014-b0003.

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This paper examines which basis functions are efficient to employ a combined method of Hull and White (1990) with the Monte Carlo simulation when we price a callable range note or a callable bond. We use the Huge and Rom-Poulsen (2007) method which has modified the least squared Monte Carlo simulation proposed by Longstaff and Schwartz (2001) to reduce the estimation errors of the continuation value or the underlying assets. To use Monte carlo Simulation for pricing the early exercise premium, it is essential to accurately estimate the continuation value, because the investors will choose the higher value between the exercise and the continuation value at the possible early exercise dates. The main purpose of this paper is to analyze the estimation errors originating from the choice of the basis functions for the underlying asset and the continuation value estimation. We choose the callable bond and the callable range accrual note to show which basis functions are reliable to reduce the estimation errors. For this purpose, we replicate the callable range accrual note with a portfolio of a fixed rate bond and a delayed digital option. We use several basis functions such as a constant, the instantaneous interest rates, and the range in order to see which basis function is efficient for our purpose. We examine several combinations of the basis functions depending on which basis functions will be used for the underlying asset or the continuation value estimation. We show that the range which is an important determinant of the callable range accrual note is an effective basis function to accurately determine the underlying asset and the continuation value for the pricing of the callable range accrual note.
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Baaquie, Belal E., Xin Du, Pan Tang, and Yang Cao. "Pricing of range accrual swap in the quantum finance Libor Market Model." Physica A: Statistical Mechanics and its Applications 401 (May 2014): 182–200. http://dx.doi.org/10.1016/j.physa.2014.01.042.

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Lin, Shih-Kuei, Shin-Yun Wang, Carl R. Chen, and Lian-Wen Xu. "Pricing Range Accrual Interest Rate Swap employing LIBOR market models with jump risks." North American Journal of Economics and Finance 42 (November 2017): 359–73. http://dx.doi.org/10.1016/j.najef.2017.07.018.

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He, Jie-Cao, Chang-Chieh Hsieh, Zi-Wei Huang, and Shih-Kuei Lin. "Valuation of callable range accrual linked to CMS Spread under generalized swap market model." International Review of Financial Analysis, September 2023, 102956. http://dx.doi.org/10.1016/j.irfa.2023.102956.

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Zhang, Joshua Xingzhi. "Pricing Callable Constant Maturity Swap Spread Range Accruals Under the Two Factor Linear Gaussian Martingale Model Using Fast Fourier Transform." SSRN Electronic Journal, 2011. http://dx.doi.org/10.2139/ssrn.1815298.

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Xiao, Tim. "AN EFFICIENT LATTICE ALGORITHM FOR THE LIBOR MARKET MODEL." September 27, 2020. https://doi.org/10.5281/zenodo.4053698.

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The LIBOR Market Model has become one of the most popular models for pricing interest rate products. It is commonly believed that Monte-Carlo simulation is the only viable method available for the LIBOR Market Model. In this article, however, we propose a lattice approach to price interest rate products within the LIBOR Market Model by introducing a shifted forward measure and several novel fast drift approximation methods. This model should achieve the best performance without losing much accuracy. Moreover, the calibration is almost automatic and it is simple and easy to implement. Adding this model to the valuation toolkit is actually quite useful; especially for risk management or in the case there is a need for a quick turnaround.
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Dissertations / Theses on the topic "Callable range accrual swap"

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Chao, Tzu-Hsien, and 趙子賢. "Callable LIBOR Exotics Valuation in Lognormal Forward LIBOR Model, Cases of Callable Inverse Floater, Callable Cumulative Inverse Floater, and Callable Daily Range Accrual Note." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/88041380636389746401.

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碩士<br>國立政治大學<br>金融研究所<br>94<br>The market of the structured notes has been blossoming. The lognormal forward LIBOR model is more suitable for the valuation of structured notes than do the traditional interest rate models. In this article, we perform three case studies of the valuation of the structured notes linked to LIBOR in lognormal forward LIOBR model. It is easier to implement the lognormal forward LIBOR model by Monte Carlo simulation due to the non-Markovian property. Therefore, the least-squares Monte Carlo approach is used to deal with the callable feature of the structured notes in our case studies.
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Feng, Kuan-Chun, and 馮冠群. "Pricing and Empirical Analysis of Callable Range Accrual Linked to CMS: Comparison of LIBOR and GARCH Market Models." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/ueqqv2.

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碩士<br>國立政治大學<br>統計學系<br>106<br>Through the least squares Monte Carlo method, Using the Lognormal Forward LIBOR Model (LFM) and GARCH (Generalized Autoregressive conditional heteroskedasticity) market models to price the derivatives of the CMS (Constant Maturity Swap) Range Accrual. In this paper, since the closed form of solution can’t be derived under the range accrual, firstly we based on the dynamic process under LFM, the forward LIBOR interest rate and CMS interest rate are simulated, and the derivatives is evaluated by the least square Monte Carlo method. There are two ways to estimate the volatility. The first one is estimated by historical data. The second is to change the hypothetical form of LFM's forward rate instantaneous volatility to the GARCH volatility model, and the two CMS simulation results are compared with the real market price. The empirical results show that the hypothetical form of LFM's forward interest rate instantaneous volatility which changed to the GARCH model, it’s CMS simulation is closer to the real market price.
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