bond valuation
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2021 ◽  
Vol 150 ◽  
pp. 111201
Author(s):  
Byung-June Kim ◽  
Bong-Gyu Jang

Author(s):  
Mmakganya Mashoene ◽  
Mishelle Doorasamy ◽  
Rajendra Rajaram

The purpose of this study is to investigate the suitable arbitrage-free term-structure model that might be able to fit the South African inflation-indexed spot-rate curve. The instrument has relatively less tradability in the market, which then translates into a lack of adequate data for bond valuation/pricing. Pricing deviations might give inflated/deflated projections on the value of government debt; consequently, higher estimated interest cost to be paid. A proper valuation of these instruments is mandatory as they form part of government funding/borrowing and the country’s budgeting processes in the medium term. The performance of newly developed non-linear multifactor models that follows the Nelson-Siegel (1987) framework was compared to the arbitrage-free Vasicek (1977) model and linear parametric models to assess any significant deviations in forecasting the real spot-rate curve over a short period. Models with constant parameters (i.e. linear parametric, cubic splines, Nelson-Siegel (1987) and Svensson (1994)) gave a perfect fit, they proved to marginally lose fitting capabilities during periods of higher volatility. Therefore, it could be concluded that the application of either Nelson-Siegel (1987) model or Svensson (1994) model on forecasting South African real spot-rate curve gave a perfect fit. However, for a solid conclusion to be derived, it is imperative to explore the performance of these models over a period of stressed market and economic conditions.


2021 ◽  
Vol 1821 (1) ◽  
pp. 012053
Author(s):  
Imroatus Siyamah ◽  
Endah RM Putri ◽  
Chairul Imron

2021 ◽  
Vol 10 (1) ◽  
pp. 85-93
Author(s):  
Ubudia Hiliaily Chairunnnisa ◽  
Abdul Hoyyi ◽  
Hasbi Yasin

The basic assumption that is often used in bond valuations is the assumption on the Black-Scholes model. The practical assumption of the Black-Scholes model is the return of assets with normal distribution, but in reality there are many conditions where the return of assets of a company is not normally distributed and causing improperly developed bond valuation modeling. The Fast-Fourier Transform model (FFT) was developed as a solution to this problem. The Fast-Fourier Transformation Model is a Fourier transformation technique with high accuracy and is more effective because it uses characteristic functions. In this research, a modeling will be carried out to calculate bond valuations designed to take advantage of the computational power of the FFT. The characteristic function used is the Variance Gamma, which has the advantage of being able to capture data return behavior that is not normally distributed. The data used in this study are Sustainable Bonds I of Bank Danamon Phase I Year  2019 Series B, Sustainable Bonds II of Bank CIMB Niaga II Phase IV Year 2018 Series C, Sustainable Subordinated Bonds II of Bank UOB Indonesia Phase II 2019. The results obtained are FFT model using the Variance Gamma characteristic function gives more precise results for the return of assets with not normal distribution.  Keywords: Bonds, Bond Valuation, Black-Scholes, Fast-Fourier Transform, Variance Gamma


2020 ◽  
Vol 33 ◽  
pp. 101215 ◽  
Author(s):  
Subramanian R. Iyer ◽  
Betty J. Simkins ◽  
Heng Wang
Keyword(s):  

2019 ◽  
Vol 20 (3) ◽  
pp. 483-497
Author(s):  
Juan Dong ◽  
Lyudmila Korobenko ◽  
A. Deniz Sezer

Author(s):  
Yiying Cheng

This chapter introduces the analysis and valuation of bonds with embedded options. For callable bonds, it discusses their unique reinvestment risk and negative convexity. For both callable bonds and puttable bonds, the chapter introduces two additional measures to gauge their risk: yield-to-call and yield-to-put, respectively. The chapter reviews the application of the spot rate curve in bond valuation and introduces the Z-spread to measure bond-specific risk more accurately. To model interest rate risk, the chapter builds a binomial interest rate model and calibrates it with on-the-run Treasury issues. The option-adjusted-spread (OAS) is introduced to measure the bond-specific risk excluding the option effect. The difference between Z-spread and OAS represents the option effect. Common measures of convertible bond risk and value are discussed including the possibility of valuating a convertible bond using option-pricing models and its drawbacks.


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