Coupon Bond Option Pricing on the Basis of Multiple Factors Affine Term Structure Model of Interest Rates

Wenyu, Liu; Xiong, Minghuan; Wang, Xiaoguang; Zhou, Rongxi

doi:10.1109/bife.2011.46

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…Zhou et al [17] develop an algorithm for parameter estimation of a yield curve model by a particle swam optimization method. Liu et al [18] estimate a three-factor affine yield curve model by Kalman filter method. For other literature on estimation of yield curve models, Ren et al [19], Qing and Huahua [20], Liu et al [21], and Maciel et al [22] deal with estimation of yield curve models for government bonds.…”

Section: A Level Factor Representingmentioning

confidence: 99%

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Interest Rate Model With Investor Attitude and Text Mining

et al. 2020

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This paper develops and estimates an interest rate model with investor attitude factors, which are extracted by a text mining method. First, we consider two contrastive attitudes (optimistic versus conservative) towards uncertainties about Brownian motions driving economy, develop an interest rate model, and obtain an empirical framework of the economy consisting of permanent and transitory factors. Second, we apply the framework to a bond market under extremely low interest rate environment in recent years, and show that our three-factor model with level, steepening and flattening factors based on different investor attitudes is capable of explaining the yield curve in the Japanese government bond (JGB) markets.Third, text mining of a large text base of daily financial news reports enables us to distinguish between steepening and flattening factors, and from these textual data we can identify events and economic conditions that are associated with the steepening and flattening factors. We then estimate the yield curve and three factors with frequencies of relevant word groups chosen from textual data in addition to observed interest rates. Finally, we show that the estimated three factors, extracted only from the bond market data, are able to explain the movement in stock markets, in particular Nikkei 225 index.INDEX TERMS Interest rate model, text mining, filtering.

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Section: A Level Factor Representingmentioning

confidence: 99%

“…The two-factor and a three-factor models are estimated in a state space framework shown below, where system equations describe a discretization of state variables x j (j = 1, 2, 3) in (18).…”

Section: B State Space Modelsmentioning

confidence: 99%