Arbitrage Free Nelson Siegel model (AFNS model) 為滿足無套利條件且具優良配適與預測能力之利率模型，本研究探討 AFNS model 參數之校準方法。文中以台灣公債利率資料與美國公債利率資料為例，使用兩種不同的方式，搭配最小平方法與 Nelder-Mead 方法來校準參數，並比較其計算結果之差異。本文發現第二種參數校準方式可以有效率且準確地找出參數校準值。

Arbitrage-Free Nelson Siegel models is an affine term structure model that satisfies no-arbitrage condition and displays good fit and superior forecasting performance. This study explores the calibration method of AFNS model parameters. In this paper, the interest rate data of Taiwan government bonds and US government bonds are used as examples. Two methods are used, combined with the least square method and the Nelder-Mead method to calibrate the parameters, and the differences in the calculation results are compared. This article found that the second calibration method can efficiently and accurately find the parameter calibration value.

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