Comparison of non-linear optimization algorithms for yield curve estimation

Manousopoulos, Polychronis; Michalopoulos, Michalis

doi:10.1016/j.ejor.2007.09.017

Cited by 23 publications

(23 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…outperform the other (Manousopoulos & Michalopoulos, 2009). In this paper, we employed the most representative type of each method (cubic splines and Nelson-Siegel) with the goal of estimating the zero-coupon yield curve.…”

Section: Methodology and Resultsmentioning

confidence: 99%

Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve

Lorenčič

2016

Naše Gospodarstvo/Our Economy

View full text Add to dashboard Cite

Understanding the relationship between interest rates and term to maturity of securities is a prerequisite for developing financial theory and evaluating whether it holds up in the real world; therefore, such an understanding lies at the heart of monetary and financial economics. Accurately fitting the term structure of interest rates is the backbone of a smoothly functioning financial market, which is why the testing of various models for estimating and predicting the term structure of interest rates is an important topic in finance that has received considerable attention for many decades. In this paper, we empirically contrast the performance of cubic splines and the Nelson-Siegel model by estimating the zero-coupon yields of Austrian government bonds. The main conclusion that can be drawn from the results of the calculations is that the Nelson-Siegel model outperforms cubic splines at the short end of the yield curve (up to 2 years), whereas for medium-term maturities (2 to 10 years) the fitting performance of both models is comparable.

show abstract

Section: Methodology and Resultsmentioning

confidence: 99%

Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve

Lorenčič

2016

Naše Gospodarstvo/Our Economy

View full text Add to dashboard Cite

show abstract

“…c i andγ i as well asd i andα i are obtained by regressingβ it andλ t on an intercept andβ i,t−h andλ t−h , respectively 3 . Differently from [2], we consider the λ parameter as time variant because, according to [20], the results are improved and it is not a good proxy for the Brazilian bonds market fix this parameter by observing the fixed-income market behavior. Thus, forecasting the yield curve is equivalent to forecasting {β 1t ,β 2t ,β 3t ,λ t }.…”

Section: Forecasting Yield Curve Level Slope and Curvaturementioning

confidence: 99%

Evolving Functional Fuzzy Model For Interest Rate Term Structure Forecasting

Maciel¹,

Gomide²,

Ballini³

2016

Anais Do 10. Congresso Brasileiro De Inteligência Computacional

View full text Add to dashboard Cite

“…The parameters λ t and β 3t control the possible presence of a hump in the yield curve. Specifically, λ t determines the position (time) of the hump, while β 3t determines its magnitude and direction [20]. Note that β 1t , β 1t + β 2t and λ t should obviously be positive, while λ t should have an upper bound, e.g.…”

Section: Yield Curve Modelingmentioning

confidence: 99%

“…Differently from [2], we consider the λ parameter as time variant because, according to [20], the results are improved and it is not a good proxy for the Brazilian bonds market fix this parameter by observing the fixed-income market behavior. Thus, forecasting the yield curve is equivalent to forecasting {β 1t ,β 2t ,β 3t ,λ t }.…”

Section: Forecasting Yield Curve Level Slope and Curvaturementioning

confidence: 99%

See 1 more Smart Citation

Evolving Functional Fuzzy Model for Term Structure of Interest Rates Forecasting

Maciel¹,

Gomide²,

Ballini³

2012

L&NLM

View full text Add to dashboard Cite

-Evolving fuzzy systems use data streams to continuously adapt the structure and functionality of fuzzy rule-based models. It gradually develops the model structure and its parameters from a stream of data, which is essential when dealing with complex and nonstationary systems. In this paper, we suggest the use of functional evolving fuzzy modeling in the form of Takagi-Sugeno (eTS) model to forecast Brazilian government bond yields through the Nelson-Siegel function. In this case the eTS adaptively estimates the parameters Nelson-Siegel function to perform forecasts. This is a crucial procedure for bond portfolio management, derivatives and bonds pricing. The experiments reported here use daily data of the Brazilian National Treasury Bills of the period from January 2007 to December 2009 for one, three, six, nine and twelve months ahead forecasting horizons. The evolving model was compared with autoregressive and random walk models, in terms of root mean squared error. Results indicate that eTS is a promising approach to deal with government bond yields forecasting because it gives more accurate Nelson-Siegel parameters values than traditional approaches. Resumo -Sistemas nebulosos evolutivos utilizam fluxos de dados para adaptar, continuamente, sua estrutura e parâmetros em modelos nebulosos baseados em regras. Desenvolvem gradualmente a estrutura do modelo e seus parâmetros a partir de fluxos de dados, o queé essencial para o tratemento de sistemas complexos e não-estacionários. Neste artigo,é sugerida a utilização da modelagem funcional nebulosa evolutiva na forma de um modelo do tipo Takagi-Sugeno (eTS) para a previsão da curva de juros no Brasil por meio da função de Nelson-Siegel. Neste caso, o modelo eTS estima, de forma adaptativa, os parâmetros da função de Nelson-Siegel para realizar previsões. A previsão da curva de jurosé essencial para administração de portfólios baseados em títulos públicos, e na precificação de títulos e derivativos. Os experimentos reportados no artigo utilizam dados diários das Letras do Tesouro Nacional no período de Janeiro de 2007 a Dezembro de 2009 para horizontes de previsão de 1, 3, 6, 9 e 12 meses. O modelo evolutivo foi comparado com os modelos autoregressivo e de passeio aleatório em termos da métrica de raiz do erro quadrático médio. Os resultados indicam que o modelo eTSé uma abordagem promissora para o problema de previsão da curva de juros, uma vez que foi capaz de proporcionar estimativas mais acuradas para os parâmetros de Nelson-Siegel em comparação com as abordagens tradicionais. Keywords -Palavras-chave -Sistemas Nebulosos Evolutivos, Previsão de Séries-Temporais, Curva de Juros e Taxa de Juros.

show abstract

Comparison of non-linear optimization algorithms for yield curve estimation

Cited by 23 publications

References 16 publications

Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve

Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve

Evolving Functional Fuzzy Model For Interest Rate Term Structure Forecasting

Evolving Functional Fuzzy Model for Term Structure of Interest Rates Forecasting

Contact Info

Product

Resources

About