Arbeitspapier

Comparación de pronósticos de la estructura temporal de tasas de interés de México para distintas especificaciones del modelo afín

Four specifications of an affine model with risk aversion and no arbitrage conditions are estimated for the Mexican Term Structure of Interest Rates, contrasting their empirical properties and the accuracy of their in and out of sample forecasts. The traditional models are extended by adding macroeconomic variables to analyze if the latter provide sufficient information to improve the adjustment and the forecast of interest rates. Using monthly data of the Zero Coupon Bonds, VIX, WTI, exchange rate, inflation and growth in the period 2002-2017, it is found that, although there is no superiority of a single model for the in and/or out of sample forecast of the yield curve, adding macroeconomic variables helps to improve the short and medium term forecasts independently of the type of factors used.

Sprache
Spanisch

Erschienen in
Series: Working Papers ; No. 2020-01

Klassifikation
Wirtschaft
Hypothesis Testing: General
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Forecasting Models; Simulation Methods
Interest Rates: Determination, Term Structure, and Effects
Money and Interest Rates: Forecasting and Simulation: Models and Applications
Asset Pricing; Trading Volume; Bond Interest Rates
Thema
Afin Model
Yield Curve Forecast
Principal Components
Kalman Filter
No-Arbitrage Condition

Ereignis
Geistige Schöpfung
(wer)
Lelo-de-Larrea, Alejandra
Ereignis
Veröffentlichung
(wer)
Banco de México
(wo)
Ciudad de México
(wann)
2020

Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Lelo-de-Larrea, Alejandra
  • Banco de México

Entstanden

  • 2020

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