nep-ets New Economics Papers
on Econometric Time Series
Issue of 2006‒12‒04
six papers chosen by
Yong Yin
SUNY at Buffalo
  1. Temporal aggregation and bandwidth selection in estimating long memory By Souza, Leonardo
  2. Long memory and non-linearity in Stock Markets By Bond, Derek; Dyson, Kenneth
  3. Income convergence? Evidence of non-linearity in the East Asian Economies: A comment By Liew, Venus Khim-Sen; Ahmad, Yusuf
  4. Factor Model Forecasts for New Zealand By Matheson, Troy D
  5. TESTING NONLINEARITIES BETWEEN BRAZILIAN EXCHANGE RATE AND INFLATION VOLATILITIES By Christiane R. Albuquerque; Marcelo S. Portugal
  6. Implied Volatility using Variance Decomposition Method By Kim, Joocheol; Kim, WooWhan; Kim, KiHyung
  1. By: Souza, Leonardo
    Abstract: This paper aims at showing that a temporal aggregation and a specific bandwidth reduction lead to the same asymptotic properties in estimating long memory by Geweke and Porter-Hudak’s (1983) and Robinson’s (1995b) estimators (henceforth GPH and GSPR). In other words, irrespectively of the level of temporal aggregation, the asymptotic properties of the estimator are uniquely determined by the number of periodogram ordinates used in the estimation, provided some mild additional assumptions are imposed. Monte Carlo simulations show that this result is a good approximation in finite samples. A real example with the daily US Dollar/French Franc exchange rate series is also provided.
    Keywords: Temporal Aggregation; Long Memory; Bandwidth; Spectrum
    JEL: C10
    Date: 2006–09
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:108&r=ets
  2. By: Bond, Derek; Dyson, Kenneth
    Abstract: In this paper the long memory and non-linear properties of share prices in the UK’s Stock Exchange and AIM are explored. The results suggest that the most commonly traded shares exhibit long memory thus raising interesting issues about the validity of normal assumptions of market efficiencies.
    Keywords: Efficient Markets; Long Memory; Nonlinear Models
    JEL: G14 C22
    Date: 2006–09
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:252&r=ets
  3. By: Liew, Venus Khim-Sen; Ahmad, Yusuf
    Abstract: This study demonstrates the usefulness of Kapetanois et al. (2003) test in differentiating the two stages of income convergence—long run convergence and catching up. A re-examination of the “Four Asian Dragons” economies, in which their income differentials with respect to Japan have been identified as non-linear stationary in Liew and Lim (2005), reveals that the economy of Hong Kong, Korea and Singapore are catching up, while Taiwan has yet to catch up, with the Japan economy.
    Keywords: Income convergence; catching up; long run convergence; East Asia; non-linear unit root test
    JEL: F43 C32 O40
    Date: 2006–03
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:519&r=ets
  4. By: Matheson, Troy D
    Abstract: This paper focuses on forecasting four key New Zealand macroeconomic variables using a dynamic factor model and a large number of predictors. We compare the (simulated) real-time forecasting performance of the factor model with a variety of other time-series models (including the Reserve Bank of New Zealand’s published forecasts), and we gauge the sensitivity of our results to alternative variable-selection algorithms. We find that the factor model performs particularly well at longer horizons.
    JEL: G00 G0
    Date: 2006–04–13
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:807&r=ets
  5. By: Christiane R. Albuquerque; Marcelo S. Portugal
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:anp:en2006:162&r=ets
  6. By: Kim, Joocheol; Kim, WooWhan; Kim, KiHyung
    Abstract: This paper provides a new method-what is called variance decomposition method- to calculate market volatility index implied in option price and compares the prediction quality of realized volatility with VIX that is well known as volatility index. The volatility using variance decomposition has an advantage, since it reflects market participants’ expectation. Our method is based on the variance calculation decomposed into two components which are conditioned on other variable, strike price in this paper. We use high-frequency data (daily based) to calculate variance decomposition volatility as well as VIX and compare the prediction quality of these indexes for realized volatility. The empirical result shows that variance decomposition volatility index is similar to the dynamics of VIX and shows good prediction power of realized volatility. We also discuss our findings in long range dependence of realized volatility with respect to variance decomposition and VIX.
    Keywords: Realized Volatility; Implied Volatility; Variance decomposition; VIX
    JEL: G13 G12 G32
    Date: 2006–11
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:936&r=ets
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