nep-ets New Economics Papers
on Econometric Time Series
Issue of 2013‒09‒13
three papers chosen by
Yong Yin
SUNY at Buffalo

  1. Exact Simulation of Wishart Multidimensional Stochastic Volatility Model By Chulmin Kang; Wanmo Kang
  2. Segmentation procedure based on Fisher's exact test and its application to foreign exchange rates By Aki-Hiro Sato; Hideki Takayasu
  3. Modeling the impact of forecast-based regime switches on macroeconomic time series By Bel, K.; Paap, R.

  1. By: Chulmin Kang; Wanmo Kang
    Abstract: In this article, we propose an exact simulation method of the Wishart multidimensional stochastic volatility (WMSV) model, which was recently introduced by Da Fonseca et al. \cite{DGT08}. Our method is based onanalysis of the conditional characteristic function of the log-price given volatility level. In particular, we found an explicit expression for the conditional characteristic function for the Heston model. We perform numerical experiments to demonstrate the performance and accuracy of our method. As a result of numerical experiments, it is shown that our new method is much faster and reliable than Euler discretization method.
    Date: 2013–09
  2. By: Aki-Hiro Sato; Hideki Takayasu
    Abstract: This study proposes the segmentation procedure of univariate time series based on Fisher's exact test. We show that an adequate change point can be detected as the minimum value of p-value. It is shown that the proposed procedure can detect change points for an artificial time series. We apply the proposed method to find segments of the foreign exchange rates recursively. It is also applied to randomly shuffled time series. It concludes that the randomly shuffled data can be used as a level to determine the null hypothesis.
    Date: 2013–09
  3. By: Bel, K.; Paap, R.
    Abstract: Forecasts of key macroeconomic variables may lead to policy changes of governments, central banks and other economic agents. Policy changes in turn lead to structural changes in macroeconomic time series models. To describe this phenomenon we introduce a logistic smooth transition autoregressive model where the regime switches depend on the forecast of the time series of interest. This forecast can either be an exogenous expert forecast or an endogenous forecast generated by the model. Results of an application of the model to US inflation shows that (i) forecasts lead to regime changes and have an impact on the level of inflation; (ii) a relatively large forecast results in actions which in the end lower the inflation rate; (iii) a counterfactual scenario where forecasts during the oil crises in the 1970s are assumed to be correct leads to lower inflation than observed.
    Keywords: forecasting;nonlinear time series;inflation;regime switching
    Date: 2013–08–08

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