nep-ets New Economics Papers
on Econometric Time Series
Issue of 2021‒11‒15
five papers chosen by
Jaqueson K. Galimberti
Auckland University of Technology

  1. Multiplicative Component GARCH Model of Intraday Volatility By Xiufeng Yan
  2. Generalized Spectral Tests for High Dimensional Multivariate Martingale Difference Hypotheses By Xuexin WANG
  3. Autoregressive conditional duration modelling of high frequency data By Xiufeng Yan
  4. Dynamic Interdependence and Volatility Transmission from the American to the Brazilian Stock Market By Edson Z. Monte; Lucas B. Defanti
  5. US Policy Responses to the Covid-19 Pandemic and Sectoral Stock Indices: A Fractional Integration Approach By Guglielmo Maria Caporale; Luis A. Gil-Alana; Emmanuel Joel Aikins Abakah

  1. By: Xiufeng Yan
    Abstract: This paper proposes a multiplicative component intraday volatility model. The intraday conditional volatility is expressed as the product of intraday periodic component, intraday stochastic volatility component and daily conditional volatility component. I extend the multiplicative component intraday volatility model of Engle (2012) and Andersen and Bollerslev (1998) by incorporating the durations between consecutive transactions. The model can be applied to both regularly and irregularly spaced returns. I also provide a nonparametric estimation technique of the intraday volatility periodicity. The empirical results suggest the model can successfully capture the interdependency of intraday returns.
    Date: 2021–11
  2. By: Xuexin WANG (Xiamen University)
    Abstract: This study proposes new generalized spectral tests for multivariate Martingale Difference Hypotheses, especially suitable for high-dimensionality situations. The new tests are based on the martingale difference divergence covariance (MDD) proposed by Shao and Zhang (2014). It considers block-wise serial dependence of all lags, therefore, is consistent against general block-wise nonparametric Pitman’s local alternatives at the parametric rate n−1/2, where n is the sample size, and free of a user-chosen parameter. In order to cope with the highdimensionality in the sense that the dimension of time series is comparable to or even greater than the sample size, it is pivotal to employ a bias-reduced estimator for each individual MDD in the test statistic. Monte Carlo simulations reveal that the bias-reduced statistic generally performs better than its competitors substantially. Moreover, it is robust to heteroskedasticity of unknown forms and heavy-tails in the data generating processes. We apply our approach to test the efficient market hypothesis on the US stock market, using data sets on the monthly and daily data of portfolios sorted by industry. Our test results provide strong evidence against the efficient market hypothesis with respect to the US stock market at monthly frequency
    Keywords: Efficient Market Hypothesis; Generalized Spectral Tests; Nonintegrable Weighting Function; High-dimensionality; Bias Reduction
    JEL: C12 C22
    Date: 2021–11–06
  3. By: Xiufeng Yan
    Abstract: This paper explores the duration dynamics modelling under the Autoregressive Conditional Durations (ACD) framework (Engle and Russell 1998). I test different distributions assumptions for the durations. The empirical results suggest unconditional durations approach the Gamma distributions. Moreover, compared with exponential distributions and Weibull distributions, the ACD model with Gamma distributed innovations provide the best fit of SPY durations.
    Date: 2021–11
  4. By: Edson Z. Monte; Lucas B. Defanti
    Abstract: The main aim of this paper is to verify the dynamic interdependence and transmission of volatility from the American (SP500) to the Brazilian stock market (IBOVESPA and sectoral indexes). Estimates were performed by GARCH/BEKK methodology, considering the period from January 2007 to December 2019. In the periods considered as “critical events†there was a significant increase in the conditional covariance between SP500 and Brazilian stock indexes (IBOVESPA and sector indices), which suggests for the hypothesis of financial contagion. The covariance increased more intensely and persistently during the so-called subprime crisis, one that had a major impact on the Brazilian economy, especially for the financial and industrial indexes. Furthermore, conditional variance estimates for Brazilian indexes revealed that that internal turmoil, whether economic or political, regardless of the international scenario (“critical events†), affected the volatility of the Brazilian stock market. These results have important implications regarding the future decisions of economic agents (politicians and investors), contributing to a better understanding of the behavior of the Brazilian stock market vis-à -vis the American stock market and the internal turbulences in the Brazilian economy, whether political or economic.
    Keywords: United States; Brazil; Stock Market; Volatility; GARCH-BEKK.
    JEL: G17 C32 C58
    Date: 2021–10–09
  5. By: Guglielmo Maria Caporale; Luis A. Gil-Alana; Emmanuel Joel Aikins Abakah
    Abstract: This paper uses fractional integration methods to assess the impact of US policy responses (containment and health measures, income support policy, debt-relief policy, changes in the Effective Federal Funds Rate, monetary and fiscal announcements) to the COVID-19 pandemic on US sectoral stock indices for Technology, Telecom, Health Care, Real Estate, Consumer Staples, Consumer Discretionary, Industrials, Basic Materials, Energy and Utilities from 1 January 2020 to 11 June 2021. The results provide evidence of mean reversion for seven sectoral stock indices (Consumer Discretionary, Consumer Staples, Health, Industrials, Technology, Telecom and Utilities), with orders of integration significantly below (though close to) 1 under the assumption of white noise errors. By contrast, three indices (Basic Materials, Energy and Real Estate) are found to be highly persistent (d ≥ 1), with shocks having permanent effects. As for the policy responses, it appears that the containment and health restrictions, income support policy, and debit relief policy have had no impact. By contrast, changes in the Effect Federal Funds Rate have had a significant and positive effect on all sectors except Energy and Industrial, and similarly monetary and fiscal announcements have had a positive and significant effect in most cases. Finally, the higher mortality rate caused by the Covid-19 pandemic has affected negatively most sectoral stock indices.
    Keywords: Covid-19 pandemic, US sectoral stock indices, fractional integration
    JEL: C22 C32 G15
    Date: 2021

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