Understanding and modeling the volatility measurements is important for forecasting the risk and for evaluating asset allocation decisions of stock market. The study have used the daily frequency data from January 1, 2002 to September 30, 2016 as an in-sample period to perform empirical analyses for modeling and predicting the volatility dynamics of Mexican stock market (IPC). To facilitate the variance forecast, the competing models are ARCH (p, q), GARCH (p, q), and its variations i.e. Glosten Jagnnathon Runkle GARCH, GARCH in Mean, Exponential GARCH, and Quadratic GARCH. The results of residual diagnostics suggested that stock market of Mexico is characterized by heteroskedasticity, multicolinearity, non-normality, and serial correlation. Volatility measurements by ARCH and GARCH signify that the current conditional variance of Mexico is determined by its past price behavior and previous day volatility. Today’s volatility does impact the current stock returns as indicated by GARCH-M. Results of EGARCH explained that any large size news produces high volatility as compared to small size news. Effects of bad news are greater on the volatility of the Mexican stock market than good news. GJR GARCH described the asymmetric behavior of returns and variance in the politically conflicted regime during 2006-2012. Moreover, QGARCH effect is not linear. Findings have the implications for individuals and corporate investors about retaining their risky stocks.
| Published in | Journal of Public Policy and Administration (Volume 2, Issue 3) |
| DOI | 10.11648/j.jppa.20180203.13 |
| Page(s) | 32-39 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2018. Published by Science Publishing Group |
Volatility, ARCH Family, Mexican Stock Market
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APA Style
Vina Javed Khan, Abdul Qadeer, Bezon Kumar. (2018). Financial Forecasting by Autoregressive Conditional Heteroscedasticity (ARCH) Family: A Case of Mexico. Journal of Public Policy and Administration, 2(3), 32-39. https://doi.org/10.11648/j.jppa.20180203.13
ACS Style
Vina Javed Khan; Abdul Qadeer; Bezon Kumar. Financial Forecasting by Autoregressive Conditional Heteroscedasticity (ARCH) Family: A Case of Mexico. J. Public Policy Adm. 2018, 2(3), 32-39. doi: 10.11648/j.jppa.20180203.13
AMA Style
Vina Javed Khan, Abdul Qadeer, Bezon Kumar. Financial Forecasting by Autoregressive Conditional Heteroscedasticity (ARCH) Family: A Case of Mexico. J Public Policy Adm. 2018;2(3):32-39. doi: 10.11648/j.jppa.20180203.13
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Download@article{10.11648/j.jppa.20180203.13,
author = {Vina Javed Khan and Abdul Qadeer and Bezon Kumar},
title = {Financial Forecasting by Autoregressive Conditional Heteroscedasticity (ARCH) Family: A Case of Mexico},
journal = {Journal of Public Policy and Administration},
volume = {2},
number = {3},
pages = {32-39},
doi = {10.11648/j.jppa.20180203.13},
url = {https://doi.org/10.11648/j.jppa.20180203.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jppa.20180203.13},
abstract = {Understanding and modeling the volatility measurements is important for forecasting the risk and for evaluating asset allocation decisions of stock market. The study have used the daily frequency data from January 1, 2002 to September 30, 2016 as an in-sample period to perform empirical analyses for modeling and predicting the volatility dynamics of Mexican stock market (IPC). To facilitate the variance forecast, the competing models are ARCH (p, q), GARCH (p, q), and its variations i.e. Glosten Jagnnathon Runkle GARCH, GARCH in Mean, Exponential GARCH, and Quadratic GARCH. The results of residual diagnostics suggested that stock market of Mexico is characterized by heteroskedasticity, multicolinearity, non-normality, and serial correlation. Volatility measurements by ARCH and GARCH signify that the current conditional variance of Mexico is determined by its past price behavior and previous day volatility. Today’s volatility does impact the current stock returns as indicated by GARCH-M. Results of EGARCH explained that any large size news produces high volatility as compared to small size news. Effects of bad news are greater on the volatility of the Mexican stock market than good news. GJR GARCH described the asymmetric behavior of returns and variance in the politically conflicted regime during 2006-2012. Moreover, QGARCH effect is not linear. Findings have the implications for individuals and corporate investors about retaining their risky stocks.},
year = {2018}
}
TY - JOUR T1 - Financial Forecasting by Autoregressive Conditional Heteroscedasticity (ARCH) Family: A Case of Mexico AU - Vina Javed Khan AU - Abdul Qadeer AU - Bezon Kumar Y1 - 2018/11/27 PY - 2018 N1 - https://doi.org/10.11648/j.jppa.20180203.13 DO - 10.11648/j.jppa.20180203.13 T2 - Journal of Public Policy and Administration JF - Journal of Public Policy and Administration JO - Journal of Public Policy and Administration SP - 32 EP - 39 PB - Science Publishing Group SN - 2640-2696 UR - https://doi.org/10.11648/j.jppa.20180203.13 AB - Understanding and modeling the volatility measurements is important for forecasting the risk and for evaluating asset allocation decisions of stock market. The study have used the daily frequency data from January 1, 2002 to September 30, 2016 as an in-sample period to perform empirical analyses for modeling and predicting the volatility dynamics of Mexican stock market (IPC). To facilitate the variance forecast, the competing models are ARCH (p, q), GARCH (p, q), and its variations i.e. Glosten Jagnnathon Runkle GARCH, GARCH in Mean, Exponential GARCH, and Quadratic GARCH. The results of residual diagnostics suggested that stock market of Mexico is characterized by heteroskedasticity, multicolinearity, non-normality, and serial correlation. Volatility measurements by ARCH and GARCH signify that the current conditional variance of Mexico is determined by its past price behavior and previous day volatility. Today’s volatility does impact the current stock returns as indicated by GARCH-M. Results of EGARCH explained that any large size news produces high volatility as compared to small size news. Effects of bad news are greater on the volatility of the Mexican stock market than good news. GJR GARCH described the asymmetric behavior of returns and variance in the politically conflicted regime during 2006-2012. Moreover, QGARCH effect is not linear. Findings have the implications for individuals and corporate investors about retaining their risky stocks. VL - 2 IS - 3 ER -
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