scholarly journals Covid-19 and the Technology Bubble 2.0: Evidence from DCC-MGARCH and Wavelet Approaches

2021 ◽  
pp. 109-127
Author(s):  
Caner Özdurak ◽  
Cengiz Karataş
Keyword(s):  
Time Scale ◽  
Jel Classification ◽  
Garch Models ◽  
Time Varying ◽  
Technology Stocks ◽  
Technology Bubble ◽  
Dot Com ◽  
As If

There has probably never been as big a divergence between markets and economies as there is in the pandemic period. This paper is an attempt to test the ‘time-varying’ and ‘time-scale dependent’ volatilities of major technology stocks, FAANG and Microsoft, for analyzing the possibility of a second technology bubble in the markets. Consistent with the results of DCC-GARCH models, our analysis based on the application of the Wavelet approach also indicates that major technology behave and move as if they were all one stock in the pandemic period which makes us to be cautious about a second dotcom crisis since %26 of S&P 500 market cap is driven by FAANG and Microsoft stocks. JEL classification numbers: C58, D53, O14. Keywords: Dot-com crisis, tech bubble, DCC-GARCH, FAANG, Wavelet.

Economic Institutions and Growth Nexus: The Role of Governance and Democratic Institutions—Evidence from Time Varying Parameters’ (TVPs) Models

2016 ◽  
Vol 55 (4I-II) ◽  
pp. 675-688
Author(s):  
Ghulam Murtaza ◽  
Muhammad Zahir Faridi
Keyword(s):  
Structural Changes ◽  
Jel Classification ◽  
Economic Institutions ◽  
Time Varying ◽  
Democratic Institutions ◽  
Main Hypothesis ◽  
Dynamic Relationship ◽  
Rolling Window

The present study has investigated the channels through which the linkage between economic institutions and growth is gauged, by addressing the main hypothesis of the study that whether quality of governance and democratic institutions set a stage for economic institutions to promote the long-term growth process in Pakistan. To test the hypothesis empirically, our study models the dynamic relationship between growth and economic institutions in a time varying framework in order to capture institutional developments and structural changes occurred in the economy of Pakistan over the years. Study articulates that, along with some customary specifics, the quality of government and democracy are the substantial factors that affect institutional quality and ultimately cause to promote growth in Pakistan. JEL Classification: O40; P16; C14; H10 Keywords: Economic Institutions, Growth, Governance and Democracy, Rolling Window Two-stage Least Squares, Pakistan

Time scale reachability and controllability of time‐varying linear systems

2021 ◽  
Author(s):  
Bacem Ben Nasser ◽  
Mohamed Djemai ◽  
Michael Defoort ◽  
Taous‐Meriem Laleg‐Kirati
Keyword(s):  
Linear Systems ◽  
Time Scale ◽  
Time Varying

QMLE of periodic time-varying bilinear– GARCH models

2018 ◽  
Vol 48 (13) ◽  
pp. 3291-3310
Author(s):  
Abdelouahab Bibi ◽  
Ahmed Ghezal
Keyword(s):  
Garch Models ◽  
Time Varying

scholarly journals Controllability and observability of linear impulsive adjoint dynamic system on time scale

2020 ◽  
Vol 51 (3) ◽  
pp. 201-217
Author(s):  
Nusrat Yasmin ◽  
Safia Mirza ◽  
Awais Younus ◽  
Asif Mansoor
Keyword(s):  
Dynamic System ◽  
Time Scales ◽  
Time Scale ◽  
Continuous Case ◽  
Time Varying ◽  
Controllability And Observability

This paper deals with the controllability, observability of the solution of time-varying system on time scales. We obtain new results about controllability and observability and generalize to a time scale some known properties about stability from the continuous case.

scholarly journals Asymptotics of Cholesky GARCH models and time-varying conditional betas

2018 ◽  
Vol 204 (2) ◽  
pp. 223-247 ◽  
Author(s):  
Serge Darolles ◽  
Christian Francq ◽  
Sébastien Laurent
Keyword(s):  
Garch Models ◽  
Time Varying ◽  
Conditional Betas

scholarly journals Multi-Time Scale Spillover Effect of International Oil Price Fluctuation on China’s Stock Markets

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4641
Author(s):  
Jingran Zhu ◽  
Qinghua Song ◽  
Dalia Streimikiene
Keyword(s):  
Crude Oil ◽  
Time Scale ◽  
Stock Markets ◽  
Spillover Effect ◽  
Oil Price ◽  
Time Varying ◽  
Price Fluctuation ◽  
The Impact ◽  
Oil Price Fluctuation

With the continuous increase of China’s foreign-trade dependence on crude oil and the accelerating integration of the international crude oil market and the Chinese finance market, the spillover effect of international oil price fluctuation on China’s stock markets increasingly attracts the attention of the public. In order to explore the impact of international oil price fluctuation on China’s stock markets and the time-varying spillover differences of industry sectors, this study proposes three research hypotheses and constructs a multi-time scale analysis framework based on wavelet analysis and a time-varying t-Copula model. In this paper, we use the Shanghai Composite Index as the representative of a general trend of the stock market, and we use the stock index of the China Securities Industry as the counterpart of industrial sectors. Based on the data from 5 January 2005 to 31 May 2020, this paper measures and analyzes the spillover effect of international oil price fluctuation on China’s stock markets, under different volatility periods. The results show that, firstly, the spillover effect of international oil price fluctuation on the Chinese stock markets is different. In the short and medium volatility period, the changes in international oil price are ahead of the changes in the Chinese stock markets, while the latter is ahead of the former under long-term fluctuations. Secondly, the spillover effect of international oil price fluctuation on China’s industry stock indexes is persistent. As the time scale increases, the tail dependency will increase. Finally, the impact of risk events aggravates the volatility of the stock markets in the short-term, while the mid- to long-term impact mainly affects the volatility trend. Investment risk control can make overall arrangement on the basis of the characteristics of oil price impact under different fluctuation stages.

scholarly journals Hybrid CUSUM Change Point Test for Time Series with Time-Varying Volatilities Based on Support Vector Regression

Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 578
Author(s):  
Sangyeol Lee ◽  
Chang Kyeom Kim ◽  
Sangjo Lee
Keyword(s):  
Time Series ◽  
Support Vector Regression ◽  
Stock Price ◽  
Real Data ◽  
Support Vector ◽  
Garch Models ◽  
Time Varying ◽  
Tuning Parameters ◽  
Scope Of Application ◽  
Validation Set

This study considers the problem of detecting a change in the conditional variance of time series with time-varying volatilities based on the cumulative sum (CUSUM) of squares test using the residuals from support vector regression (SVR)-generalized autoregressive conditional heteroscedastic (GARCH) models. To compute the residuals, we first fit SVR-GARCH models with different tuning parameters utilizing a time series of training set. We then obtain the best SVR-GARCH model with the optimal tuning parameters via a time series of the validation set. Subsequently, based on the selected model, we obtain the residuals, as well as the estimates of the conditional volatility and employ these to construct the residual CUSUM of squares test. We conduct Monte Carlo simulation experiments to illustrate its validity with various linear and nonlinear GARCH models. A real data analysis with the S&P 500 index, Korea Composite Stock Price Index (KOSPI), and Korean won/U.S. dollar (KRW/USD) exchange rate datasets is provided to exhibit its scope of application.

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