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Predicting volatility is a must in the finance domain. Estimations of volatility, along with the central tendency … assignment of diversifying assets in order to form efficient portfolios with a higher risk to reward ratio. The objective of this … research is to analyze the influence of COVID-19 on the return and volatility of the stock market indices of the top 10 …
Persistent link: https://www.econbiz.de/10012611427
intervention. Based on a GARCH framework and change point detection, we test for a structural break in the effectiveness of … volatility at the turn of the millennium when Japanese foreign exchange intervention started to remain unsterilized. …
Persistent link: https://www.econbiz.de/10011604696
moderation of output volatility compared to the well-known break during the mid-1980s. The period of analysis runs from 1962Q2 to … unconditional volatility and procedures of structural break detection (Inclan-Tiao test and autoregressive conditional …
Persistent link: https://www.econbiz.de/10013288271
The aim of this paper is to study the integration of volatility in the three markets, viz. spot, futures and options … moments (GMM) is used to capture the simultaneous equation modelling of volatility in the three markets. The integration of … the volatility in the three markets is also tested for structural breaks. The main finding of the paper is that the …
Persistent link: https://www.econbiz.de/10012611100
breaks) in the volatility of financial time series. Comparative study of three techniques: ICSS, NPCPM and Cheng's algorithm … is carried out via numerical simulation in the case of simulated T-GARCH models and two real series, namely German and US … breaks in volatility, while Cheng's technique works well only when a single break occurs. …
Persistent link: https://www.econbiz.de/10011551444
to the volatility estimator. Furthermore, the reduced memory estimates obtained by utilising an estimator accounting for …
Persistent link: https://www.econbiz.de/10015271520
nonlinear volatility models (symmetric and asymmetric Generalized AutoRegressive Conditional Heteroskedasticity [GARCH … volatility of Borsa Istanbul 100 Index (BIST-100). Sample data cover the period from January 2008 to December 2017. The main …]-type models) were used to model and estimate BIST-100 volatility in response to political news. The findings of the paper …
Persistent link: https://www.econbiz.de/10015192170
We apply the GARCH-MIDAS framework to forecast the daily, weekly, and monthly volatility of five highly capitalized … quality, we determine the most important exogenous drivers of volatility in Cryptocurrency markets. We find that the Global … Global Real Economic Activity provides superior volatility predictions for both, bull and bear markets. In addition, the …
Persistent link: https://www.econbiz.de/10014284448
events on the returns and volatility of commercial banks. It observes that insured and run-prone uninsured depositors choose … the case of Pakistan's commercial banking sector. The estimated volatility series for commercial banks is measured through … the GARCH model, which explains the current financial and political distress for the case of shocks from COVID-19. We …
Persistent link: https://www.econbiz.de/10014332387
the market volatility and asymmetric behavior of Bitcoin, EUR, S&P 500 index, Gold, Crude Oil, and Sugar during the COVID …-19 pandemic. We applied the GARCH (1, 1), GJR-GARCH (1, 1), and EGARCH (1, 1) econometric models on the daily time series … returns data ranging from 27 November 2018 to 15 June 2021. The empirical findings show a high level of volatility persistence …
Persistent link: https://www.econbiz.de/10014332825