Results 31 to 40 of about 3,903 (204)
Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis
, 2012 In this paper, we contribute to the literature on energy market co-movement by studying its dynamics in the time-frequency domain. The novelty of our approach lies in the application of wavelet tools to commodity market data.
Barunik, Jozef, Vacha, Lukas
core +1 more source
FINANCIAL INTEGRATION OF INDIAN AND DEVELOPED MARKETS: A DCC GARCH ANALYSIS
, 2022 Abstract The stock market is the main channel of financial integration for emerging economies like India. Globalization, deregulation of the market, capital account convertibility, and information and technology are the key factors contributing to the integration of the world markets.
Dr. ANURAG AGNIHOTRI, SHAGUNARORA
openaire +1 more source
Seasonality and Dynamic Spatial Contagion of Air Pollution in 42 Chinese Cities
The Scientific World Journal, 2013 To monitor and improve the urban air quality, the Chinese government has begun to make many efforts, and the interregional cooperation to cut and improve air quality has been required.
Zhanqiong He +2 more
doaj +1 more source
Cogent Economics & Finance, 2016 This paper empirically compares the usefulness of information included in the volatility index (VIX) against several generalized autoregressive conditional heteroskedasticity (GARCH) models for predicting downside risk in the US stock market.
Chikashi Tsuji
doaj +1 more source
Return and Volatility Spillovers Among Major Cotton Markets
Agribusiness, EarlyView.ABSTRACT This study explores return and volatility transmission among major cotton markets. Several events have disrupted cotton supply and demand in recent years, leading to heightened price volatility and significant shifts in market interconnections.
Susmitha Kalli +3 more
wiley +1 more source
Financial technology and ESG market: A wavelet-DCC GARCH approach
Research in International Business and Financeتبحث هذه الورقة في الحركة المشتركة بين أسواق التكنولوجيا المالية والحوكمة البيئية والاجتماعية والحوكمة من منظور مجال التكرار الزمني. نحن نستخدم نهجًا اقترحه فاشا وبارونيك (2012) ونشمل تحليل تماسك الموجات الصغيرة والارتباط الشرطي الديناميكي من نموذج GARCH متعدد المتغيرات (DCC GARCH). نجد علاقة إيجابية كبيرة ثنائية الاتجاه بين مؤشرات FinTech و ESG.
Babak Naysary, Keshab Shrestha
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A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios
Journal of Forecasting, EarlyView.ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley +1 more source
A wavelet approach towards examining dynamic association, causality and spillovers [PDF]
International Journal of Data and Network Science, 2019 This paper presents an integrated granular framework of wavelet decomposition, DCC-GARCH, ADCC-GARCH, Diks-Panchenko nonlinear Granger’s causality and Diebold-Yilmaz spillover assessment techniques to understand temporal correlation, causal interplay and
Indranil Ghosh, Tamal Datta Chaudhuri
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Intraday Functional PCA Forecasting of Cryptocurrency Returns
Journal of Forecasting, EarlyView.ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley +1 more source
Algorithm of Assessing Dynamic Correlation between Time Series Connected by TVP-Regression Model
Вестник Российского экономического университета имени Г. В. ПлехановаThe present research proposes algorithm of assessing dynamic correlation of time series connected by TVP-regression model. Topicality of this task is stipulated by the fact that this model often describes asset behavior on finance markets, while modeling
N. A. Moiseev, G. V. Aivazian
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