Results 31 to 40 of about 727,591 (368)
Chaos Theory and Applications, 2023 A time series data contains a large amount of information in itself. Chaos data and volatility data which calculated by any time series are also derivative information included in the same time series. According to these assumptions, it is very important
Hüseyin Serdar Yalçınkaya +1 more
doaj +1 more source
The Cross-Section of Volatility and Expected Returns
, 2006 We examine the pricing of aggregate volatility risk in the cross-section of stock returns. Consistent with theory, we find that stocks with high sensitivities to innovations in aggregate volatility have low average returns. Stocks with high idiosyncratic
Andrew Ang +3 more
semanticscholar +1 more source
Management : Journal of Contemporary Management Issues, 2021 This paper investigates the leverage effect in African countries by applying normal and non-normal distribution densities. Furthermore, we investigate the possible opportunities for portfolio diversification in South Africa, Nigeria, and Egypt.
Abdullah Ejaz +2 more
doaj +1 more source
Forecasting Volatility in Indian Stock Market using Artificial Neural Network with Multiple Inputs and Outputs [PDF]
International Journal of Computer Applications, 2015, 2016 Volatility in stock markets has been extensively studied in the applied finance literature. In this paper, Artificial Neural Network models based on various back propagation algorithms have been constructed to predict volatility in the Indian stock market through volatility of NIFTY returns and volatility of gold returns. This model considers India VIX,
arxiv +1 more source
Local volatility under rough volatility
Mathematical Finance, 2023 AbstractSeveral asymptotic results for the implied volatility generated by a rough volatility model have been obtained in recent years (notably in the small‐maturity regime), providing a better understanding of the shapes of the volatility surface induced by rough volatility models, supporting their calibration power to SP500 option data.
Florian Bourgey +3 more
openaire +3 more sources
INVESTIGATING VOLATILITY BEHAVIOUR: EMPIRICAL EVIDENCE FROM ISLAMIC STOCK INDICES
Journal of Islamic Monetary Economics and Finance, 2020 The main purpose of this research is to apply five univariate GARCH models to the daily stock returns of four major sharia stock indices. Two symmetric versions of the GARCH model (GARCH and MGARCH) and three asymmetric versions (EGARCH, TGARCH and ...
Burhanuddin Burhanuddin
doaj +1 more source
International Journal of Financial Studies, 2021 The present research investigates the impact of trading volume on stock return volatility using data from the Greek banking system. For our analysis, the empirical study uses daily measures of volatility constructed from intraday data for the period 5 ...
Athanasios Tsagkanos +3 more
doaj +1 more source
The ATM implied volatility slope, the (dual) volatility swap, and the (dual) zero vanna implied volatility [PDF]
arXiv, 2022 Exact relationships between the short time-to-maturity ATM implied volatility slope, the (dual) volatility swap, and the (dual) zero vanna implied volatility are given.
arxiv
Modeling and Forecasting Realized Volatility
, 2001 This paper provides a general framework for integration of high-frequency intraday data into the measurement, modeling, and forecasting of daily and lower frequency volatility and return distributions.
T. Andersen +3 more
semanticscholar +1 more source
Local volatility under rough volatility [PDF]
arXiv, 2022 Several asymptotic results for the implied volatility generated by a rough volatility model have been obtained in recent years (notably in the small-maturity regime), providing a better understanding of the shapes of the volatility surface induced by rough volatility models, and supporting their calibration power to S&P500 option data. Rough volatility
arxiv