Search results for "Volatility clustering"
showing 7 items of 7 documents
The Influence of Oil Price on Renewable Energy Stock Prices: An Analysis for Entrepreneurs
2020
Abstract This study investigates the relationship between oil price fluctuations and renewable energy stock returns using daily data on Brent crude oil prices and global renewable energy stock market indices between 29 November 2010 and 18 February 2020. The investigation is based on the existing evidence on positive correlations between stock prices and oil prices, but it also considers the shift from non-renewable to renewable sources of energy. A two-stage GARCH(1,1) model and a Granger causality test were applied. Our results show that volatility clustering is present in the renewable energy companies‘ stock prices, but, oil price volatility does not seem to induce any significant effec…
Is the EUA a new asset class?
2022
The listing of a new asset requires knowledge of its statistical properties prior to its use for hedging, speculative or risk management purposes. In this paper, the authors study the stylised facts of European Union Allowances (EUAs) returns. The majority of the phenomena observed, such as heavy tails, volatility clustering, asymmetric volatility and the presence of a high number of outliers are similar to those observed in both commodity futures and financial assets. However, properties such as negative asymmetry, positive correlation with stocks indexes and higher volatility levels during the trading session, typical of financial assets, and the existence of inflation hedge and positive …
Volatility Transmission Models: A Survey
2005
This study reviews the literature on volatility transmission in order to determine what we have learnt about the different methodologies applied. In particular, GARCH, regime switching and stochastic volatility models are analysed. In addition, this study covers several concrete aspects such as their scope of application, the overlapping problem, the concept of efficiency and asymmetry modelling. Finally, emerging topics and unanswered questions are identified, serving as an agenda for future research.
Modeling the coupled return-spread high frequency dynamics of large tick assets
2015
Large tick assets, i.e. assets where one tick movement is a significant fraction of the price and bid-ask spread is almost always equal to one tick, display a dynamics in which price changes and spread are strongly coupled. We introduce a Markov-switching modeling approach for price change, where the latent Markov process is the transition between spreads. We then use a finite Markov mixture of logit regressions on past squared returns to describe the dependence of the probability of price changes. The model can thus be seen as a Double Chain Markov Model. We show that the model describes the shape of return distribution at different time aggregations, volatility clustering, and the anomalo…
Understanding the determinants of volatility clustering in terms of stationary Markovian processes
2016
Abstract Volatility is a key variable in the modeling of financial markets. The most striking feature of volatility is that it is a long-range correlated stochastic variable, i.e. its autocorrelation function decays like a power-law τ − β for large time lags. In the present work we investigate the determinants of such feature, starting from the empirical observation that the exponent β of a certain stock’s volatility is a linear function of the average correlation of such stock’s volatility with all other volatilities. We propose a simple approach consisting in diagonalizing the cross-correlation matrix of volatilities and investigating whether or not the diagonalized volatilities still kee…
Univariate and multivariate statistical aspects of equity volatility
2004
We discuss univariate and multivariate statistical properties of volatility time series of equities traded in a financial market. Specifically, (i) we introduce a two-region stochastic volatility model able to well describe the unconditional pdf of volatility in a wide range of values and (ii) we quantify the stability of the results of a correlation-based clustering procedure applied to synchronous time evolution of a set of volatility time series.
Empirical Study on the Relationship between the Cross-Correlation among Stocks and the Stocks' Volatility Clustering
2013
In this paper we discuss univariate and multivariate statistical properties of volatility with the aim of understanding how these two aspects are interrelated. Specifically, we focus on the relationship between the cross-correlation among stock's volatilities and the volatility clustering. Volatility clustering is related to the memory property of the volatility time-series and therefore to its predictability. Our results show that there exists a relationship between the level of predictability of any volatility time-series and the amount of its inter-dependence with other assets. In all considered cases, the more the asset is linked to other assets, the more its volatility keeps memory of …