Modelling stock volatilities during financial crises: A time varying coefficient approach

We examine how the most prevalent stochastic properties of key financial time series have been affected during the recent financial crises. In particular we focus on changes associated with the remarkable economic events of the last two decades in the volatility dynamics, including the underlying volatility persistence and volatility spillover structure. Using daily data from several key stock market indices, the results of our bivariate GARCH models show the existence of time varying correlations as well as time varying shock and volatility spillovers between the returns of FTSE and DAX, and those of NIKKEI and Hang Seng, which became more prominent during the recent financial crisis. Our theoretical considerations on the time varying modelwhich provides the platformupon which we integrate our multifaceted empirical approaches are also of independent interest. In particular, we provide the general solution for time varying asymmetric GARCH specifications, which is a long standing research topic. This enables us to characterize these models by deriving, first, their multistep ahead predictors, second, the first two time varying unconditional moments, and third, their covariance structure.Open Access funded by European Research Council under a Creative Commons license

Large building facilities towards energy transition

Received: February 10th, 2023 ; Accepted: May 28th, 2023 ; Published: July 6th, 2023 ; Correspondence: [email protected] buildings complexes present significant amounts of energy consumption. Sport centers compose a more special case of large volume buildings, compared to other facilities. This is related not only to the specific requirements of the thermal environment regarding the type of activities taking place as well as the considerable loads enforced by the presence of people. The aim of this paper is to evaluate the energy consumption of a Sports center, through energy audits, extract energy baselines and propose energy-saving interventions and RES utilization. More precisely, a cost-benefit analysis will be carried out to assess the energy production and the relevant contribution of the potential energy interventions. As a result, the priority list of proposed measures will be extracted, with all the data regarding energy gains, capital costs, and cash flows. Particularly, a capital budgeting analysis of each measure will support the final decision of a holistic energy approach at the specific building facilities

Athree-dimensionalasymmetric powerHEAVYmodel

This article proposes the three‐dimensional HEAVY system of daily, intra‐daily, and range‐based volatility equations. We augment the bivariate model with a third volatility metric, the Garman–Klass estimator, and enrich the trivariate system with power transformations and asymmetries. Most importantly, we derive the theoretical properties of the multivariate asymmetric power model and explore its finite‐sample performance through a simulation experiment on the size and power properties of the diagnostic tests employed. Our empirical application shows that all three power transformed conditional variances are found to be significantly affected by the powers of squared returns, realized measure, and range‐based volatility as well. We demonstrate that the augmentation of the HEAVY framework with the range‐based volatility estimator, leverage and power effects improves remarkably its forecasting accuracy. Finally, our results reveal interesting insights for investments, market risk measurement, and policymaking

On the macro-drivers of realized volatility: the destabilizing impact of UK policy uncertainty across Europe

This is an Accepted Manuscript of an article published by Taylor & Francis in The European Journal of Finance on 28 Feb 2020, available online: https://www.tandfonline.com/doi/full/10.1080/1351847X.2020.173243

On the Economic fundamentals behind the Dynamic Equicorrelations among Asset classes: Global evidence from Equities, Real estate, and Commodities

We reveal the macroeconomic determinants of the dynamic correlations between three global asset markets: equities, real estate, and commodities. Conditional equicorrelations, computed by the GJR-GARCH-DECO model, are explained by the macro-financial proxies of economic policy and financial uncertainty, credit conditions, economic activity, business and consumer confidence, and geopolitical risk. Our results suggest that elevated cross-asset correlations are associated with higher uncertainty, tighter credit conditions, and lower geopolitical risk, while lower correlations are related to stronger economic activity, business, and consumer confidence. We further focus on economic policy uncertainty (EPU) as a potent catalyst of the asset markets integration process and conclude that EPU magnifies all macro-effects across all correlations. Lastly, we investigate the global financial crisis effect on the time-varying impact of the correlations’ macro-drivers. The crisis structural break amplifies the influence that all determinants exert on the evolution of correlations apart from the geopolitical risk upshot, which is alleviated after the crisis advent

Financial volatility modeling with option-implied information and important macro-factors

Copyright © 2021 The Author(s). The research debate on the informational content embedded in option prices mostly approves the incremental predictive power of implied volatility estimates for financial volatility forecasting beyond that contained in GARCH and realized variance models. Contributing to this ongoing debate, we introduce the novel AIM-HEAVY model, a tetravariate system with asymmetries, option-implied volatility, and economic uncertainty variables beyond daily and intra-daily dispersion measures included in the benchmark HEAVY specification. We associate financial with macroeconomic uncertainties to explore the macro-financial linkages in the high-frequency domain. In this vein, we further focus on economic factors that exacerbate stock market volatility and represent major threats to financial stability. Hence, our findings are directly connected to the current world-wide Coronavirus outbreak. Financial volatilities are already close to their crisis-peaks amid the generalized fear about controversial economic policies to support societies and the financial system, especially in the case of the heavily criticized UK authorities’ delayed and limited response

Short- and long-run cross-border European sustainability interdependences

Copyright © The Author(s) 2024. The increasing interest in climate change risks, environmental degradation, corporate social responsibility, and environmental, social, governance principles has motivated the recent soaring focus of policymakers, market practitioners, and academics on sustainable investments. In this vein, we investigate the cross-country interconnectedness among sustainability equity indices. Using a bivariate Dynamic Conditional Correlations-Mixed Data Sampling (DCC-MIDAS) specification, we study the short- and long-run time-varying dependence dynamics between European and five international (Australia, Brazil, Japan, US, and Canada) sustainability benchmarks. Our cross-country dynamic correlation analysis identifies the interdependence types and hedging characteristics in the short- and long-run across the business cycle. The significant macro- and crisis-sensitivity of the sustainability correlation pattern unveils strong countercyclical cross-country sustainability interlinkages for most index pairs and crisis periods. We further reveal the high- and low-frequency contagion transmitters or interdependence drivers in the macro environment during the 2008 global financial turmoil, the European sovereign debt crisis, and the recent pandemic-induced crash. Finally, we demonstrate that climate change risks and policy considerations are potent catalysts for both countercyclical and procyclical cross-border sustainability spillovers

Modelling Returns and Volatilities During Financial Crises: a Time Varying Coefficient Approach

We examine how the most prevalent stochastic properties of key financial time series have been affected during the recent financial crises. In particular we focus on changes associated with the remarkable economic events of the last two decades in the mean and volatility dynamics, including the underlying volatility persistence and volatility spillovers structure. Using daily data from several key stock market indices we find that stock market returns exhibit time varying persistence in their corresponding conditional variances. Furthermore, the results of our bivariate GARCH models show the existence of time varying correlations as well as time varying shock and volatility spillovers between the returns of FTSE and DAX, and those of NIKKEI and Hang Seng, which became more prominent during the recent financial crisis. Our theoretical considerations on the time varying model which provides the platform upon which we integrate our multifaceted empirical approaches are also of independent interest. In particular, we provide the general solution for low order time varying specifications, which is a long standing research topic. This enables us to characterize these models by deriving, first, their multistep ahead predictors, second, the first two time varying unconditional moments, and third, their covariance structure