Results 121 to 130 of about 2,971 (265)
Estimating the volatility of cryptocurrencies during bearish markets by employing GARCH models. [PDF]
Heliyon, 2019 Kyriazis ΝA +4 more
europepmc +1 more source
International Journal of Finance &Economics, EarlyView.ABSTRACT This paper investigates the intricate relationship between climate policy uncertainty (CPU) and energy market dynamics, focusing on fossil‐based and renewable/low‐carbon energy assets. Utilising a comprehensive dataset spanning from April 1987 to December 2023, comprising monthly observations of CPU, stock market returns, spot oil prices and ...
Dimitrios Asteriou, Anastasia Dimiski
wiley +1 more source
, 2020 Bu çalışmada ,Risk hesaplamada kullanılan alternatif metodlar karşılaştırılmış ve IMKB 30 hisselerini içeren bir portföy belirli bir risk düzeyinde maximum getir sağlamasın için portföy oluşturan hisse senetlerinin hangi oranda dağıtılması gerektiğinin hesaplaması yapılmıştır.
openaire +1 more source
International Studies of Economics, EarlyView.Abstract This paper examines the link between climate risk, energy consumption, and financial market performance in a sample of emerging countries over the period 2000–2024. The objective is to model the dynamic interactions between these three dimensions, in order to understand the extent to which energy dependence and exposure to climate risks ...
Abdelkader Mohamed Derbali
wiley +1 more source
From Reactive to Proactive Volatility Modeling With Hemisphere Neural Networks
Journal of Applied Econometrics, EarlyView.ABSTRACT We revisit maximum likelihood estimation (MLE) for macroeconomic density forecasting through a novel neural network architecture with dedicated mean and variance hemispheres. Our architecture features several key ingredients making MLE work in this context.
Philippe Goulet Coulombe +2 more
wiley +1 more source
Forecasting Related Time Series
Journal of Applied Econometrics, EarlyView.ABSTRACT A collection of time series are “related” if they follow similar stochastic processes and/or they are statistically dependent. This paper proposes a related time series (RTS) forecasting model that exploits these relationships. The model's foundation is a set of univariate Gaussian autoregressions, one for each series, which are then augmented
Ulrich K. Müller, Mark W. Watson
wiley +1 more source
Revisiting EWMA in High‐Frequency‐Based Portfolio Optimization: A Comparative Assessment
Journal of Applied Econometrics, EarlyView.ABSTRACT This paper compares the statistical and economic performance of state‐of‐the‐art high‐frequency (HF) based multivariate volatility models with a simpler, widely used alternative, the Exponentially Weighted Moving Average (EWMA) filter. Using over two decades of 100 U.S.
Laura Capera Romero, Anne Opschoor
wiley +1 more source
Estimating and Forecasting Volatility of Financial Time Series in Pakistan with GARCH-type Models
Lahore Journal of EconomicsIn this paper we compare the performance of different GARCH models such as GARCH, EGARCH, GJR and APARCH models, to characterize and forecast financial time series volatility in Pakistan.
G.R. Pasha, Tahira Qasim, Muhammad Aslam
doaj
Laser &Photonics Reviews, EarlyView.By precisely engineering the geometry of a fiber‐based optical resonator, the interaction between confined light and external ultrasound waves is significantly amplified without sacrificing light confinement, boosting the ultrasound detection sensitivity beyond 0.5 mPa/√Hz.
Tai‐Anh La +2 more
wiley +1 more source