Results 51 to 60 of about 36,906 (198)

Risk Forecasting in Shipping Exchange‐Traded‐Fund (ETF) Markets

open access: yesInternational Journal of Finance &Economics, EarlyView.
ABSTRACT This article examines the risk properties of freight‐derivative‐based exchange‐traded funds (ETFs), focusing on the Breakwave Dry Bulk Shipping ETF (BDRY), and evaluates the accuracy of Value‐at‐Risk (VaR) and Expected Shortfall (ES) forecasts across a range of econometric models.
Christos Katris   +2 more
wiley   +1 more source

Parameter estimates for two-state MS-GJR-GARCH(1,1) model with skewed Student’s-t distribution.

open access: yes, 2018
Parameter estimates for two-state MS-GJR-GARCH(1,1) model with skewed Student’s-t distribution.
Haslifah M. Hasim (4839987)   +2 more
core   +1 more source

An Empirical Evaluation of GARCH Models in Value-at-Risk Estimation: Evidence from the Macedonian Stock Exchange

open access: yesBusiness Systems Research, 2013
Background: In light of the latest global financial crisis and the ongoing sovereign debt crisis, accurate measuring of market losses has become a very current issue. One of the most popular risk measures is Value-at-Risk (VaR). Objectives: Our paper has
Bucevska Vesna
doaj   +1 more source

The predictive capacity of GARCH-type models in measuring the volatility of crypto and world currencies.

open access: yesPLoS ONE, 2021
This paper provides a thorough overview and further clarification surrounding the volatility behavior of the major six cryptocurrencies (Bitcoin, Ripple, Litecoin, Monero, Dash and Dogecoin) with respect to world currencies (Euro, British Pound, Canadian
Viviane Naimy   +3 more
doaj   +1 more source

Quantile‐Dependent Volatility Interconnectedness Between Commodity Markets, Oil Price Uncertainty, and Global Supply Chain Pressure

open access: yesAustralian Economic Papers, Volume 65, Issue 3, Page 222-260, September 2026.
ABSTRACT This study examines volatility interconnectedness among selected agricultural commodities and precious/industrial metals, together with oil price uncertainty and global supply chain pressure, over the period January 1998 to June 2024 using a Quantile‐on‐Quantile connectedness framework.
Muhammed Benli, Halil Altıntaş
wiley   +1 more source

ESTIMATING VOLATILITY CLUSTERING USING GJR-GARCH MODEL: A CASE STUDY FOR GERMAN STOCK MARKET [PDF]

open access: yesAnalele Universităţii Constantin Brâncuşi din Târgu Jiu : Seria Economie, 2022
The purpose of this article is to concentrate on the stylized data in the financial series of the major index DAX of the German stock market. Moreover, we investigated the effects of positive and negative news on the volatility of the stock market of ...
RACHANA BAID   +4 more
doaj  

Tail Dependence: The Impact of Risk Spillovers on Real Estate Markets in Times of Economic and Geo‐Political Uncertainty

open access: yesInternational Review of Finance, Volume 26, Issue 3, September 2026.
ABSTRACT The first half of the 2020's has seen a degree of economic and geo‐political uncertainty not observed since the 1970s. This paper looks at how listed real estate is exposed to capital market shocks by estimating Conditional Value‐at‐Risk (CoVaR), which captures the sensitivity of real estate returns to extreme movements in broader equity ...
Stanimira Milcheva   +2 more
wiley   +1 more source

Forecasting Malaysian gold using a hybrid of ARIMA and GJR-GARCH models

open access: yesApplied Mathematical Sciences, 2015
An effective way to improve forecast accuracy is to use a hybrid model. This paper proposes a hybrid model of linear autoregressive moving average (ARIMA) and non-linear GJR-GARCH model also known as TARCH in modeling and forecasting Malaysian gold.
Ahmad, Maizah Hura   +3 more
openaire   +2 more sources

Rainfall Variability and Agroecological Resilience in Ghana: Evidence From Spatial and Volatility Models

open access: yesMeteorological Applications, Volume 33, Issue 3, May/June 2026.
Rainfall across Ghana's agroecological zones is fragmented and volatile: extremes are localised, volatility regimes vary, forest rainfall leads savannas by 2–3 days, and the Transitional Zone records the most intense events, underscoring the need for zone‐specific adaptation for agriculture, water, and climate resilience.
Fred Fosu Agyarko   +4 more
wiley   +1 more source

Determination of Risk Value Using the ARMA-GJR-GARCH Model on BCA Stocks and BNI Stocks

open access: yesOperations Research: International Conference Series, 2021
Stocks are common investments that are in great demand by investors. Stocks are also an investment instrument that provides returns but tends to be riskier. The return time series is easier to handle than the price time series. In investment activities, there are the most important components, namely volatility and risk.
Rizki Apriva Hidayana   +2 more
openaire   +1 more source

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