Forecast volatility in value of the EUR/USD

QR Code

Forecast volatility in value of the EUR/USD

Currency volatility is unobservable but plays an important role on the international financial market, especially the EUR/USD volatility. In an attempt to select the most accurate model for forecasting this currency volatility, the EWMA models and the GARCH family models under normal and student-t d...

Full description

Bibliographic Details
Main Author:	ZHONG, YANJI
Format:	Dissertation (University of Nottingham only)
Language:	English
Published:	2013
Online Access:	https://eprints.nottingham.ac.uk/26749/

Similar Items

Determinants of Exchange Rate (USD).
by: Chen, Key Ying, et al.
Published: (2016)

Value-at-risk for the USD/ZAR exchange rate: The variance-gamma model
by: Kemda, L., et al.
Published: (2015)

Bitcoin as hedging alternatives from gold, stocks and USD - GARCH model for risk/volatility analysis
by: Kua, Kim Tai
Published: (2024)

Volatility of the USD: Effects from economic policy uncertainty, monetary policy uncertainty and geopolitical risk
by: Thaw, Jia Yee
Published: (2023)

The Short-time Effects of US News on the GBP/USD
by: Xu, Yaofei
Published: (2013)

The role of implied volatility in volatility combining forecasts
by: Ho, Jen Sim, et al.
Published: (2024)

A three-way analysis of the relationship between the USD value and the prices of oil and gold: a wavelet analysis
by: Alatrturi, Basheer H. M., et al.
Published: (2018)

Forecasting Oil price and Volatility
by: Yu, Man Tao
Published: (2009)

An Analysis of the Factors that Determine the Foreign Exchange Rate for USD/GBP (Cable)
by: Li, Fulei
Published: (2014)

Is MYR/USD a random walk? New evidence from the BDS test
by: Lim, Kian Ping, et al.
Published: (2003)

Forecasting Malaysian stock market volatility
by: Ng, Chee Pung, et al.
Published: (2012)

Application of forecast combination in volatility modelling
by: James, Adam, et al.
Published: (2011)

Modelling the volatility transmission and conditional correlations between A and B shares in forecasting value-at-risk
by: Da Veiga, Bernardo, et al.
Published: (2008)

The foreign exchange management for the machinery manufacturing industry –Based on the exchange rate of USD/CNY
by: Feng, Kunxian
Published: (2019)

Garch Models: Forecasting Volatility and Pricing Options
by: Joshi, Sahil
Published: (2010)

Bitcoin volatility forecasting with the HAR-type models
by: Zhang, Jiawei
Published: (2019)

Forecasting of Realised Volatility with the Random Forests Algorithm
by: Luong, C., et al.
Published: (2018)

Erratum to: The prognostic ability of the STarT Back Tool was affected by episode duration (Eur Spine J, (2016), 10.1007/s00586-015-3915-0)
by: Morso, L., et al.
Published: (2016)

Implied volatility forecasting in the options market: a survey
by: Mohamad, Azhar
Published: (2016)

Forecasting volatility in Chinese and Hong Kong stock markets.
by: Wu, Ming
Published: (2011)

Performance of GARCH models in forecasting stock market volatility.
by: Choo, Wei Chong, et al.
Published: (1999)

Time horizon volatility forecasting of Malaysian property stocks
by: Gooi, Leong Mow
Published: (2019)

Volatility forecasting in the Chinese commodity futures market with intraday data
by: Ying, Jiang, et al.
Published: (2016)

Volatility forecasting model selection with exponentially weighted information criteria.
by: Choo, Wei Chong
Published: (2009)

Forecasting stock market volatility on Bursa Malaysia Plantation Index
by: Lee, Hui Shan, et al.
Published: (2016)

Forecast accuracy test of stochastic volatility models: traditional models vs Volatility Hang Seng Index
by: Pan, Fangxin
Published: (2013)

[Review of the book "Fintech in Islamic Finance-theory and practice" by Umar A. Oseni and S. Nazim Ali, eds.] Publisher: Routledge (June 30, 2019) Length: 374 pages ISBN: 1351025562, 9781351025560 Price: HardCover USD150/Paperback USD39.95
by: Omoola, Sodiq
Published: (2019)

Impact of range bar and ergodic process on early price trend detection using evidences from USD/CNY currency
by: Pang, Tor Nee
Published: (2021)

Forecasting Volatility and Analyzing the Features of Volatility by three different methods- empirical study based on SSE 50ETF
by: Zou, YuanFang
Published: (2019)

Modeling and Forecasting Volatility: An Empirical Evidence from the Bombay Stock Exchange
by: Thakker, Jai
Published: (2011)

Modelling and Forecasting the Volatility of Stock Price Index : ASEAN-5 Countries
by: Hoh, Chai Ping
Published: (2014)

Forecasting S&P 100 Implied Volatility Using Artificial Neural Network
by: Roongroje, Thipawan
Published: (2009)

Volatility forecasting in Bull and Bear Cycles: Evidence from the Cryptocurrency Market
by: Morris, Jack
Published: (2021)

Asymmetry dynamic volatility forecast evaluations using interday and intraday data
by: Chin, Wen Cheong, et al.
Published: (2012)

Modeling and forecasting volatility of index return: an empirical evidence of FTSE 100 Index
by: ZHU, Lin
Published: (2013)

MODELLING AND FORECASTING VOLATILITY BY GARCH-TYPE MODELS: THE CASE OF VIETNAM STOCK EXCHANGE
by: Mai, Thi Thanh Hien
Published: (2008)

Volatility Forecasting in Bull and Bear Markets: Evidence from the US stock market
by: Sideris, Epameinondas
Published: (2016)

Modelling and Forecasting Volatility by GARCH models: The Empirical Evidence of China’s Stock Markets
by: Zhang, Jiahao
Published: (2019)

Volatility Forecasting during Stock Disaster in China A-share Stock Market
by: BAO, JINGYI
Published: (2018)

Modified Box-Jenkins and GARCH for forecasting highly volatile time series data
by: Siti Roslindar, Yaziz
Published: (2019)