Results 31 to 40 of about 13,792,513 (203)

Commonality in the LME aluminium and copper volatility processes through a Figarch lens [PDF]

, 2007
We consider dynamic representation of spot and three month aluminium and copper volatilities. These are the two most important metals traded in the London Metal Exchange (LME).
Figuerola-Ferretti, Isabel, Gilbert, Christopher L.   +1 more
core   +1 more source

Short‐run wavelet‐based covariance regimes for applied portfolio management

Journal of Forecasting, Volume 39, Issue 4, Page 642-660, July 2020., 2020
Abstract Decisions on ass et allocations are often determined by covariance estimates from historical market data. In this paper, we introduce a wavelet‐based portfolio algorithm, distinguishing between newly embedded news and long‐run information that has already been fully absorbed by the market.
Theo Berger, Ramazan Gençay
wiley   +1 more source

Growth enterprise market in Hong Kong: Efficiency evolution and long memory in return and volatility [PDF]

Journal of Asian Business and Economic Studies, 2020
Purpose – Growth enterprise market (GEM) in Hong Kong is acknowledged as one of the world’s most successful examples of small and medium enterprise (SME) stock market.
Trang Nguyen, Taha Chaiechi, Lynne Eagle, David Low   +3 more
doaj   +1 more source

How Does Internet Information Affect Oil Price Fluctuations? Evidence from the Hot Degree of Market

Discrete Dynamics in Nature and Society, Volume 2020, Issue 1, 2020., 2020
Not only the fundamentals of supply and demand but also international oil prices are affected by nonfundamental indicators such as emergencies. With the development of big data technology, many unstructured and semistructured factors can be reflected through Internet information. Based on this, this paper proposes a HD‐based oil price forecasting model
Lu-Tao Zhao, Shi-Qiu Guo, Jing Miao, Ling-Yun He, Alfred Peris   +4 more
wiley   +1 more source

Uma avaliação da volatilidade dos preços da soja no mercado internacional com dados de alta frequência An evaluation of the volatility of soybeans prices in the international market using high frequency data

Gestão & Produção, 2012
Neste trabalho foram avaliados os ajustes de cinco modelos para previsão da variância, utilizando-se uma série de preços de soja, uma commodity negociada na bolsa de mercadorias de Chicago (CBOT), com dados de alta frequência. Os modelos utilizados foram
Mario Domingues Simões, Marcelo Cabus Klotzle, Antonio Carlos Figueiredo Pinto, Gabriel Levrini   +3 more
doaj   +1 more source

INTERNATIONAL TOURIST ARRIVALS IN THAILAND: FORECASTING WITH ARFIMA-FIGARCH APPROACH [PDF]

Annals of the University of Petrosani: Economics, 2010
Forecasting is an essential analytical tool for tourism policy andplanning. This paper focuses on forecasting methods based on ARFIMA(p,d,q)-FIGARCH(p,d,q).
KANCHANA CHOKETHAWORN, THANES SRIWICHAILAMPHAN,, SONGSAK SRIBOONCHITTA, CHUKIAT CHAIBOONSRI, JITTAPORN SRIBOONJIT, PRASERT CHAITIP   +5 more
doaj  

THE LONG MEMORY BEHAVIOR IN TIME-VARYING BETA: AN EMPIRICAL APPLICATION ON BIST

SDÜ Vizyoner Dergisi, 2020
The study aims to investigate the long memory behavior in time-varying beta, a systematic risk indicator, in İstanbul Stock Exchange (BIST) sub-indices. Using the data regarding BIST national indices, sub-indices and two-year benchmark bond interest rate
İsmail Çelik, Hüseyin Keskin
doaj   +1 more source

Enhanced state-space estimation of long-memory commodity volatility using the Unscented Kalman Filter and variational Bayes method for non-linear modeling

Frontiers in Applied Mathematics and Statistics
This study addresses the limitations of the Kalman Filter (KF) by extending the application of the Unscented Kalman Filter (UKF) and the variational Bayes method (VBM) for estimating long-memory (LM) volatility models.
Kisswell Basira, Lawrence Dhliwayo, Florance Matarise   +2 more
doaj   +1 more source

Does the Oil Market Volatility have Long Run Memory? [PDF]

Pizhūhishnāmah-i Iqtiṣād-i Inirzhī-i Īrān, 2011
This paper has examined the long memory of oil market volatility. For this purpose, the paper has employed different types of long run ARCH models including FIGARCH-BBM, FIGARCH-chung, FIEGARCH, FIAPARCH-BBM and FIAPARCH-chung and short run ones ...
Seed Rasekhi, Amir Khanalipour
doaj  

Forecasting daily conditional volatility and h-step-ahead short and long Value-at-Risk accuracy: Evidence from financial data

Journal of Finance and Data Science, 2016
In this article we evaluate the daily conditional volatility and h-step-ahead Value at Risk (VaR) forecasting power of three long memory GARCH-type models (FIGARCH, HYGARCH & FIAPARCH).
Samir Mabrouk
doaj   +1 more source