Evaluation of Dual Long Memory Properties with Emphasizing the Skewed and Fat-Tail Distribution: Evidence from Tehran Stock Exchange [PDF]
Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī, 2014 This paper investigates the presence of long memory in the Tehran stock market, using the ARFIMA, GPH, GSP and FIGARCH models. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatilities of TEPIX ...
Mohammad Javad Mohagheghnia +3 more
doaj
THE IMPACT OF THE FINANCIAL CRISIS ON LONG MEMORY: EVIDENCE FROM EUROPEAN BANKING INDICES [PDF]
Annals of the University of Oradea: Economic Science, 2014 We have analyzed the impact of the financial crisis on the existence of the long term dependency for European banking indices. By estimating Hurst Exponent, ARFIMA and FIGARCH models we found that major financial crisis such as, Mexican, Asian and ...
Pece Andreea Maria +3 more
doaj
Discrete Dynamics in Nature and Society, Volume 2026, Issue 1, 2026.Today, the astonishing growth of digital currency has attracted many bold investors. This has caused digital currencies to be gradually introduced as a new asset class with its own criteria. However, the relationship between traditional assets and new assets is not yet deeply understood. This study’s objective is to investigate the dynamic relationship
Farzaneh Shams Tarnabi, Fabio Tramontana
wiley +1 more source
Volatility and Return Transmission among Cement Industry Stock Prices: an Application of Multivariate FIGARCH Modeling in High Frequency Financial time Series [PDF]
فصلنامه پژوهشهای اقتصادی ایران, 2011 Long memory in asset returns and volatilities is a new research area, both in theoretical and empirical modeling of high frequent financial time series. The most popular techniques of time series modeling with long memory is the ARFIMA-FIGARCH, but this ...
Gholamreza Keshavarz Haddad +2 more
doaj
Moving Average Market Timing in European Energy Markets: Production Versus Emissions
Energies, 2018 This paper searches for stochastic trends and returns predictability in key energy asset markets in Europe over the last decade. The financial assets include Intercontinental Exchange Futures Europe (ICE-ECX) carbon emission allowances (the main driver ...
Chia-Lin Chang +3 more
doaj +1 more source
Comparing the accuracy of the model Meta heuristic and Econometric in forecasting of financial time series with long-term memory (Case Study, Stock Index of Cement Industry in Iran) [PDF]
تحقیقات مالی, 2011 Data with high frequency have a particular type of none stationary that is called fractional none stationary. This property causes the emergence of long-term memory in financial time series with high frequency. The existence of long-term memory in cement
Farnaz Barzinpour +3 more
doaj
Estimation and Prediction of Commodity Returns Using Long Memory Volatility Models
RisksModelling the volatility of commodity prices and creating more reliable models for estimating and forecasting commodity price returns are crucial.
Kisswell Basira +4 more
doaj +1 more source
AxiomsWe present the first application of the Multifractal Model of Asset Returns (MMAR) to an implied volatility index, using 36 years of daily CBOE VIX observations spanning four economic cycles. Three general conclusions emerge. First, implied volatility is
Georgy Urumov, Panagiotis Chountas
doaj +1 more source
The effect of COVID-19 on long memory in returns and volatility of cryptocurrency and stock markets. [PDF]
Chaos Solitons Fractals, 2021 Lahmiri S, Bekiros S.
europepmc +1 more source
Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008-2019). [PDF]
SN Bus Econ, 2022 Vogl M.
europepmc +1 more source