Solar X-ray variability in terms of a fractional heteroskedastic time series model
Анотація
The Sun is variable in activity with changes on time-scales as short as minutes to as long as a solar cycle. Although the most accurate measurements are limited to the satellite era, the past four decades, looking at the solar variability over this period provides a possible link between complex dynamics of the Sun and the accompanying radiation. Measurements of the latter and their analysis by sophisticated time series methods encourage forecasting future values of the time series. Our data analysis work focuses on the soft X-ray emission observed at the current solar minimum, in 2017 September July. We have found two different (active and inactive) states of the solar activity using a Hidden Markov Model, and we show that in the periods of high-solar activity the energy distribution of soft X-ray solar flares is well described by an ARFIMA-GARCH model, whereas in the case of low-solar activity an ARFIMA model is best fitted. Switching from the inactive state to the active one is caused by explosive phenomena in the Sun. The model describes three effects detected in our empirical studies. One of them is a long-term dependence, the second is variance changing in time, and the third corresponds to heavy-tailed distributions of the X-ray data. Moreover, the model takes into account memory effects in soft X-ray emission due to the Sun’s magnetic field evolution. All this together allows us to suggest a statistically justified model for explaining the solar activity variability at the current solar minimum.
Класифікація
Ідентифікатори
Рецензії (0)
Написати рецензіюРецензій ще немає. Будьте першим!
Схожі роботи
Is market fear persistent? A long-memory analysis
Схоже за: Financial Risk and Volatility Modeling · Market Dynamics and Volatility · Complex Systems and Time Series Analysis
Long memory and data frequency in financial markets
Схоже за: Financial Risk and Volatility Modeling · Market Dynamics and Volatility · Complex Systems and Time Series Analysis
BRICS Capital Markets Co-Movement Analysis and Forecasting
Схоже за: Financial Risk and Volatility Modeling · Market Dynamics and Volatility · Complex Systems and Time Series Analysis
Long memory in the Ukrainian stock market and financial crises
Схоже за: Financial Risk and Volatility Modeling · Market Dynamics and Volatility · Complex Systems and Time Series Analysis
Exploring frequency of price overreactions in the Ukrainian stock market
Схоже за: Financial Risk and Volatility Modeling · Market Dynamics and Volatility · Complex Systems and Time Series Analysis
Persistence in high frequency financial data: the case of the EuroStoxx 50 futures prices
Схоже за: Financial Risk and Volatility Modeling · Market Dynamics and Volatility · Complex Systems and Time Series Analysis