Results 1 to 10 of about 229 (64)
Capturing asymmetry in COVID-19 counts using an improved skewness measure for time series data [PDF]
MethodsX, 2023 Capturing asymmetry among time series is an important area of research as it provides a range of information regarding the behaviour and distribution of the underlying series, which in turn proves to be useful for prediction.
Sudeep R. Bapat
doaj +2 more sources
Skew selection for factor stochastic volatility models. [PDF]
J Appl Stat, 2020 Nakajima J.
europepmc +2 more sources
Portmanteau test statistics for seasonal serial correlation in time series models. [PDF]
Springerplus, 2016 Mahdi E.
europepmc +2 more sources
Predictability of cryptocurrency returns: evidence from robust tests
Dependence Modeling, 2022 The paper provides a comparative empirical study of predictability of cryptocurrency returns and prices using econometrically justified robust inference methods.
He Siyun, Ibragimov Rustam
doaj +1 more source
Dependence Modeling, 2022 This paper analyzes approximately 100 Gigabytes of raw text data from Twitter with keywords “AAPL,” “S&P 500,” “FTSE100” and “NASDAQ” to explore the relationship between sentiment and the returns and prices on the Apple stock and the S&P 500, FTSE 100 ...
Huang Zibin, Ibragimov Rustam
doaj +1 more source
Locf imputation for Astra Agro Lestari Tbk. (Indonesia) and Anadolu Group (Turkey) stock
Majalah Ilmiah Matematika dan Statistika, 2022 This study aims to apply time series graphs on stock of Astra Agro Lestari Tbk. and Anadolu Group with last observation carried forward (LOCF) imputation. The imputation was used because the data for the two companies had missing values on several dates.
Fadhlul Mubarak +2 more
doaj +1 more source
Testing for explosive bubbles: a review
Dependence Modeling, 2023 This review discusses methods of testing for explosive bubbles in time series. A large number of recently developed testing methods under various assumptions about innovation of errors are covered.
Skrobotov Anton
doaj +1 more source
Time series aggregation, disaggregation and long memory [PDF]
, 2007 We study the aggregation/disaggregation problem of random parameter AR(1) processes and its relation to the long memory phenomenon. We give a characterization of a subclass of aggregated processes which can be obtained from simpler, "elementary", cases ...
A. Philippe +12 more
core +5 more sources
Functional generalized autoregressive conditional heteroskedasticity [PDF]
, 2015 Heteroskedasticity is a common feature of financial time series and is commonly addressed in the model building process through the use of ARCH and GARCH processes. More recently multivariate variants of these processes have been in the focus of research
Aue, Alexander +2 more
core +2 more sources
Stationarity and geometric ergodicity of a class of nonlinear ARCH models [PDF]
, 2006 A class of nonlinear ARCH processes is introduced and studied. The existence of a strictly stationary and $\beta$-mixing solution is established under a mild assumption on the density of the underlying independent process.
Sa\"{ı}di, Youssef +1 more
core +2 more sources