Modeling the dependency between stock market returns is a difficult task when returns follow a complicated dynamics. It is not easy to specify the multivariate distribution relating two or more return series. In this paper, a methodology based on fitting ARIMA, GARCH and ARMA-GARCH models and copula functions is applied. In such methodology, the dependency parameter can easily be rendered condi...

Kurs JISDOR selama pandemi COVID-19 berpengaruh terhadap perekonomian Indonesia, sehingga tujuan penelitian ini adalah memodelkan data kurs pandemi. Model dibentuk mengikuti sifat- sifat yang dimiliki tersebut. Data memiliki tren dan non stasioner, maka di differencing 1, menjadi stasioner setelah uji ADF. Kemudian sesuai plot ACF, PACF, nilai minimum AIC SIC didapatkan model tepat ARIMA(1,1,1)...

The Indonesian rupiah (IDR) exchange rate is used to gauge Indonesia's economic stability. Maintaining the IDR rate's stability critical since it has a direct impact on national monetary situation, particularly during Covid-19 pandemic. Forecasting important do and one way assess government policy. data series be here are from Yahoo Finance. It consists of 271 taken August 2017 October 2022. Th...

Identification is the most important stage of all stages modeling process. This research identifies a suitable order for two different time series models ARIMA and GARCH. For GARCH distributions that GARCH-STD GARCH-GED with sample sizes in fitting forecasting stationary non-stationary data structures was considered. The study recommends use smallest information criterion like AIC BIC to select...

This paper aims to forecast the closing prices of Shanghai and Shenzhen 300 Index using time series models. By combining ARIMA GARCH models, study improve accuracy short-term predictions for index enhance risk management capabilities. The research begins by collecting preprocessing historical data Index. Then, an ARIMA-GARCH model is established, parameters are estimated tested. Finally, used i...

this paper attempts to compare the forecasting performance of the arima model and hybrid arma-garch models by using daily data of the iran’s exchange rate against the u.s. dollar (irr/usd) for the period of 20 march 2014 to 20 june 2015. the period of 20 march 2014 to 19 april 2015 was used to build the model while remaining data were used to do out of sample forecasting and check the forecasti...

4. Course Outline: (i) Review of Linear ARMA/ARIMA Time Series Models and their Properties. (ii) An Introduction to Spectral Analysis of Time Series. (iii) Fractional Differencing and Long Memory Time Series Modelling. (iv) Generalized Fractional Processes. Gegenbaur Processes. (v) Topics from Financial Time Series/Econometrics: ARCH and GARCH Models. (vi ) Time Series Modelling of Durations: A...