Stock exchange indexes have become useful resources to analyze the economic behavior of countries. Information on the returns and the volatility of these may be helpful in forecasting as well. The Hang Seng index (HSI) is the principal stock index of Hong Kong which compiles stock share prices of the most important firms of the autonomous region as well as mainland China. To follow the behavior of an economy its of paramount importance to explore stock indexes. This paper will provide a handful insight on the modelling of this index.
This paper focuses on making an econometric modelling of the Hang Seng index, Hong Kong’s principal stock index, which selects the principal companies in Hong Kong over four industries: Commerce and Industry, Finance, Utilities, and Properties. This time series ranges from January 4, 2010 to February 28, 2018.
The term paper structure will be as following: First it will make a brief description of the data and a brief overview of the recent evolution of the HSI returns and volatility since 2010. Afterwards, the econometric modelling will take place to analyze the returns and volatility of the index diverse models. Finally, interpretations of the results of the models will be provided to decide which model better fits the HSI series.
The estimations and tests of this paper were done with R/RStudio statistical software and with the use of specialized libraries for time series analysis (forecast, tseries, rugarch, moments, aTSA and FinTS)