The role of volatility risk in DIVIDEND FORECASTING
Financial market volatility is an important input for investment, option pricing, and financial market regulation. It plays furthermore a central role in dividends forecasting. The aim of this project is to identify the best forecasting model for the S&P 500 returns using forecasting models which account for volatility variation over time. Once such model is identified , it will be used by the industry partner to understand the implication of time varying volatility and volatility uncertainty on predictability of return and cash flow within a present value context.
You will need to carry on the following steps. Notice that Excel is not accepted as the software in this ARP, you are very welcome to use EViews, R , Matlab or Python
Collect daily data on the S&P 500 prices from the 28 pf Feb 2017 till the 28 of feb 2023 included. Generate the daily log returns.
Collect daily data on the S&P 500 dividends for the same time period as above and generate the dividend growth rate.
Present the descriptive statistics and hypothesis tests for stationary for the two series above
Identify for the two series above two models which account for mean dependence.
Identity for the two series above two models which account for volatility dependence
Test if the returns volatility impacts on the growth rate of the dividends.
Read the provided article and wite a 10 line summary of the findings of the authors.
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