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build time-series predictive models (full-sample and real-time) to predict future equity premium i.e. equity return in excess of the risk-free rate.

by | May 22

In this task, you are required to build time-series predictive models (full-sample and real-time) to predict
future equity premium i.e. equity return in excess of the risk-free rate. You will use term structure of
interest rates and default yield spreads as your predictors.
1.2 Data
1. Download Predictor2018.csv from Blackboard.
2. The file contains various aggregate economic variables from Jan 1871 to Dec 2018. More details
about the variable definition can be found in Welch and Goyal (2008).
3. You want to build predictive models on monthly frequency data. Your sample period is from Jan
1926 to Dec 2018.
4. You are interested in the following variables:
• Rfree: Risk-free rate,
• tbl: Treasury-bill rate,
• lty: Long-term government bond yield,
• AAA: AAA-rate coporate bond yield,
• BAA: BAA-rated corporate bond yield,
• CRSP_SPvw: S/P 500 stock market returns including dividends.
1.3 The Variables
A. Construct the term structure of interest rates (tms) and default yield spreads (dfy) variables. (5
marks)

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