This assignment is an individual assignment.
This assignment requires is split into four parts. The relevant data is provided on Blackboard.
Part One: Asset pricing and abnormal returns
Select any ten (10) equities listed on the New York Stock Exchange (NYSE) or NASDAQ and download their daily adjusted close price series from Yahoo Fund Screener or Refinitiv Eikon. In addition, download data on the daily S&P 500 return (MKT-RF) and the risk-free rate (RF), small- minus-big (SMB), and high-minus-low (HML) portfolios from the Fama-French website. The data series should cover the period from 1 January 2010 to 31 December 2022. Compile your data series into a single excel file and upload it to EViews.
a) Construct an equal-weighted and price-weighted portfolios of all the 10 stocks you selected and estimate the excess return on the two portfolios.
Note: The price-weighted portfolios should be estimated using the end-of-year adjusted close price for the equities and rebalanced annually. For instance, the end-of-year price of 2010 should be used as the weight for 2011, and so on.
b) Estimate the capital asset pricing model (CAPM) and Fama-French Three Factor (FF3) regressions for the equal-weighted and price-weighted portfolios and test for abnormal return in each case.
c) Interpret the coefficients on the CAPM and FF3 regressions for the price-weighted portfolios and comment on the statistical significance of all the coefficients.
d) Compare the CAPM and FF3 regression models using the Adjusted R-Squared and comment on how the model fits the data series.
e) Conduct a hypothesis test to determine if the residuals of the price-weighted regression outputs are different from 0.
f) Discuss the normality of the residuals from the price-weighted portfolio regression using the Jarque-Bera and Kolmogorov-Smirnov tests.
g) Check for heteroskedasticity in the residuals for the price-weighted portfolio using the White Test and BPG Test. Interpret your results.
h) Check for autocorrelation in the residuals for both equal-weighted and price-weighted portfolios using the DW test and BG test. Interpret your results.
(30 marks)
Part 2: Time Series Modelling
Choose any two (2) equities from your portfolio in Part One and carry out the following analysis.
a) Perform the Augmented Dickey-Fuller (ADF) and Phillip Perron (PP) tests for stationarity on the price and return series of the equities you selected. Interpret your results fully.
b) Fit an appropriate ARMA (p, q) model for the return series using the Box-Jenkins methodology. Explain the Box-Jenkins procedure and how you implemented it.
c) Conduct an “out-of-sample” forecast for the last year (2022) based on the ARMA model specified in b) above and analyse the forecast accuracies using RMSE, MAPE and the Theil Inequality Coefficient. Comment on the quality of the forecast from the ARMA model.
d) Fit an ARCH(q) model for the two equity stocks. Comment on your choice of order q and interpret your ARCH (q) results.
e) Fit the appropriate GARCH model for the two equity stocks and test for the leverage effects.
(40 marks)
Part 3: VAR and VECM models
Choose only one question from this section Part 3A Vector Autoregressive Models
Collect quarterly on the following series from the FRED Database (Federal Reserve Bank Economic Data).
• Real Gross Domestic Product [GDPC1]
• Industrial Output [INDPRO]
• Consumer price index [USACPIALLMINMEI]
• Federal fund effective rate [FEDFUNDS]
• Yield spreads (difference between the US 3 months T-Bill and 10-Year Treasury Constant Maturity Rate) [T10Y3M].
Merge the above data with:
• The quarterly returns on your price-weighted portfolio.
• The quarterly returns on the SP 500 index.
Compile all your data series in a single excel file for the period 2010Q1 to 2022Q4 and upload it to EViews.
a) Estimate an unrestricted vector autoregressive model for all the seven variables indicated above.
b) Conduct a Granger causality test between the returns on your price-weighted portfolio and all the variables. Comment on your results thoroughly.
c) Conduct an impulse response analysis of all the factors on your price-weighted portfolio returns (ignoring all other impulse responses). Comment on your results thoroughly.
(20 marks)
3B Modelling long-run relationships (VECM)
From the Country data.xlsx file, select any six (6) market index series and
a) Make five (5) pairs of data with one data series fixed and test for cointegration among the variables.
b) Critically comment on the assumptions used for the co-integration tests and on your results for each of the cointegration tests in light of the following issues:
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