Project 1 1. Pick a firm from finance.yahoo.com. Its under quote lookup (on right-side of page). It should have data from 2005. Do not pick Google or Amazon as this is the examples I use. I suggest a...

The course topic of the assignment is financial forecasting where you use R programming language to predict and solve financial questions.


Project 1 1. Pick a firm from finance.yahoo.com. Its under quote lookup (on right-side of page). It should have data from 2005. Do not pick Google or Amazon as this is the examples I use. I suggest a Dow firm. See https://money.cnn.com/data/dow30/. Plot daily prices, daily and monthly returns. Give daily and monthly summary statistics and compare them to the S&P. Compute the daily and monthly confidence interval and moments (include skewness and kurtosis. Plot the histogram and the histogram with normal. Discuss. Is it a normal? Discuss the Jarque Bera test. Has the mean changed for daily returns since 2010? The last year? 2. Plot chartseries and add technical indicators. Include MACD and discuss. Add additional technical indicators and discuss. Mention momentum, moving average and Williams. 3. Present PerformanceAnalytics statistics including graphs for cumulative returns, relative performance and BarVaR and BarES. Discuss these statistics. Also include table of downside risk. Briefly discuss why they are important. 4. Using monthly data, what is the relationship between your firm i and the market? Mention alpha, beta. Is it equal to one? Give confidence intervals for 95% and 99%. Why is this regression used in finance? Do a scatterplot Graph histogram of residuals. 5. Does the relationship differ for daily data? Run a t test for you firm, and compare it to the market CH1W. 6. What are the Fama and French factors? Why are they used? Discuss the three factor, five factor model and momentum. Run regression over first year and last year. See Example 2.6 in the chapter code. Has the relationship changed for 1st and last year compared to full sample. A year has 253 trading days. 7. Do size and book-to-market help explain your firm? What type of regression is this? Why is this regression used? (why is it important in finance?) Is beta affected? 8. Do investment and profits help explain your firm? Explain. What these factors are. How about momentum? What is this variable? Give confidence intervals for 95% and 99%. 9. Which model works best CAPM? 3 Factor, 5 or 6 Factor. ANOVA and Wald/F tests. Try an encompassing test. Also do the F test in R using restricted and unrestricted. 10. Is there a missing variables problem for the CAPM coefficient? Is there multicollinearity? Try an interaction term. Try a squared term. What does this mean? Project 2 11. Is there a January effect? What do these mean? How do you do these regressions? Try monthly data for the Fama and French three factor model. Any changes? Is there a Halloween effect? (Discuss Halloween strategy or anomaly in stock returns) 12. Graph the fitted line and residuals. Is there heteroskedasticity in the data? What does this mean? Why does it occur? What are the tests? 13. How can you correct for it? What are robust standard errors? Does correcting for heteroskedasticity change the results? 14. Is there autocorrelation in the data? What does this mean? What are the tests? How can you correct for it? Why does it occur? 15. Is the relationship nonlinear between the market and firm? Explain the Ramsey and rainbow test. Nonnormal? Explain. Are there large outliers? Discuss the qq plot. Time Series and Forecasting 16. What is the relationship between your firm and economic activity? Inflation, employment growth industrial production and unemployment? Can they predict economic activity or does economic activity predict it? Hint: Discuss Granger Causality 17. Forecast inflation using a distributed lag of unemployment. Forecast unemployment using a distributed lag of inflation. 18. Estimate inflation past lags and an ar model. Repeat for unemployment. What is AIC? Does inflation granger cause unemployment? Unemployment granger cause inflation? 19. Do returns forecast recessions? What type of regression is this? Does the leading indicator help forecast recessions? 20. Do rolling regression for the three factor model. Does the coefficients change over time? Repeat using a different window. Do rolling mean for your stock return and the market, are they evolving similarly. Why are we doing rolling? Project 3 21. Does your stock follow a random walk? Give several tests. What is a random walk? Implications for stock market. Does GDP, and other macro variables have a unit root? Is GDP trend or difference stationary? Try industrial production and one other monthly variables. What is a unit root? Implications 22. Is there a break in real GDP growth ? Inflation? Unemployment? Download an interest rate from FRED and see if there is a structural break. Excessive Reserves? What does a structural break? Do both breakpoint, F test and CUSUM (graph it). 23. Is there a break in your firm? Is the relationship between the market and your firm stable? In the 3 Factor model. Do multiple break tests and graph. Explain why is this important? 24. Pick a Dow firm and ACF and PACF. Discuss. Give the summary for earnings. Can you take a log? When there is an increase in sales what happens to earnings? Try in levels (logs if possible), and then standarize. 25. Adjust the regression for autocorelation and heteroskedasticity. Is there a change? Try Granger Causality between earnings and sales. 26. What is seasonality? How do we eliminate it? Do earnings and sales have to be seasonalize? Regress the variables on four quarters. How important is seasonality? 27. Try LAD or quantile regression and explain. Are there large outliers? 28. Can you forecast earnings using sales? Gross Profit? Investment? Debt? 29. Run a panel data regression estimating earnings. Use sales. Does investment (capxy)also explain earnings? What is a panel data regression? Different types? Why do we use them? 30. Try ARIMA and ARMA modelling of a macro variable. Try it for your firm. What is ARIMA and ARMA? 31. What is the relationship between money growth and inflation? Implication? Is it stable? Does it take time? Explain?