1.Design a regression to test if the U.S. stock market welcomes Donald Trump to be the president. Please explain precisely your variables and data sources. Hint: simply using a dummy variable is insufficient. The stock market might soar or plunge after the election not because of his tenure, but due to other factors. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
2.Design a regression to test if the U.S. stock market follows the Chinese stock market, or the opposite. Please explain precisely your variables and data sources. Hint: stock prices are usually regarded as random walks. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
3.Design a regression to test the relationship between P/E ratio and P/B ratio of a stock ABC. Please explain precisely your variables. You do not need to explain the data source, though. The stock ABC is a fictitious stock, so there is no real source that you can find it! Hint: this is a very hard question. If you are thinking about P/E=β0+β1P/B, it is apparently very wrong. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
4.Design a regression to test if MPAcc students will receive a better start up salary than the MF graduates. Please explain precisely your variables and data sources. Hint: obviously, calculating the post- graduation average salary is not a good idea. It is ridiculous to draw a conclusion merely base on the mean. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
5.Design a regression to forecast crude oil price. Please explain precisely your variables and data sources. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
6.Design a regression to forecast the probability of a company being listed as “ST”. Please explain precisely your variables and data sources. Hint: this is about the stocks that are added “ST” at the front of their ticker for the first time. This does not include the ones with *ST. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
7.Design a regression to tell which month of the year an investor is most likely receiving the best return from the Chinese stock market. Please explain precisely your variables and data sources.Hint: there should NOT be 12 dummy variables, otherwise there will be multicollinearity problem. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
8.Design a regression to tell if the Chinese stock market is rational. Please explain precisely your variables and data sources. Hint: if the volatility of the stock market cannot be forecasted or explained by any variable significantly, the market is then regarded as with low degree of rationality. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
9.Design a regression to tell if the Chinese stock market is not efficient at all. Please explain precisely your variables and data sources. Hint: if the market is not (even weak-from) efficient, then historical information would bring investors excessive returns. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
10.Design a regression to tell which ratio affects stock price more significantly, the current ratio or the quick ratio. Please explain precisely your variables and data sources. Hint: you need to investigate many companies from different industries. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
11.Design a regression to tell the reasons of Chinese Yuan appreciation or depreciation. Please explain precisely your variables and data sources. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
12.Design a regression to tell the relationship between the Chinese CPI and PPI. Please explain precisely your variables and data sources. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
13.Design a regression to tell the relationship between the Shanghai stock market and the Shenzhen stock market. Please explain precisely your variables and data sources. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
14.Design a regression to tell if the Hong Kong stock market is more affected by the U.S. stock market, or the Chinese mainland stock market. Please explain precisely your variables and data sources. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.
15.Design a regression to tell if the trade war argument between the U.S. and China recently most likely affects the capital market in a transient way or in a long term way. Please explain precisely your variables and data sources. Hint: being transient is defined as less than 1 week. Pay attention as you design the model to avoid violation any of the assumptions that prevent your estimate from being BLUE. Please explain briefly the rational of your design.