Abstract

The stock market is an integral part of investments as well as the economy. The prediction of stock prices is an exciting and challenging problem that has been considered by many due to the complexity and noise within the market and to the potential profit that can be yielded from accurate predictions. We aim to construct and compare models used for the prediction of weekly closing prices for some of the top stocks in the New York Stock Exchange (NYSE) and to discuss the relationship between stock prices and the predictor variables. Relationships explored in the study include that with macroeconomic variables such as the Federal Funds Rate and the M1 money supply and market indexes such as the CBOE Volatility Index, the Wilshire 5000 Total Market Full Cap Index, the CBOE interest rate for 10-year T-notes and bonds, and NYSE commodity indexes including XOI and HUI. Models are built using methods of regression analysis and time series analysis. Models are analyzed and compared with one another by considering their predictive ability, accuracy, fit to the underlying model assumptions, and usefulness in application. The final models considered are a pooled regression model involving the median weekly closing price across all stocks, a varying intercept model considering the weekly closing price for each individual stock, and an ARIMA time series model that predicts the median weekly closing stock price based on past prices.

Highlights

  • Introduction to Data Data DescriptionWhen it comes to creating an investment portfolio to build up held assets, there are several different asset classes to choose including bonds, cash equivalents, and equities

  • The regression coefficient for VIX is -0.1587 and indicates that holding all other variables constant, when the Chicago Board Options Exchange (CBOE) Volatility Index increases by 1 point, it is estimated that the median closing stock price for the top stocks in the New York Stock Exchange (NYSE) 100 will decrease by an average of approximately 16 cents

  • The coefficient for HUI is -0.0094 and indicates that holding all other variables constant, when the Gold Index increases by 1 point, it is predicted that the median closing stock price for the top stocks in the NYSE 100 will decrease by an average of approximately 1 cent

Read more

Summary

Introduction to Data

When it comes to creating an investment portfolio to build up held assets, there are several different asset classes to choose including bonds, cash equivalents, and equities. 12 stocks belong to the Industrial (IDU) sector Industry groups within this sector include construction, and industrial goods and services such as building materials, industrial equipment, aerospace, electrical components, and industrial transportation. The Wilshire 5000 Total Market Full Cap Index is known as being a comprehensive measure of equity in the U.S market by including the average price of nearly 5000 different stocks from various exchanges. The NYSE does not have an index for summarizing the prices of softs, so instead this model looks to the other two commodity groups. The changes in prices of fuels are modeled using the NYSE ARCA Oil and Gas Index (XOI). The changes in prices of precious metals are modeled by the NYSE ARCA Gold Bugs Index (HUI).

Introduction to the Study
20 Time 30
Findings
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call