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Activity Number: 86 - SPEED: Statistics and Econometrics
Type: Contributed
Date/Time: Sunday, July 29, 2018 : 5:05 PM to 5:50 PM
Sponsor: Business and Economic Statistics Section
Abstract #332812
Title: Advantageous Statistical Tools for Stock Market Investing
Author(s): Kenneth Davis*
Companies:
Keywords: Stock Market Equity Investing; Regression; Time Series; Neural Network; Value at Risk (VaR); Machine Learning
Abstract:

Applying statistical tools to equity investing can greatly facilitate the accumulation of material gains for investors.

The use of readily available economic indicators, as well as the various pre-existing numerical concoctions involved in investing and finance, can be shown to produce stunningly accurate predictions.

Multiple linear regression, ARIMA, GARCH, and Neural Networks will be compared and shown to explain between 92% and 99% of the observed variance in the S&P 500 stock market index. The indicator Value at Risk (VaR) will be shown to protect from losses in 90% or greater of instances, while reporting a 15% or lower "false alarm rate" which involve only an opportunity loss.

The use of specific statistical tools in simultaneity can create superior performance and understanding in equity investing, while leading to advantageous long term outcome.


Authors who are presenting talks have a * after their name.

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