|
Activity Number:
|
508
- Forecasting and Modeling Financial Volatility
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Wednesday, July 31, 2019 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
Business and Economic Statistics Section
|
|
Abstract #306448
|
Presentation
|
|
Title:
|
Creating Stock Portfolios Using Hidden Markov Models
|
|
Author(s):
|
Qing Ji* and Nagaraj Neerchal
|
|
Companies:
|
University of Maryland, Baltimore County and University of Maryland, Baltimore County
|
|
Keywords:
|
hidden Markov Model;
portfolio selection;
stock market data;
S&P 500
|
|
Abstract:
|
Hidden Markov models (HMM) have been widely used to analyze stock market data in the statistical literature. Due to hidden market trends, the structure of HMM fits well with stock data. By utilizing historical stock closing values over a fixed training period, we evaluate stock performances in terms of capital gain using HMM. Stocks are selected into a yearly portfolio based on the model. We used out-of-sample testing to investigate our portfolio selection method and showed annual capital gains from 2010 to 2018. The performances of proposed portfolios were compared to the S&P 500 index.
|
Authors who are presenting talks have a * after their name.
