Determination of the Best Simple Moving Average By Stochastic Processes
Abstract
In this study, we consider one of the most popular technical indicators and try to determine the best fitting
simple moving average to a given data. Here we utilize from a general mean reverting stochastic process
where the mean is time dependent. We propose an identification algorithm which mainly concentrates
on the normality of the residual terms after the data is demeaned from simple moving average and also provide
evidence that our algorithm works quite well for determination of the “best” simple moving average.
Keywords
References
- ALIA, Mohammad, BABAIB, Mohamed, BOYLAN John, SYNTETOSD, Aris (2015), “On the use of Simple Moving Averages for supply chains where information is not shared”, IFAC-PapersOnLine, 48(3), pp. 1756-1761.
- ANDREW, Lo, MACKINLAY, Archie C. (2002), A Non-Random Walk Down Wall Street. Princeton University Press.
- BROCK, William, LAKONISHOK, Josef, LeBARON, Blake (1992), “Simple Technical Trading Rules and the Stochastic Properties of Stock Return”, The Journal of Finance, 47(5), pp. 1731–1764.
- CARLSON, Charles B. (2004), Winning with the Dow's Losers: Beat the Market with Underdog Stocks, HarperCollins.
- CHEN, Chien-Hua, SU Xuan-Qi, LIN Jun-Baio (2016), “The role of information uncertainty in moving-average technical analysis: A study of individual stock-option issuance in Taiwan”, Finance Research Letters, 18, pp. 263-272.
- EDWARDS, Robert, MCGEE, John, BESSETTI, Charles (2007), Technical Analysis of Stock Trends, CRC Press.
- FAMA, Eugene (1965), “The Behavior of Stock Market Prices”, Journal of Business, 38, pp. 34–105.
- GENÇAY, Ramazan (1998), “The predictability of security returns with simple technical trading rules”, Journal of Empirical Finance, 5 pp. 347–359.
Details
Primary Language
Turkish
Subjects
-
Journal Section
Research Article
Authors
Deniz İlalan
This is me
Publication Date
January 1, 2017
Submission Date
April 11, 2017
Acceptance Date
-
Published in Issue
Year 2017 Volume: 9 Number: 16