Abstract
This paper proposes Strength Investing (SI) as a new computable methodology for investing and trading in global macro financial markets. SI is actually the foremost mainstream investing methodology in developed economies and in China too. Insisting in that practice is the main criterion for testing truth of financial theory, SI goes beyond modern portfolio theory emphasizing diversification, but concentrates on a minimal diversification of capital on strong market forces. SI takes over value investing in that it offers a complete top-down procedure for optimal selection of markets (assets) with relative strength, with market timing included. It overcomes the weakness of trend following by dynamically shifting capital to strong markets with stronger trends, so frequent stop-loss triggering can be largely avoided. SI mainly aims at international stock index markets and most liquid stocks, while its principles and techniques can be adapted to commodity futures and foreign exchanges (forex).
(Supported by the National Social Science Foundation of China with Grant 17BGL231).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Elton, E.J., Gruber, M.J., Brown, S.J., Goetzmann, W.N.: Modern Portfolio Theory and Investment Analysis, 9th edn. Wiley, Hoboken (2014)
Pan, H.: Intelligent portfolio theory – a new paradigm for invest-in-trading. In: Proceedings of 2019 IEEE International Conference on Cyber-Physical Systems (ICPS 2019) Special Session on Financial Big Data for Intelligent Systems, 6–9 May 2019, Taipei (2019)
Graham, B., Dodd, D.: Security Analysis: Principles and Technique. McGraw-Hill, New York (1934)
Soros, G.: The Alchemy of Finance. Simon & Shuster, New York (1987)
Jegadeesh, N., Titman, S.: Returns to buying winners and selling losers: implications for stock market efficiency. J. Finance 48(48), 65–91 (1993)
Low, R.K.Y., Tan, E.: The role of analysts’ forecasts in the momentum effect. Int. Rev. Financ. Anal. 48, 67–84 (2016)
Crombez, J.: Momentum, rational agents and efficient markets. J. Psychol. Financ. Mark. 2(2), 190–200 (2001)
Fama, E.F., French, K.R.: Common risk factors in the returns on stocks and bonds. J. Financ. Econ. 33, 3–56 (1993)
Frazzini, A., Kabiller, D., Pedersen, L.H.: Buffett’s Alpha. NBER Working Paper 19681 (2013). http://www.nber.org/papers/w19681
Pan, H.: Yin-Yang volatility in scale space of price-time – a core structure of financial market risk. China Finance Rev. Int. 2(4), 377–405 (2012)
Dai, M., Zhang, Q., Zhu, Q.J.: Optimal trend following trading rules (2011). http://ssrn.com/abstract=1762118
Pan, H., Zhang, C.: FEPA - EPA: an adaptive integrated prediction model of financial time series. Chin. Manag. Sci. 26(6), 26–38 (2018)
Sornette, D.: Why Stock Markets Crash – Critical Events in Complex Financial Systems. Princeton University Press, Princeton (2003)
Antonacci, G.: Dual Momentum Investing: An Innovative Approach for Higher Returns with Lower Risk. McGraw-Hill Education, New York (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Pan, H. (2020). Strength Investing - A Computable Methodology for Capturing Strong Trends in Price-Time Space in Stocks, Futures, and Forex. In: Bucciarelli, E., Chen, SH., Corchado, J. (eds) Decision Economics: Complexity of Decisions and Decisions for Complexity. DECON 2019. Advances in Intelligent Systems and Computing, vol 1009. Springer, Cham. https://doi.org/10.1007/978-3-030-38227-8_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-38227-8_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-38226-1
Online ISBN: 978-3-030-38227-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)