Higher-order Markov chains for capital market decision-making
Higher-order Markov chains for capital market decision-making

Summary/Abstract: Analysing capital market returns is fundamental to decision-making by individual investors. Advanced methods require extensive knowledge and appropriate tools, whereas individual investors often make decisions intuitively or after a very simplified analysis. The aim of the study discussed in this paper is to present the idea of higher-order Markov chains and their models and to demonstrate that the combination of higher-order Markov chains with the technical analysis in its basic form provides support for investment decisions. This approach takes into account three aspects. The first one is the linguistic practice of observing rates of return through the construction of rate-of-return intervals (a large increase, a small decrease, no change, etc.), the second is related to investors’ attitude towards risk through the aggregation of return intervals and the selection of investment strategies based on technical analysis, and the third concerns the investor's memory horizon through the construction of higher-order Markov chains.

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