On the Symbolic Analysis of Market Indicators with the Dynamic Programming Approach
Symbolic analysis of time series of economic indicators offers an advantage of transferring quantitative values into qualitative concepts by indexing a subset of intervals with a set of symbols. In a similar way, computer codes routinely process continuous problems in a discrete manner. This work explains an appealing analogy between the DNA code of life and the symbol series derived from financial markets. In particular, it is shown that similarity scoring schemes and the alignment gap concept known in bioinformatics have even more natural and deeper analogies in the economic systems. The symbolic analysis does not solely mean a loss of information; in also allows us to quantify a similarity degree between various financial time series (and their subsequences) in a rigorous way, which is a novel concept of practical importance in economic applications. Our symbolic analysis concept is illustrated by two types of market indicator series, namely the analysis of Dow Jones vs. NIKKEI 225 indices on one side, and the CZK/EUR exchange rate vs. Prague money market rates on the other side. The present framework may also yield a significantly reduced computational complexity as compared to the neural networks in the class of similarity-comparison algorithms.
KeywordsExchange Rate Market Indicator Index Volatility Symbolic Analysis Money Market Rate
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