Am currently investigating long term memory in interest rate data.

The two sources I am using are Peters (1996), "Fractal Market Analysis" and an article published in the Journal of Fixed Income, "Investigating Long Memory in Yield Spreads" (S2009) by McCarthy, Pantalone & Li.

I am unsure as to whether this type of question is appropriate for the forum but I would like to know if:

1) more recent research is available. An article reviewing the empirical studies conducted so far would be helpful.

2) if R/S (Rescaled Range) analysis is still applied today on financial time series (the book by Peters is > 20 years old)

3) or if wavelet-type analysis is considered more pertinent

4) and finally, in conducting R/S analysis, one can compute the V-stat to detect long term memory in the data. Lo (1991) published an article with an improved version of the test. The article contains a table of critical values. I would like to one if this is still most recent table to date?



There are two chapters of Baniel Bloch's A Practical Guide to Quantitative Portfolio Trading covering fractal market hypothesis.


The book is written in 2014, so it reviews a great number of more recent research in the last two decades, both theoretical and empirical.

As for different methods used to detect long-term memory, R/S analysis, modified R/S analysis, wavelet, DFA, a basic introduction and comparison is available in the book, and Bloch also made a detailed simulation to test the efficiency of these methods.

Hope this helps!


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