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A response surface analysis of critical values for the lead‐lag ratio with application to high frequency and non‐synchronous financial data
Author(s) -
O'Neill Michael,
Rajaguru Gulasekaran
Publication year - 2020
Publication title -
accounting and finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.645
H-Index - 49
eISSN - 1467-629X
pISSN - 0810-5391
DOI - 10.1111/acfi.12546
Subject(s) - spurious relationship , lag , lead–lag compensator , granger causality , econometrics , lead (geology) , statistics , sampling (signal processing) , benchmark (surveying) , surface (topology) , mathematics , computer science , engineering , geology , computer network , geodesy , filter (signal processing) , control engineering , geomorphology , computer vision , geometry
Granger causality tests are being supplanted by new methods such as the Lead‐Lag Ratio, particularly in finance where data arrives at random times and systematic sampling often produces spurious results. Existing approaches are insufficient; outside of block‐sampling using a bootstrap, the lead‐lag ratio has generally been assessed against a benchmark of 1 without regard for statistical significance. We use simulations to generate a response surface for the Lead‐Lag Ratio. Our modelled critical values are applied to reassess the findings of three previous studies of lead/lag relations between financial return series with high frequency data. Our response surface method proves to be a convenient and efficient alternative to using a bootstrap.