Abstract
This paper investigates the lead–lag relationships in high-frequency data. We propose multinomial dynamic time warping (MDTW) that deals with non-synchronous observation, vast data, and time-varying lead–lag. MDTW directly estimates the lead–lags without lag candidates. Its computational complexity is linear with respect to the number of observation and it does not depend on the number of lag candidates. The experiments adopting artificial data and market data illustrate the effectiveness of our method compared to the existing methods.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Brock, W. A., & Kleidon, A. W. (1992). Periodic market closure and trading volume. Journal of Economic Dynamics and Control, 16(3–4), 451–489. https://doi.org/10.1016/0165-1889(92)90045-g.
Chiba, K. (2017). Estimation of the lead-lag parameter between two stochastic processes driven by fractional Brownian motions. arXiv:1705.10466.
Dobreva, D., & Schaumburgb, E. (2017). High-frequency cross-market trading: Model free measurement and applications. Working paper.
Eun, C. S., & Shim, S. (1989). International transmission of stock market movements. The Journal of Financial and Quantitative Analysis, 24(2), 241. https://doi.org/10.2307/2330774.
Garbade, K. D., & Silber, W. L. (1979). Dominant and satellite markets: A study of dually-traded securities. The Review of Economics and Statistics, 61(3), 455. https://doi.org/10.2307/1926079.
Hayashi, T., & Koike, Y. (2017). Multi-scale analysis of lead-lag relationships in high-frequency financial markets. arXiv:1708.03992.
Hayashi, T., & Koike, Y. (2018). Wavelet-based methods for high-frequency lead-lag analysis. SIAM Journal on Financial Mathematics, 9(4), 1208–1248. https://doi.org/10.1137/18m1166079.
Hayashi, T., & Yoshida, N. (2005). On covariance estimation of non-synchronously observed diffusion processes. Bernoulli, 11(2), 359–379. https://doi.org/10.3150/bj/1116340299.
Hendershott, T., & Riordan, R. (2012). High frequency trading and price discovery. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1928510.
Hoffmann, M., Rosenbaum, M., & Yoshida, N. (2013). Estimation of the lead-lag parameter from non-synchronous data. Bernoulli, 19(2), 426–461. https://doi.org/10.3150/11-bej407.
Huth, N., & Abergel, F. (2014). High frequency lead/lag relationships: Empirical facts. Journal of Empirical Finance, 26, 41–58. https://doi.org/10.1016/j.jempfin.2014.01.003.
Ito, T., Lyons, R. K., & Melvin, M. T. (1998). Is there private information in the FX market? The Tokyo experiment. The Journal of Finance, 53(3), 1111–1130. https://doi.org/10.1111/0022-1082.00045.
Kawaller, I. G., Koch, P. D., & Koch, T. W. (1987). The temporal price relationship between s&p 500 futures and the s&p 500 index. The Journal of Finance, 42(5), 1309–1329. https://doi.org/10.1111/j.1540-6261.1987.tb04368.x.
Lo, A. W., & MacKinlay, A. C. (1990). An econometric analysis of nonsynchronous trading. Journal of Econometrics, 45(1–2), 181–211. https://doi.org/10.1016/0304-4076(90)90098-e.
Lucca, D. O., & Moench, E. (2015). The pre-FOMC announcement drift. The Journal of Finance, 70(1), 329–371. https://doi.org/10.1111/jofi.12196.
Müller, M. (2007). Information retrieval for music and motion. Berlin: Springer. https://doi.org/10.1007/978-3-540-74048-3.
Peiers, B. (1997). Informed traders, intervention, and price leadership: A deeper view of the microstructure of the foreign exchange market. The Journal of Finance, 52(4), 1589–1614. https://doi.org/10.1111/j.1540-6261.1997.tb01122.x.
Raihan, T. (2017). Predicting US recessions: A dynamic time warping exercise in economics. SSRN Electronic Journal,. https://doi.org/10.2139/ssrn.3047649.
Salvador, S., & Chan, P. (2007). FastDTW: Toward accurate dynamic time warping in linear time and space. Intelligent Data Analysis, 11(5), 561–580. https://doi.org/10.3233/IDA-2007-11508.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Ito, K., Sakemoto, R. Direct Estimation of Lead–Lag Relationships Using Multinomial Dynamic Time Warping. Asia-Pac Financ Markets 27, 325–342 (2020). https://doi.org/10.1007/s10690-019-09295-z
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10690-019-09295-z