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Koike Lab
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A lab that uses the statistics of stochastic processes to analyze high-frequency financial data.
AboutAbout the lab
Estimating covariance from high-frequency data.
Koike Lab works in probability and statistics, studying statistical inference for continuous-time stochastic process models.
Such models typically arise as high-frequency trading data of financial assets.
Specifically, the lab works on the problem of estimating the covariance structure of stochastic process models from data observed at high frequency.
Recently, the lab has been interested in modeling the lead-lag effect, in which a time lag arises in the covariance structure, and in the connection between high-frequency data analysis and high-dimensional statistics.
Key terms
- Stochastic process
- A mathematical representation of a quantity that changes over time under the influence of chance
- Covariance
- A value that expresses the degree to which two quantities increase or decrease together
- Lead-lag effect
- A phenomenon in which the movement of one value appears in the movement of another value after a time lag
ResearchResearch themes
The lab studies statistical inference for continuous-time stochastic process models that are observed discretely at high frequency. Its research themes also include statistics for high-dimensional data and applications to the analysis of high-frequency financial data.
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MembersFaculty
- Associate ProfessorYuta KoikePublications ↗
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Tickers ( )” Francisco Gonzalez / CC BY 2.0 (cropped)
- Statistics of High-Frequency Data: “Qtstalker candlestick chart” user:yndesai / CC0 (cropped)
- Related lab (Masuda Lab): “NIG-process” Thomas Steiner and Martin Keller-Ressel / CC BY-SA 2.5 (cropped)
- Related lab (Uchida Lab): “Ornstein-uhlenbeck simulation” Loxley / CC BY-SA 4.0 (cropped)
- Related lab (Aida Lab): “BMonSphere” Thomas Steiner / CC BY-SA 2.5 (cropped)
- Related lab (Okada Lab): “2D Random Walk Trace” Purpy Pupple / CC BY-SA 3.0 (cropped)
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