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Kurose Lab
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The lab analyzes economic and financial data using Bayesian statistics.
AboutAbout the lab
Modeling economic and financial data with statistics.
Kurose Lab conducts research analyzing economic and financial time series data using methods from statistics and econometrics.
Using Bayesian statistics, it analyzes data within the framework of state space models, including multivariate, high-dimensional data in which multiple series are handled simultaneously.
The lab also studies methods for generating random numbers from specific probability distributions and has published its results in papers.
Key terms
- Bayesian statistics
- A statistical approach that makes inferences by updating prior beliefs, held before obtaining data, in light of the observed data
- State space model
- A model that assumes an unobservable state and describes its change over time through its relationship with the observed data
- Stochastic volatility model
- A model in which the magnitude of price fluctuations is assumed to change randomly over time
ResearchResearch themes
Kurose Lab studies the analysis of economic and financial time series data using statistical methods. Its current work covers nonlinear, non-Gaussian state space models and the analysis of multivariate, high-dimensional economic and financial time series.
*Illustrative imageState space model analysis of economic and financial data
The lab analyzes economic and financial time series with state space models that have latent variables. Using Bayesian inference, it targets nonlinear, non-Gaussian models and multivariate, high-dimensional data.
*Illustrative imageEstimating volatility using price ranges
The lab studies models that estimate the magnitude of price fluctuations (volatility) using information from both returns and price ranges. It has also presented, at academic conferences, a method for speeding up the estimation of stochastic volatility models.
*Illustrative imageRandom number generation from specific distributions
The lab studies methods for generating random numbers from specific probability distributions, such as the truncated gamma distribution and the truncated generalized inverse Gaussian distribution. It has published a paper on the unimodal truncated gamma distribution.
MembersFaculty
- Assistant ProfessorYuta Kurose
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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: “No Known Restrictions Trading Floor, New York Stock Exchange (Highsmith LOC) ( )” Carol M. Highsmith / Public domain (cropped)
- State space model analysis of economic and financial data: “Exchange rates sign” Dvortygirl / CC BY-SA 4.0 (cropped)
- Estimating volatility using price ranges: “Philippine-stock-market-board” Katrina.Tuliao / CC BY 2.0 (cropped)
- Random number generation from specific distributions: “Galton board” Svjo / CC BY-SA 3.0 (cropped)
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