Shemyakin, Arkady portrait

Shemyakin, Arkady

Professor
Degree
Ph.D., Russian Academy of Sciences-Siberia
Office
OSS 221
Phone
(651) 962-5522
Fax
651-962-5670
Mail
OSS 201

Arkady Shemyakin did his graduate study at Novosibirsk State University and post-graduate study at the Sobolev Institute of Mathematics in Novosibirsk, Russia. His main research interests lie in the field of Bayesian Statistics, non-informative priors, and copula analysis with the emphasis on applications to Insurance and Finance.

Dr. Shemyakin has taught full-time at Novosibirsk State University and as a visiting professor at several schools including Astrakhan State University in Russia, University of Minnesota and Heriot-Watt University in Edinburgh, UK.

Arkady is the current President of American Siberian Education Foundation and the past President of the Twin Cities chapter of American Statistical Association. He serves on the editorial boards and as a reviewer for several statistical journals. Besides that, he tries to spend as much time as possible playing chess, tennis, and skiing.

Fall 2014 Courses

Fall 2014 Courses
Course - Section Title Days Time Location
ACSC 464 - 01 Mathematical Finance - T - R - - - 1330 - 1510 OWS 251
CRN: 40967 4 Credit Hours Instructor: Arkady Shemyakin The focus of this course is on applications of probability, stochastic processes, and other mathematical tools to problems in finance. Both discrete and continuous models, including binomial, Brownian motion, and geometric Brownian motion models will be used to investigate the effects of randomness in financial markets and the behavior of financial instruments. The mathematical realization of arbitrage and hedging strategies will be examined, including the Arbitrage Theorem and the concept of risk-neutral pricing. Applications will include the pricing of equity options, currency transactions and the use of duration and convexity in fixed income analysis. The course will be of interest to students of actuarial science, mathematics, finance and economics who want to develop a better quantitative understanding of financial risk. Offered fall semester. Prerequisites: a grade of C- or above in MATH 313 or MATH 303 and ACSC 264 or a course in FINC approved by the instructor

Schedule Details

Location Time Day(s)
STAT 314 - 01 Mathematical Statistics - T - R - - - 0955 - 1135 OSS 214
CRN: 41216 4 Credit Hours Instructor: Arkady Shemyakin Populations and random sampling; sampling distributions. Theory of statistical estimation; criteria and methods of point and interval estimation. Theory of testing statistical hypotheses; non-parametric methods. Offered in fall semester. Prerequisite: MATH 240 and 313 NOTE: Students who recieve credit for MATH 314 may not receive credit for MATH 303.

Schedule Details

Location Time Day(s)
STAT 314 - 02 Mathematical Statistics - T - R - - - 1525 - 1700 OSS 227
CRN: 41713 4 Credit Hours Instructor: Arkady Shemyakin Populations and random sampling; sampling distributions. Theory of statistical estimation; criteria and methods of point and interval estimation. Theory of testing statistical hypotheses; non-parametric methods. Offered in fall semester. Prerequisite: MATH 240 and 313 NOTE: Students who recieve credit for MATH 314 may not receive credit for MATH 303.

Schedule Details

Location Time Day(s)
STAT 460 - 01 Statistical Research/Practicum - - - - - - - -
CRN: 43382 Instructor: Arkady Shemyakin Students will work individually with the instructor to identify a statistical research topic of current interest or to identify a real practical problem, for which statistics can be used to produce a feasible solution. State and local governments, companies, businesses, TV channels, or even faculty doing research should be the natural source of real practical problems to be solved. For either the research or the practical problem, the final outcome should be a report with publication potential.

Schedule Details

Location Time Day(s)

J-Term 2015 Courses

J-Term 2015 Courses
Course - Section Title Days Time Location

Spring 2015 Courses

Spring 2015 Courses
Course - Section Title Days Time Location
STAT 314 - 01 Mathematical Statistics - T - R - - - 1330 - 1510 OSS 227
CRN: 21674 4 Credit Hours Instructor: Arkady Shemyakin Populations and random sampling; sampling distributions. Theory of statistical estimation; criteria and methods of point and interval estimation. Theory of testing statistical hypotheses; non-parametric methods. Offered in fall semester. Prerequisite: MATH 240 and 313 NOTE: Students who recieve credit for MATH 314 may not receive credit for MATH 303.

Schedule Details

Location Time Day(s)
STAT 333 - 01 Applied Statistical Methods - T - R - - - 0955 - 1135 OSS 214
CRN: 20911 4 Credit Hours Instructor: Arkady Shemyakin Regression and exponential smoothing methods; Stochastic Time Series: auto- and cross-correlation, autoregressive moving average models; application to forecasting. Prerequisites: MATH 303 or 314 or STAT 314 or permission of instructor

Schedule Details

Location Time Day(s)
STAT 333 - 02 Applied Statistical Methods - T - R - - - 1525 - 1700 OSS 227
CRN: 21746 4 Credit Hours Instructor: Arkady Shemyakin Regression and exponential smoothing methods; Stochastic Time Series: auto- and cross-correlation, autoregressive moving average models; application to forecasting. Prerequisites: MATH 303 or 314 or STAT 314 or permission of instructor

Schedule Details

Location Time Day(s)
STAT 370 - 01 Bayesian Models - - - - - - - -
CRN: 22880 Instructor: Arkady Shemyakin The course covers a range of statistical models used in applications including: Actuarial Science, Finance, Health and Social Sciences. It is oriented towards practical model construction and problem sovling. Review of parametric statistical models and principles of statistical inference. Application to loss and ruin models. Construction of empirical and parametric models and model selection. Credibility theory. Simulation. Offered every other year. Prerequisite: MATH 313 and STAT 314 or STAT 220 and STAT 320

Schedule Details

Location Time Day(s)
STAT 460 - 01 Statistical Research/Practicum - - - - - - - -
CRN: 22881 Instructor: Arkady Shemyakin Students will work individually with the instructor to identify a statistical research topic of current interest or to identify a real practical problem, for which statistics can be used to produce a feasible solution. State and local governments, companies, businesses, TV channels, or even faculty doing research should be the natural source of real practical problems to be solved. For either the research or the practical problem, the final outcome should be a report with publication potential.

Schedule Details

Location Time Day(s)