quant phd programs

You are using an outdated browser. This website is best viewed in IE 9 and above. You may continue using the site in this browser. However, the site may not display properly and some features may not be supported. For a better experience using this site, we recommend upgrading your version of Internet Explorer or using another browser to view this website.

- Download the latest Internet Explorer - No thanks (close this window)

• Penn GSE Environmental Justice Statement
• Philadelphia Impact
• Global Initiatives
• Diversity & Inclusion
• Catalyst @ Penn GSE
• Penn GSE Leadership
• Program Finder
• Academic Divisions & Programs
• Professional Development & Continuing Education
• Teacher Programs & Certifications
• Undergraduates
• Dual and Joint Degrees
• Faculty Directory
• Research Centers, Projects & Initiatives
• Lectures & Colloquia
• Books & Publications
• Academic Journals
• Application Requirements & Deadlines
• Tuition & Financial Aid
• Campus Visits & Events
• International Students
• Options for Undergraduates
• Non-Degree Studies
• Contact Admissions / Request Information
• Life at Penn GSE
• Penn GSE Career Paths
• Living in Philadelphia
• DE&I Resources for Students
• Student Organizations
• Career & Professional Development
• News Archive
• Events Calendar
• The Educator's Playbook
• Find an Expert
• Race, Equity & Inclusion
• Counseling & Psychology
• Education Innovation & Entrepreneurship
• Education Policy & Analysis
• Higher Education
• Language, Literacy & Culture
• Teaching & Learning
• Support Penn GSE
• Contact Development & Alumni Relations
• Find a Program
• Request Info
• Make a Gift
• Current Students
• Staff & Faculty

Search form

Quantitative methods, doctor of philosophy (ph.d.), you are here, a doctoral program focused on measurement and evaluation that trains students to create new research methodologies and design empirical data analyses. .

The Quantitative Methods Ph.D. program is designed to prepare future professors at research universities and principal investigators at research and assessment organizations in education, psychology, and related human services fields.

What Sets Us Apart

About the program.

Rigorous coursework across the field of education will prepare students with the tools needed to conduct cutting-edge research and assessment.  

Fall: 4 courses; Spring: 4 courses

Research apprenticeship Yes

Culminating experience Dissertation

The Ph.D. program in Quantitative Methods is designed to prepare students for faculty positions at universities as well as important responsibilities at research and assessment organizations. Graduates will be prepared to design first-rate empirical research and data analyses and to contribute to the development of new research methodologies. Students who apply directly to the doctoral-level study program following a baccalaureate degree will enroll in the core courses described for the  M.S.Ed. degree in Statistics, Measurement, Assessment, and Technology (SMART)  and the more advanced courses for the Ph.D. degree. This will include the development of independent empirical research projects.

Doctoral degree studies include advanced graduate coursework, a research apprenticeship, a Ph.D. Candidacy Examination, and the completion of a doctoral dissertation that represents an independent and significant contribution to knowledge. The research apprenticeship provides students with an opportunity to collaborate with a faculty sponsor on an ongoing basis and to participate in field research leading to a dissertation. 

For information about courses and requirements, visit the  Quantitative Methods Ph.D. program in the University Catalog .

Our Faculty

Affiliated Faculty

Eric T. Bradlow K.P. Chao Professor, The Wharton School Ph.D., Harvard University

Timothy Victor   Adjunct Associate Professor, Penn GSE 

"Penn GSE’s Quantitative Methods Ph.D. program equipped me with the methodological skills to do impactful applied education research as soon as I graduated."

Anna Rhoad-Drogalis

Our graduates.

Graduates go on to careers as university professors, researchers and psyshometricians for government agencies, foundations, nonprofits organizations, and corporations. 

Alumni Careers

• Assistant Professor, Texas A&M University-Corpus Christi
• Associate Director, Bristol-Myers Squibb
• Lead Psychometrician, American Institute of Certified Public Accountants
• Research Analyst, Penn Child Research Center, University of Pennsylvania
• Senior Director, Educational Testing Service
• Senior Researcher, Mathematica

Admissions & Financial Aid

Please visit our Admissions and Financial Aid pages for specific information on the application requirements , as well as information on tuition, fees, financial aid, scholarships, and fellowships.

Contact us if you have any questions about the program.

Graduate School of Education University of Pennsylvania 3700 Walnut Street Philadelphia, PA 19104 (215) 898-6415 [email protected] [email protected]

Christine P. Lee Program Manager (215) 898-0505 [email protected]

Please view information from our Admissions and Financial Aid Office for specific information on the cost of this program.

All Ph.D. students are guaranteed a full scholarship for their first four years of study, as well as a stipend and student health insurance. Penn GSE is committed to making your graduate education affordable, and we offer generous scholarships, fellowships, and assistantships.

Related News & Research

Karen weaver analyzes division iii college closures in “forbes”.

Dean Katharine Strunk supports fair pay for student teachers in Pennsylvania

Education law lecture explores landmark case demanding equitable school funding for Pennsylvania

Laura Perna cites trust issues in the FAFSA overhaul for “The Atlantic”

Center on Standards, Alignment, Instruction, and Learning

The Center on Standards, Alignment, Instruction, and Learning (C-SAIL) examines how college- and career-ready standards are implemented, if they improve student learning, and what instructional tools measure and support their implementation.

Penn Early Childhood and Family Research Center

The Penn Early Childhood and Family Research Center aims to advance the use of science in a context of public trust to address problems affecting the well-being of young children and families facing systemic injustice and disadvantage.

You May Be Interested In

Related programs.

• Education Policy M.S.Ed. 
• Education, Culture, and Society Ph.D. 
• Higher Education Ph.D. 
• Quantitative Methods M.Phil.Ed.
• Statistics, Measurement, Assessment, and Research Technology M.S.Ed.

Related Topics

• Skip to Content
• Catalog Home
• Institution Home
• Graduate Catalog /
• Graduate School of Education /

Quantitative Methods, PhD

The Ph.D. program in Quantitative Methods is designed to prepare students for faculty positions at universities and important responsibilities at research and assessment organizations. Graduates will be prepared to design first rate empirical research and data analyses and to contribute to development of new research methodologies.

Doctoral degree studies include advanced graduate coursework, a research apprenticeship, a Ph.D. Candidacy Examination, and the completion of a doctoral dissertation that represents an independent and significant contribution to knowledge. The research apprenticeship provides students with an opportunity to collaborate with a faculty sponsor on an ongoing basis and to participate in field research leading to a dissertation.

Students who apply directly to the doctoral-level study program following a baccalaureate degree will enroll in the core courses described for M.S.Ed. degree in SMART and the more advanced courses for the Ph.D. degree. This will include the development of independent empirical research projects.

For more information: http://www.gse.upenn.edu/qm/phd

View the University’s Academic Rules for PhD Programs .

The Ph.D. degree program in Quantitative Methods requires a minimum of 20 course units or relevant courses and advanced degree accomplishments. A maximum of eight (8) credits from other institutions may be taken into account in reducing this basic requirement where appropriate.

Required Milestones

Qualifications evaluation (also known as program candidacy).

A Qualifications Evaluation of each student is conducted after the completion of 6 but not more than 8 course units. The evaluation is designed by the specialization faculty and may be based on an examination or on a review of a student’s overall academic progress.

Preliminary Examination (Also known as Doctoral Candidacy)

A Candidacy Examination on the major subject area is required.  The candidacy examination is a test of knowledge in the student's area of specialization, requiring students to demonstrate knowledge and reasoning in the key content areas in their specialization as defined by their academic division. This examination is normally held after the candidate has completed all required courses.

Oral Proposal

All doctoral candidates must present their dissertation proposals orally and in person to the dissertation committee.

Final Defense of the Dissertation

The final dissertation defense is approximately two hours in length and is based upon the candidate’s dissertation. 

The degree and major requirements displayed are intended as a guide for students entering in the Fall of 2023 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.

Print Options

Print this page.

The PDF will include all information unique to this page.

A PDF of the entire 2023-24 catalog.

A PDF of the 2023-24 Undergraduate catalog.

A PDF of the 2023-24 Graduate catalog.

• Youth Program
• Wharton Online

PhD Program

• Program of Study

Wharton’s PhD program in Finance provides students with a solid foundation in the theoretical and empirical tools of modern finance, drawing heavily on the discipline of economics.

The department prepares students for careers in research and teaching at the world’s leading academic institutions, focusing on Asset Pricing and Portfolio Management, Corporate Finance, International Finance, Financial Institutions and Macroeconomics.

Wharton’s Finance faculty, widely recognized as the finest in the world, has been at the forefront of several areas of research. For example, members of the faculty have led modern innovations in theories of portfolio choice and savings behavior, which have significantly impacted the asset pricing techniques used by researchers, practitioners, and policymakers. Another example is the contribution by faculty members to the analysis of financial institutions and markets, which is fundamental to our understanding of the trade-offs between economic systems and their implications for financial fragility and crises.

Faculty research, both empirical and theoretical, includes such areas as:

• Structure of financial markets
• Formation and behavior of financial asset prices
• Banking and monetary systems
• Corporate control and capital structure
• Saving and capital formation
• International financial markets

Candidates with undergraduate training in economics, mathematics, engineering, statistics, and other quantitative disciplines have an ideal background for doctoral studies in this field.

Effective 2023, The Wharton Finance PhD Program is now STEM certified.

• Course Descriptions
• Course Schedule
• Dissertation Committee and Proposal Defense
• Meet our PhD Students
• Visiting Scholars

More Information

• Apply to Wharton
• Doctoral Inside: Resources for Current PhD Students
• Wharton Doctoral Program Policies
• Transfer of Credit
• Research Fellowship

Smart. Open. Grounded. Inventive. Read our Ideas Made to Matter.

Which program is right for you?

Through intellectual rigor and experiential learning, this full-time, two-year MBA program develops leaders who make a difference in the world.

A rigorous, hands-on program that prepares adaptive problem solvers for premier finance careers.

A 12-month program focused on applying the tools of modern data science, optimization and machine learning to solve real-world business problems.

Earn your MBA and SM in engineering with this transformative two-year program.

Combine an international MBA with a deep dive into management science. A special opportunity for partner and affiliate schools only.

A doctoral program that produces outstanding scholars who are leading in their fields of research.

Bring a business perspective to your technical and quantitative expertise with a bachelor’s degree in management, business analytics, or finance.

A joint program for mid-career professionals that integrates engineering and systems thinking. Earn your master’s degree in engineering and management.

An interdisciplinary program that combines engineering, management, and design, leading to a master’s degree in engineering and management.

Executive Programs

A full-time MBA program for mid-career leaders eager to dedicate one year of discovery for a lifetime of impact.

This 20-month MBA program equips experienced executives to enhance their impact on their organizations and the world.

Non-degree programs for senior executives and high-potential managers.

A non-degree, customizable program for mid-career professionals.

PhD Program in Finance

2023-24 curriculum outline.

The MIT Sloan Finance Group offers a doctoral program specialization in Finance for students interested in research careers in academic finance. The requirements of the program may be loosely divided into five categories: coursework, the Finance Seminar, the general examination, the research paper, and the dissertation. Attendance at the weekly Finance Seminar is mandatory in the second year and beyond and is encouraged in the first year.  During the first two years, students are engaged primarily in coursework, taking both required and elective courses in preparation for their general examination at the end of the second year.  Students are required to complete a research paper by the end of their fifth semester, present it in front of the faculty committee and receive a passing grade.  After that, students are required to find a formal thesis advisor and form a thesis committee by the end of their eighth semester. The Thesis Committee should consist of at least one tenured faculty from the MIT Sloan Finance Group.

Required Courses

The following set of required courses is designed to furnish each student with a sound and well-rounded understanding of the theoretical and empirical foundations of finance, as well as the tools necessary to make original contributions in each of these areas. Finance PhD courses (15.470, 15.471, 15.472, 15.473, 15.474) in which the student does not receive a grade of B or higher must be retaken.

First Year - Summer

Math Camp begins on the second Monday in August. 

First Year - Fall Semester

14.121/14.122 Micro Theory I/II

14.451/14.452 Macro Theory I/II ( strongly recommended)

14.380/14.381 — Statistics/Applied Econometrics

15.470 — Asset Pricing

First Year - Spring Semester

14.123/14.124 Micro Theory III/IV

14.453/14.454 Macro Theory III/IV (strongly recommended)

14.382 – Econometrics

15.471 – Corporate Finance

Second Year - Fall Semester

15.472 — Advanced Asset Pricing

  14.384 — Time-Series Analysis or  14.385 — Nonlinear Econometric Analysis  (Enrolled students receive a one-semester waiver from attending the Finance Seminar due to a scheduling conflict)

15.475 — Current Research in Financial Economics

Second Year - Spring Semester

15.473 — Advanced Corporate Finance

 15.474 — Current Topics in Finance (strongly encouraged to take multiple times)

15.475 — Current Research in Financial Economics

Recommended Elective Courses

Beyond these required courses, students are expected to enroll in elective courses determined by their primary area of interest. There are two informal “tracks” in Financial Economics: Corporate Finance and Asset Pricing. Recommended electives are designed to deepen the student's grasp of material that will be central to the writing of his/her dissertation. Students also have the opportunity to take courses at Harvard University. There is no formal requirement to select one track or another, and students are free to take any of the electives.

Psychological Sciences

  Alert Content Goes Here

• Graduate Program

Quantitative Methods

Program overview.

Faculty in the Quantitative Methods (QM) program train students in state-of-the-art statistical methods and engage in research that develops and applies such methods. Students in the QM doctoral program develop expertise in the principles of research design and in the theoretical foundations and application of advanced statistical models for human behavior. Students work closely on research projects with a faculty mentor throughout their graduate career, and often collaborate with other faculty and students. QM faculty collectively have expertise in factor analysis and structural equation modeling; network analysis; measurement and item response theory; exploratory data analysis; mediation and moderation; longitudinal methods; multilevel modeling; mixture modeling; categorical data analysis; and generalized linear models. Quantitative faculty approach the study of these topics from a variety of angles, such as: developing computational tools to promote the use of new or existing methods; evaluating the performance of such methods under real-world conditions; and applying these methods in novel and sophisticated ways to solve substantive problems. Several QM faculty have substantive specializations in, for example, individual differences, personality psychology, clinical psychology, learning sciences, and developmental psychology, which facilitate intensive investigation of analytic approaches critical to those substantive domains. Students may pursue greater or lesser degrees of substantive psychological training, in addition to quantitative training, depending on their and their advisors' interests.

The QM program is housed within the Department of Psychology and Human Development at Peabody College-- a top-ten ranked school of education for the past ten years. This unique context exposes QM students to a variety of applications, methods, and statistical problems that arise in psychological and educational research, as well as the social sciences more generally.

QM faculty teach courses on a broad variety of fundamental and advanced topics in design and data analysis. These courses are attended by students from a variety of social science disciplines, as well as by QM students. QM students are encouraged to tailor their curriculum to maximize relevancy for their particular research interests, background, and career goals. QM course offerings include correlation and regression; analysis of variance; psychological and educational measurement; data science methods; multivariate analysis; psychological, field, and clinical research methods; item response theory (basic and advanced); exploratory/graphical data analysis; structural equation modeling; factor analysis; latent growth curve modeling; categorical data analysis; multilevel modeling; mixture modeling; nonparametric statistics; individual differences; causal analysis in field experiments and quasi-experiments; network analysis; statistical consulting; and meta-analysis. Additionally, many of our students get an optional Minor in Biostatistics . Students may also take courses in Scientific Computing , and/or other areas of psychology and education. Several research centers on campus also provide QM students with training opportunities. Vanderbilt’s new Data Science Institute (DSI) offers numerous workshops, short courses, colloquia, and collaboration opportunities using data science methods and tools. QM faculty also serve as teaching faculty and/or faculty affiliates of the DSI and are involved with the development, operations, and strategic goals of the DSI. Also, the Vanderbilt Kennedy Center maintains a statistics and methodology core which provides a methodology lecture series as well as statistical consulting training and resources. Additionally, students gain presentation and research skills by participating in the Quantitative Methods Forum (schedule below).

Core faculty

More information about individual faculty's research programs can be obtained from their websites by clicking on their names. Alternately, a list of QM faculty is available here . Prospective students are encouraged to contact core QM faculty with shared interests to ask questions about the program. Core QM faculty recruit and train Ph.D. students through the QM program.

• Sun-Joo Cho (item response theory; generalized latent variable modeling; test development and validation)
• * Alex Christensen (network analysis; data science; psychometrics; measurement)
• David Cole (structural equation modeling; mediation analysis; longitudinal methods; developmental psychopathology)
• Shane Hutton (survival analysis; dynamical systems modeling)
• David Lubinski (measurement; assessment; individual differences; intellectual talent development)
• Kristopher Preacher (structural equation modeling; multilevel modeling; mediation and moderation)
• Sonya Sterba (mixture models; multilevel and longitudinal methods; latent variable models)
• Chris Strauss (measurement and assessment; multilevel measurement; structural equation modelling)
• Hao Wu (model evaluation; uncertainty quantification; robust and nonparametric methods; structural equation modeling)

         (* = interested in recruiting a QM Ph.D. student to start in the 2024-2025 academic year)

Emeritus faculty

• Joseph Rodgers (general multivariate methods; exploratory/graphical data analysis; multidimensional scaling and measurement; behavior genetics; adolescent development)
• Jim Steiger (structural equation modeling; model evaluation; inferential methods; statistical computing)
• Andrew Tomarken (categorical data analysis; generalized linear models; longitudinal methods; clinical psychology)

Affiliated faculty

• Li Chen (statistical consulting; quantitative pedagogy)
• Scott Crossley (natural language processing)
• Will Doyle (data science; education policy)
• Kelly Goldsmith (business analytics, marketing, consumer psychology)

The program maintains its own quantitative computer lab, and additionally individual faculty have labs and computing resources that support their research programs. There are also computing labs in the department and elsewhere in Peabody College that are supplied with statistical software often used for classroom teaching.  Special funds for research-related software and computing equipment, as well as external workshop and conference travel, are available to QM students.

Information for Prospective QM Applicants

QM doctoral program graduates are prepared for faculty positions in academic settings, methodology positions in basic or applied research centers, or methodology positions in industry. Students work together with their advisor and advisory committee to refine their career goals, and tailor their research, coursework, and teaching experiences accordingly. The American Psychological Association reports that there are far more jobs for doctoral students trained in quantitative methods in psychology than there are applicants. Further information can be found here , here , and here .

The QM program is designed to lead to a Ph.D. degree within 5 years. In the first two years, students take a series of fundamental methods courses and begin working on research with their advisor. To build students' oral presentation skills, students present their research to the program on a yearly basis. Students who did not enter with a full year of calculus also complete such coursework in the Mathematics Department during this time. In their third year, students complete their masters thesis and continue research in collaboration with their advisor and others, while furthering their expertise with an individualized set of advanced coursework. Students take an exam in their third or fourth year that is based on reading lists related to content in courses they have taken up until that point. In their fourth and fifth years students finish their coursework and conduct a dissertation project under the guidance of their advisor and other committee members, while building additional independent research and/or teaching skills relevant to their particular career goals.

Doctoral applicants admitted to the QM program receive a guaranteed 5 years of stipend and tuition support, which usually takes the form of a combination of research assistantships and/or teaching assistantships in quantitative courses (for instance, the introductory graduate statistics sequence). Additionally, QM students have a successful track record of obtaining prestigious NSF fellowships. Senior students routinely also may obtain other kinds of stipends as statistical analysts or consultants for various research projects and grants on campus; these opportunities serve as valuable supplementary training experiences. Some students also serve as teaching instructors for their own section of an undergraduate statistics course or undergraduate measurement course in order to deepen their teaching credentials. Application instructions are available here .

QM Masters Program

In Spring 2014, the QM program launched a terminal M.Ed. in Quantitative Methods. This program is distinct from our longstanding research-focused Ph.D. program. More information about the goals and expectations for applicants to our M.Ed. program can be found here .

Graduate QM Minor

Doctoral students outside the QM program may elect to minor in quantitative methods. This formal minor involves taking four advanced methods courses from the QM program beyond the first year required graduate statistics sequence (6 courses total). The minor requires a 3.5 average GPA (for all 6 minor courses), with no grade below a B. The minor provides students with exceptional training in the application of complex psychometric and statistical procedures and provides students with skills that can enhance the quality of their research program over the course of their career. Many students find that the credential of a graduate minor in quantitative methods is a valuable asset in the pursuit of research-oriented academic positions or quantitatively-oriented industry positions after graduation. Detailed information on minor requirements can be obtained from the Psychological Sciences graduate student handbook. For more information, contact Kris Preacher .

Undergraduate QM Minor

The QM program offers an 18-credit undergraduate minor in quantitative methodology. For information on our new undergraduate QM minor, please click here .

Quantitative Methods Colloquium Series

The QM program offers a weekly Quantitative Methods Colloquium Series which covers novel methodological advances, cutting-edge applications of quantitative methods, inclusivity in QM, teaching pedagogy in QM, QM professional development activities, QM outreach, and QM workshops. The QM colloquium series features a mix of external speakers from different settings (e.g., academia and industry) and different stages of their careers in order to expose our QM students to a variety of career paths and perspectives. Each semester our QM forum also contains internal program speakers, QM students and QM faculty, to allow us to share our research with, and gain feedback from, our colleagues. For more information on the QM Colloquium please visit the Colloquium schedule .

Quantitative Methods Outreach

At least once per year the QM Colloquium Series features an Open House where statistical consulting problems presented by Peabody faculty guest(s) receive a program-level discussion. Additionally, our QM program offers a statistical consulting course on a yearly basis to which Peabody faculty can submit statistical problems to serve as student projects. QM faculty also maintain a listserv ([email protected]) to which Peabody faculty can submit statistical problems that are limited in scope. Submitted questions will first be considered for open house or course project slots and secondarily for a graduate assistant to the QM faculty for further attention.

Fall 2024 QM Course Offerings

• PSY-GS 8861-01: Statistical Inference . TR 1:15p - 2:30p Hutton
• PSY-GS 8870-01 / PSY-PC 3735-01: Correlation and Regression . TR 9:30a - 10:45a Strauss
• PSY-GS 8873-01: Structural Equation Modeling . TR 11:00a - 12:15p Cole
• PSY-GS 8876-01 / PSY-PC 3724-01: Psychological Measurement / Psychometrics . T 4:15p - 7:05p Lubinski
• PSY-GS 8878-01 / PSY-PC 7878-01: Statistical Consulting . T 1:15p - 4:05p Strauss
• PSY-GS 8879-01 / PSY-PC 3743-01: Factor Analysis . F 10:10a - 1:00p Preacher
• PSY-GS 8882-01: Multilevel Modeling . W 10:10a - 1:00p Preacher

Undergraduate

• PSY-PC 2110-01: Introduction to Statistical Analysis . TR 11:00a - 12:15p Hutton
• PSY-PC 2110-05: Introduction to Statistical Analysis . MWF 11:15a - 12:05p Chen
• PSY-PC 2110-06: Introduction to Statistical Analysis . MWF 12:20a - 1:10p Osina
• PSY-PC 2110-07: Introduction to Statistical Analysis . MWF 10:10a - 11:0 0a Chen
• PSY-PC 2110-08: Introduction to Statistical Analysis . TR 9:30a - 10:45a Vinci-Booher
• PSY-PC 2110-09: Introduction to Statistical Analysis . TR 1:15p - 2:30p Wu
• PSY-PC 2110-10: Introduction to Statistical Analysis . TR 2:45p - 4:00p Wu
• PSY-PC 3722-01: Psychometric Methods . TR 8:00a - 9:15a Cho

PhD Programs with Quantitative Concentrations

Public policy.

• Social Sciences

Public Health Sciences

Comparative human development, political science.

The University has PhD degree programs in various departments and schools that provide a concentration on quantitative methods. New doctoral applicants who are interested in developing specialty in quantitative methods, depending on their disciplinary interests, may look into one of these degree programs.

Doctoral Programs in Quantitative Methods

Business administration.

Econometrics and Statistics , one of the eight dissertation areas in the Booth School PhD program, is concerned with the combination of economic, mathematical, and computer techniques in the analysis of economic and business problems such as forecasting, demand and cost analyses, model-building, and testing empirical implications of theories. Study in this area integrates a comprehensive program of course work with extensive research. The program is designed for students who wish to do research in statistical methods that are motivated by business applications. Students are able to design an individual program of study by combining courses in specific areas of business, such as economics, finance, accounting, marketing, or international business with advanced courses in statistical methods.  Empirical work has always been an important part of the research effort at Chicago Booth in all fields of study. Econometrics and statistics courses are thus useful choices in satisfying the basic discipline or coordinated sequence.

Quantitative Methods  are a key component of the Core curriculum. Specialized Fields in Quantitative Methods include:

• Quantitative Study of Inequality
• Applied econometrics

          Tools of Policy Analysis provides in-depth and technical expertise that can be applied to a broad range of subject          areas.The following are included among the five specialties: Program evaluation, statistics, and survey methods. 

Methods in Human Development Research . Research on human development over the life span and across social and cultural contexts thrives on multiple theoretical perspectives. This research requires creation and improvement of a wide range of research methods appropriately selected for and tailored to specific human development problems. Faculty in the department employ research methods that span the full range from primarily qualitative to primarily quantitative and to strategic mix of both. Across all the substantive domains in Comparative Human Development, theoretical understanding is greatly advanced by methodology; therefore the Department pays serious attention to research design, data collection, analytic strategies, and presentation, evaluation, and interpretations of evidence. The Department has contributed some of the most influential work on psychological scaling on the basis of the item response theory (IRT), multivariate statistical methods, analysis of qualitative data, modeling of human growth, and methods for cross-cultural analysis. Current research interests include (a) assessment of individual growth and change in important domains of development that are often intertwined, (b) examination and measurement of the structure, process, and quality of individual and group experiences in institutionalized settings such as families, schools, clinics, and neighborhoods, and (c) evaluation of the impact of societal changes or interventions on human development via changes in individual and group experiences, with particular interest in the heterogeneity of growth, process, and impact across demographic sub-populations and across social cultural contexts.

Concentration in Biostatistics ,The PhD program in the Department of Public Health Sciences is supported by a core methodological curriculum in population-based research on human health. Students completing a concentration in biostatistics will be prepared to develop state-of-the-art quantitative reasoning and techniques of statistical science, mathematics, and computing, and to apply these to current and future research problems in biomedical science and population health. In addition, these students will complete a minor program of study in a substantive area of application. As such they will be particularly well prepared to engage in collaborative population-based health research. 

Methodology  is one of the five fields in the department. Many students choose the department’s introductory sequence in quantitative methods, followed by more advanced seminars in data analysis and model building. Students with more advanced methodological skills can take further coursework in the department or related courses in economics, public policy or statistics.

Special Fields in Methodology . The Department of Sociology at the University of Chicago has a rich group of faculty members who provide graduate training and conduct research in methods and models for sociological research. These methods can be divided roughly into four categories: Field and ethnographic methods; statistical methods; survey and related methods; and mathematical modeling methods. PhD. students are required to demonstrate competence in two special fields. The Special Field Requirement is generally met during the third and fourth years of graduate study. Students must pass the Preliminary Examination at the PhD. level before meeting the Special Field Requirement. This requirement may be met in three ways: by examination, with a review essay, or through a specified sequence of methods courses. Five types of special fields in methodology are recognized: (1) social statistics, (2) survey research methods, (3) qualitative methods (4) methodology for social organization research, and (5) mathematical sociology.

Quantitative Methods

In an era of dwindling resources and increasing competition, optimization questions have assumed a new and urgent importance . To that end, doctoral seminars in Quantitative Methods focus on advanced optimization applications and methodologies. Related courses are available from areas such as industrial and electrical engineering and computer sciences.

Faculty collaboration with other areas of management and related engineering programs enables students to participate in research on a stimulating range of optimization applications . Current areas of faculty interest in applied optimization include transportation, communication, distribution, and manufacturing systems. Other application domains include auditing, scheduling, and quality control.

A specialization in statistics and its applications address managerial problems in which randomness or uncertainty complicates the decision environment, offering students a rich variety of topics for research. Current faculty research interests in applied statistics include data mining, reliability theory, stochastic marketing models, auditing and acceptance sampling, statistical decision theory, and statistical quality and process control.

Download the Fact Sheet

Request More Information

Most Trusted #4

Morning Consult, 2022

Best Value School #7

The Wall Street Journal / Times Higher Education, 2022

Most Innovative School in the U.S. Top 10

US News and World Report, 2023

Want to Learn More? 

If you would like to receive more information about doctoral study in Quantitative Methods, please fill out the form and an Admissions Specialist will be in touch to connect you with a department representative!

Contact us for more information. [email protected]

Program Details

Faculty and Students

• Quantitative Finance Specialization
• Academic Programs
• Management Science and Analytics (Ph.D.)

The Quantitative Finance specialization in the Ph.D. in Management Science and Analytics program is excellent preparation for either academic careers or for students who want to apply the theoretical, analytical, and quantitative rigor of management science to careers in finance.

Dissertation research in this area may include a wide range of topics such as risk modeling, financial time series analysis, and investment analysis.

Required courses for the Quantitative Finance specialization (three credits per course):

• MSC 621—Corporate Finance
• MSC 623—Investments
• MSC 631—Theory of Finance I
• MSC 633—Theory of Finance II
• MSF 545/MSC 613—Structured Fixed Income Portfolios
• MSF 546/MSC 614—Quantitative Investment Strategies

View the curriculum for the Ph.D. in Management Science (MSC) program and MSC course descriptions .

Career Opportunities

Industry and Research

The specialization in Quantitative Finance prepares students for a wide range of careers in finance, particularly in areas such as investment and commercial banking, trading, and risk management. This background also opens career opportunities across industries in business functions focused on finance, financial modeling, economics, and risk compliance.

Chicago’s position as a global center for finance and fintech, as well as the home to the world’s largest markets in financial derivatives, make it a prime location for internships, networking, and job opportunities for Stuart students in quantitative finance.

Our graduates are ready to step into roles such as:

• Senior quantitative analyst or quantitative analytics manager-economic modeling
• Quantitative developer, senior quantitative modeler, or quantitative risk modeler
• Research data scientist, senior quantitative researcher, or quantitative researcher-asset management
• Portfolio risk analyst, senior quantitative risk analyst, or exotic rates quantitative analyst
• Equity derivatives quantitative strategist or quantitative portfolio strategist
• Senior quantitative markets analyst or machine learning analyst

Students interested in academic careers are supported by strong mentoring relationships with our faculty, opportunities to co-author papers published in prestigious scholarly journals, and help in securing adjunct positions to develop their teaching skills.

As a result, our graduates have launched teaching and research careers as finance faculty members at colleges and universities in the United States and around the world, such as:

• Carnegie Mellon University
• Beijing Normal University
• Lewis University
• Brooklyn College - City University of New York
• Benedictine University
• Northeastern Illinois University
• East China Normal University
• Saint Michael’s College (Vermont)

Learn more...

Boston University Academics

Boston University

• Campus Life
• Schools & Colleges
• Degree Programs
• Search Academics
• PhD in Mathematical Finance

The PhD in Mathematical Finance is for students seeking careers in research and academia. Doctoral candidates will have a strong affinity for quantitative reasoning and the ability to connect advanced mathematical theories with real-world phenomena. They will have an interest in the creation of complex models and financial instruments as well as a passion for in-depth analysis.

Learning Outcomes

The PhD curriculum has the following learning goals. Students will:

• Demonstrate advanced knowledge of literature, theory, and methods in their field.
• Be prepared to teach at the undergraduate, master’s, and/or doctoral level in a business school or mathematics department.
• Produce original research of quality appropriate for publication in scholarly journals.

After matriculation into the PhD program, a candidate for the degree must register for and satisfactorily complete a minimum of 16 graduate-level courses at Boston University. More courses may be needed, depending on departmental requirements.

PhD in Mathematical Finance Curriculum

The curriculum for the PhD in Mathematical Finance is tailored to each incoming student, based on their academic background. Students will begin the program with a full course load to build a solid foundation in not only math and finance but also the interplay between them in the financial world. As technology plays an increasingly larger role in financial models, computer programming is also a part of the core coursework.

Once a foundation has been established, students work toward a dissertation. Working closely with a faculty advisor in a mutual area of interest, students will embark on in-depth research. It is also expected that doctoral students will perform teaching assistant duties, which may include lectures to master’s-level classes.

Course Requirements

The minimum course requirement is 16 courses (between 48 and 64 credits, depending on whether the courses are 3 or 4 credits each). Students’ course choices must be approved by the Mathematical Finance Director prior to registration each semester. The following is a typical program of courses.

• GRS EC 701 Microeconomic Theory
• GRS MA 711 Real Analysis
• GRS MA 779 Probability Theory I
• QST FE 918 Doctoral Seminar in Finance
• GRS EC 703 Advanced Microeconomic Theory
• GRS MA 776 Partial Differential Equations
• GRS MA 781 Probability Theory 2
• QST FE 920 Advanced Capital Market Theory
• GRS EC 702 Macroeconomic Theory
• GRS MA 783 Advanced Stochastic Processes
• QST MF 850 Advanced Computational Methods
• QST MF 922 Advanced Mathematical Finance
• GRS EC 704 Advanced Microeconomic Theory
• GRS MA 751 Statistical Machine Learning
• QST MF 810 FinTech Programming
• QST MF 921 Topics in Dynamic Asset Pricing

Additional Requirements

Qualifying examination.

Students must appear for a qualifying examination after completion of all coursework to demonstrate that they have:

• acquired advanced knowledge of literature and theory in their area of specialization;
• acquired advanced knowledge of research techniques; and
• developed adequate ability to craft a research proposal.

Guidelines for the examination are available from the departments. Students who do not pass either the written and/or oral comprehensive examination upon first try will be given a second opportunity to pass the exam. Should the student fail a second time, the student’s case will be reviewed by the Mathematical Finance Program Development Committee (MF PDC), which will determine if the student will be withdrawn from the PhD program. In addition, the PhD fellowship (if applicable) of any student who does not pass either the written and/or oral comprehensive examination after two attempts will be suspended the semester after the exam was attempted.

Dissertation

Following successful completion of the qualifying examination, the student will develop a research proposal for the dissertation. The final phase of the doctoral program is the completion of an approved dissertation. The dissertation must be based on an original investigation that makes a substantive contribution to knowledge and demonstrates capacity for independent, scholarly research.

Doctoral candidates must register as continuing students for DS 999 Dissertation, a 2-credit course, for each subsequent regular semester until all requirements for the degree have been completed. PhD students graduating in September are required to register for Dissertation in Summer Session II preceding graduation.

Academic Standards

Time limit for degree completion.

After matriculation into the PhD program, a candidate for the degree must meet certain milestones within specified time periods (as noted in the table below) and complete all degree requirements within six years of the date of first registration. Those who fail to meet the milestones within the specified time, or who do not complete all requirements within six years, will be reviewed by the PhD PDC and may be dismissed from the program. A Leave of Absence does not extend the six-year time limit for degree completion.

Performance Review

The Mathematical Finance Program Development Committee will review the progress of each doctoral candidate. Students must maintain a 3.30 cumulative grade point average in all courses to remain in good academic standing. Students who are not in good academic standing will be allowed one semester to correct their status. Prior to the start of the semester, the student must submit a letter to the Faculty Director (who will forward it to the PDC) explaining why the student has fallen short of the CGPA requirement and how the student plans to correct the situation. Failure to increase the CGPA to acceptable levels may result in probation or withdrawal from the program, at the discretion of the PhD Program Development Committee (PDC).

Graduation Application

Students must submit a graduation application at least seven months before the date they expect to complete degree requirements. It is the student’s responsibility to initiate the process for graduation. The application is available online and should be submitted through the Specialty Master’s & PhD Center website for graduation in January, May, or August.

If graduation must be postponed beyond the semester for which the application is submitted, students should contact the Specialty Master’s & PhD Center to defer the date. If students wish to postpone their graduation date past the six-year time limit for completion, they must formally petition the PhD Program Development Committee (PDC) for an extension. The petition, which must include the reason(s) for the extension as well as a detailed timetable for completion, is subject to departmental and PDC approval.

PhD degree requirements are complete only when copies of the dissertation have been certified as meeting the standards of Questrom School of Business and have been accepted by Mugar Memorial Library.

Related Bulletin Pages

• Questrom School of Business Courses
• Abbreviations and Symbols

Beyond the Bulletin

• Questrom PhD Program
• Questrom PhD in Mathematical Finance Course Requirements
• Questrom PhD Program Admissions
• Questrom School of Business Undergraduate Program
• Minor in Business Administration & Management
• Minor in Innovation & Entrepreneurship
• Professional Evening MBA (PEMBA)
• Online MBA (OMBA)
• Dual Degree MBA Programs
• MS in Business Analytics
• MS in Management Studies
• MS in Mathematical Finance & Financial Technology
• PhD in Business Administration & Management
• Graduate Certificate in Business Analytics
• Graduate Certificate in Financial Technology
• Academic and Student Resources
• Honorary, Service, and Professional Organizations

Terms of Use

Note that this information may change at any time. Read the full terms of use .

related websites

• Questrom School of Business

Accreditation

Boston University is accredited by the New England Commission of Higher Education (NECHE).

• © Copyright
• Mobile Version

Graduate Education

Office of graduate and postdoctoral education, quantitative and computational finance, program contact.

Laura Czyzewski CODA Georgia Institute of Technology 756 West Peachtree St. NW Atlanta, GA 30308

Application Deadlines

• Early Round - Oct. 15
• Standard Round - Dec. 31
• Final Round for International candidates currently outside the US - March 15
• Final Round for US citizens, permanent residents and International candidates currently in the US - June 1
• Standard Round - Sept. 1
• Final Round - Oct. 1

Admittance Terms

Degree programs.

• Master's, Quantitative and Computational Finance

Interdisciplinary Programs

Quantitative and Computational Finance is offered by the College of Sciences, the College of Engineering, and Scheller College of Business. Students must select a home school from one of the following disciplines:

• Industrial and Systems Engineering
• Mathematics

Standardized Tests

TOEFL Requirements

• Institute Code: 5248
• Internet-based: 95, with minimum section scores of 19

IELTS Academic Requirements

• ≥ 7 (minimum band score for Reading, Listening, and Speaking is 6.5; minimum band score for Writing is 5.5)

GRE Requirements

• Institute Code: R5248
• General Test: Required

GMAT Requirements

• Institute Code: HWK-54-37

Application Requirements

• Three Letters of Recommendation

Program Costs

• Go to " View Tuition Costs by Semester ," and select the semester you plan to start. Graduate-level programs are divided into sections: Graduate Rates–Atlanta Campus, Study Abroad, Specialty Graduate Programs, Executive Education Programs
• Find the degree and program you are interested in and click to access the program's tuition and fees by credit hour PDF.
• In the first column, determine the number of hours (or credits) you intend to take for your first semester.
• Determine if you will pay in-state or out-of-state tuition. Learn more about the difference between in-state and out-of-state . For example, if you are an in-state resident and planning to take six credits for the Master of Architecture degree, the tuition cost will be $4,518.
• The middle section of the document lists all mandatory Institute fees. To see your total tuition plus mandatory fees, refer to the last two columns of the PDF.

The Office of Graduate Education has prepared an admissions checklist to help you navigate through the admissions process.

We've detected unusual activity from your computer network

To continue, please click the box below to let us know you're not a robot.

Why did this happen?

Please make sure your browser supports JavaScript and cookies and that you are not blocking them from loading. For more information you can review our Terms of Service and Cookie Policy .

For inquiries related to this message please contact our support team and provide the reference ID below.

College of Education

Measurement, quantitative methods, & learning sciences doctoral program.

The University of Houston's Measurement, Quantitative Methods, & Learning Sciences (MQM-LS) doctoral program equips students with the skills necessary to design, conduct and interpret quantitative research projects that help solve our society's most difficult problems. Students develop a broad understanding of psychological and learning theories while also receiving strong quantitative methods training. With these skills, our graduates can measure and analyze a wide variety of topics and issues in psychology and education with unique insights. Students received a wide variety of research opportunities within the Department of Psychological, Health, & Learning Sciences; the College of Education and UH. Our mix of quantitative methods training and learning sciences training produces strong candidates ready to compete in a competitive job market.

• PHLS Faculty
• Mission & Values
• Student & Alumni Profiles

About the Program

• 69 hours of minimum required coursework
• 4 years to complete program when enrolled full-time (at least 9 hrs/semester)
• MQM-LS Student Handbook
• MQM-LS Program at a Glance
• Factors Considered in Graduate Admissions and Awarding of Fellowships
• UH Graduate School

What will I learn while attending the MQM-LS program?

MQM-LS students gain knowledge of measurements and quantitative research methods and theoretical foundations in human development and learning theory through:

• Candidacy research project
• Comprehensive Examination Portfolio
• Dissertation

What can I do with my degree?

Upon completion of the program, graduates will be qualified to enter careers in a varity of roles and settings, including:

• University and college professors
• Researchers in Research and Accountability Divisions of public school systems
• Data analysts or research specialists
• Independent consultants

Important MQM-LS Resources

The following is a collection of important program resources:

• American Psychological Association Division 5 (Quantitative and Qualitative Methods)
• American Psychological Association Division 15 (Educational Psychology)
• American Psychological Association Division 45 (The Society for the Psychological Study of Culture, Ethnicity, and Race)
• American Educational Research Association Division C (Learning and Instruction)
• American Educational Research Association Division D (Measurement & Research Methodologies)

MQM-LS Faculty

The following is a list of current mqm-ls faculty:, dr. weihua fan.

Measurement, Quantitative Methods & Learning Sciences

Faculty Profile | Email

Dr. Allison Master

Dr. margit wiesner.

• PHLS Homepage
• Our Programs

The MQM-LS faculty's research seeks to develop and improve research approaches and techniques while applying them to better understanding issues in psychology, education and youth behavior. Visit the PHLS Research Portal to learn more about our diverse interests and discover faculty pursuing answers to the questions that matter to you. 

Feel free to contact faculty directly to learn more about their research. You can find contact information in the Research Portal or by visiting the COE Faculty Directory .

• PHLS Research Portal

Financial Aid

All MQM-LS doctoral students are encouraged to apply for scholarships through the UH and the College of Education. To learn more about how to fund your graduate studies, visit the Graduate Funding page .

Graduate Tuition Fellowship

Graduate Tuition Fellowship (GTF) provides tuition remission for 9 credit hours, during the academic year, to students who enroll in at least 9 credit hours. During the summer term, GTFs are contingent upon available budget. Not all years in the graduate program may be covered by this program.

Assistantships

Graduate appointments are usually available to students during the first two years of graduate studies. The program doesn't cover mandatory fees or course fees. Not all years in the graduate program are covered by this program. 

To learn more about funding your education, contact the COE's College of Graduate Studies at  [email protected]  or call 713-743-7676.

• COE Financial Aid and Scholarships
• UH Graduate Funding
• UH Graduate Financial Information

Houston, Texas

Houston is the fourth largest city in the United States and one of the nation's most diverse cities. This fact benefits our students and faculty both personally and professionally. Home to more than 100 different nationalities and where more than 60 different languages are spoken, Houston is the perfect environment to practice what you're learning in the classroom. The city also boasts more than 12,000 theater seats and 11,000 diverse restaurants featuring cuisines from around the globe (Don't know where to start? Just ask a Houstonian, and they're sure to bombard you with at least a dozen places to eat.) 

Houston is bustling with culture, energy and offers something for everyone inside and outside the classroom.

(Background photo: “ Metropolis ” by eflon is licensed under CC BY 2.0 .)

• Student Housing & Residential Life
• Greater Houston Partnership - Welcome to Houston

Ready to Apply?

Mqm-ls program application deadline: feb. 1 (domestic students), mqm-ls program application deadline: feb. 1 (international students).

Are you ready to apply to the University of Houston MQM-LS doctoral program ? Yes? You can learn more about the application process by visiting the College of Education's Graduate Admissions page  or jump right into the application process by visiting the UH's How to Apply to Graduate School page .

If you need more information about the MQM-LS program, we are here to help. You can always contact the COE Office of Graduate Studies by phone at 713-743-7676  or by email .

The Measurement, Quantitative and Learning Sciences doctoral program is a member of UH's Psychological, Health, & Learning Sciences department .

Program Director:  Dr. Margit Wiesner

UH College of Education Stephen Power Farish Hall 3657 Cullen Blvd., Room 491 Houston, TX 77204-5023

Undergraduate: [email protected] or 713-743-5000 Graduate: [email protected] or 713-743-7676 General: [email protected] or 713-743-5010

Follow along with the video below to see how to install our site as a web app on your home screen.

Note: This feature may not be available in some browsers.

2024 QuantNet Ranking of Best Financial Engineering Programs

The 2024 QuantNet ranking is best positioned to help prospective applicants decide where to apply and enroll in these master quantitative programs.

Baruch College

Princeton university, carnegie mellon university, university of california, berkeley, columbia university, university of chicago, cornell university, new york university, massachusetts institute of technology.

NYU Tandon School of Engineering

Georgia institute of technology, north carolina state university, university of california, los angeles, johns hopkins university, university of washington, rutgers university, university of illinois urbana-champaign, stevens institute of technology, university of minnesota, boston university, fordham university, university of california, san diego.

*Base + sign on bonus (US only) Eligible STEM degree as designated by DHS for the 24 months OPT extension purpose.

• Published 12/12/23
• Page views 4,022,333

Latest reviews

• Yesterday at 10:49 PM

• Ziyuan Kong
• Monday at 9:54 PM

• Monday at 12:11 AM

• Friday at 9:19 PM

Latest tracker

Columbia mfe, stevens mfe, nyu mathfin, columbia mafn, chicago msfm, ncsu finmath enrolled, latest posts.

• Latest: hcccc
• 16 minutes ago

• Latest: Paul Lopez
• 20 minutes ago

• Latest: strattb
• 40 minutes ago

• Latest: kizo
• Today at 10:45 AM

• Latest: yannten
• Today at 10:35 AM

• Latest: Daniel Duffy
• Today at 4:49 AM
• Latest: lam.nguyen
• Yesterday at 10:50 PM

• Latest: MikeLawrence
• Yesterday at 9:20 PM

• Latest: pierreyvessojic
• Yesterday at 4:21 PM
• This site uses cookies to help personalise content, tailor your experience and to keep you logged in if you register. By continuing to use this site, you are consenting to our use of cookies. Accept Learn more…

Financial Mathematics

FinMath's 1st Annual Poker Tournament

Celebrate Eric Liu's (MSFM 2024) big win at our Poker Tournament, proudly sponsored by Chicago Trading Company!

Welcome to Financial Mathematics

A pioneer in its field, our Program offers accelerated, integrated coursework that explores the deep-rooted relationship that exists between theoretical and applied mathematics and the ever-evolving world of finance. Our mission is to equip our students with a solid foundation in mathematics, and in doing so provide them with practical knowledge that they can successfully apply to complicated financial models. Whether you are interested in becoming a full-time student, completing the program in five quarters, or a part-time professional taking one to two courses each quarter, all graduates of the Financial Mathematics program quickly distinguish themselves as leaders in their field; program alumni have gone forth to find success at companies like JP Morgan, UBS, and Goldman Sachs. Read more

Our guiding mission is to make novel and unique contributions to the science of psychology through the development, evaluation, and application of advanced quantitative methodologies. We primarily focus on methods for measuring and modeling individual behavior, particularly when assessed repeatedly over time. We also strive to meaningfully embed our quantitative and methodological work within the broad realm of the psychological sciences.

Please explore the resources we provide here for more details about our research, teaching, and service missions, and contact us if you have any additional questions.

Diversity and Inclusion

The Quantitative Psychology Program in the Department of Psychology and Neuroscience at the University of North Carolina Chapel Hill supports the University’s core values encouraging diversity and equal educational and employment opportunities throughout our community. We unequivocally denounce racism and other forms of hateful and discriminatory behavior with regard to culture, ethnicity, gender, sexual orientation, socioeconomic status, and age, among others. We are strongly committed to promoting diversity in our program as we consider an ideal scientific community to be one that includes a diverse representation of individuals at all academic levels. We are especially committed to training early career scientists of diverse backgrounds, and we encourage students from backgrounds historically underrepresented in the sciences to apply, including but not limited to BIPOC, LGBTQIA+, first generation college students, and those of low socioeconomic status. Our views reflect University policy as reflected the UNC Policy on Prohibited Discrimination, Harassment and Related Misconduct and the policy of University Office for Diversity and Inclusion . Please also see the Code of Conduct [PDF] for members of our Program, approved by the Equal Opportunity and Compliance Office at UNC .

Serving technical professionals globally for over 75 years. Learn more about us.

MIT Professional Education 700 Technology Square Building NE48-200 Cambridge, MA 02139 USA

Accessibility

Real Estate Finance: Advanced - Live Virtual

Walter Torous

Enhance your ability to analyze the financial risks and opportunities of today's real estate marketplace by leveraging quantitative analytics techniques taught in popular MIT graduate courses. Over the course of two accelerated days, you’ll master common real estate financial analysis methods, acquire new approaches for financial modeling, and assess cutting-edge quantitative tools for managing portfolio risk. 

THIS COURSE MAY BE TAKEN INDIVIDUALLY OR AS PART OF THE  PROFESSIONAL CERTIFICATE PROGRAM IN REAL ESTATE FINANCE & DEVELOPMENT .

Real estate investment markets, like other markets and the underlying economy, face times perhaps more uncertain than any in over a generation. Crises ranging from climate change to migration to pandemics raise questions for real estate investors. To be successful in today's uncertain market, commercial real estate industry participants need at least some familiarity with not only the basics, but also some more advanced and cutting-edge real estate financial analysis techniques, approaches to financial modeling, newly available real estate data sources, and quantitative tools available to manage portfolio risk. 

This course provides insights into analyzing the investment risks and opportunities in today's marketplace by utilizing quantitative analytics taught in popular graduate courses at MIT. Current real estate investment market dynamics and trends, possible developments in securitization and derivatives, example transactions and identification of the most active capital sources will also be discussed.

This course has been approved for 16 CPD credits toward renewal of the  CoreNet Global  MCR designation.

Certificate of Completion from MIT Professional Education

• Understand fundamental financial economic concepts and tools as applied to real estate investment.
• Become conversant with the cutting-edge of real estate investment, relevant for institutional investment management.
• Understand the basics of real estate risk management techniques and products.

Program Outline

The course runs 9:00 am – 5:00 pm Tuesday-Wednesday. Please note all times are US Eastern Daylight Time. Schedule is subject to change.

TOPICS WILL INCLUDE:

Portfolio Theory & Real Estate

Classical Mean-Variance Optimization and the Risk Parity simplification applied to the mixed asset (total wealth) portfolio implications for real estate.

Commercial Real Estate Investing & Portfolio Construction

Institutional real estate investment industry, portfolio foundations, and top-down/bottom-up strategies.

Introduction to Derivatives

Gain an understanding of the most fundamental or derivative contracts including forwards, swaps, and options.

Hedging Real Estate Risk

Using derivatives and other financial contracts to minimize risks associated with real estate investment.

Sruyvesant Town Case Discussion

Discussion of one of the largest and most complex private real estate investment deals in history.

Private Equity in Real Estate

This session will cover the nature of private equity investment in real estate and discussion of current best practices.

CRE Price Index Based Derivatives

Concept and possibility for synthetic investment, revolution of the industry.

Industry Academic Panel

Exploration of Real Estate capital market innovations.

Other Instructors

• Mark Roberts
• Alexander van de Minne
• Manish Srivastava
• Robert M. White, Jr.

This course is applicable to a wide range of professionals across the real estate, banking, finance/investment, and insurance industries. Specifically, the course may be of interest to analysts and investment professionals, fund managers, investment portfolio managers, financial advisors, investment bankers, fixed-income analysts, financial risk managers, global financial market specialists, and professionals working in macroeconomic policy. More generally, this class can be valuable to anyone dealing with global financial markets and real estate investments.

Requirements

Laptops or tablets are required to access course materials. All materials will be distributed electronically.

Testimonials

The type of content you will learn in this course, whether it's a foundational understanding of the subject, the hottest trends and developments in the field, or suggested practical applications for industry.

How the course is taught, from traditional classroom lectures and riveting discussions to group projects to engaging and interactive simulations and exercises with your peers.

What level of expertise and familiarity the material in this course assumes you have. The greater the amount of introductory material taught in the course, the less you will need to be familiar with when you attend.

RIT graduate pursues Ph.D. across time zones

Nastaran Nagshineh, center, defended her Ph.D. thesis at RIT in April. Faculty from RIT’s Rochester and Dubai campuses served on her thesis committee and include, from left to right, Kathleen Lamkin-Kennard, Steven Weinstein, Nathaniel Barlow, and David Kofke (a professor at the University at Buffalo). Mohamed Samaha participated remotely and appears on the video screen behind the group and alongside Nagshineh’s picture.

Nastaran Nagshineh is one of the first Ph.D. candidates to bridge RIT’s Rochester and Dubai campuses. Her accomplishment creates a path for future students at the university’s international campuses.

Nagshineh completed her Ph.D. in mathematical modeling while working full time as a mathematics lecturer at RIT Dubai in the United Arab Emirates, teaching as many as five classes a semester. She described her Ph.D. journey as “an exercise in perseverance” due to competing demands and long days. Rochester is eight hours behind Dubai, and the time difference meant many late-night classes and meetings.

“I saw this collaboration as an opportunity, rather than as a challenge, because my primary adviser, Dr. Steven Weinstein (RIT professor of chemical engineering), and my co-adviser, Dr. Mohamed Samaha (RIT Dubai associate professor of mechanical engineering), both have the same area of research interest,” she said. “They both worked toward my success.”

Nagshineh is one of 67 RIT Ph.D. students who defended their thesis this academic year and who will earn their doctorate. RIT awarded 63 Ph.D. degrees in 2023.

In 2020-2021, RIT’s Graduate School met and surpassed the university’s goal of conferring 50 Ph.D. degrees during an academic year. That number will continue to grow as students cycle through the seven new Ph.D. programs that RIT has added since 2017, said Diane Slusarski , dean of RIT’s Graduate School.

Meeting these goals puts RIT on a path toward achieving an “R1,” or research-intensive designation, from the Carnegie Classification of Institutions of Higher Learning. RIT is currently ranked as an R2 institution . Many factors go into changing a university’s status, including research investment and maintaining a three-year average of 70 Ph.D. degrees awarded per year, according to Slusarski.

“We have met the goals of the strategic plan, and now we look forward to contributing to the research innovation in the future,” Slusarski said. “We want to help the new programs thrive and win national research awards.”

RIT’s emphasis on high-level research is seen in Nagshineh’s Ph.D. work. She applies mathematical modeling to the field of fluid dynamics. Her research has been published in top-tier journals and has gained notice, said Weinstein, her thesis adviser.

Weinstein describes Nagshineh’s accomplishments as “a testament to a fantastic work ethic and commitment” and is inspirational to younger students at Rochester and Dubai.

“The collaboration between RIT Dubai/Rochester has continued,” he said. “Another paper was submitted a few weeks ago with Mohamed Samaha and Nate Barlow (RIT associate professor in the School of Mathematics and Statistics) as co-authors, as well as Cade Reinberger, a younger Ph.D. student in my research group.”

Mathematical modeling is one of RIT’s newer Ph.D. degree programs, and Nagshineh is among its earliest graduates. The program has doubled in size since it began accepting students in 2017, Slusarski said. This past fall, the mathematical modeling program had 35 students, with two graduating this year.

Altogether, RIT has 13 Ph.D. degree programs currently enrolling 438 students, with computing and information sciences accounting for the largest with 117 students. RIT’s other Ph.D. programs include astrophysical sciences and technology , biomedical and chemical engineering , business administration , color science , electrical and computer engineering, imaging science , mechanical and industrial engineering , microsystems engineering , and sustainability .

New programs in cognitive science and physics will launch in the fall.

The growth in RIT graduate education—with more than 3,000 master’s and doctoral students—reflects a demographic change in the student population, Slusarski said. “We have a higher percentage of women in the graduate programs than we have for RIT undergraduate programs.”

RIT’s graduate programs enroll 42 percent women, according to Christie Leone , assistant dean for the Graduate School.

Nagshineh, who also holds an MS in electrical engineering from RIT Dubai, welcomes her role as a mentor to other women students on both campuses.

“As a young woman in an Arabic country, the power of women is often underestimated and undervalued, and I hope to serve as a role model to female students, especially those that question their path,” Nagshineh said.

She plans to continue in her career as a professor and a researcher. “I would like to pursue a research program where I can advise my own students and teach them more deeply.”

Recommended News

May 15, 2024

RIT researchers expect a rise in deepfake use in political campaigns   

Spectrum News interviews Christopher Schwartz, research scientist in the Department of Cybersecurity, and Kelly Wu, computing and information sciences Ph.D. student, about generating and detecting artificial intelligence deepfakes.

RIT and Synapse VP launch immersive LA program training the next generation in cutting-edge virtual production techniques

RIT is offering a groundbreaking partnership with Synapse Virtual Production (Synapse VP) to deliver an exclusive in-person Virtual Production (VP) immersion course in Los Angeles through RIT Certified.

May 14, 2024

Vatican conference on ‘climate resilience’ is the latest in a long line of environment initiatives by Pope Francis and the Catholic Church   

The Conversation features an article co-authored by Lawrence Torcello, associate professor in the Department of Philosophy, about a global conference emphasizing climate resilience and drawing on Catholic teachings and Pope Francis' advocacy, hosted by the Vatican.

Researchers introduce new way to study, help prevent landslides   

Prevention Web highlights a study co-authored by Nishant Malik, assistant professor in the School of Mathematics and Statistics, about developing a new method using machine learning to accurately predict landslide movements, aiding global risk assessment efforts.

PhD Proposal: On Quantum Query Complexity, Divide-and-Conquer, and Regular Languages

Our recent work investigated the use of divide-and-conquer strategies in the design of quantum query algorithms. Following a brief review of these findings, this talk will focus on ongoing work aimed at strengthening one of our earlier results. In particular, we will propose a randomized quantum query algorithm for checking membership in a specific regular language. The analysis of this algorithm will be discussed, with an emphasis on some of the technical details. We conclude with some of the potential implications of our research. Specifically, we will briefly discuss how we hope to strengthen a result of Aaronson, Grier and Schaeffer on the query complexity of star-free regular languages.

Follow Puck Worlds online:

• Follow Puck Worlds on Twitter

Site search

Filed under:

• Kontinental Hockey League

Gagarin Cup Preview: Atlant vs. Salavat Yulaev

Share this story.

• Share this on Facebook
• Share this on Twitter
• Share this on Reddit
• Share All sharing options

Share All sharing options for: Gagarin Cup Preview: Atlant vs. Salavat Yulaev

Gagarin cup (khl) finals:  atlant moscow oblast vs. salavat yulaev ufa.

Much like the Elitserien Finals, we have a bit of an offense vs. defense match-up in this league Final.  While Ufa let their star top line of Alexander Radulov, Patrick Thoresen and Igor Grigorenko loose on the KHL's Western Conference, Mytischi played a more conservative style, relying on veterans such as former NHLers Jan Bulis, Oleg Petrov, and Jaroslav Obsut.  Just reaching the Finals is a testament to Atlant's disciplined style of play, as they had to knock off much more high profile teams from Yaroslavl and St. Petersburg to do so.  But while they did finish 8th in the league in points, they haven't seen the likes of Ufa, who finished 2nd. 

This series will be a challenge for the underdog, because unlike some of the other KHL teams, Ufa's top players are generally younger and in their prime.  Only Proshkin amongst regular blueliners is over 30, with the work being shared by Kirill Koltsov (28), Andrei Kuteikin (26), Miroslav Blatak (28), Maxim Kondratiev (28) and Dmitri Kalinin (30).  Oleg Tverdovsky hasn't played a lot in the playoffs to date.  Up front, while led by a fairly young top line (24-27), Ufa does have a lot of veterans in support roles:  Vyacheslav Kozlov , Viktor Kozlov , Vladimir Antipov, Sergei Zinovyev and Petr Schastlivy are all over 30.  In fact, the names of all their forwards are familiar to international and NHL fans:  Robert Nilsson , Alexander Svitov, Oleg Saprykin and Jakub Klepis round out the group, all former NHL players.

For Atlant, their veteran roster, with only one of their top six D under the age of 30 (and no top forwards under 30, either), this might be their one shot at a championship.  The team has never won either a Russian Superleague title or the Gagarin Cup, and for players like former NHLer Oleg Petrov, this is probably the last shot at the KHL's top prize.  The team got three extra days rest by winning their Conference Final in six games, and they probably needed to use it.  Atlant does have younger regulars on their roster, but they generally only play a few shifts per game, if that. 

The low event style of game for Atlant probably suits them well, but I don't know how they can manage to keep up against Ufa's speed, skill, and depth.  There is no advantage to be seen in goal, with Erik Ersberg and Konstantin Barulin posting almost identical numbers, and even in terms of recent playoff experience Ufa has them beat.  Luckily for Atlant, Ufa isn't that far away from the Moscow region, so travel shouldn't play a major role. 

I'm predicting that Ufa, winners of the last Superleague title back in 2008, will become the second team to win the Gagarin Cup, and will prevail in five games.  They have a seriously well built team that would honestly compete in the NHL.  They represent the potential of the league, while Atlant represents closer to the reality, as a team full of players who played themselves out of the NHL. 

• Atlant @ Ufa, Friday Apr 8 (3:00 PM CET/10:00 PM EST)
• Atlant @ Ufa, Sunday Apr 10 (1:00 PM CET/8:00 AM EST)
• Ufa @ Atlant, Tuesday Apr 12 (5:30 PM CET/12:30 PM EST)
• Ufa @ Atlant, Thursday Apr 14 (5:30 PM CET/12:30 PM EST)

Games 5-7 are as yet unscheduled, but every second day is the KHL standard, so expect Game 5 to be on Saturday, like an early start. 

Loading comments...

• Yekaterinburg
• Novosibirsk
• Vladivostok

• Tours to Russia
• Practicalities
• Russia in Lists

Rusmania • Deep into Russia

Out of the Centre

Savvino-storozhevsky monastery and museum.

Zvenigorod's most famous sight is the Savvino-Storozhevsky Monastery, which was founded in 1398 by the monk Savva from the Troitse-Sergieva Lavra, at the invitation and with the support of Prince Yury Dmitrievich of Zvenigorod. Savva was later canonised as St Sabbas (Savva) of Storozhev. The monastery late flourished under the reign of Tsar Alexis, who chose the monastery as his family church and often went on pilgrimage there and made lots of donations to it. Most of the monastery’s buildings date from this time. The monastery is heavily fortified with thick walls and six towers, the most impressive of which is the Krasny Tower which also serves as the eastern entrance. The monastery was closed in 1918 and only reopened in 1995. In 1998 Patriarch Alexius II took part in a service to return the relics of St Sabbas to the monastery. Today the monastery has the status of a stauropegic monastery, which is second in status to a lavra. In addition to being a working monastery, it also holds the Zvenigorod Historical, Architectural and Art Museum.

Belfry and Neighbouring Churches

Located near the main entrance is the monastery's belfry which is perhaps the calling card of the monastery due to its uniqueness. It was built in the 1650s and the St Sergius of Radonezh’s Church was opened on the middle tier in the mid-17th century, although it was originally dedicated to the Trinity. The belfry's 35-tonne Great Bladgovestny Bell fell in 1941 and was only restored and returned in 2003. Attached to the belfry is a large refectory and the Transfiguration Church, both of which were built on the orders of Tsar Alexis in the 1650s.  

To the left of the belfry is another, smaller, refectory which is attached to the Trinity Gate-Church, which was also constructed in the 1650s on the orders of Tsar Alexis who made it his own family church. The church is elaborately decorated with colourful trims and underneath the archway is a beautiful 19th century fresco.

Nativity of Virgin Mary Cathedral

The Nativity of Virgin Mary Cathedral is the oldest building in the monastery and among the oldest buildings in the Moscow Region. It was built between 1404 and 1405 during the lifetime of St Sabbas and using the funds of Prince Yury of Zvenigorod. The white-stone cathedral is a standard four-pillar design with a single golden dome. After the death of St Sabbas he was interred in the cathedral and a new altar dedicated to him was added.

Under the reign of Tsar Alexis the cathedral was decorated with frescoes by Stepan Ryazanets, some of which remain today. Tsar Alexis also presented the cathedral with a five-tier iconostasis, the top row of icons have been preserved.

Tsaritsa's Chambers

The Nativity of Virgin Mary Cathedral is located between the Tsaritsa's Chambers of the left and the Palace of Tsar Alexis on the right. The Tsaritsa's Chambers were built in the mid-17th century for the wife of Tsar Alexey - Tsaritsa Maria Ilinichna Miloskavskaya. The design of the building is influenced by the ancient Russian architectural style. Is prettier than the Tsar's chambers opposite, being red in colour with elaborately decorated window frames and entrance.

At present the Tsaritsa's Chambers houses the Zvenigorod Historical, Architectural and Art Museum. Among its displays is an accurate recreation of the interior of a noble lady's chambers including furniture, decorations and a decorated tiled oven, and an exhibition on the history of Zvenigorod and the monastery.

Palace of Tsar Alexis

The Palace of Tsar Alexis was built in the 1650s and is now one of the best surviving examples of non-religious architecture of that era. It was built especially for Tsar Alexis who often visited the monastery on religious pilgrimages. Its most striking feature is its pretty row of nine chimney spouts which resemble towers.

Plan your next trip to Russia

Ready-to-book tours.

Your holiday in Russia starts here. Choose and book your tour to Russia.

The Unique Burial of a Child of Early Scythian Time at the Cemetery of Saryg-Bulun (Tuva)

<< Previous page

Pages:  379-406

In 1988, the Tuvan Archaeological Expedition (led by M. E. Kilunovskaya and V. A. Semenov) discovered a unique burial of the early Iron Age at Saryg-Bulun in Central Tuva. There are two burial mounds of the Aldy-Bel culture dated by 7th century BC. Within the barrows, which adjoined one another, forming a figure-of-eight, there were discovered 7 burials, from which a representative collection of artifacts was recovered. Burial 5 was the most unique, it was found in a coffin made of a larch trunk, with a tightly closed lid. Due to the preservative properties of larch and lack of air access, the coffin contained a well-preserved mummy of a child with an accompanying set of grave goods. The interred individual retained the skin on his face and had a leather headdress painted with red pigment and a coat, sewn from jerboa fur. The coat was belted with a leather belt with bronze ornaments and buckles. Besides that, a leather quiver with arrows with the shafts decorated with painted ornaments, fully preserved battle pick and a bow were buried in the coffin. Unexpectedly, the full-genomic analysis, showed that the individual was female. This fact opens a new aspect in the study of the social history of the Scythian society and perhaps brings us back to the myth of the Amazons, discussed by Herodotus. Of course, this discovery is unique in its preservation for the Scythian culture of Tuva and requires careful study and conservation.

Keywords: Tuva, Early Iron Age, early Scythian period, Aldy-Bel culture, barrow, burial in the coffin, mummy, full genome sequencing, aDNA

Information about authors: Marina Kilunovskaya (Saint Petersburg, Russian Federation). Candidate of Historical Sciences. Institute for the History of Material Culture of the Russian Academy of Sciences. Dvortsovaya Emb., 18, Saint Petersburg, 191186, Russian Federation E-mail: [email protected] Vladimir Semenov (Saint Petersburg, Russian Federation). Candidate of Historical Sciences. Institute for the History of Material Culture of the Russian Academy of Sciences. Dvortsovaya Emb., 18, Saint Petersburg, 191186, Russian Federation E-mail: [email protected] Varvara Busova  (Moscow, Russian Federation).  (Saint Petersburg, Russian Federation). Institute for the History of Material Culture of the Russian Academy of Sciences.  Dvortsovaya Emb., 18, Saint Petersburg, 191186, Russian Federation E-mail:  [email protected] Kharis Mustafin  (Moscow, Russian Federation). Candidate of Technical Sciences. Moscow Institute of Physics and Technology.  Institutsky Lane, 9, Dolgoprudny, 141701, Moscow Oblast, Russian Federation E-mail:  [email protected] Irina Alborova  (Moscow, Russian Federation). Candidate of Biological Sciences. Moscow Institute of Physics and Technology.  Institutsky Lane, 9, Dolgoprudny, 141701, Moscow Oblast, Russian Federation E-mail:  [email protected] Alina Matzvai  (Moscow, Russian Federation). Moscow Institute of Physics and Technology.  Institutsky Lane, 9, Dolgoprudny, 141701, Moscow Oblast, Russian Federation E-mail:  [email protected]

Shopping Cart Items: 0 Cart Total: 0,00 € place your order

Price pdf version

student - 2,75 € individual - 3,00 € institutional - 7,00 €

Copyright В© 1999-2022. Stratum Publishing House