Part-time Research Associate / Assistant I/II / Technical Assistant (Projec at Open University of Hong Kong

, Hong Kong, China -

Full Time

Start Date

Immediate

Expiry Date

09 Jun, 26

Salary

0.0

Posted On

11 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Collation, Volatility Estimation, Statistical Analysis, Econometric Analysis, Futures Research, Options Research, Large Database Manipulation, Empirical Investigation, Time-Series Analysis, Cross-Sectional Analysis

Industry

Higher Education

Description

Founded in 1989, Hong Kong Metropolitan University (HKMU) is a modern, vibrant and dynamic university. We tailor our professional programmes to adapt to market trends and meet industry needs, thus providing our students with quality professional education and clear career paths. Being the first University of Applied Sciences (UAS) in Hong Kong, we pledge to play a pioneering role in enhancing recognition of vocational and professional education and training, and nurturing talents with both applied skills and knowledge. As a faculty-driven, student-centred university in support of innovative teaching and learning, strategic research, and stakeholder outreach to provide maximum benefit to our communities, we conduct research that advances knowledge and enhances teaching, focusing on strategic areas, including digital humanities and literature, international business, gerontechnology, personalised care, smart city, open and innovative education, and bilingual learning and teaching. HKMU is becoming an ever more vital link in addressing and helping Hong Kong to solve many difficult challenges – as part of our involvement in, and commitment to, the ‘metropolis’ of Hong Kong. Our plans to expand into the Greater Bay Area (GBA) will also cultivate talent to serve Hong Kong and the wider metropolitan GBA. For more information about the University, please visit https://www.hkmu.edu.hk. We are now looking for a suitable person to fill the following position in the Lee Shau Kee School of Business and Administration: Major Duties and Responsibilities The appointee will be responsible mainly for the following: Collate high-frequency data extracted from the continuous bid-ask quotes of index futures and options data; Estimate the realized volatility for arbitrary time intervals on each trading day over a 25-year period using various approximation techniques; Conduct cross-sectional and time-series statistical and econometric analysis of the realized volatility; and Produce tables and diagrams to present the research findings. Candidates Candidates should possess the following qualifications, experience, and competence: A Ph.D. degree in finance and/or mathematics; Experience in futures and options research; Experience in manipulating a large database that contains continuous options and futures data; Experience in conducting empirical investigations with statistical and econometric models; and Publication record in the field of finance and/or mathematics is preferred. Terms and Conditions for Appointment Successful candidate will be appointed on a temporary part-time contract in April 2026. Benefits will be provided in accordance with the statutory provisions. To Apply Candidates who are interested in joining us may submit their applications via the University’s eRecruitment System. The personal data collected will be used for the purpose of considering your application for employment. For details, please refer to the “Personal Data (Privacy) Notice for Job Applicant” on the University’s website. If you are not contacted by the University within eight weeks from the closing date of application, you may assume that your application was unsuccessful.

Responsibilities

The appointee will be primarily responsible for collating high-frequency data from index futures and options quotes, estimating realized volatility over 25 years using various techniques, and conducting statistical and econometric analysis on the results. This includes producing tables and diagrams to present the research findings.