数量金融理学硕士

具有经济学，金融或STEM（科学，技术，工程和数学）学科教育背景且具有公认的定量人才的有抱负的学生将非常适合此课程。本课程涵盖与金融市场的数学建模以及金融证券的定价和对冲有关的广泛主题。本课程为您提供从事定量金融职业所需的必要的理论，数学和计算技能。如果您是一名有竞争力的学生，正在寻找可以充分利用您的定量才能的金融职业，那么这就是您的课程。对于希望进一步探索该学科理论层面的毕业生，课程内容为博士学位提供了完美的基础。在金融。该课程被国际专业风险管理者协会（PRMIA）授予“风险管理认证”，确认该课程适合于
The MSc in Quantitative Finance provides a rigorous grounding across a wide range of mathematical modelling methods and techniques for financial markets. From the pricing and hedging of financial securities to managing the risk in portfolios of equity, fixed income and derivative securities. A challenging programme, it equips students with the necessary theoretical, mathematical and computational skills needed to pursue a rewarding career in finance. Ambitious students with an educational background in Economics, Finance or STEM (Science, Technology, Engineering, and Mathematics) subjects and with a proven quantitative talent will be ideally suited to this programme. For graduates wishing to pursue further the theoretical dimension to the discipline, the curriculum content also provides the perfect basis for a Ph.D. in Finance.<br><br>The course was awarded Risk Management Accreditation by the Professional Risk Managers International Association (PRMIA), confirming the suitability of the course for preparing graduates for a career as professional risk managers. Graduating students obtain exemptions to PRMIA level 1 and 2 exams.<br><br>The programme can be undertaken on a full-time or part-time basis. The part-time option enables current professionals with the relevant background to combine working life with study, however this is dependent on students employment commitments. Note that this is not a dedicated part-time programme and that part-time students will be required to attend lectures, tutorials and complete group assignments in conjunction with the full-time cohort, for whom the schedule is primarily during working hours for a block of hours on several days a week. Modules in autumn trimester will be delivered in a compressed format meaning that modules are taught intensively over two 6 week periods, requiring additional attendance at lectures and tutorials. Employer support is therefore essential.<br><br>12 Months