The application of the concepts and methods of financial engineering is a key component of contemporary investment finance. Financial Engineering, or quantitative finance as it is also known, is a multidisciplinary field that applies theories from financial economics, physics, mathematics, probability, statistics, operations research, and econometrics to solve problems in investment finance using the techniques and tools of engineering.
Because of their skill with coding and capacity to model financial data to aid in improved decision-making, quants are among the most in-demand professions on the market.
The Financial Engineering Course at IIQF places an emphasis on how technical tools may handle particular market difficulties, while also training you to spot inefficiencies, spot opportunities, and create novel new products. The Financial Engineering Course also takes into account the systemic character of financial markets and prepares you for the difficulties of operating in sizable, linked systems.
Interactive online lectures:
Students can pursue their career and personal goals while still studying at their own speed with IIQF's online financial engineering course. Professionals can acquire advanced knowledge and skills to advance their professions.
Students can expect to study through both pre-recorded and live interactive lectures. The course enables students to engage in focused debate and dialogue with instructors.
Being time-responsible is a crucial requirement for success in an online course. Students must set aside time to attend lectures, participate in class discussions, and take exams in addition to their other obligations. Self-motivation is a necessary quality for successful online learners.
Course content:
Optional primers include Introduction to Investment Finance, Introduction to Financial Mathematics, Introduction to Probability & Statistics, and Introduction to Programming (Python).
Basic stochastic processes, Brownian motion, stochastic calculus, and Black-Scholes-Merton models are all terms used in probability theory.
Artificial Intelligence for Quantitative Finance Theoretical and practical Python implementation of Monte Carlo simulation methods and numerical methods for partial differential equations.
Calculation of the Value of Equity, Interest Rate, Currency, and Credit Derivatives Swaps requires a thorough understanding of the concepts and instructions in Python modeling and application. Coverage of market risk, credit risk, operational risk, compliance risk, and other financial risk management topics using both theoretical and practical modeling.
Career opportunities:
For individuals with academic backgrounds in engineering, mathematics, and other numerical specializations, the Financial Engineering course has opened up very exciting and profitable job options in the field of Quantitative Investment Management. In addition to the intellectually engaging difficulties that professions in this field offer to those with mathematical skills, it goes without saying that the pay is pretty good.
Candidates who successfully complete the course are prepared for careers as quantitative investment managers or quantitative analysts in financial institutions such as investment banks, hedge funds, private equity firms, large broking houses, investment research and analytics organizations, etc.
Faculty:
The course is taught by highly regarded Quant practitioners and academics in Quantitative Finance, with backgrounds from some of the top universities in the world, including Stanford (USA), Columbia (USA), London Business School, IIM, IIT, ISI, and more. These individuals have worked with the top global investment banks and firms in New York, London, Singapore, Sydney, and other cities.
Admissions procedure is straightforward:
- Submit Your Application
- Make a call to a counselor.
- Await application approval
- Join the upcoming batch after paying the fee.
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