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Advanced Algorithmic Trading And Portfolio Management

By Prof. Abhinava Tripathi   |   IIT Kanpur
Learners enrolled: 9475   |  Exam registration: 380
ABOUT THE COURSE:
Over the next few decades, machine-learning (ML) and AI will transform not only the finance industry but also other industries that borrow significantly from finance. This program has been carefully designed to help future analysts, traders, brokers, consultants and other industry professionals who are either currently exposed to, or foresee artificial intelligence, machine-learning and data science proliferate their work environment. The operating environment for investment management firms continues to evolve, with technological innovations and shifting investor preferences at the heart of this change. In that context, Artificial Intelligence (AI) is providing new opportunities to both professionals and investors. Portfolio management (e.g., mutual funds) industry is at the forefront of this transformation. The objective of this course is to help the students familiarize with advanced concepts related to risk management with portfolios, in the backdrop of Artificial Intelligence and Machine Learning techniques in financial markets, trading, and asset management. This program aims to demonstrate the applications of modern portfolio construction and optimization techniques. This includes solving real-life wealth management problems to improve investment decisions.

INTENDED AUDIENCE: Management students (Ph.D. and MBA), Commerce students (B.Com., M.Com.), Chartered Accountants, Finance professionals (Investment analysts, banking professionals, accountants, credit analysts), Engineering graduates

INDUSTRY SUPPORT: Financial Analytics, Data Science & Data Analytics, Business Analytics, Banking & Financial Services, Consulting and Advisory firms, Investment Banks
Summary
Course Status : Completed
Course Type : Elective
Language for course content : English
Duration : 8 weeks
Category :
  • Management Studies
Credit Points : 2
Level : Undergraduate/Postgraduate
Start Date : 24 Jul 2023
End Date : 15 Sep 2023
Enrollment Ends : 07 Aug 2023
Exam Registration Ends : 21 Aug 2023
Exam Date : 24 Sep 2023 IST

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.


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Course layout

Week 1: Introduction to R Programming, R Fundamentals, Basic mathematical and logical operations with R, working with different data-types in R, wrangling with dataframes, Exploratory data analysis and data visualization with R. 
Week 2: Introduction to Portfolio Construction : Risk-return framework in financial markets, risk diversification with portfolios, portfolio optimization in mean-variance framework, concept of market risk and beta, Portfolio Possibility curve, Efficient frontier, Minimum Variance portfolios, Introduction to risk-free lending and borrowing
Week 3: Asset Pricing Models: Capital Asset Pricing Model (CAPM), Capital Market Line, Security Market Line, Fallings of CAPM, Single-Index and Multi-Index models, Expected Risk and Return with Index models, 3-Factor Fama-French Model
Week 4: Portfolio Management and Performance Evaluation: Portfolio Management strategies, Active vs Passive Portfolio Management, Value vs Growth investing, One-parameter performance measures Timing & Selection performance measures, application of asset pricing models in performance management
Week 5: Introduction to Algorithmic Trading: Technical analysis and trend determination, Dow Theory, Moving averages, Momentum indicators, Classical price patterns.
Week 6: Advanced time-series regression algorithms: ARMA/ARIMA models,  Mean reverting trading strategies with vector error correction models and cointegration, model risk management, back testing, model validation, and stress testing with R
Week 7: Advanced time-series algorithms for financial risk-management: Value-at-risk, Expected Shortfall, ARCH/GARCH models, implementation with R
Week 8: Advanced topics: Alternative versions of CAPM, Delineating Efficient Frontier,  Performance Evaluation with Multi-index models, Portfolio construction, optimization, back-testing, and visualization with R

Books and references

1. Machine Learning in Finance by M. Dixon, I Halperin, and P. Bilokon, Springer, 1st Edition
2. Advances in Financial Machine Learning, Marcos Lopez, Wiley, 1st Edition
3. Machine Learning for Asset Managers, Marcos Lopez, Cambridge University Press, 1st Edition
4. Machine Learning for Algorithmic Trading, Stefan Jansen, 2nd Edition, Packt
5. Elton & Gruber, “Modern Portfolio Theory”, Wiley, 9th Edition
6. Reilly, Frank,K., “Investment Analysis and Portfolio Management,” 5th Edition, Dryden.

Instructor bio

Prof. Abhinava Tripathi

IIT Kanpur
Prof. Abhinava Tripathi is a Faculty of Finance and Accounting at IME, Indian Institute of Technology, Kanpur. Previously, he was working at DOMS, IIT Roorkee. He has completed his Ph.D. degree from Indian Institute of Management, Lucknow. He has done his B-Tech. from Indian Institute of Technology, Roorkee and MBA from Indian Institute of Management, Kozhikode. He has more than 5 years of industry experience in investment banking, corporate banking, credit rating, and project finance advisory firms. His current research focuses on the subject of market-microstructure and liquidity in global financial markets. Prof. Abhinava Tripathi has published research papers in international refereed journals, including the Journal of Asset Management, Studies in Economics and Finance, Finance Research Letters, and Managerial Finance, Applied Economics, International Review of Economics and Finance.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.
The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
Date and Time of Exams: 24 September 2023 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 6 assignments out of the total 8 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Kanpur .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team


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