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Martin Haugh and Garud Iyengar
Financial Engineering is a multidisciplinary field involving finance and economics, mathematics, statistics, engineering and computational methods. The emphasis of FE & RM Part II will be on the use of simple stochastic models to (i) solve portfolio...
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Financial Engineering is a multidisciplinary field involving finance and economics, mathematics, statistics, engineering and computational methods. The emphasis of FE & RM Part II will be on the use of simple stochastic models to (i) solve portfolio optimization problems (ii) price derivative securities in various asset classes including equities and credit and (iii) consider some advanced applications of financial engineering including algorithmic trading and the pricing of real options. We will also consider the role that financial engineering played during the financial crisis. We hope that students who complete the course and the prerequisite course (FE & RM Part I) will have a good understanding of the "rocket science" behind financial engineering. But perhaps more importantly, we hope they will also understand the limitations of this theory in practice and why financial models should always be treated with a healthy degree of skepticism.
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Explores advanced applications of financial engineering, such as algorithmic trading and real options pricing, which are highly relevant to industry
Builds a strong foundation for intermediate learners by covering portfolio optimization, derivative pricing, and advanced financial engineering concepts
Taught by Martin Haugh and Garud Iyengar, recognized for their work in financial engineering
Develops technical skills in financial engineering, including mathematical modeling, statistical analysis, and computational methods
Advises students to complete the prerequisite course (FE & RM Part I) before taking this course
Requires students to have a strong background in finance, economics, mathematics, and programming

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Reviews summary

Challenging course: financial engineering part ii

Financial Engineering and Risk Management Part II is a challenging yet rewarding course that delve into advanced concepts in the field. Students will appreciate the in-depth explanations and well-designed material. However, some may find the pace and lack of clear explanations in some modules to be a drawback.
Course provides in-depth knowledge in financial engineering.
"Very Deep lectures"
"In-depth content and well-supported forum."
"This course covers the principles very well."
Course is challenging but offers valuable content.
"Tough but good!"
"Excellent course material, well taught and challenging quiz assignments."
"Challenging and complete."
Course moves at a fast pace.
"Some weeks lacked references (text books), and in some lectures the instructor went about quick recitals of the mathematical formulas without any insights or intuition."
"The instructors also seemed knowledgeable (the second star), but appeared to be always in a hurry."
Explanations could be improved.
"Explanation could have been a little bit better in some modules."
"The presenter is only reading the slides."
"Teacher doesn't explain the material, just reads from the slides."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Financial Engineering and Risk Management Part II with these activities:
Organize and review course materials
Regularly organizing and reviewing course materials enhances retention, improves understanding, and aids in exam preparation.
Show steps
  • Review lecture notes, textbooks, and other course materials regularly.
  • Organize notes and materials using a preferred system (e.g., digital note-taking apps, physical binders).
  • Summarize key concepts and formulas for quick reference.
  • Identify areas where further clarification or practice is needed.
Review basic probability and statistics concepts
Refreshing basic probability and statistics concepts provides a strong foundation for understanding financial engineering models.
Browse courses on Probability
Show steps
  • Review lecture notes or textbooks covering probability and statistics.
  • Practice solving problems related to probability distributions, random variables, and statistical inference.
  • Complete online quizzes or exercises to test understanding.
  • Seek clarification from instructors or peers if needed.
Attend industry conferences and meetups
Networking events provide opportunities to connect with professionals in the financial engineering field, gain insights, and explore career paths.
Browse courses on Networking
Show steps
  • Identify relevant industry conferences and meetups.
  • Register and attend the events.
  • Engage in conversations with attendees, including professionals, recruiters, and potential mentors.
  • Exchange contact information and follow up with connections.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Identify and reach out to potential mentors
Mentorship provides guidance, support, and industry insights, enhancing the learning experience and career development.
Show steps
  • Identify potential mentors within the financial engineering field.
  • Research their backgrounds, expertise, and availability.
  • Craft a professional email or message introducing yourself and expressing interest in mentorship.
  • Follow up politely if no response is received within a reasonable time.
Read "Options, Futures, and Derivatives" by John C. Hull
This book provides a comprehensive overview of derivatives, complementing lecture materials and enhancing understanding of key concepts.
Show steps
  • Read assigned chapters and take notes on key concepts.
  • Review examples and case studies to reinforce understanding.
  • Complete end-of-chapter exercises to test knowledge.
  • Summarize and discuss main takeaways with peers or in online forums.
Solve practice problems on portfolio optimization
Practice portfolio optimization problems to improve understanding of concepts and techniques.
Browse courses on Portfolio Optimization
Show steps
  • Review lecture notes and textbook materials on portfolio optimization.
  • Access online resources or textbooks for additional practice problems.
  • Solve practice problems covering various aspects of portfolio optimization, such as risk-return analysis, diversification, and asset allocation.
  • Check solutions and compare results with reference materials or online forums.
Follow tutorials on derivative pricing
Guided tutorials provide step-by-step instructions for pricing derivatives, enhancing understanding of valuation models.
Show steps
  • Identify reputable online platforms or resources offering tutorials on derivative pricing.
  • Select tutorials that align with the specific derivative types covered in the course.
  • Follow the tutorial instructions, applying the provided formulas and examples.
  • Practice pricing derivatives using the learned techniques.
  • Review and巩固understanding by re-watching tutorials or referring to additional resources.
Develop a financial model for a real-world scenario
Creating a financial model for a real-world scenario allows for practical application of course concepts and enhances problem-solving skills.
Browse courses on Financial Modeling
Show steps
  • Identify a specific financial problem or opportunity.
  • Gather relevant financial data and market information.
  • Choose appropriate financial models and techniques to analyze the data.
  • Build a financial model using spreadsheet software or modeling tools.
  • Validate and refine the model through sensitivity analysis and scenario testing.

Career center

Learners who complete Financial Engineering and Risk Management Part II will develop knowledge and skills that may be useful to these careers:
Quantitative Analyst
Quantitative Analysts develop financial models, utilizing various techniques from mathematics, statistics, and computer science. The Financial Engineering and Risk Management Part II course can help build a strong foundation for this role by providing students with knowledge in portfolio optimization, derivative pricing, algorithmic trading, and real options pricing. These concepts are essential for success as a Quantitative Analyst.
Quantitative Trader
Quantitative Traders use mathematical and statistical models to trade financial instruments. The Financial Engineering and Risk Management Part II course can help build a strong foundation for this role by providing students with knowledge in financial modeling, derivative pricing, and risk management.
Financial Engineer
Financial Engineers design and develop financial products and services. The Financial Engineering and Risk Management Part II course can provide students with a strong foundation for this role by providing them with knowledge in financial modeling, derivative pricing, and risk management.
Hedge Fund Manager
Hedge Fund Managers manage hedge funds, which are investment funds that use complex strategies to generate high returns. The Financial Engineering and Risk Management Part II course can help build a strong foundation for this role by providing students with knowledge in portfolio optimization, derivative pricing, and risk management.
Financial Risk Manager
Financial Risk Managers identify and assess financial risks within an organization. The Financial Engineering and Risk Management Part II course may be useful for this role by providing students with a deeper understanding of risk management techniques and the use of stochastic models in risk assessment.
Portfolio Manager
Portfolio Managers manage investment portfolios on behalf of clients. The Financial Engineering and Risk Management Part II course may be useful for this role by providing students with a deeper understanding of portfolio optimization and risk management.
Investment Analyst
Investment Analysts analyze and evaluate investment opportunities and make recommendations to clients. The Financial Engineering and Risk Management Part II course may be useful for this role by providing students with a deeper understanding of financial modeling and investment analysis.
Trader
Traders buy and sell financial instruments for profit. The Financial Engineering and Risk Management Part II course may be useful for this role by providing students with a deeper understanding of financial markets and trading strategies.
Data Scientist
Data Scientists use data to solve business problems. The Financial Engineering and Risk Management Part II course may be useful for this role by providing students with a deeper understanding of data analysis and modeling techniques.
Actuary
Actuaries assess and manage financial risks for insurance companies. The Financial Engineering and Risk Management Part II course may be useful for this role by providing students with a deeper understanding of risk management and financial modeling.
Compliance Officer
Compliance Officers ensure that organizations comply with laws and regulations. The Financial Engineering and Risk Management Part II course may be useful for this role by providing students with a deeper understanding of financial regulations and compliance procedures.
Auditor
Auditors examine and evaluate financial statements to ensure accuracy and compliance with regulations. The Financial Engineering and Risk Management Part II course may be useful for this role by providing students with a deeper understanding of financial accounting and auditing procedures.
Financial Consultant
Financial Consultants provide financial advice to clients. The Financial Engineering and Risk Management Part II course may be useful for this role by providing students with a deeper understanding of financial planning and investment analysis.
Credit Analyst
Credit Analysts assess the creditworthiness of borrowers. The Financial Engineering and Risk Management Part II course may be useful for this role by providing students with a deeper understanding of credit risk and financial modeling.
Risk Analyst
Risk Analysts identify and assess risks within organizations. The Financial Engineering and Risk Management Part II course may be useful for this role by providing students with a deeper understanding of risk management techniques and financial modeling.

Reading list

We've selected 15 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Financial Engineering and Risk Management Part II.
Provides a mathematical foundation for financial engineering, covering topics such as stochastic processes, stochastic differential equations, and stochastic integration. It valuable resource for those who want to gain a deeper understanding of the mathematical underpinnings of financial engineering.
Provides a comprehensive overview of financial risk management, with a focus on advanced topics such as credit risk, operational risk, and systemic risk. It valuable resource for students and practitioners alike.
Provides a practical guide to algorithmic trading, covering topics such as trading strategies, order types, and risk management. It valuable resource for those who want to learn how to develop and implement algorithmic trading strategies.
Provides an in-depth analysis of advanced financial risk management topics, such as value at risk (VaR), expected shortfall (ES), and stress testing. It valuable resource for those who want to gain a deeper understanding of risk management techniques.
Provides a practical introduction to numerical methods for finance. It covers a wide range of topics, including Monte Carlo simulation, finite difference methods, and partial differential equations.
Provides an introduction to real options, which are options to invest in or sell real assets. It valuable resource for those who want to learn how to use options pricing techniques to evaluate investment projects.
Provides a comprehensive overview of risk management and financial institutions, making it a useful reference tool for those interested in financial engineering. It covers topics such as market risk, credit risk, operational risk, and liquidity risk.
Provides an analysis of the financial crisis of 2008 and its aftermath, covering topics such as the causes of the crisis, the response of policymakers, and the lessons learned. It valuable resource for those who want to gain a deeper understanding of the financial crisis and its implications for the future.
Provides an introduction to machine learning for asset managers, covering topics such as supervised learning, unsupervised learning, and time series analysis. It valuable resource for those who want to learn how to use machine learning to improve investment performance.
Provides a comprehensive introduction to stochastic calculus, with a focus on applications to finance. It valuable resource for students and practitioners alike.
Provides a practical guide to risk management. It valuable resource for students and practitioners alike.
Provides a comprehensive overview of the mathematics of risk. It valuable resource for students and practitioners alike.
Provides a comprehensive overview of risk management in insurance. It valuable resource for students and practitioners alike.

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