11 thoughts on “Financial Engineering Examples

  1. It is true it is difficult to do the valuation of a company that works in two sectors or two different kind of business. However it is important to know that the combination of the won business units will create value in the synergies in SG&A, then a combination of two kind of business not reduce the value of the company.

  2. You can’t call this video Financial Engineering examples of you only talk about it at the end of the video 😏

  3. LOL @ "Businesses are full of people; and people are not the same thing as parts used in a machine" – yeah right

  4. This is excellent for people who become intimidated with the finance industry and financial engineering. Wish you the best to continue this channel

  5. The content of this video is a gross misrepresentation of what financial engineering is. A more appropriate title would be Corporate Finance examples. The example given is more akin to security analysis than financial engineering of which is within the domain of quantitative finance. The following is the definition of financial engineering on the International Association for Quantitative Finance's website: (www.iaqf.org/financial-engineering)

    " Financial engineering is the application of mathematical methods to the solutions of problems in finance. It is also known as financial mathematics, mathematical finance, and computational finance. Financial engineering draws on tools from applied mathematics, computer science, statistics, and economic theory."

    In other words, financial engineering is the cross section of math, statistics, computer science, and finance. In order to implement financial engineering you must employ the use of quantitative methods. These methods vary depending on what role you perform within quantitative finance and how the industry is changing, but quants/financial engineers will have a background in statistics, programming, math(typically calculus and linear algebra), and finance. For instance prior to 2008, quants were heavily focused on creating the pricing models for derivative securities being created by investment banks. Today, with the rapidly growing interest in machine learning and other areas of artificial intelligence, it is now more necessary than ever for quants to deepen their programming knowledge . This is not to say that quants weren't programming in the past, but is simply an illustration of the fact that a major part of being a quant is to constantly be learning and also to monitor and adjust to your environment, of which is dynamic. Whereas in the past quants were able to focus solely on the mathematics of their models, there is now a greater demand for them to employ could programming practices. Here's a video in which Emanuel Derman speaks about the changes over time relative to the weighting of specific areas of quantitative finance and thus financial engineering. https://www.youtube.com/watch?v=AtjjMIeUJbU

    Quantitative Researchers/Traders for instance employ the use of statistical hypothesis testing, backtesting algorithmic strategies, creating execution systems, employ the use of derivative pricing models for risk analysis, portfolio composition etc, optimization of parameters, portfolio optimization, risk management, etc.

    Employment as a financial engineer or quant can range from being in a strat group at investment bank, risk dept. at an investment bank, quant at a hedge fund, or quantitative trader at a prop firm.There are a lot of different types of quants, some of them can be viewed here: https://www.youtube.com/watch?v=Ubg0fX2mLUQ&t=57s .

  6. After your first video, you've boosted my confidence and understanding on the industry. Thank you so much

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