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Quant Finance Essentials
Quantitative Finance, using programming, step - by step !
Created by Dr. Spyros Giannelos ., offered on Udemy
To make sure that we score courses properly, we pay a lot of attention to the reviews students leave on courses and how many students are taking a course in the first place. This course has a total of 505 students which left 70 reviews at an average rating of 4.75, which is average.
We analyze course length to see if courses cover all important aspects of a topic, taking into account how long the course is compared to the category average. This course has a length of 2 hours 14 minutes, which is pretty short. This might not be a bad thing, but we've found that longer courses are often more detailed & comprehensive. The average course length for this entire category is 7 hours 54 minutes.
This course currently has a bestcourses score of 6.2/10, which makes it an average course. Overall, there are probably better courses available for this topic on our platform.
We learn fundamental applications - frequently encountered - on quant finance
Applications on C++, Matlab as well
Step- by - step, no prerequisites.
Who I am:
I am a Research Fellow, leading the Research in industry projects in Mathematical Optimization & Data Science applied to Energy Investments, at Imperial College London.
I have a PhD in Analytics and Mathematical Optimization, applied to Energy Investments, from Imperial College London.
The old energy landscape is steadily being replaced by a new energy landscape that produces and consumes Big Data. To understand the new energy landscape we therefore need to adapt and make use of state-of-the-art Big Data algorithms and methods based on the latest advances on Data Science & Optimization.
I offer specialized education and consultancy on Data Science, Optimization, Finance, all focused on energy investments.
Make sure you sign up to be informed about my regular free webinars, to participate in quizzes, and to download publications and extra material.
No pre-requisites are needed: You do not have to know Programming (eg Python or MATLAB or C ++) at ALL because we go through all the commands needed , in great detail and with many examples.
We start from scratch, so that you do not need to have done any preparatory work in advance at all. Just follow what is shown on screen, because we go slowly as we explain everything in detail.
Nothing for you to guess or search online because we go slowly, and fully explain what is shown on screen.
If you are an experienced programmer, then you may find that the videos go very slowly. This is true because I break down every command, especially the complex ones. There are other online courses on Udemy that simply give the code, and give you an overall description of it, and then you have to figure out what it does. In my courses, we do the opposite: we go very slowly and examine every command. This is why some videos may be 30 minutes, and this is because we go in depth , and fully describe the code.
In this course, there is NOTHING for you to search around on google because every line of code is explained in detail.
So in the end of the course you will feel confident that you OWN everything that has been taught!
For the contents of this course, please watch the promo video and also read the contents and the reviews. This course has received very high reviews, on a consistent basis. This course has also been designed based on interview material (banks, energy companies/ organisations, software engineering roles etc) so by the end of it, you will be fully covered and confident that you will do well.
As you can read in my profile, I am Head of Research so I have extensive experience in this field. So you are in good hands. Good luck, and anything you need, I am and will be here to help you.
What you will learn
- The coding practices are focused on Matlab and on C++
- Understand what Stochastic Optimization is, and specifically what scenarios are and what is "uncertainty" and sources of uncertainty.
- Understand the different levels of Uncertainty
- Implement Monte Carlo Simulations
- Model the histograms of different distributions
- There are no requirements. We learn, step by step, by doing.