| 001 BONUS-3-January22.pdf | 30.1 KB | ||
| 001 Download & Read Financial Data on Python.mp4 | 22.6 MB | ||
| 001 Download & Read Financial Data on Python_en.vtt | 1.9 KB | ||
| 001 Extras.html | 102.4 B | ||
| 001 Installation and building basic program.mp4 | 43.6 MB | ||
| 001 Installation and building basic program_en.vtt | 6.4 KB | ||
| 001 Python code for converting Lognormal datasets to Normal ones.mp4 | 23.5 MB | ||
| 001 Python code for converting Lognormal datasets to Normal ones_en.vtt | 2.7 KB | ||
| 001 Uncertainty.mp4 | 13.5 MB | ||
| 001 Uncertainty_en.vtt | 3.2 KB | ||
| 001 code.txt | 512 B | ||
| 001 slides.pdf | 86.8 KB | ||
| 002 Construct scenarios & determine their probabilities.mp4 | 98.5 MB | ||
| 002 Construct scenarios & determine their probabilities_en.vtt | 14.2 KB | ||
| 002 Probability evaluation using vectors.mp4 | 187 MB | ||
| 002 Probability evaluation using vectors_en.vtt | 24.8 KB | ||
| 002 Proof on Python Does log() convert any dataset to a normal one.mp4 | 14.4 MB | ||
| 002 Proof on Python Does log() convert any dataset to a normal one_en.vtt | 1.8 KB | ||
| 002 Read data in Python from online sources.mp4 | 17.5 MB | ||
| 002 Read data in Python from online sources_en.vtt | 1.4 KB | ||
| 002 c-code.txt | 1.1 KB | ||
| 002 code.txt | 409.6 B | ||
| 002 slides.pdf | 93.8 KB | ||
| 003 Bernoulli process with biased trials (part 1).mp4 | 65.2 MB | ||
| 003 Bernoulli process with biased trials (part 1)_en.vtt | 11.3 KB | ||
| 003 Deep insight into Uniform Distribution with MATLAB & Python.mp4 | 143.9 MB | ||
| 003 Deep insight into Uniform Distribution with MATLAB & Python_en.vtt | 25.3 KB | ||
| 003 Python code for converting any non-Normal dataset to Normal via Box-Cox.mp4 | 31.8 MB | ||
| 003 Python code for converting any non-Normal dataset to Normal via Box-Cox_en.vtt | 3.7 KB | ||
| 003 Uniform-probability-distribution-and-investments.url | 102.4 B | ||
| 003 code.txt | 716.8 B | ||
| 003 slides.pdf | 101.5 KB | ||
| 004 Bernoulli process with biased trials (part 2).mp4 | 80 MB | ||
| 004 Bernoulli process with biased trials (part 2)_en.vtt | 10.6 KB | ||
| 004 Normal Distribution interpretations.mp4 | 47.6 MB | ||
| 004 Normal Distribution interpretations_en.vtt | 9.6 KB | ||
| 005 Bernoulli process with biased trials (part 3).mp4 | 59.2 MB | ||
| 005 Bernoulli process with biased trials (part 3)_en.vtt | 6.5 KB | ||
| 005 Monte Carlo and simulated Probabilities.mp4 | 63.2 MB | ||
| 005 Monte Carlo and simulated Probabilities_en.vtt | 7.1 KB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| external-links.txt | 102.4 B | ||
| ▲ 47 total files | |||
Quant Finance Essentials using Python C++ & MATLAB
https://DevCourseWeb.com
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 912 MB | Duration: 2h 14m
We look into Key Quantitative Finance, using programming, step - by step !
What you'll learn
This is a course that provides some fundamental coding tutorials especially for those aiming for a Quant career.
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
Requirements
There are no requirements. We learn, step by step, by doing.
Description
We are looking at some fundamental coding tutorials especially for those aiming for a Quant career in Finance since these are topics that frequently come up. Since these topics come up often, we are looking at them, not through theory, but through practice.
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 3.1 GB | freecoursewb | 2 years | 0 | 0 | |
| 2.7 GB | freecoursewb | 2 years | 5 | 0 |
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