Buy Quantitative Finance and Algorithmic Trading in Python – Holczer Balazs Course at GBesy. We actively participate in Groupbuys and are committed to sharing knowledge with a wider audience. Rest assured, the quality of our courses matches that of the original sale page. If you prefer, you can also buy directly from the sale page at the full price (the SALEPAGE link is directly provided in the post).
Salepage link: At HERE. Archive: http://archive.is/wip/dXlQ0
$139.99 $34 – Quantitative Finance and Algorithmic Trading in Python – Holczer Balazs
Quantitative Finance & Algorithmic Trading in Python
Markowitz-portfolio theory, CAPM, Black-Scholes formula and Monte-Carlo simulations
This course is about the fundamental basics of financial engineering. First of all you will learn about stocks, bonds and other derivatives. The main reason of this course is to get a better understanding of mathematical models concerning the finance in the main. Markowitz-model is the first step. Then Capital Asset Pricing Model (CAPM). One of the most elegant scientific discoveries in the 20th century is the Black-Scholes model: how to eliminate risk with hedging. Nowadays machine learning techniques are becoming more and more popular. So you will learn about regression, SVM and tree based approaches. Hope you will like it!
Course Curriculum
Introduction
- Introduction (1:22)
- Why to use Python
- Financial models (3:03)
Stock Market Basics
- Present value / future value of money (5:10)
- Time value of money implementation (3:02)
- Stocks / shares (5:10)
- Commodities (1:18)
- Currencies and the FOREX (3:56)
- Fundamental terms: short and long (1:55)
Bonds
- Bonds basics (3:09)
- Bond price and interest rate (3:14)
- Bond price and maturity (2:06)
- Bonds pricing implementation (4:29)
Modern Portfolio Theory (Markowitz-model)
- The main idea – diverzification (5:17)
- Mathematical formulation (5:00)
- Expected return of the portfolio (5:27)
- Expected variance (risk) of the portfolio (4:53)
- Efficient frontier (5:33)
- Sharpe ratio (3:03)
- Capital allocation line (3:30)
- Modern Portfolio Theory implementation – getting data from Yahoo (6:08)
- Modern Portfolio Theory implementation – weights
- Modern Portfolio Theory implementation – mean and variance (4:03)
- Modern Portfolio Theory implementation – Monte-Carlo simulation (5:52)
- Modern Portfolio Theory implementation – optimization (8:10)
Capital Asset Pricing Model (CAPM)
- Systematic and unsystematic risk (2:05)
- Capital asset pricing model formula (3:48)
- The beta value (4:49)
- Capital asset pricing model and linear regression (2:40)
- Capital asset pricing model implementation I (4:07)
- Capital asset pricing model implementation II (5:17)
- Capital asset pricing model implementation III (3:45)
Derivatives Basics
- Introduction to derivatives (1:45)
- Future contracts (2:52)
- Interest rate swaps (2:01)
- Options basics (2:32)
- Call option (4:54)
- Put option (2:45)
- American and european options (2:18)
Random Behaviour in Finance
- Types of analysis (5:20)
- Random behaviour of returns (4:32)
- Winer-process (5:12)
- Stochastic calculus introduction (4:20)
- Ito’s lemma in higher dimensions (5:04)
- Brownian-motion implementation (4:06)
Black-Scholes Model
- Black-Scholes model introduction – the portfolio (6:44)
- Black-Scholes model introduction – dynamic delta hedge (6:09)
- Black-Scholes model introduction – no arbitrage principle (4:37)
- Solution to Black-Scholes equation (4:06)
- The greeks (4:36)
- Black-Scholes model implementation I (5:39)
- Black-Scholes model implementation II – Monte-Carlo (9:56)
- How to make money with Black-Scholes model? (1:56)
- Long Term Capital Management (LTCM) (6:03)
Value At Risk (VaR)
- What is Value-at-Risk? (3:09)
- Value-at-Risk introduction (7:40)
- Value at risk implementation I (5:07)
- Value at risk implementation II – Monte-Carlo simulation (6:04)
Machine Learning in Finance
- What is machine learning? (6:08)
- Logistic regression introduction (3:27)
- Logistic regression implementation (10:20)
- K-nearest neighbor (kNN) classifier introduction (8:02)
- K-nearest neighbor (kNN) classifier implementation (3:52)
- Support vector machine (SVM) introduction (7:12)
- Support vector machine (SVM) implementation (3:39)
Long-Term Investing
- Value investing (2:50)
- Efficient market hypothesis
Course Material
- Slides
- Sourcecode
$139.99 $34 – Quantitative Finance and Algorithmic Trading in Python – Holczer Balazs
Buy the Quantitative Finance and Algorithmic Trading in Python – Holczer Balazs course at the best price at GBesy.. After your purchase, you will get access to the downloads page. You can download all the files associated in your order at here and we will also send a download notification email via your mail.
Unlock your full potential with Quantitative Finance and Algorithmic Trading in Python – Holczer Balazs courses. our courses are designed to help you excel.
Why wait? Take the first step towards greatness by purchasing Quantitative Finance and Algorithmic Trading in Python – Holczer Balazs courses today. We offer a seamless and secure purchasing experience, ensuring your peace of mind. With our trusted payment gateways, Stripe and PayPal, you can confidently complete your transaction knowing that your financial information is protected.
Stripe, known for its robust security measures, provides a safe and reliable payment process. With its encrypted technology, your sensitive data remains confidential throughout the transaction. Rest assured that your purchase is protected.
PayPal, a globally recognized payment platform, offers an additional layer of security. With its buyer protection program, you can feel confident in your purchase. PayPal ensures that your financial details are safeguarded, allowing you to focus on your learning journey.
Is it secure? to Use of?
- Your identity is completely confidential. We do not share your information with anyone. So it is absolutely safe to buy the Quantitative Finance and Algorithmic Trading in Python – Holczer Balazs course.
- 100% Safe Checkout Privateness coverage
- Communication and encryption of sensitive knowledge
- All card numbers are encrypted using AES at relaxation-256 and transmitting card numbers runs in a separate internet hosting atmosphere, and doesn’t share or save any data.
How can this course be delivered?
- After your successful payment this “Quantitative Finance and Algorithmic Trading in Python – Holczer Balazs course”, Most of the products will come to you immediately. But for some products were posted for offer. Please wait for our response, it might take a few hours due to the time zone difference.
- If this happens, please wait. The technical department will process the link shortly after. You will receive notifications directly by e-mail. We appreciate your wait.
What Shipping Methods Are Available?
- You will receive a download link in the invoice or YOUR ACCOUNT.
- The course link always exists. use your account to login and download the Quantitative Finance and Algorithmic Trading in Python – Holczer Balazs course whenever you need.
- You only need to visit a single link, and you can get all the Quantitative Finance and Algorithmic Trading in Python – Holczer Balazs course content at once.
- You can do your learning online. You can be downloaded for better results and can study anywhere on any device. Make sure your system does not sleep during the download.
How Do I Track Order?
- We always notice the status of your order immediately after your payment. After 7 days if there is no download link, the system will automatically complete your money.
- We love to hear from you. Please don’t hesitate to email us with any comments, questions and suggestions.
Reviews
There are no reviews yet.