6-09-2021, 06:31 | view 👀:111 | 🙍 oneddl | redaktor: FreshWap.CC | Rating👍:

Udemy - Data science for algorithmic trading

Name: Udemy - Data science for algorithmic trading
Author: FreshWap.CC

We will create a algorithmic trading strategy that earns 50% annually.
What you'll learn
Use numpy to do scientific calculation
Use pandas to import and organize data
Use MatDescriptionlib to visualize data
Use, create, understand mathematical model
Machine learning for algorithmic trading
Features Engineering
Statistics for finance
Create an easy-to-reuse backtesting universe
Automatically take sales and buy positions
Data import with a API
Requirements
title>Data science for algorithmic trading | Udemy
@font-face {
font-family: 'Udemy Sans';
font-style: normal;
font-weight: 400; /* To match token @font-weight-normal */
font-display: fallback;
src: local('Udemy Sans Regular'),
local('UdemySans-Regular'),
url('https://www.udemy.com/staticx/udemy/fonts/Udemy-Sans-Regular-v1.woff2') format('woff2');
}
@font-face {
font-family: 'Udemy Sans';
font-style: normal;
font-weight: 700; /* To match token @font-weight-bold */
font-display: fallback;
src: local('Udemy Sans Bold'),
local('UdemySans-Bold'),
url('https://www.udemy.com/staticx/udemy/fonts/Udemy-Sans-Bold-v1.woff2') format('woff2');
}
@font-face {
font-family: 'Theinhardt Mono';
font-display: fallback;
src: local('Theinhardt Mono Regular'),
local('TheinhardtMono-Regular'),
url('https://www.udemy.com/staticx/udemy/fonts/Theinhardt-Mono-Regular-v2.woff2') format('woff2');
}
@font-face {
font-family: SuisseWorks;
font-style: normal;
font-weight: 700; /* To match token @font-weight-bold */
font-display: fallback;
src: local('SuisseWorks Bold'),
local('SuisseWorks-Bold'),
url('https://www.udemy.com/staticx/udemy/fonts/SuisseWorks-Bold-v1.woff2') format('woff2');
}
Skip to contentCategories
Description
It's with pride that I offer this data science course for algorithmic trading. It is the fruit of several years of work in the field in order to truly understand all the subtleties of the world of quantitative finance.
\n
Using libraries will allow you to do complex mathematical calculations applied to finance in just a few lines of code. We will see how to create a algorithm of trading from data import to automatic positions. You will create an algorithm that will yield more than 50% annually on the Nasdaq 100 using an algorithm.
\n
\n
In summary, we will study:
The numpy library to do scientific calculations
The pandas library to organize and visualize data
The MatDescriptionlib library to make powerful graphics
Features engineering
Linear regression for finance
Machine vector support
Decision tree
Random Forest
Apply and understand the Sharpe ratio
Apply and understand the Sortino ratio
Understanding the volatility of a stock market asset
Understand and create a backtesting universe that is easy to reuse
Backtest the strategy
Who this course is for:Everyone

Buy Premium From My Links To Get Resumable Support,Max Speed & Support Me

.html
++++++++++++++++++++++++++
https://ddownload.com/cdrmfpy3hw8n/wtb2q.Data.science.for.algorithmic.trading.rar

rapidgator

https://rapidgator.net/file/4a1737691849bdef9865238dafb76017/wtb2q.Data.science.for.algorithmic.trading.rar.html

Links are Interchangeable - No Password - Single Extraction

⚠️ Dead Link ?
You may submit a re-upload request using the search feature. All requests are reviewed in accordance with our Content Policy.

Request Re-upload

Udemy - Data science for algorithmic trading

Comments (0)

Log in