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We explore what is carry trading and how to apply it in Python. Why today's economic landscape it is a profitable strategy and what risks are associated with it.

Learn tips for successful web scraping in Python: check website's rules, request rate, dynamic content, and data format. Scrape responsibly!

Learn how to extract data from websites using Python with web scraping. Use the requests and beautifulsoup libraries to get started and save the extracted data. Learn more about Scrapy, Selenium, lxml, Pandas and mechanicalsoup

Learn how to use yfinance, a Python library to fetch financial market data such as stock prices, dividends, financial statements, options, and sustainability data for a company or index. With yfinance, you can easily retrieve and analyze financial data for informed decision-making.

Learn how to do a Fourier decomposition in Python in order to break down a complex signal into simpler trigonometric functions for easier analysis and prediction.

Learn how to predict stock price using Geometric Brownian Motion (GBM) process by updating the stock price over multiple time steps using randomly generated normal variables and the mean return and standard deviation of the stock's returns

Python script for Monte Carlo simulation of stock price prediction using the geometric Brownian motion model to determine the mean, upper, and lower bounds of the simulated prices.

Compute Black-Scholes option pricing model in Python using numpy and scipy.stats.norm, formula calculates price of European call or put option based on inputs of underlying asset price, strike price, time to expiration, risk-free rate, volatility, and option type

Python function calculates order flow by subtracting sell volume from buy volume. Call order_flow(buy_volume, sell_volume) with volume of buy and sell orders.