Day 3: Python Strings – Basic Foundations for Algorithmic Trading Welcome to Day 3 of 100 Days of Hell with Python Algo Trading! Today we will be focusing on one of the most fundamental data types in Python – Strings. As the saying goes, “The devil is in the details”. Strong basics build a strong […]
Python Strings | 3/100 Days of Python Algo trading Read More »
Time series data is omnipresent in fields ranging from finance to engineering, often necessitating a change in the frequency of data points to suit analysis needs. Pandas, a powerful Python data manipulation library, provides a suite of functions ideal for this task. In this article, we’ll delve into resampling methods that condense or expand our
Pandas Time Series Data In Python: A Guide to Resampling Read More »
In the world of algorithmic trading with Python, traders continuously seek high-performance crypto trading strategies that maximize profits and minimize risks. One such quantitative analysis approach is the Obelisk Ichimoku ZEMA strategy, a combination of Ichimoku Cloud, Zero Lag Exponential Moving Average (ZEMA), and trend-following indicators. This blog will guide quantitative traders in the USA
Building an AI-Powered Trading Bot on AWS Ubuntu Server: A Step-by-Step Guide Introduction In this tutorial, we will guide you through the process of “How to setup freqtrade AI crypto trading bot” on an Ubuntu virtual server hosted on AWS, you can even setup on your localhost also. From securing your server to configuring the
Freqtrade Guide for Beginners: How to Configure Freqtrade for Algorithmic Trading Read More »
For quantitative traders and crypto investors, backtesting and optimizing a Freqtrade strategy is crucial for maximizing profitability. Whether you are trading in the USA or Singapore, mastering algorithmic trading Python with backtesting & Hyperopt will enhance your strategies. In this guide, we’ll cover: Downloading market data for crypto trading strategies Backtesting in Freqtrade to improve
Data Downloading, Backtesting & Hyperopt in Freqtrade for Algorithmic Trading Read More »
Decoding Freqtrade: A Guide to Key Configuration Parameters in config.json For quantitative traders and crypto investors, setting up Freqtrade correctly is essential for successful algorithmic trading in Python. A well-optimized config.json ensures: Accurate trade execution Better risk management Let’s break down the provided config.json file with explanations for each parameter: