Python Operators + if-else + Loops | 2/100 Days of Python Algo trading

Algorithmic Trading and Python: The Technology of the Future Algorithmic trading is rapidly transforming the financial markets. Automating trading strategies through Python has now become extremely beneficial for quantitative traders. In this session, we will not only learn Python Operators and Conditional Statements (If-Else) but also touch upon the tools used in Freqtrade Strategy, Crypto […]

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Pandas Time Series Data In Python: A Guide to Resampling

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

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Unveiling the Obelisk Ichimoku ZEMA Strategy | Backtesting & Hyperoptimization for Algorithmic Trading

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

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MacheteV8B: The Trend-Following Powerhouse for Algorithmic Trading in Python

Algorithmic trading in Python has revolutionized how quantitative traders execute high-frequency trades. One of the most effective crypto trading strategies today is the MacheteV8B Freqtrade strategy, a trend-following powerhouse designed for optimal trade execution and profitability. In this guide, we’ll cover: How MacheteV8B enhances quantitative analysis for trading Implementing the strategy in Python for crypto

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Harnessing Market Volatility with Freqtrade: The Volatility System Trading Strategy

Market volatility presents both risks and opportunities for quantitative traders. With the right algorithmic trading Python strategy, traders can capitalize on price swings for profitable trades. One such approach is the Volatility System Trading Strategy, designed to identify high-probability entry and exit points in the crypto market. In this blog, we will explore: How market

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Fixing ‘No Module Named Finta’ Error in Freqtrade for Algorithmic Trading Python

Outline Introduction In the realm of cryptocurrency trading, automated bots have become increasingly popular for executing trades efficiently and swiftly. Freqtrade is one such open-source cryptocurrency trading bot that utilizes various indicators for decision-making. However, users might encounter an error stating ‘No module named ‘finta,” which can impede the bot’s functionality. In this article, we

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“Freqtrade Masterclass: Automate your Crypto Trading in just 30 days” Day-2

Are you a quantitative trader looking to master algorithmic trading Python? This Freqtrade Masterclass will help you automate crypto trading strategies in just 30 days! In Day 2, we’ll cover: Understanding Freqtrade and its components How to set up and configure Freqtrade Implementing quantitative analysis for trading Optimizing strategies for the USA & Singapore markets

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Freqtrade Masterclass: Automate Your Crypto Trading in Just 30 Days (Day 1)

Day 1- Basic introduction of freqtrade Freqtrade is a Python-based algorithmic trading software designed for automated trading in cryptocurrency markets. Here are some of its key features: Overall, Freqtrade offers a comprehensive set of features for algorithmic cryptocurrency trading, making it a popular choice among traders and developers alike. Users can leverage its powerful tools

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Freqtrade Guide for Beginners: How to Configure Freqtrade for Algorithmic Trading

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

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Data Downloading, Backtesting & Hyperopt in Freqtrade for Algorithmic Trading

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

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