
Discover the power of data, learn to pool data with indicators and analysis, fetch data quickly from exchanges and Excel, and apply machine learning with backtesting for profitable strategies.
Explore a real-world dataset in Excel that pairs the S&P 500 with Bitcoin, showing open, high, low, close, adjusted close, volume, and spread with z score and compare multiple assets.
Log in to the data builder and pull live crypto, ETFs, forex, commodities, and stocks from Binance, Poloniex, SMP data, or FMP, or upload your own CSV.
Extract two decades of stock and ETF data by fetching the SPI ticker from the S&P provider, selecting daily bars with maximum data, and saving to Excel.
Pull Bitcoin and stock data using Data Builder, combine up to five tickers, and add indicators like Bollinger bands, moving averages, and RSI with various look back options.
Append tickers as rows to expand the dataset with btc usd and RSI, transforming open, high, low, close, and volume into a combined asset view for ML training.
Learn how to convert minute data into dollar bars by aggregating price action based on volume, reducing noise and creating a single open-high-low-close bar per volume threshold for safer predictions.
Explore backtesting with data builder by pulling 20 years of data, applying a 21-day moving average, and testing a simple long strategy against market returns.
Start using the tools, import your own crypto data, and experiment to become familiar with data before advancing to Data Builder and data engineer.
Many retail traders and retail quants are looking to leverage the power of data to find and profit from predictable behaviour in the markets. They are faced with the ever increasing challenge: where to find data affordably and without having to learn programming. Due to popular request, this course has been put together to show you exactly how to use the Crypto Wizards DataBuilder tool in order to do this quickly without hassle.
Data is powerful. In this course, you will learn how to extract any financial data you like for both intraday and daily data and add complex information to your dataset which you simply just cannot find anywhere else. This includes adding in co-integration (see statistical arbitrage course), technical indicators and more.
This course has been designed for registered members of the software platform, Crypto Wizards. If you are not a registered member, you will likely not get much out of this course. However, you will learn about general principles around financial time series data and equally gain some knowledge on how how to capitalise on this.
We will cover:
How to extract and join multiple assets worth of time-series data within a few clicks
How to add technical indicators
How to add relationship metrics such as correlation and co-integration
How to convert time-series to dollar-bars and why
How to append data as rows instead of columns to support with complex machine learning
This course is a primer and precursor to the follow up course: Data Engineer. In order to perform feature engineering on your data, you must first know how to extract and structure basic data.