1 - blog.quantinsti.com/install-ta-lib…
Learn how to install the Ta-Lib python library on Windows, macOS as well as Linux. Also, create technical indicators using Ta-Lib and plot them.
2 - bit.ly/3oGT2ln
This blog will empower you to be able to use the Python codes to fetch the stock market data of your favourites stocks, build the strategies using this stock market data and analyse this data.
3 - blog.quantinsti.com/gini-index/
Gini Index is preferred over Information gain because unlike information gain, it is computationally intensive as it doesn’t involve the logarithm function used to calculate entropy in information gain.
4 - blog.quantinsti.com/creating-heatm…
Seaborn is an easy-to-use library that provides us with powerful tools for better and more aesthetic visualizations. One can tweak the Seaborn plots to suit one’s requirement and make heatmaps using Python for various use cases. #heatmap#seaborn
5 - blog.quantinsti.com/market-making/
From this knowledge house blog you will learn Who are the market makers, How & how much they earn, algorithmic market making, benefits & differences between brokers & market makers.
🗺What is the history of the Stock Market?
💱How did trading originate?
📈What are some of the key events of the Stock Market?
We explore the entire timeline of finance and trading leading up to the present day via this series of tweets.
The 1300s
Venetian moneylenders began to sell debt issues to other lenders and to individual investors; and traded in government securities. They carried slates with information on the various issues for sale & meet with clients, much like a broker does today. #StockMarketOrigins
The late 1400s
Belgium (then, Antwerp), became the centre of international trade. Merchants would bring in goods anticipating that prices would rise and earn them a profit. #Bondtrading also occurred during this period. #StockMarketOrigins