In this tutorial, we will be discussing how to decompose stocks time-series into different components in order to have a good idea about the complexities of the time-series models and how to accurately capture them and account for them in our model.
In this article we will learn about Natural Language Toolkit – “NLTK”. NLTK is one of the key libraries which is widely used for Natural Language Processing in Python. NLTK can be used in a vareity of ways improving your way of looking at text.
In this tutorial, we will be learning how to create candlestick charts along with volume bars and moving average lines in Python.
Leverage Effect using VIX and Python Hi All! Today, in the part 13 of Financial Analytics series, we will be learning about an alternative method of identifying Leverage Effect using VIX and Python. If you’re new to this series, we suggest that you start from here. What is VIX? VIX is also called as […]
In this tutorial, we’ll continue exploring stylized fact and will go through Stylized fact 5: understanding leverage effect using Python.
While working with dataframes we do come across a problem of combining multiple dataframes together or you can say “Concat & Append Dataframes”
In this tutorial, we’ll continue exploring stylized fact and will go through Stylized fact 4: Decreasing auto-correlation trend in squared/absolute returns.
In this tutorial, we’ll continue exploring stylized fact and will go through Stylized fact 3: Is auto-correlation absent in returns? and will see if there is decreasing auto-correlation trend in squared/absolute returns using Python.
Volatility Check in Returns charts Hi All! In our previous tutorial, we had introduced stylized facts, what the five stylized facts are and had also covered stylized fact 1 – Distribution of returns – Is it non-Gaussian? In this tutorial, we will be covering stylized fact 2 – “Are Volatility clusters formed in returns […]