Note from the editors: Towards Data Science is a Medium publication primarily based on the study of data science and machine learning. We are not health professionals or epidemiologists, and the opinions of this article should not be interpreted as professional advice. …
Long Short-Term Memory (LSTM) is one type of recurrent neural network which is used to learn order dependence in sequence prediction problems. Due to its capability of storing past information, LSTM is very useful in predicting stock prices. …
This article is the second part of my earlier article about sentiment analysis of the stock market in Python. If you haven’t gone through the first part of my article, you are welcome to visit the previous article to gain the overall picture of the topic:
Stock market sentiments can be valuable info that hints at future price action. Many often stock investors react to the market sentiments in making their decision to buy or sell their assets. …
Sometimes we need a massive amount of financial data to enable a thorough investment portfolio analysis. When our financial data keep growing, a proper data storage system is required to allow us to store them and access them in a consistent manner. …
In stock investment, one major interest of investors is to estimate the future stock movement. While there are various theories developed to predict stock movement based on historical prices, Random Walk Theory suggests that there is no relationship between the current stock prices and the future prices. …
Most financial data are time-series data. They are a sequence of data points indexed in time order. One of the most common examples is the stock market OHLC data indexed by dates.
Could you imagine a financial or investment analysis without a visualization? Without a chart for data visualization, our financial data will just look none other than a series of gibberish numbers.
In this article, I will introduce a powerful Python-based plotting library dedicated to financial visualization. It is Mplfinance. Through…
The acquisition of financial data is as important as the development of an algorithm in a quantitative financial project. Without data, there is no way we can implement and backtest our trading strategy or algorithms.
In this article, I am going to introduce three Python packages that enable us to…
Does our salary really grow with our years of working experience? While this can be answered based on our general understandings of the job market, we will use a simple data-driven approach to verify the fact. …
