Six Days Workshop On Basic and Applied Python with Machine Learning Application to Stock Market Data
Hosted by : Visvesvaraya National Institute of Technology
Department : Students
The percentage of people who invest in the stock markets is around 1% in India. This figure is far below compared to developed countries like the USA. The number of people using algorithmic trading is even very less. Strong domestic investment in the stock markets is important for nation building. One of the main reasons for this scenario is the lack of knowledge and skills required for trading in the stock markets. The main feature of the workshop is to demystify machine learning for the participants. We strongly believe in the old saying by Confucius: “I hear and I forget. I see and I remember. I do and I understand.” In that light we will first learn the Python programming language. We will also learn the basic math behind some of the machine learning techniques and apply our learnings to the stock market data. The first objective of the workshop is to provide knowledge and skill required for investing or trading in the stock market. The human emotion i.e. fear and greed is one of the main reasons for losses in the stock market investing. Because of the digitization of stock exchanges, it is now possible to allow automated algorithms to perform trading actions that automate your trades and in turn, reduces the influence of human emotional factor. The next objective of the workshop is to train the participant on machine learning and algorithmic trading using the python programming language. Another salient feature of this workshop is the programming competition. This competition will feature 4 coveted prizes to be won along with citations (One first prize, One runner-up, and Two Consolation). The level of the workshop would be basic to intermediate
Basics of computation
Machine learning using Python.
Stock market data analysis using Python.
Technical Analysis of stock market data.
Back-testing of trading Strategy.
Algorithmic Trading [Demo]
HOW TO APPLY