Data-Driven Stock Market Forecasting Using Supervised Learning Techniques

Abstract

One of the most intricate and sophisticated
forms of trade is the stock market, also referred to as
the stock exchange. Small businesses, brokerage firms,
and the banking industry all rely on this one entity to
generate income and distribute risks; it's a very
intricate arrangement. This article discusses utilising
machine learning algorithms to anticipate the future
stock price on the exchange using open-source libraries
and already-existing algorithms in order to make this
unstable business model a little more predictable. We'll
see if this straightforward implementation yields
respectable outcomes. The result is entirely dependent
on math and makes numerous axiomatic assumptions
that may or may not be true at the time of prediction