The questions that followed

Over the coming months we connected regularly, discussing the overall concept, how we could create an algorithm.

We intended to create a ‘simple’ algorithm that would analyse the sentiment of a stock which would in turn tell us if the stock was likely to be viewed favourably by retail traders.

We would get in there early, buy the stock before the crowd, make a killing and live happily ever after.

The target for us was, and is still, to simply get in ahead of the crowd.

Over the few months we developed a better understanding of other factors which impact the perceived value of a stock, we learnt that there is much more to analyse than simply sentiment. Through our learning curve (read ‘trial and error’) we then integrated all this into our strategy.

This journey of discovery also extended to understanding what kind of traders we wanted to be.

There are many ways to trade, which is one of the confusing elements when contending with all the information out there.

How much the time do you have to research?
How much time do you have to monitor stock, whether daily, weekly, monthly?
How long you want to be in the trade for?

We asked ourselves all these questions to build something that would work for us and our personalities.

We work full time, this has an impact on time i.e. we don’t have lots of time so we like automation.

However, we both understand the value in data and how it can help make decisions. We don’t like to fly blind, for us that’s not sustainable.

There are obvious reasons why hedge funds use data at the centre of their decision making. Therefore, our system had to automate data capture analysis to help us make our decisions.