Reference: http://ocel.ai/story-telling/
- Who are the people or communities in need of help?
- During the difficult times as a common man, I just don’t want to rely on the primary source of income. But, with me being occupied in my primary work, I want help from a system which can aid me by analyzing news archive of how the industry performed over the time and how much does that reflect into actual stock prices. By using this system, it can help me make the right choice with data that’s present in the market.
- What problem happened to them?
- In this world of increasing markets, it helps me to monitor, analyze and respond quickly and wisely. These models offer the ability to find the associations based on historical information for identifying the trends to develop. The automation of these models help traders or investors with limited knowledge on the industry to adopt the trends instantly. It assists to enhance more opportunities in the number of marketers to perform effectively.
- When did the problem take place?
- It’s no exaggeration to say Deep learning models are majorly fueled by Data itself. More the data, more is the robustness and performance of a model. Current goal of the idea is to prove the models performance on historic data and the historic stock prices, but the prediction can be on the current day prediction based on historic knowledge.
- Where means two things: 1) The environment and settings that the people or the community is living in, and 2) the place/location where the problem take place.
- In the world of economies there is a saying “if the US sneezes, the global market catches cold”. This opinion is backed from the earlier economy downfalls. In light of this we consider the most challenging markets to be US given its breadth and depth of the industry. We consider such a dataset to analyze the market.
- As per the statistics, 53% of the United States population (more than half of the people) are anxious about their financial status and this is because of financial illiteracy. When these kind of models come up, they help in reducing the stress to some extent causing due of the lack of financial knowledge and guide them in the right path to invest.
- Why means the possible causes and/or origin of the problem.
- Accomplishing research before making an investment is a must since it is hard earned money that is about to be invested and is expected to get maximum returns. To make these accurate decisions on investments, the idea is to introduce deep learning models that allow laymen to analyze complex patterns of stock market data and look for feasible permutations to increase the chances of returns and reduce the risk once after starting to invest in any specific product and also enables investors to identify the intrinsic worth of a security even before investing in it.
- How: If you would like, you can add a dimension of how. How did it happen? Sometimes, the answer to how can be covered by what, when and where.
- When the data extracted, will be fed to the neural networks, it will be able to analyze the patterns and habits from the news archive. Also, with the use of extensive training techniques, Neural networks will be knowledgeable to understand news and current data and should be able to predict its worth to buy.
