Sharpe Capital: The New Generation of Crowd Sentiment
Naturally, crowd behaviour has been widely studied in fields such as psychology, statistics, and economics. Much of this research shows that the collective wisdom of a diverse group of people is more accurate than a single opinion (even from an expert) in forecasting an outcome.
Organized crowds have always played an important role in human society. It’s how we come together in a marketplace—a diverse group of individuals going about our business, yet all subject to a degree of predictable behaviour and certain rules of group dynamics.
For stock market investors, sentiment can be an important factor in determining stock prices. Now our ability to harness the collective wisdom of millions of investors on social media means that we can measure sentiment in a predictive manner. In real time.
Sharpe Capital uses quantitative modelling of financial data and collecting predictions on asset prices from "The Crowd". Sharpe Capital combines Crowd prediction with Machine Learning modelling algorithm to look for patterns in financial data that are predictive of future asset price. They integrated Artificial Neural Networks to offer powerful Machine Learning prediction capabilities, because ANNs are inspired by the behaviour of the human brain.
The utilization of crowd sentiment in machine learning helps in efficiently analyzing unprecedented amounts of data. It is thus poised to revolutionize the way machine intelligence functions.
Many companies have begun to generate revenue streams by analyzing the reputation and background of their clients in online media, such as established news sources, blogs, and micro-blogs. The obstacle occurs in understanding the accurate polarity. The combination of machine learning and crowdsourcing has a number of advantages in terms of sentiment analysis.
Sharpe Capital technology allows a huge number of unlabeled items to be classified and provide robust statistics about sentiment trends. Statistics can be generated after the annotation process ends. The extent to which this can be done relies on the amount of concept drift that occurs over a period of time in the specific domain of interest. The primary objective is to produce unbiased assessments of sentiment in a dynamic collection of news articles, thereby identifying and visualizing trends and differences between varied sources.
Learn more about Sharpe Capital at their official website:
https://sharpe.capital/