Recent events involving GameStop, AMC, and other stocks have shaken Wall Street. It is thought to be a result of a group of retail investors known as r/wallstreetbets, also known as WallStreetBets (WSB). It is a subreddit where participants discuss option and stock trading.
Billions of dollars have been lost due to a lack of alternative data monitoring. GameStop revolt is just an example of a lost opportunity to optimize public data in order to make informed investment predictions.
This time, alternative data was overlooked, and it cost more than anyone could have imagined. Real-time sentiment monitoring could have prevented this fallout.
Alternative data tracking gives out signals that help make informed strategic decisions or even foresee certain events. Various signals, including cryptocurrency price predictions, can be spotted in social media. Specifically in public chat forums and message boards.
Alternative data gathering by tracking NYSE and Nasdaq tickers in message boards
Hedge funds and other asset management companies — even those that do not regularly go short — will have to adjust after the recent GameStop revolt. These companies already use alternative data to track e-commerce, real estate offerings, news and job changes data, and get ahead of earnings reports. But they will now have to watch the message boards.
It can be done by tracking the number of times New York Stock Exchange (NYSE) and Nasdaq tickers are mentioned in the top 100 posts on specific message boards (like Reddit) in real-time.
Social media signals for alternative cryptocurrency price prediction
Companies can analyze publicly available social media and public message board signals as a medium for user sentiment. Which may help predict the price fluctuations of alternative cryptocurrencies.
It can be done by extracting public social messages on an hourly basis for a period of time, classifying each post as positive, neutral, or negative.
Companies can compile these public messages into an hourly sentiment index, creating an unweighted and weighted index, with the latter giving larger weight to sharing of those messages.
These two indices, alongside the raw summations of positive, negative, and neutral sentiment can be data points of hourly pricing data to train different models.
Price predictions produced from this model can be compared to historical price data, with the resulting predictions possibly having a high correlation with the testing data.
Social media platforms can serve as powerful social signals for predicting price movements in the highly speculative alternative cryptocurrency, or “alt-coin,” market.
After the recent fallout, alternative data for finance has more value than ever. Especially structured sentiment data that comes in real-time, at a large scale. A reliable flow of such data can help make informed and strategic decisions.
If you would like to talk about our solutions for companies in the financial sector, please get in touch with us at email@example.com, and we will be happy to offer a solution for your case.