STOCK2DAY is the mobile and smart community for retail investors. The system uses a combination of the wisdom of crowds, gamifications and machine learning techniques to create the best informational environment, individually personalized for all kinds of retail investors, in terms of quantity, quality, and timeliness, so that they can make informed decisions and better investment return.
1. Based on their usage behaviours and other factors, we use “recommender system” to selectively present the most interesting stocks, one by one, personalised for each user. The “stock card” is packed with just enough information for the user to cast their votes for “bull” or for “bear”. Both experienced and first-time investors can interact with the system immediately with confidence. The positions are effective for 7 days which can also be closed or extended before they expire.
2. The system individually calculates daily “hit rate and performance” for each user by comparing their positions with the actual price movements at the market close. Then it statistically combines the daily figures with the historical ones accumulated in the system to segregate users who can consistently predict individual stock price movement (smart crowd) from ones who simply got it right by luck (lucky fools). These performance indicators will be used to monitor progress of individual investing skills. The best performers will also be listed on the “STOCK2DAY Smart Crowd” daily.
3. Before the market open every morning, the system feeds hit rates, performances and voting positions of users who are categorized by the system as smart crowd for each stock, together with other related usage behaviours of all users, into the “STOCK2DAY Smart Crowd Predicting Model” to make individual stock predictions. The stocks with the highest confident level in both directions will be published to the participating users as “STOCK2DAY BULL” and “STOCK2DAY BEAR” before the market open everyday.
4. The system serves as the social network platform for retail investors to exchange ideas and opinions with their hit rate and performance as proof of their investing skills and the social status. The system also introduces users with similar investing interest to each other so that they may choose to cooperate, provides personalised press releases, and informs them with potential risks and opportunities, powered by various machine learning techniques such as collaborative filtering and anomaly detections, etc.