Genesis
In 2012, we started to study algorithmic trading to manage family assets. Originally, our model was based technical analysis in stock trading. By our previous versions, we found that manually (Ad-hot) seeking parameter takes amounts of time and cost. Besdies, it is also unreliable and inaccurate. Thus, we started to develop efficient algorithm for parameter estimation.
At the same time, we also found that technical analysis has weakly mathematical backup. Thus, we tried to use a common model applied in option price modeling, that is Gemetric Brownian Movement (GBM). Based on mathematical backup, we believe that we can easier find pros and cons in GBM model. Beside, it is more systemtical and theoretical to analysis GBM model. In this period, we also defined flow of machine learning (ML) for algorithmic trading.
Until 2018, we have broken through our model limits and computing performace. The former makes our learning algorithm for more flexible solution changed by market; the later makes our computation more efficient. Immediately, we conclude our solution to funtSim ™, a optimizer toolkit for descrete function. Because of the breakthroughs, Elliot Hou, Ao-ping, funder of Yunping IT Ltd., starts to establish this company to share his experience to people in the world. We hope that the sharing can help our customers to make benifits and to solve problems in financial turmoil.
Members
Elliot Hou, Ao-ping
Funder, Yunping Information Technology Ltd.
CTO, Yunping Information Technology Ltd.
Ph.D. Candidate in Computer Science, Virginia Polytechnic Institute and State University
Certificate in Quantitative Finance (CQF) with Distinction
Master of Science at Virginia Polytechnic Institute and State University.
Products
Customers can use online cash flow (not yet) or offline remittance to purchase points for later use on various web pages.
Teaching
We offer full online courses or offline workshops to teach students how to program their trading models to determine buy and sell points. In addition, we teach them how to control costs and risks in real-world cases.
History Prices
We provide historical price data of domestic and foreign stocks, cryptocurrencies and mutual funds, and customers can retrieve prices by URL on google colab. Therefore, clients can use this data to conduct their backtesting procedures and use them in future transactions.
Technical Stock Picking
The historical stock price is calculated by the quantitative financial formula, and through the screening of different conditions, the customer can choose the stock with good current performance.
Back Testing and Optimitzation
Customers can upload their backtesting programs to this site so they can find better returns with optimized trading model parameters. Optimized parameters can help their trades make better profits in real-world situations.
Leaderboard
For customers with no programming background, we provide an optimized leaderboard, allowing them to use other people's code for backtesting or evaluating transactions, and the leaderboard also allows programmers to exchange code with each other.
Portfolios
For VIP customers, we can customize the investment portfolio, so that customers can manage and trade multiple stocks at one time within the allowable funds. Customers will use our advanced and well-trained trading model in this product. If necessary, please contact customer service .