Who we are
DerivEdg is a team of Data Science enthusiasts. We use data science / machine learning to analyze time series data to unravel the price behavior of instruments that are traded using two way auction mechanism. Our background is Engineering, Information Technology, Management Science and Mathematics/Statistics. We do not pretend to know all aspects of trading as we are not trained in that area. We trade for our personal accounts once in a while.
Our assumptions about price discovery
In a finite time frame, in two way auction markets, selling and buying exhaustions do happen. We are trying to build algorithms to identify these exaustions as price reversal areas. At the point of selling exhaustion, there will be no more sellers and buyers step in. Selling stops and buying resumes. Same thing happens on the buying side as well.
Why we share our signals and associated information
We share our results in real-time on Twitter and Stocktwits to make sure our signals are properly validated with timestamps provided by Twitter/Stocktwits.
We are data scientists with passion to study market behavior
We also know that trading is not just identifying the turning points. Our system currently does not recognise the following and hence not considered within the model:
- Position sizing
- Instrument selection
- Risk management such as stop-loss, hedging etc.