Meet The Coach
Arijit Banerjee, CMT, CFTe is the chief mentor and technical market strategist of Share Trading Class. He is a consulting technical analyst, contributed technical expertise at different trading and investment organizations. His long history of understanding market dynamics, and portfolio management has made him an esteemed research analyst. He has taught many traders to trade more effectively and intuitively.
Arijit is a CMT-Charter holder and has earned the right to use Chartered Market Technician designation. The CMT is a globally recognized study program in technical analysis, financial market research and investment management. He also holds CFTe, another global certification from the International Federation of Technical Analysts (IFTA), USA. Further, he is a member of CMT Association USA and has connection with finest trading professionals across the globe. SEBI, the regulatory body of Indian financial market, also recognized his expertise and gave him the credibility of a SEBI Registered Research Analyst (INH300006582). Arijit completed his B.Tech from the West Bengal Institute of Technology.
Mr Banerjee is a swing trader focusing on multi-timeframes that extend from a few days to a few weeks. He prefers trading with the trend, and his disciplined trend following approach results in larger compounded returns year after years as compared to typical buy-and-hold strategies.
Arijit takes classical and quantitative approach in trading using simple strategies and repeatable processes. He often uses a three-step process to find his trading stocks:
- A weight-of-the-evidence approach to establish the broad market environment (bull market or bear market).
- Using trend and momentum filters to identify strong sectors, industry groups, and stocks.
- Pattern analysis and momentum oscillators are used to identify tradable pullbacks.
Other elements of his trading strategy include market cycle, relative strength and volume analysis with proper trade entry, exit, target and stoploss. For investment, he looks for corrections within bigger trend to identify mean-reversion setups.