Coding newbie here! I am trying to code the following strategy and have not been successful yet. Will appreciate some help
Here is the logic I am trying to code (in python)
- 10 stocks universe [AAPL, AMZN, MSFT, GOOGL, JPM, V, MA, NVDA, ROKU, BAC]
- Algo runs every minute
- Max positions in portfolio at any time = 5 stocks
Buy 10 shares when the following conditions are met
- RSI (14 days) > 60
- ADX ( 14 days) > 25
- CCI (14 days) > 90
- Last price > SMA (5 days)
- MACD (6, 13) > 0
- For any of the 5 positions in portfolio, if unrealized loss of >5%, then place a limit but order for an extra one share at 0.95% of my average purchase price (average down)
- For any of the 5 positions in portfolio, if unrealized profit is > 2%, then place limit sell order for 5% profit.
- Wait at least 2 days before rebuying a closed position
The entry part of your strategy (the entry signals and combining them) is rather straightforward. You can use the data.history and the built-in indicators library (see the bollinger band template) to compute and define your signal_fn, (you can also use ta-lib directly if you prefer). For the exit part of your strategy, you need to query the context variable for the positions like below:
def compute_pnls(context):
for asset in context.portfolio.positions:
pos = context.portfolio.positions[asset]
pnl = pos.amount*(pos.last_sale_price - pos.cost_basis)
pct_pnl = pos.last_sale_price/pos.cost_basis - 1
You can insert the function above inside handle_data (before anything else) to check for exit condition. Also set a variable to track if you want to wait for n-days to exit. At the before_trading_starts - which is fired everyday once, you can check for this variable and reset it back when n-days are over.
Note: the attributes above for pnls are different in live trading, replace amount by quantity, and last_sale_price by last_price. Or you can directly query unrealized_pnl for the current (unrealized) profit or loss. If you need more help, please send a mail to blueshift-support@quantinsti.com with your current effort.