kinetick 1.0.15

1. Get Market Data

To get started, you need to first create a Blotter script:

# blotter.py
from kinetick.blotter import Blotter

class MainBlotter(Blotter):
    pass # we just need the name

if __name__ == "__main__":
    blotter = MainBlotter()
    blotter.run()

Then run the Blotter from the command line:

$ python -m blotter

If your strategy needs order book / market depth data, add the --orderbook flag to the command:

$ python -m blotter --orderbook

2. Write your Algorithm

While the Blotter running in the background, write and execute your algorithm:

# strategy.py
from kinetick.algo import Algo

class CrossOver(Algo):

    def on_start(self):
        pass

    def on_fill(self, instrument, order):
        pass

    def on_quote(self, instrument):
        pass

    def on_orderbook(self, instrument):
        pass

    def on_tick(self, instrument):
        pass

    def on_bar(self, instrument):
        # get instrument history
        bars = instrument.get_bars(window=100)

        # or get all instruments history
        # bars = self.bars[-20:]

        # skip first 20 days to get full windows
        if len(bars) < 20:
            return

        # compute averages using internal rolling_mean
        bars['short_ma'] = bars['close'].rolling(window=10).mean()
        bars['long_ma']  = bars['close'].rolling(window=20).mean()

        # get current position data
        positions = instrument.get_positions()

        # trading logic - entry signal
        if bars['short_ma'].crossed_above(bars['long_ma'])[-1]:
            if not instrument.pending_orders and positions["position"] == 0:

                """ buy one contract.
                 WARNING: buy or order instrument methods will bypass bot and risk assessor.
                 Instead, It is advised to use create_position, open_position and close_position instrument methods
                 to route the order via bot and risk assessor. """
                instrument.buy(1)

                # record values for later analysis
                self.record(ma_cross=1)

        # trading logic - exit signal
        elif bars['short_ma'].crossed_below(bars['long_ma'])[-1]:
            if positions["position"] != 0:

                # exit / flatten position
                instrument.exit()

                # record values for later analysis
                self.record(ma_cross=-1)


if __name__ == "__main__":
    strategy = CrossOver(
        instruments = ['ACC', 'SBIN'], # scrip symbols
        resolution  = "1T", # Pandas resolution (use "K" for tick bars)
        tick_window = 20, # no. of ticks to keep
        bar_window  = 5, # no. of bars to keep
        preload     = "1D", # preload 1 day history when starting
        timezone    = "Asia/Calcutta" # convert all ticks/bars to this timezone
    )
    strategy.run()

To run your algo in a live environment, from the command line, type:

$ python -m strategy --logpath ~/orders

The resulting trades be saved in ~/orders/STRATEGY_YYYYMMDD.csv for later analysis.

3. Login to bot

While the Strategy running in the background:

Assuming you have added the telegram bot to your chat

• /login <password> - Password can be found in the strategy console. This step is required if you have not provided your telegram chat id as an env var

• /zlogin <totp> Command to login to zerodha using totp

commands

• /report - get overview about trades

• /help - get help

• /resetrms - resets RiskAssessor parameters to its initial values.

Configuration

Can be specified either as env variable or cmdline arg