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A basic low fidelity financial modelling tool

tasks:

  • kdb should be populated based on queries and fill gaps
  • multiple data vendors should be able to be used for backfilling (google/yahoo)
  • initial backfilling should use daily data and request it over a 200 week period

? - how to identify the value of the signals when using mean reversion/trend following ie mean reversion in a turbulent market, trend follow in a regular market

what is "performance" ie sharp ratio or % return (over index?)

ideas:

  • set out exit plans/notifications before purchasing
  • focus on 'bullish' international markets (latam/euro/asia/africa)
  • map all stocks to etfs
  • identifying/structing porfolio and position sizes vs trading signals
  • strategy scaling for capital size

(49/51% coin flip is optimized to only invest 2% (< 2% is too small a gain, 4% makes loss))

environment

Currentlty the .env file contains the following keys

Variable Description
KDB_LICENSE_B64 Kdb-x licence key as provided by kdb
TWS_USERID Interactive brokers user id to authenticate with
TWS_PASSWORD Interactive brokers user password to authenticate with
TRADING_MODE Interactive brokers platform trading mode (paper or live)
READ_ONLY_API Interactive brokers option for making data read only

See https://github.com/gnzsnz/ib-gateway-docker for more details regarding the environment variables

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livebooks for learning financial trading strategies

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