PingPong.jl
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panifie
Cryptocurrency trading bot, and backtesting framework in julia
# v1 v1 is [tagged](https://github.com/panifie/PingPong.jl/releases/tag/v1.0.0) The test suite is mostly passing, although there are still 1 or 2 flapping tests. The pre built images are on the [docker registry](https://hub.docker.com/u/panifie) v1...
Hello, Currently following documentation but ```julia julia> using PingPong julia> @environment! julia> s = st.strategy(:Example) Name: Example (Sim) Config: No Margin, 10.0(USDT)(Base Size), 100.0(USDT)(Initial Cash) Universe: 3 instances, 1 exchanges...
## Isolated margin - [ ] Funding rate estimation (currently we just use higher trading fees) - [ ] Updating margin of open positions - [ ] Updating leverage of...
The backtest could be made more interactive by either: - (terminal) use a progress bar (which we already have used for other things like scrapers) - (graphical) update a makie...
Some strategies work based on past profitability, so they require a way to calc the profits of previous trades. Because ping pong does not make assumptions about execution of trades...
## backtest - [ ] There are many repeated function calls like `openat,closeat,etc...` that could be memoized - [ ] Consider either removing `getproperty` for asset instances and strategies or...
Although not really recommended, embedding python strategies is a very easy task.
Basically all functions with arguments any combination of `Strategy` `AssetInstance` `Order` `Trade` etc... have "loose" signatures. Meaning for example that you could call them with arguments where the strategy refers...
- [x] Spread: always enabled - [x] Slippage: for large trades - [ ] Market impact: for very large trades