Hi,

It'd be useful if classes from the order hierarchy, in particular the BracketOrder were made open. We've been forced to duplicate a large part of the code so we could model an specific kind of order.

TIA, Martin Paoletta

Hi! We've been working on porting our (already on production) crypto Backtrader strategy to Roboquant very easily, and find the design decisions you made very sound. We did find a rounding issue on position sizes operating with crypto coins, the same issue we had to fix on Backtrader.

Whenever we have more than one concurrent bracket order, when one of the limit orders (tp or sl) is executed, and the order quantity is substracted from the position size, the position can end up having a very small amount due to rounding errors using doubles. We managed to solve the issue rewriting part of the Position class (mostly the plus method), maintaining a read only double size so the change is encapsulated in the Position. We can fork your repo and create a PR if that's ok, or we can chat about that if you want.

Thanks for creating Roboquant!

Regards, Martin

Hi, currently order execution is using the open price. This is something that is done on the execution method on the order, and while a refactor of the sim execution part would allow to change it somehow, it still needs the broker to send the whole candlestick in order to do something like backtrader does:

https://www.backtrader.com/docu/order-creation-execution/order-creation-execution/

It probably was a backtesting strategy choice, but it'd be great to allow for different strategies regarding this. This probably means having a proper OHLC data class instead of a map. Do you have any thoughts regarding this?

Best regards and thanks again for this wonderful project, Martin

Alpaca's getBars API hasbarTimePeriodDuration which enable us to retrieve different bar durations, such as 5m/15m etc. As for now this value is hardcodedto 1.

I encounter this exception often with JDK17 when I try to get live data or get a lot of historic data. Exception in thread "DefaultDispatcher-worker-2" com.google.gson.JsonIOException: Failed making field 'java.lang.Throwable#detailMessage' accessible; either change its visibility or write a custom TypeAdapter for its declaring type at com.google.gson.internal.reflect.ReflectionHelper.makeAccessible(ReflectionHelper.java:22) at com.google.gson.internal.bind.ReflectiveTypeAdapterFactory.getBoundFields(ReflectiveTypeAdapterFactory.java:158) at com.google.gson.internal.bind.ReflectiveTypeAdapterFactory.create(ReflectiveTypeAdapterFactory.java:101) at com.google.gson.Gson.getAdapter(Gson.java:501) at com.google.gson.Gson.fromJson(Gson.java:990) at com.google.gson.Gson.fromJson(Gson.java:956) at com.google.gson.Gson.fromJson(Gson.java:905) at com.google.gson.Gson.fromJson(Gson.java:876) at com.oanda.v20.Context.execute(Context.java:303) at com.oanda.v20.pricing.PricingContext.get(PricingContext.java:179) at org.roboquant.oanda.OANDALiveFeed$subscribeOrderBook$3.invokeSuspend(OANDALiveFeed.kt:139) at kotlin.coroutines.jvm.internal.BaseContinuationImpl.resumeWith(ContinuationImpl.kt:33) at kotlinx.coroutines.DispatchedTask.run(DispatchedTask.kt:106) at kotlinx.coroutines.scheduling.CoroutineScheduler.runSafely(CoroutineScheduler.kt:570) at kotlinx.coroutines.scheduling.CoroutineScheduler$Worker.executeTask(CoroutineScheduler.kt:750) at kotlinx.coroutines.scheduling.CoroutineScheduler$Worker.runWorker(CoroutineScheduler.kt:677) at kotlinx.coroutines.scheduling.CoroutineScheduler$Worker.run(CoroutineScheduler.kt:664) Suppressed: kotlinx.coroutines.DiagnosticCoroutineContextException: [StandaloneCoroutine{Cancelling}@4d705c18, Dispatchers.Default] Caused by: java.lang.reflect.InaccessibleObjectException: Unable to make field private java.lang.String java.lang.Throwable.detailMessage accessible: module java.base does not "opens java.lang" to unnamed module @51a9ad5e at java.base/java.lang.reflect.AccessibleObject.throwInaccessibleObjectException(AccessibleObject.java:387) at java.base/java.lang.reflect.AccessibleObject.checkCanSetAccessible(AccessibleObject.java:363) at java.base/java.lang.reflect.AccessibleObject.checkCanSetAccessible(AccessibleObject.java:311) at java.base/java.lang.reflect.Field.checkCanSetAccessible(Field.java:180) at java.base/java.lang.reflect.Field.setAccessible(Field.java:174) at com.google.gson.internal.reflect.ReflectionHelper.makeAccessible(ReflectionHelper.java:19) ... 16 more

Hi, We've stumbled on a limitation that we haven't been able to circunvent while backtesting shorts. We are currently using BracketOrders for our trades, but the problem happens on every order type. When the sim broker updates the account and makes a withdraw, it actually increases the account's cash amount when we are shorting (which is consistent with the sell operation), but it is not something that happens in a real exchange. Do you have a suggestion regarding using short on the sim broker? Our current idea would be to create a new simbroker handling this. We could also try to support this on current simbroker.

Regards, Martin

Right now classic and lab notebooks render different. Classic notebooks use iframes for embedding HTML output while lab notebooks directly insert the HTML snippet. This makes it important that the environment is detected/set correctly otherwise the output is not rendered correctly.

Classic notebooks can also directly insert an HTML snippet, but somehow the echarts library doesn't load correctly when added it to the main HTML page. It only works in an iframe in a classic notebook.

possible reasons:

1. requirejs that is loaded in a classic notebook stops echarts from loading correctly
2. the load script that is generated by kotlin kernel contains a bug

Existing conversion methods in ZonedPeriod are assuming the underlying object will have specific units which is not true.

Example: 5.minutes.toMinutes() //Method threw 'java.time.temporal.UnsupportedTemporalTypeException' exception.

In that case the Duration object actually holds seconds. Instead, it will be better to use the existing conversion methods in the Java API itself.

Several places in the code base, documentation is missing or not complete. To see what is missing in a certain module, you can run:

mvn dokka:dokka -P release -pl roboquant

Before the 1.0 release, at least all key Classes and Interfaces in the core roboquant module should be well documented.

Hi, we are currently upgrading to the new version and found out that the tag property was removed from . We were using it to map client order id from Binance and we generally use it when syncyng different order types. Is this being replaced with something different? We are reading in our fork, and would happily create a PR for this but weren't sure about the rationale behind this.

When using time scale, the metric charts sometimes shows a wrong graph (one x value has multiple y values). When using the step scale all is fine. Can been seen using for example using Alpaca Live Feed provider during trading hours.

There is a mistake either in the captured metric data or more likely the chart itself cannot deal with very small differences in time (currently passed as a string).

When subscribing to assets in live feeds, it is sometime desirable to group actions together is they arrive closely after each other. Otherwise every action would result in its own event.

This could be implemented in the abstract base class LiveFeed by support a "queue" where actions are put before a timeout is triggered and send all of them in a single Event.

Right now the live-trading crypto broker are not fully implemented. Help would be welcome since limited exposure to crypto trading using Binance or other pure Crypto brokers.

Currently, AFAIK, roboquant only supports .csv local historical data.

However, this is not great in terms of storage efficiency, and there are many alternatives (e.g pickle, feather, parquet...) with various combinations of compressions (e.g. zip, gzip...).

Would it be possible to add native support for some of these other formats?

(Personally I use zip-compressed pickle as the best compromise between size and read/write times)

df.to_pickle('foo.pkl', compression='zip')

pd.read_pickle('foo.pkl', compression='zip')

For common and often used CSV files formats, have a pre-defined CSVConfig file that makes it convenient to parse those files without having to manually configure the CSVConfig.