- Move BacktestingFutureChainProvider provider to Lean.Engine.DataFeeds along with its options equivalent.
- EmptyFutureChainProvider: provider that returns an empty list of symbols
- CachingFutureChainProvider: implements caching by date
- BacktestingFutureChainProvider: provider that gets chain from local files
- LiveFutureChainProvider: provider that gets chain from external source (empty list of symbols for now)
Since we were not rounding off feeToPriceRatio, we were reducing order quantity more than needed in limit cases.
Fixes RegressionTests that were wrongly modified.
In quantity calculation, we didn't reduce the order quantity by decimal numbers, leading to a big step when dealing with crypto-currencies. For example, from 2.3456 it would drop to 1.3456 where values in between should've been tested.
Unlike other methods used to add securities to the algorithm that return a Security or a derived object, AddData was returning void. This commit change it to return Security for consistency.
Currently the HistoryRequest includes information regarding the tick type, but that information is not passed to the HistoryPacket. Therefore, only the common data types for a history request are returned for history requests. This is problematic for crypto history requests that specify Trade History.
Currently, Crypto security types are restrictied to history requests that return QuoteBars. This removes that restriction and allows Crypto securities to make TradeBar history requests.
Often users will request History with a string instead of a Symbol. Because of the implicit conversion between Symbol and string, this only works if the ticker has been first added to the algorithm as a security using a method like AddSecurity(), AddEquity() etc. This commit checks for failed implicit conversions in History request and returns an error message to the user that should better enable users to debug what has gone wrong.
Adding a scatter plot is an involved process because there's not
direct and easy way to just define a series object. This change
allows an algorithm to simply define the series without pumping
any data into it. This allows the user to set the series type and
the unit for the series
This change will make it easier to add other planned brokerage features:
for Interactive Brokers, besides Financial Advisor support, we will be adding IB algorithmic orders soon (PR #1203).
The properties in the default instance can be modified by users duing Initialize.
These properties are always copied into all new orders submitted with any method available (Order, SetHoldings, etc.)
This appears to be causing exceptions in travis when running the automated
test suite. I'm still unsure why it's only failing on this branch and not
on the master branch.
Creates a class that wraps a PyObject that represents a ISecurityInitializer object for the case where we use a class to initialize securities
Adds SetSecurityInitializer method that accepts a PyObject that may represent a method, a function or class that is used to initialize securities
ToFunc method is used to convert a PyObject that represents a method into a System.Func. Since this method will be used across different classes, we are moving it to PythonUtil class.
In this new nuget package, we have included two versions Python.Runtime.dll for macOS
We also add the instructions to compile pythonnet for different operational systems
Adds support for fee, fill and slippage custom modelling.
Adds CustomModelsAlgorithm to showcase the new feature
Modifies C# version of CustomModelsAlgorithm to match existing data in github
In python algorithm using Universe Selection, the selector method should return a List<Symbol>. To make it more pythonic, we allow returning python list. The conversion is, then, performed in C# side.
Michael