Files
quantconnect--lean/Engine/AlgorithmManager.cs
T
Martin-Molinero 83f9499b4a Option Margin Strategies (#5511)
* Refactor HasSufficientBuyingPowerForOrder implementations

Adds Sufficient and Insufficient helper methods to HashSufficientbuyingPowerForOrderParameters
enabling syntax like:

return paraeeters.Sufficient()
returnparameters.Insufficient(reason)

The next change will add the initial margin required which will simply require
updating both of these helper methods to accept the value.

* IBuyingPowerModel: Add margin functions Maintenance/Initial/ForOrder

These were originally hidden in an effort to only expose what's necessary
for the engine to perform its work. Additionally, we encapsulated all of
the method arguments into parameters classes to prevent having to break
anyone in the future. Not including these foundational methods turns out to
be an oversight. These methods are not required by the engine, but rather by
other models. Another possible solution here is to add an additional abstraction
and include these methods on this new abstraction. BuyingPowerModel would then
explicitly implement these methods and models that depend on them would require
two code paths, one for when the buying power model implements this interface
and another for when it doesn't.

Tests were additionally updated to remove test model implementations created for
the sole purpose of exposing these private methods.

* Add ConstantBuyingPowerModel

Provides an implementation of IBuyingPowerModel that returns the same
constant value

* Update BuyingPowerModelPythonWrapper to use reflection for method names

Having a bunch of hard-coded strings is a sure fire way for someone to
overlook when changing methods. This change ensures that noone needs to
remember that this code exists :)

Cleans up the syntax around verifying a python object implements a particular
C# interface via the ValidateImplementationOf<T> method by having it return a
value since the only use cases are in constructors when setting the models.

I was initially going to update ALL python wrappers to validate the passed
in models, but such a change could break many things that are 'working' right
now. Such an effort should be saved for its own dedicated PR.

* Add Parameters/Result types for new buying power model methods

* Support computing maintenance margin for arbitrary quantities

The existing GetMaintenanceMargin function assumes that we're only interested
in the maintenance margin for the entirety of the provided security's holdings.
This makes it impossible to perform what-if analysis or to even ask how much
maintenance margin is devoted to a particular subset of the security's holdings.
This change adds the quantity to the MaintenanceMarginParameters class. Futures
and Options models also depend on holdings cost and holdings value, so they have
also been added to the parameters type. Finally, static factory methods were
added to improve discernment of intent: ForCurrentHoldings provides the existing
behavior and then ForQuantityAtCurrentPrice to support what-if scenarios where
we're looking for the change in maintenance margin if we were to execute an order
for the securiy at the current time step. Obviously a constructor is provided to
set all of the values explicitly, using any price metric the caller desires.

* Address review

- Fix BPM xml documentation
- Fix python unit tests and PythonWrapper validate method

* Add SecurityHolding.QuantityChanged event

Adding event handlers will allow us to orchestrate complex
events from distant parts of the codebase through wiring
them up. If we continue down this path, it will move us away
from the current, very 'mechanical' data flows expressed in
LEAN and towards a more modern, event processing based system.
This is but a baby step in that direction and the initial use
case is using this QuantityChanged event to trigger resolution
of the algoritm's positions groups. This is part of an effort
to improve the fidelity of options margin modeling where we'll
model an OptionStrategy as an IPositionGroup. This will allow
us to compute the margin requirements of an OptionStrategy as
a unit instead of computing margin of each security individually
in isolation.

See #4065

* PortfolioManager: Group fields and remove unused field

This codebase generally places fields as the first members, but
this class had some fields at the top, then some properties, and
then some more fields. This change brings all the fields together
at the top of the file and also removes pointless comments placed
directly above some of the fields. Additionally, an unused field
was removed.

* Remove unused _currencyConverter from Security

Looks like at some point the only code using this member variable was removed
and the necessary clean up was overlooked.

* Add Parse.Enum functions

* Support disabling regression algorithms by language via config.json

Adds 'regression-test-languages' to config.json and filters regerssion algorithms to
run based on this value. When cycling on a particular feature, it's nice to be able
to run the entire regression set while ignoring the python algorithms. Once the C#
algorithms are all passing, one can then go back and run C# and Python in a final run,
since 99% of feature work doesn't impact python specifically.

* Implement IComparable in SecurityIdentitfier

This can be used to deterministically sort securities and symbols

* Add .editorconfig to enforce common formatting for json/sh files

* Fix typo in IBuyingPowerModel.GetBuyingPower xml docs

* Add ListEquals/GetListHashCode and OrderDirection.Closes(PositionSide)

ListEquals and GetListHashCode are designed to be used together as they
complement each other according to C#'s requirements for Equals and
GetHashCode functions.

PositionSide.ToOrderDirection() extension simply converts a PositionSide
to its logical equivalent OrderDirection. Long->Buy, Short->Sell, None->Hold

OrderDirection.Closes(PositionSide) determines if a particular OrderDirection
would have the effect of reducing a position's absolute size. This function
greatly improves the readability of buying power functions that must provide
adjustments when an order/contemplated trade reduces/closes an existing position.
OrderDirection.Buy.Closes(PositionSide.Short)
OrderDirection.Sell.Closes(PositionSide.Long)
All other combinations return false

Adds ToArray/ToImmutableArray convenience functions that combine a call
to Select followed by To(Immutable)Array all in one function call.

* Add decimal.DiscretelyRoundBy extension method

Supports rounding a decimal value by an arbitrarily chosen maximum precision,
or 'quanta'

* Update FutureMarginBuyingPowerModelTests to respect the security's lot size

* Add core position group classes and abstractions

* Add initial/maintenance margin support, buying power model consistency tests

* Add SufficientBuyingPower and GetReservedBuyingPower to position group model

Includes update to BrokerageTransactionHandler to use position group BPM for
sufficient buying power checks.

* Resolve position groups on each fill

We need to update the state of our position groups on each fill so that
we can properly handle multiple orders within the same time step. We
also limit the number of positions sent into the resolver by removing
securities without any holdings.

* fixup! Add SufficientBuyingPower and GetReservedBuyingPower to position group model

* Add GetMaximumLotsFor{Target|Delta}BuyingPower

Instead of computing order quantity, these functions compute the
maximum number of position group lots, which is the position group
quantity, and is guaranteed to be a whole number, for the provided
target/delta buying power parameters.

The SecurityPositionGroupBuyingPowerModel delegates to the security's
IBuyingPowerModel by applying a scaling factor equal to the security's
lot size.

This change also updates references to IBuyingPowerModel.GetMaximum...
to use the new position group model methods.

* Convert remaining IBuyingPowerModel call sites to position groups

* Rename PositionManasger.CreateDefaultGroup -> GetOrCreateDefaultGroup

Better describes its behavior

* Add Position Groups readme.md

* Add Option Strategy BuyingPowerModel

- Adding CompositePrositionGroupResolver and
  OptionStrategyPositionGroupResolver
- Adding OptionStrategyPositionGroupBuyingPowerModel handling option
  strategies based on IBs margin table. Adding regression algorithms
- Few changes so that option strategies executed by multiple orders are
  detected
- Adjust OptionStrategyDefinitionMatch to include equity legs in the
  matching result
- Minor tweaks fixing previous rebase
- Minor fixes for existing option strategies definitions, adding new
  missing strategies.
- Fixing minor bugs in option strategy matcher. Adding more unit tests

* Address self reviews

- Fixing bug in 'PositionGroupCollection'
- Few minor simplificaitons
- Adding BasicTemplateOptionEquityStrategyAlgorithm

* Address reviews

- Improve regression algorithms margin remaining and used assert logic to be exact. Taking into account spread and fees

Co-authored-by: Michael Handschuh <mhandschuh@gmail.com>
2021-04-30 18:45:27 -03:00

1248 lines
59 KiB
C#

/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using System;
using System.Collections.Generic;
using System.Linq;
using System.Threading;
using Fasterflect;
using QuantConnect.Algorithm;
using QuantConnect.Configuration;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Interfaces;
using QuantConnect.Lean.Engine.Alpha;
using QuantConnect.Lean.Engine.DataFeeds;
using QuantConnect.Lean.Engine.RealTime;
using QuantConnect.Lean.Engine.Results;
using QuantConnect.Lean.Engine.Server;
using QuantConnect.Lean.Engine.TransactionHandlers;
using QuantConnect.Logging;
using QuantConnect.Orders;
using QuantConnect.Packets;
using QuantConnect.Securities;
using QuantConnect.Util;
using QuantConnect.Securities.Option;
using QuantConnect.Securities.Volatility;
using QuantConnect.Util.RateLimit;
namespace QuantConnect.Lean.Engine
{
/// <summary>
/// Algorithm manager class executes the algorithm and generates and passes through the algorithm events.
/// </summary>
public class AlgorithmManager
{
private IAlgorithm _algorithm;
private readonly object _lock;
private readonly bool _liveMode;
/// <summary>
/// Publicly accessible algorithm status
/// </summary>
public AlgorithmStatus State => _algorithm?.Status ?? AlgorithmStatus.Running;
/// <summary>
/// Public access to the currently running algorithm id.
/// </summary>
public string AlgorithmId { get; private set; }
/// <summary>
/// Provides the isolator with a function for verifying that we're not spending too much time in each
/// algorithm manager time loop
/// </summary>
public AlgorithmTimeLimitManager TimeLimit { get; }
/// <summary>
/// Quit state flag for the running algorithm. When true the user has requested the backtest stops through a Quit() method.
/// </summary>
/// <seealso cref="QCAlgorithm.Quit(String)"/>
public bool QuitState => State == AlgorithmStatus.Deleted;
/// <summary>
/// Gets the number of data points processed per second
/// </summary>
public long DataPoints { get; private set; }
/// <summary>
/// Initializes a new instance of the <see cref="AlgorithmManager"/> class
/// </summary>
/// <param name="liveMode">True if we're running in live mode, false for backtest mode</param>
/// <param name="job">Provided by LEAN when creating a new algo manager. This is the job
/// that the algo manager is about to execute. Research and other consumers can provide the
/// default value of null</param>
public AlgorithmManager(bool liveMode, AlgorithmNodePacket job = null)
{
AlgorithmId = "";
_liveMode = liveMode;
_lock = new object();
// initialize the time limit manager
TimeLimit = new AlgorithmTimeLimitManager(
CreateTokenBucket(job?.Controls?.TrainingLimits),
TimeSpan.FromMinutes(Config.GetDouble("algorithm-manager-time-loop-maximum", 20))
);
}
/// <summary>
/// Launch the algorithm manager to run this strategy
/// </summary>
/// <param name="job">Algorithm job</param>
/// <param name="algorithm">Algorithm instance</param>
/// <param name="synchronizer">Instance which implements <see cref="ISynchronizer"/>. Used to stream the data</param>
/// <param name="transactions">Transaction manager object</param>
/// <param name="results">Result handler object</param>
/// <param name="realtime">Realtime processing object</param>
/// <param name="leanManager">ILeanManager implementation that is updated periodically with the IAlgorithm instance</param>
/// <param name="alphas">Alpha handler used to process algorithm generated insights</param>
/// <param name="token">Cancellation token</param>
/// <remarks>Modify with caution</remarks>
public void Run(AlgorithmNodePacket job, IAlgorithm algorithm, ISynchronizer synchronizer, ITransactionHandler transactions, IResultHandler results, IRealTimeHandler realtime, ILeanManager leanManager, IAlphaHandler alphas, CancellationToken token)
{
//Initialize:
DataPoints = 0;
_algorithm = algorithm;
var backtestMode = (job.Type == PacketType.BacktestNode);
var methodInvokers = new Dictionary<Type, MethodInvoker>();
var marginCallFrequency = TimeSpan.FromMinutes(5);
var nextMarginCallTime = DateTime.MinValue;
var settlementScanFrequency = TimeSpan.FromMinutes(30);
var nextSettlementScanTime = DateTime.MinValue;
var time = algorithm.StartDate.Date;
var delistings = new List<Delisting>();
var splitWarnings = new List<Split>();
//Initialize Properties:
AlgorithmId = job.AlgorithmId;
_algorithm.Status = AlgorithmStatus.Running;
//Create the method accessors to push generic types into algorithm: Find all OnData events:
// Algorithm 2.0 data accessors
var hasOnDataTradeBars = AddMethodInvoker<TradeBars>(algorithm, methodInvokers);
var hasOnDataQuoteBars = AddMethodInvoker<QuoteBars>(algorithm, methodInvokers);
var hasOnDataOptionChains = AddMethodInvoker<OptionChains>(algorithm, methodInvokers);
var hasOnDataTicks = AddMethodInvoker<Ticks>(algorithm, methodInvokers);
// dividend and split events
var hasOnDataDividends = AddMethodInvoker<Dividends>(algorithm, methodInvokers);
var hasOnDataSplits = AddMethodInvoker<Splits>(algorithm, methodInvokers);
var hasOnDataDelistings = AddMethodInvoker<Delistings>(algorithm, methodInvokers);
var hasOnDataSymbolChangedEvents = AddMethodInvoker<SymbolChangedEvents>(algorithm, methodInvokers);
//Go through the subscription types and create invokers to trigger the event handlers for each custom type:
foreach (var config in algorithm.SubscriptionManager.Subscriptions)
{
//If type is a custom feed, check for a dedicated event handler
if (config.IsCustomData)
{
//Get the matching method for this event handler - e.g. public void OnData(Quandl data) { .. }
var genericMethod = (algorithm.GetType()).GetMethod("OnData", new[] { config.Type });
//If we already have this Type-handler then don't add it to invokers again.
if (methodInvokers.ContainsKey(config.Type)) continue;
if (genericMethod != null)
{
methodInvokers.Add(config.Type, genericMethod.DelegateForCallMethod());
}
}
}
//Loop over the queues: get a data collection, then pass them all into relevent methods in the algorithm.
Log.Trace("AlgorithmManager.Run(): Begin DataStream - Start: " + algorithm.StartDate + " Stop: " + algorithm.EndDate);
foreach (var timeSlice in Stream(algorithm, synchronizer, results, token))
{
// reset our timer on each loop
TimeLimit.StartNewTimeStep();
//Check this backtest is still running:
if (_algorithm.Status != AlgorithmStatus.Running)
{
Log.Error($"AlgorithmManager.Run(): Algorithm state changed to {_algorithm.Status} at {timeSlice.Time.ToStringInvariant()}");
break;
}
//Execute with TimeLimit Monitor:
if (token.IsCancellationRequested)
{
Log.Error($"AlgorithmManager.Run(): CancellationRequestion at {timeSlice.Time.ToStringInvariant()}");
return;
}
// Update the ILeanManager
leanManager.Update();
time = timeSlice.Time;
DataPoints += timeSlice.DataPointCount;
// We need to sample at the top of the loop in case we have a strategy
// with no data added. Time pulses would be emitted between days, and
// would cause us to skip sampling of the portfolio in those dead days.
results.Sample(time);
if (backtestMode)
{
if (algorithm.Portfolio.TotalPortfolioValue <= 0)
{
var logMessage = "AlgorithmManager.Run(): Portfolio value is less than or equal to zero, stopping algorithm.";
Log.Error(logMessage);
results.SystemDebugMessage(logMessage);
break;
}
// If backtesting, we need to check if there are realtime events in the past
// which didn't fire because at the scheduled times there was no data (i.e. markets closed)
// and fire them with the correct date/time.
realtime.ScanPastEvents(time);
}
//Set the algorithm and real time handler's time
algorithm.SetDateTime(time);
// the time pulse are just to advance algorithm time, lets shortcut the loop here
if (timeSlice.IsTimePulse)
{
continue;
}
// Update the current slice before firing scheduled events or any other task
algorithm.SetCurrentSlice(timeSlice.Slice);
if (timeSlice.Slice.SymbolChangedEvents.Count != 0)
{
if (hasOnDataSymbolChangedEvents)
{
methodInvokers[typeof (SymbolChangedEvents)](algorithm, timeSlice.Slice.SymbolChangedEvents);
}
foreach (var symbol in timeSlice.Slice.SymbolChangedEvents.Keys)
{
// cancel all orders for the old symbol
foreach (var ticket in transactions.GetOpenOrderTickets(x => x.Symbol == symbol))
{
ticket.Cancel("Open order cancelled on symbol changed event");
}
}
}
if (timeSlice.SecurityChanges != SecurityChanges.None)
{
foreach (var security in timeSlice.SecurityChanges.AddedSecurities)
{
security.IsTradable = true;
// uses TryAdd, so don't need to worry about duplicates here
algorithm.Securities.Add(security);
}
var activeSecurities = algorithm.UniverseManager.ActiveSecurities;
foreach (var security in timeSlice.SecurityChanges.RemovedSecurities)
{
if (!activeSecurities.ContainsKey(security.Symbol))
{
security.IsTradable = false;
}
}
realtime.OnSecuritiesChanged(timeSlice.SecurityChanges);
results.OnSecuritiesChanged(timeSlice.SecurityChanges);
}
//Update the securities properties: first before calling user code to avoid issues with data
foreach (var update in timeSlice.SecuritiesUpdateData)
{
var security = update.Target;
security.Update(update.Data, update.DataType, update.ContainsFillForwardData);
if (!update.IsInternalConfig)
{
// Send market price updates to the TradeBuilder
algorithm.TradeBuilder.SetMarketPrice(security.Symbol, security.Price);
}
}
//Update the securities properties with any universe data
if (timeSlice.UniverseData.Count > 0)
{
foreach (var kvp in timeSlice.UniverseData)
{
foreach (var data in kvp.Value.Data)
{
Security security;
if (algorithm.Securities.TryGetValue(data.Symbol, out security))
{
security.Cache.StoreData(new[] {data}, data.GetType());
}
}
}
}
// poke each cash object to update from the recent security data
foreach (var kvp in algorithm.Portfolio.CashBook)
{
var cash = kvp.Value;
var updateData = cash.ConversionRateSecurity?.GetLastData();
if (updateData != null)
{
cash.Update(updateData);
}
}
// security prices got updated
algorithm.Portfolio.InvalidateTotalPortfolioValue();
// fire real time events after we've updated based on the new data
realtime.SetTime(timeSlice.Time);
// process fill models on the updated data before entering algorithm, applies to all non-market orders
transactions.ProcessSynchronousEvents();
// process end of day delistings
ProcessDelistedSymbols(algorithm, delistings);
// process split warnings for options
ProcessSplitSymbols(algorithm, splitWarnings, delistings);
//Check if the user's signalled Quit: loop over data until day changes.
if (algorithm.Status == AlgorithmStatus.Stopped)
{
Log.Trace("AlgorithmManager.Run(): Algorithm quit requested.");
break;
}
if (algorithm.RunTimeError != null)
{
_algorithm.Status = AlgorithmStatus.RuntimeError;
Log.Trace($"AlgorithmManager.Run(): Algorithm encountered a runtime error at {timeSlice.Time.ToStringInvariant()}. Error: {algorithm.RunTimeError}");
return;
}
// perform margin calls, in live mode we can also use realtime to emit these
if (time >= nextMarginCallTime || (_liveMode && nextMarginCallTime > DateTime.UtcNow))
{
// determine if there are possible margin call orders to be executed
bool issueMarginCallWarning;
var marginCallOrders = algorithm.Portfolio.MarginCallModel.GetMarginCallOrders(out issueMarginCallWarning);
if (marginCallOrders.Count != 0)
{
var executingMarginCall = false;
try
{
// tell the algorithm we're about to issue the margin call
algorithm.OnMarginCall(marginCallOrders);
executingMarginCall = true;
// execute the margin call orders
var executedTickets = algorithm.Portfolio.MarginCallModel.ExecuteMarginCall(marginCallOrders);
foreach (var ticket in executedTickets)
{
algorithm.Error($"{algorithm.Time.ToStringInvariant()} - Executed MarginCallOrder: {ticket.Symbol} - " +
$"Quantity: {ticket.Quantity.ToStringInvariant()} @ {ticket.AverageFillPrice.ToStringInvariant()}"
);
}
}
catch (Exception err)
{
algorithm.RunTimeError = err;
_algorithm.Status = AlgorithmStatus.RuntimeError;
var locator = executingMarginCall ? "Portfolio.MarginCallModel.ExecuteMarginCall" : "OnMarginCall";
Log.Error($"AlgorithmManager.Run(): RuntimeError: {locator}: {err}");
return;
}
}
// we didn't perform a margin call, but got the warning flag back, so issue the warning to the algorithm
else if (issueMarginCallWarning)
{
try
{
algorithm.OnMarginCallWarning();
}
catch (Exception err)
{
algorithm.RunTimeError = err;
_algorithm.Status = AlgorithmStatus.RuntimeError;
Log.Error("AlgorithmManager.Run(): RuntimeError: OnMarginCallWarning: " + err);
return;
}
}
nextMarginCallTime = time + marginCallFrequency;
}
// perform check for settlement of unsettled funds
if (time >= nextSettlementScanTime || (_liveMode && nextSettlementScanTime > DateTime.UtcNow))
{
algorithm.Portfolio.ScanForCashSettlement(algorithm.UtcTime);
nextSettlementScanTime = time + settlementScanFrequency;
}
// before we call any events, let the algorithm know about universe changes
if (timeSlice.SecurityChanges != SecurityChanges.None)
{
try
{
var algorithmSecurityChanges = new SecurityChanges(timeSlice.SecurityChanges)
{
// by default for user code we want to filter out custom securities
FilterCustomSecurities = true
};
algorithm.OnSecuritiesChanged(algorithmSecurityChanges);
algorithm.OnFrameworkSecuritiesChanged(algorithmSecurityChanges);
}
catch (Exception err)
{
algorithm.RunTimeError = err;
_algorithm.Status = AlgorithmStatus.RuntimeError;
Log.Error("AlgorithmManager.Run(): RuntimeError: OnSecuritiesChanged event: " + err);
return;
}
}
// apply dividends
foreach (var dividend in timeSlice.Slice.Dividends.Values)
{
Log.Debug($"AlgorithmManager.Run(): {algorithm.Time}: Applying Dividend: {dividend}");
Security security = null;
if (_liveMode && algorithm.Securities.TryGetValue(dividend.Symbol, out security))
{
Log.Trace($"AlgorithmManager.Run(): {algorithm.Time}: Pre-Dividend: {dividend}. " +
$"Security Holdings: {security.Holdings.Quantity} Account Currency Holdings: " +
$"{algorithm.Portfolio.CashBook[algorithm.AccountCurrency].Amount}");
}
var mode = algorithm.SubscriptionManager.SubscriptionDataConfigService
.GetSubscriptionDataConfigs(dividend.Symbol)
.DataNormalizationMode();
// apply the dividend event to the portfolio
algorithm.Portfolio.ApplyDividend(dividend, _liveMode, mode);
if (_liveMode && security != null)
{
Log.Trace($"AlgorithmManager.Run(): {algorithm.Time}: Post-Dividend: {dividend}. Security " +
$"Holdings: {security.Holdings.Quantity} Account Currency Holdings: " +
$"{algorithm.Portfolio.CashBook[algorithm.AccountCurrency].Amount}");
}
}
// apply splits
foreach (var split in timeSlice.Slice.Splits.Values)
{
try
{
// only process split occurred events (ignore warnings)
if (split.Type != SplitType.SplitOccurred)
{
continue;
}
Log.Debug($"AlgorithmManager.Run(): {algorithm.Time}: Applying Split for {split.Symbol}");
Security security = null;
if (_liveMode && algorithm.Securities.TryGetValue(split.Symbol, out security))
{
Log.Trace($"AlgorithmManager.Run(): {algorithm.Time}: Pre-Split for {split}. Security Price: {security.Price} Holdings: {security.Holdings.Quantity}");
}
var mode = algorithm.SubscriptionManager.SubscriptionDataConfigService
.GetSubscriptionDataConfigs(split.Symbol)
.DataNormalizationMode();
// apply the split event to the portfolio
algorithm.Portfolio.ApplySplit(split, _liveMode, mode);
if (_liveMode && security != null)
{
Log.Trace($"AlgorithmManager.Run(): {algorithm.Time}: Post-Split for {split}. Security Price: {security.Price} Holdings: {security.Holdings.Quantity}");
}
// apply the split to open orders as well in raw mode, all other modes are split adjusted
if (_liveMode || mode == DataNormalizationMode.Raw)
{
// in live mode we always want to have our order match the order at the brokerage, so apply the split to the orders
var openOrders = transactions.GetOpenOrderTickets(ticket => ticket.Symbol == split.Symbol);
algorithm.BrokerageModel.ApplySplit(openOrders.ToList(), split);
}
}
catch (Exception err)
{
algorithm.RunTimeError = err;
_algorithm.Status = AlgorithmStatus.RuntimeError;
Log.Error("AlgorithmManager.Run(): RuntimeError: Split event: " + err);
return;
}
}
//Update registered consolidators for this symbol index
try
{
if (timeSlice.ConsolidatorUpdateData.Count > 0)
{
var timeKeeper = algorithm.TimeKeeper;
foreach (var update in timeSlice.ConsolidatorUpdateData)
{
var localTime = timeKeeper.GetLocalTimeKeeper(update.Target.ExchangeTimeZone).LocalTime;
var consolidators = update.Target.Consolidators;
foreach (var consolidator in consolidators)
{
foreach (var dataPoint in update.Data)
{
// only push data into consolidators on the native, subscribed to resolution
if (EndTimeIsInNativeResolution(update.Target, dataPoint.EndTime))
{
consolidator.Update(dataPoint);
}
}
// scan for time after we've pumped all the data through for this consolidator
consolidator.Scan(localTime);
}
}
}
}
catch (Exception err)
{
algorithm.RunTimeError = err;
_algorithm.Status = AlgorithmStatus.RuntimeError;
Log.Error("AlgorithmManager.Run(): RuntimeError: Consolidators update: " + err);
return;
}
// fire custom event handlers
foreach (var update in timeSlice.CustomData)
{
MethodInvoker methodInvoker;
if (!methodInvokers.TryGetValue(update.DataType, out methodInvoker))
{
continue;
}
try
{
foreach (var dataPoint in update.Data)
{
if (update.DataType.IsInstanceOfType(dataPoint))
{
methodInvoker(algorithm, dataPoint);
}
}
}
catch (Exception err)
{
algorithm.RunTimeError = err;
_algorithm.Status = AlgorithmStatus.RuntimeError;
Log.Error("AlgorithmManager.Run(): RuntimeError: Custom Data: " + err);
return;
}
}
try
{
// fire off the dividend and split events before pricing events
if (hasOnDataDividends && timeSlice.Slice.Dividends.Count != 0)
{
methodInvokers[typeof(Dividends)](algorithm, timeSlice.Slice.Dividends);
}
if (hasOnDataSplits && timeSlice.Slice.Splits.Count != 0)
{
methodInvokers[typeof(Splits)](algorithm, timeSlice.Slice.Splits);
}
if (hasOnDataDelistings && timeSlice.Slice.Delistings.Count != 0)
{
methodInvokers[typeof(Delistings)](algorithm, timeSlice.Slice.Delistings);
}
}
catch (Exception err)
{
algorithm.RunTimeError = err;
_algorithm.Status = AlgorithmStatus.RuntimeError;
Log.Error("AlgorithmManager.Run(): RuntimeError: Dividends/Splits/Delistings: " + err);
return;
}
// run the delisting logic after firing delisting events
HandleDelistedSymbols(algorithm, timeSlice.Slice.Delistings, delistings);
// run split logic after firing split events
HandleSplitSymbols(timeSlice.Slice.Splits, splitWarnings);
//After we've fired all other events in this second, fire the pricing events:
try
{
if (hasOnDataTradeBars && timeSlice.Slice.Bars.Count > 0) methodInvokers[typeof(TradeBars)](algorithm, timeSlice.Slice.Bars);
if (hasOnDataQuoteBars && timeSlice.Slice.QuoteBars.Count > 0) methodInvokers[typeof(QuoteBars)](algorithm, timeSlice.Slice.QuoteBars);
if (hasOnDataOptionChains && timeSlice.Slice.OptionChains.Count > 0) methodInvokers[typeof(OptionChains)](algorithm, timeSlice.Slice.OptionChains);
if (hasOnDataTicks && timeSlice.Slice.Ticks.Count > 0) methodInvokers[typeof(Ticks)](algorithm, timeSlice.Slice.Ticks);
}
catch (Exception err)
{
algorithm.RunTimeError = err;
_algorithm.Status = AlgorithmStatus.RuntimeError;
Log.Error("AlgorithmManager.Run(): RuntimeError: New Style Mode: " + err);
return;
}
try
{
if (timeSlice.Slice.HasData)
{
// EVENT HANDLER v3.0 -- all data in a single event
algorithm.OnData(timeSlice.Slice);
}
// always turn the crank on this method to ensure universe selection models function properly on day changes w/out data
algorithm.OnFrameworkData(timeSlice.Slice);
}
catch (Exception err)
{
algorithm.RunTimeError = err;
_algorithm.Status = AlgorithmStatus.RuntimeError;
Log.Error("AlgorithmManager.Run(): RuntimeError: Slice: " + err);
return;
}
//If its the historical/paper trading models, wait until market orders have been "filled"
// Manually trigger the event handler to prevent thread switch.
transactions.ProcessSynchronousEvents();
// sample alpha charts now that we've updated time/price information and after transactions
// are processed so that insights closed because of new order based insights get updated
alphas.ProcessSynchronousEvents();
// send the alpha statistics to the result handler for storage/transmit with the result packets
results.SetAlphaRuntimeStatistics(alphas.RuntimeStatistics);
// Process any required events of the results handler such as sampling assets, equity, or stock prices.
results.ProcessSynchronousEvents();
// poke the algorithm at the end of each time step
algorithm.OnEndOfTimeStep();
} // End of ForEach feed.Bridge.GetConsumingEnumerable
// stop timing the loops
TimeLimit.StopEnforcingTimeLimit();
//Stream over:: Send the final packet and fire final events:
Log.Trace("AlgorithmManager.Run(): Firing On End Of Algorithm...");
try
{
algorithm.OnEndOfAlgorithm();
}
catch (Exception err)
{
_algorithm.Status = AlgorithmStatus.RuntimeError;
algorithm.RunTimeError = new Exception("Error running OnEndOfAlgorithm(): " + err.Message, err.InnerException);
Log.Error("AlgorithmManager.OnEndOfAlgorithm(): " + err);
return;
}
// final processing now that the algorithm has completed
alphas.ProcessSynchronousEvents();
// send the final alpha statistics to the result handler for storage/transmit with the result packets
results.SetAlphaRuntimeStatistics(alphas.RuntimeStatistics);
// Process any required events of the results handler such as sampling assets, equity, or stock prices.
results.ProcessSynchronousEvents(forceProcess: true);
//Liquidate Holdings for Calculations:
if (_algorithm.Status == AlgorithmStatus.Liquidated && _liveMode)
{
Log.Trace("AlgorithmManager.Run(): Liquidating algorithm holdings...");
algorithm.Liquidate();
results.LogMessage("Algorithm Liquidated");
results.SendStatusUpdate(AlgorithmStatus.Liquidated);
}
//Manually stopped the algorithm
if (_algorithm.Status == AlgorithmStatus.Stopped)
{
Log.Trace("AlgorithmManager.Run(): Stopping algorithm...");
results.LogMessage("Algorithm Stopped");
results.SendStatusUpdate(AlgorithmStatus.Stopped);
}
//Backtest deleted.
if (_algorithm.Status == AlgorithmStatus.Deleted)
{
Log.Trace("AlgorithmManager.Run(): Deleting algorithm...");
results.DebugMessage("Algorithm Id:(" + job.AlgorithmId + ") Deleted by request.");
results.SendStatusUpdate(AlgorithmStatus.Deleted);
}
//Algorithm finished, send regardless of commands:
results.SendStatusUpdate(AlgorithmStatus.Completed);
SetStatus(AlgorithmStatus.Completed);
//Take final samples:
results.Sample(time, force: true);
} // End of Run();
/// <summary>
/// Set the quit state.
/// </summary>
public void SetStatus(AlgorithmStatus state)
{
lock (_lock)
{
//We don't want anyone else to set our internal state to "Running".
//This is controlled by the algorithm private variable only.
//Algorithm could be null after it's initialized and they call Run on us
if (state != AlgorithmStatus.Running && _algorithm != null)
{
_algorithm.Status = state;
}
}
}
private IEnumerable<TimeSlice> Stream(IAlgorithm algorithm, ISynchronizer synchronizer, IResultHandler results, CancellationToken cancellationToken)
{
bool setStartTime = false;
var timeZone = algorithm.TimeZone;
var history = algorithm.HistoryProvider;
// fulfilling history requirements of volatility models in live mode
if (algorithm.LiveMode)
{
ProcessVolatilityHistoryRequirements(algorithm);
}
// get the required history job from the algorithm
DateTime? lastHistoryTimeUtc = null;
var historyRequests = algorithm.GetWarmupHistoryRequests().ToList();
// initialize variables for progress computation
var warmUpStartTicks = DateTime.UtcNow.Ticks;
var nextStatusTime = DateTime.UtcNow.AddSeconds(1);
var minimumIncrement = algorithm.UniverseManager
.Select(x => x.Value.UniverseSettings?.Resolution.ToTimeSpan() ?? algorithm.UniverseSettings.Resolution.ToTimeSpan())
.DefaultIfEmpty(Time.OneSecond)
.Min();
minimumIncrement = minimumIncrement == TimeSpan.Zero ? Time.OneSecond : minimumIncrement;
if (historyRequests.Count != 0)
{
// rewrite internal feed requests
var subscriptions = algorithm.SubscriptionManager.Subscriptions.Where(x => !x.IsInternalFeed).ToList();
var minResolution = subscriptions.Count > 0 ? subscriptions.Min(x => x.Resolution) : Resolution.Second;
foreach (var request in historyRequests)
{
Security security;
if (algorithm.Securities.TryGetValue(request.Symbol, out security) && security.IsInternalFeed())
{
if (request.Resolution < minResolution)
{
request.Resolution = minResolution;
request.FillForwardResolution = request.FillForwardResolution.HasValue ? minResolution : (Resolution?) null;
}
}
}
// rewrite all to share the same fill forward resolution
if (historyRequests.Any(x => x.FillForwardResolution.HasValue))
{
minResolution = historyRequests.Where(x => x.FillForwardResolution.HasValue).Min(x => x.FillForwardResolution.Value);
foreach (var request in historyRequests.Where(x => x.FillForwardResolution.HasValue))
{
request.FillForwardResolution = minResolution;
}
}
foreach (var request in historyRequests)
{
warmUpStartTicks = Math.Min(request.StartTimeUtc.Ticks, warmUpStartTicks);
Log.Trace($"AlgorithmManager.Stream(): WarmupHistoryRequest: {request.Symbol}: Start: {request.StartTimeUtc} End: {request.EndTimeUtc} Resolution: {request.Resolution}");
}
var timeSliceFactory = new TimeSliceFactory(timeZone);
// make the history request and build time slices
foreach (var slice in history.GetHistory(historyRequests, timeZone))
{
TimeSlice timeSlice;
try
{
// we need to recombine this slice into a time slice
var paired = new List<DataFeedPacket>();
foreach (var symbol in slice.Keys)
{
var security = algorithm.Securities[symbol];
var data = slice[symbol];
var list = new List<BaseData>();
Type dataType;
var ticks = data as List<Tick>;
if (ticks != null)
{
list.AddRange(ticks);
dataType = typeof(Tick);
}
else
{
list.Add(data);
dataType = data.GetType();
}
var config = algorithm.SubscriptionManager.SubscriptionDataConfigService
.GetSubscriptionDataConfigs(symbol, includeInternalConfigs: true)
.FirstOrDefault(subscription => dataType.IsAssignableFrom(subscription.Type));
if (config == null)
{
throw new Exception($"A data subscription for type '{dataType.Name}' was not found.");
}
paired.Add(new DataFeedPacket(security, config, list));
}
timeSlice = timeSliceFactory.Create(slice.Time.ConvertToUtc(timeZone), paired, SecurityChanges.None, new Dictionary<Universe, BaseDataCollection>());
}
catch (Exception err)
{
Log.Error(err);
algorithm.RunTimeError = err;
yield break;
}
if (timeSlice != null)
{
if (!setStartTime)
{
setStartTime = true;
algorithm.Debug("Algorithm warming up...");
}
if (DateTime.UtcNow > nextStatusTime)
{
// send some status to the user letting them know we're done history, but still warming up,
// catching up to real time data
nextStatusTime = DateTime.UtcNow.AddSeconds(1);
var percent = (int)(100 * (timeSlice.Time.Ticks - warmUpStartTicks) / (double)(DateTime.UtcNow.Ticks - warmUpStartTicks));
results.SendStatusUpdate(AlgorithmStatus.History, $"Catching up to realtime {percent}%...");
}
yield return timeSlice;
lastHistoryTimeUtc = timeSlice.Time;
}
}
}
// if we're not live or didn't event request warmup, then set us as not warming up
if (!algorithm.LiveMode || historyRequests.Count == 0)
{
algorithm.SetFinishedWarmingUp();
if (historyRequests.Count != 0)
{
algorithm.Debug("Algorithm finished warming up.");
Log.Trace("AlgorithmManager.Stream(): Finished warmup");
}
}
foreach (var timeSlice in synchronizer.StreamData(cancellationToken))
{
if (algorithm.LiveMode && algorithm.IsWarmingUp)
{
if (timeSlice.IsTimePulse)
{
continue;
}
// this is hand-over logic, we spin up the data feed first and then request
// the history for warmup, so there will be some overlap between the data
if (lastHistoryTimeUtc.HasValue)
{
// make sure there's no historical data, this only matters for the handover
var hasHistoricalData = false;
foreach (var data in timeSlice.Slice.Ticks.Values.SelectMany(x => x).Concat<BaseData>(timeSlice.Slice.Bars.Values))
{
// check if any ticks in the list are on or after our last warmup point, if so, skip this data
if (data.EndTime.ConvertToUtc(algorithm.Securities[data.Symbol].Exchange.TimeZone) >= lastHistoryTimeUtc)
{
hasHistoricalData = true;
break;
}
}
if (hasHistoricalData)
{
continue;
}
// prevent us from doing these checks every loop
lastHistoryTimeUtc = null;
}
// in live mode wait to mark us as finished warming up when
// the data feed has caught up to now within the min increment
if (timeSlice.Time > DateTime.UtcNow.Subtract(minimumIncrement))
{
algorithm.SetFinishedWarmingUp();
algorithm.Debug("Algorithm finished warming up.");
Log.Trace("AlgorithmManager.Stream(): Finished warmup");
}
else if (DateTime.UtcNow > nextStatusTime)
{
// send some status to the user letting them know we're done history, but still warming up,
// catching up to real time data
nextStatusTime = DateTime.UtcNow.AddSeconds(1);
var percent = (int) (100*(timeSlice.Time.Ticks - warmUpStartTicks)/(double) (DateTime.UtcNow.Ticks - warmUpStartTicks));
results.SendStatusUpdate(AlgorithmStatus.History, $"Catching up to realtime {percent}%...");
}
}
yield return timeSlice;
}
}
/// <summary>
/// Helper method used to process securities volatility history requirements
/// </summary>
/// <remarks>Implemented as static to facilitate testing</remarks>
/// <param name="algorithm">The algorithm instance</param>
public static void ProcessVolatilityHistoryRequirements(IAlgorithm algorithm)
{
Log.Trace("ProcessVolatilityHistoryRequirements(): Updating volatility models with historical data...");
foreach (var kvp in algorithm.Securities)
{
var security = kvp.Value;
if (security.VolatilityModel != VolatilityModel.Null)
{
// start: this is a work around to maintain retro compatibility
// did not want to add IVolatilityModel.SetSubscriptionDataConfigProvider
// to prevent breaking existing user models.
var baseType = security.VolatilityModel as BaseVolatilityModel;
baseType?.SetSubscriptionDataConfigProvider(
algorithm.SubscriptionManager.SubscriptionDataConfigService);
// end
var historyReq = security.VolatilityModel.GetHistoryRequirements(security, algorithm.UtcTime);
if (historyReq != null && algorithm.HistoryProvider != null)
{
var history = algorithm.HistoryProvider.GetHistory(historyReq, algorithm.TimeZone);
if (history != null)
{
foreach (var slice in history)
{
if (slice.Bars.ContainsKey(security.Symbol))
security.VolatilityModel.Update(security, slice.Bars[security.Symbol]);
}
}
}
}
}
Log.Trace("ProcessVolatilityHistoryRequirements(): finished.");
}
/// <summary>
/// Adds a method invoker if the method exists to the method invokers dictionary
/// </summary>
/// <typeparam name="T">The data type to check for 'OnData(T data)</typeparam>
/// <param name="algorithm">The algorithm instance</param>
/// <param name="methodInvokers">The dictionary of method invokers</param>
/// <param name="methodName">The name of the method to search for</param>
/// <returns>True if the method existed and was added to the collection</returns>
private bool AddMethodInvoker<T>(IAlgorithm algorithm, Dictionary<Type, MethodInvoker> methodInvokers, string methodName = "OnData")
{
var newSplitMethodInfo = algorithm.GetType().GetMethod(methodName, new[] {typeof (T)});
if (newSplitMethodInfo != null)
{
methodInvokers.Add(typeof(T), newSplitMethodInfo.DelegateForCallMethod());
return true;
}
return false;
}
/// <summary>
/// Performs delisting logic for the securities specified in <paramref name="newDelistings"/> that are marked as <see cref="DelistingType.Delisted"/>.
/// </summary>
private static void HandleDelistedSymbols(IAlgorithm algorithm, Delistings newDelistings, List<Delisting> delistings)
{
foreach (var delisting in newDelistings.Values)
{
Log.Trace($"AlgorithmManager.HandleDelistedSymbols(): Delisting {delisting.Type}: {delisting.Symbol.Value}, UtcTime: {algorithm.UtcTime}, DelistingTime: {delisting.Time}");
if (algorithm.LiveMode)
{
// skip automatic handling of delisting event in live trading
// Lean will not exercise, liquidate or cancel open orders
continue;
}
// submit an order to liquidate on market close
if (delisting.Type == DelistingType.Warning)
{
if (delistings.All(x => x.Symbol != delisting.Symbol))
{
delistings.Add(delisting);
}
}
else
{
// mark security as no longer tradable
var security = algorithm.Securities[delisting.Symbol];
security.IsTradable = false;
security.IsDelisted = true;
// the subscription are getting removed from the data feed because they end
// remove security from all universes
foreach (var ukvp in algorithm.UniverseManager)
{
var universe = ukvp.Value;
if (universe.ContainsMember(security.Symbol))
{
var userUniverse = universe as UserDefinedUniverse;
if (userUniverse != null)
{
userUniverse.Remove(security.Symbol);
}
else
{
universe.RemoveMember(algorithm.UtcTime, security);
}
}
}
var cancelledOrders = algorithm.Transactions.CancelOpenOrders(delisting.Symbol);
foreach (var cancelledOrder in cancelledOrders)
{
Log.Trace("AlgorithmManager.Run(): " + cancelledOrder);
}
}
}
}
/// <summary>
/// Performs actual delisting of the contracts in delistings collection
/// </summary>
private static void ProcessDelistedSymbols(IAlgorithm algorithm, List<Delisting> delistings)
{
for (var i = delistings.Count - 1; i >= 0; i--)
{
var delisting = delistings[i];
var security = algorithm.Securities[delisting.Symbol];
if (security.Holdings.Quantity == 0)
{
continue;
}
if (security.LocalTime < delisting.GetLiquidationTime(security.Exchange.Hours))
{
continue;
}
// if there is any delisting event for a symbol that we are the underlying for and we are still invested retry
// they will by liquidated first
if (delistings.Any(delistingEvent => delistingEvent.Symbol.Underlying == security.Symbol
&& algorithm.Securities[delistingEvent.Symbol].Invested))
{
// this case could happen for example if we have a future 'A' position open and a future option position with underlying 'A'
// and both get delisted on the same date, we will allow the FOP exercise order to get handled first
continue;
}
var orderType = OrderType.Market;
var tag = "Liquidate from delisting";
if (security.Type.IsOption())
{
// tx handler will determine auto exercise/assignment
tag = "Option Expired";
orderType = OrderType.OptionExercise;
}
// submit an order to liquidate on market close or exercise (for options)
var request = new SubmitOrderRequest(orderType, security.Type, security.Symbol,
-security.Holdings.Quantity, 0, 0, algorithm.UtcTime, tag);
delistings.RemoveAt(i);
algorithm.Transactions.ProcessRequest(request);
// don't allow users to open a new position once we sent the liquidation order
security.IsTradable = false;
}
}
/// <summary>
/// Keeps track of split warnings so we can later liquidate option contracts
/// </summary>
private void HandleSplitSymbols(Splits newSplits, List<Split> splitWarnings)
{
foreach (var split in newSplits.Values)
{
if (split.Type != SplitType.Warning)
{
Log.Trace($"AlgorithmManager.HandleSplitSymbols(): {_algorithm.Time} - Security split occurred: Split Factor: {split} Reference Price: {split.ReferencePrice}");
continue;
}
Log.Trace($"AlgorithmManager.HandleSplitSymbols(): {_algorithm.Time} - Security split warning: {split}");
if (!splitWarnings.Any(x => x.Symbol == split.Symbol && x.Type == SplitType.Warning))
{
splitWarnings.Add(split);
}
}
}
/// <summary>
/// Liquidate option contact holdings who's underlying security has split
/// </summary>
private void ProcessSplitSymbols(IAlgorithm algorithm, List<Split> splitWarnings, List<Delisting> delistings)
{
// NOTE: This method assumes option contracts have the same core trading hours as their underlying contract
// This is a small performance optimization to prevent scanning every contract on every time step,
// instead we scan just the underlyings, thereby reducing the time footprint of this methods by a factor
// of N, the number of derivative subscriptions
for (int i = splitWarnings.Count - 1; i >= 0; i--)
{
var split = splitWarnings[i];
var security = algorithm.Securities[split.Symbol];
if (!security.IsTradable
&& !algorithm.UniverseManager.ActiveSecurities.Keys.Contains(split.Symbol))
{
Log.Debug($"AlgorithmManager.ProcessSplitSymbols(): {_algorithm.Time} - Removing split warning for {security.Symbol}");
// remove the warning from out list
splitWarnings.RemoveAt(i);
// Since we are storing the split warnings for a loop
// we need to check if the security was removed.
// When removed, it will be marked as non tradable but just in case
// we expect it not to be an active security either
continue;
}
var nextMarketClose = security.Exchange.Hours.GetNextMarketClose(security.LocalTime, false);
// determine the latest possible time we can submit a MOC order
var configs = algorithm.SubscriptionManager.SubscriptionDataConfigService
.GetSubscriptionDataConfigs(security.Symbol);
if (configs.Count == 0)
{
// should never happen at this point, if it does let's give some extra info
throw new Exception(
$"AlgorithmManager.ProcessSplitSymbols(): {_algorithm.Time} - No subscriptions found for {security.Symbol}" +
$", IsTradable: {security.IsTradable}" +
$", Active: {algorithm.UniverseManager.ActiveSecurities.Keys.Contains(split.Symbol)}");
}
var latestMarketOnCloseTimeRoundedDownByResolution = nextMarketClose.Subtract(MarketOnCloseOrder.DefaultSubmissionTimeBuffer)
.RoundDownInTimeZone(configs.GetHighestResolution().ToTimeSpan(), security.Exchange.TimeZone, configs.First().DataTimeZone);
// we don't need to do anyhing until the market closes
if (security.LocalTime < latestMarketOnCloseTimeRoundedDownByResolution) continue;
// fetch all option derivatives of the underlying with holdings (excluding the canonical security)
var derivatives = algorithm.Securities.Where(kvp => kvp.Key.HasUnderlying &&
kvp.Key.SecurityType.IsOption() &&
kvp.Key.Underlying == security.Symbol &&
!kvp.Key.Underlying.IsCanonical() &&
kvp.Value.HoldStock
);
foreach (var kvp in derivatives)
{
var optionContractSymbol = kvp.Key;
var optionContractSecurity = (Option) kvp.Value;
if (delistings.Any(x => x.Symbol == optionContractSymbol
&& x.Time.Date == optionContractSecurity.LocalTime.Date))
{
// if the option is going to be delisted today we skip sending the market on close order
continue;
}
// close any open orders
algorithm.Transactions.CancelOpenOrders(optionContractSymbol, "Canceled due to impending split. Separate MarketOnClose order submitted to liquidate position.");
var request = new SubmitOrderRequest(OrderType.MarketOnClose, optionContractSecurity.Type, optionContractSymbol,
-optionContractSecurity.Holdings.Quantity, 0, 0, algorithm.UtcTime,
"Liquidated due to impending split. Option splits are not currently supported."
);
// send MOC order to liquidate option contract holdings
algorithm.Transactions.AddOrder(request);
// mark option contract as not tradable
optionContractSecurity.IsTradable = false;
algorithm.Debug($"MarketOnClose order submitted for option contract '{optionContractSymbol}' due to impending {split.Symbol.Value} split event. "
+ "Option splits are not currently supported.");
}
// remove the warning from out list
splitWarnings.RemoveAt(i);
}
}
/// <summary>
/// Determines if a data point is in it's native, configured resolution
/// </summary>
private static bool EndTimeIsInNativeResolution(SubscriptionDataConfig config, DateTime dataPointEndTime)
{
if (config.Resolution == Resolution.Tick
||
// time zones don't change seconds or milliseconds so we can
// shortcut timezone conversions
(config.Resolution == Resolution.Second
|| config.Resolution == Resolution.Minute)
&& dataPointEndTime.Ticks % config.Increment.Ticks == 0)
{
return true;
}
var roundedDataPointEndTime = dataPointEndTime.RoundDownInTimeZone(config.Increment, config.ExchangeTimeZone, config.DataTimeZone);
return dataPointEndTime == roundedDataPointEndTime;
}
/// <summary>
/// Constructs the correct <see cref="ITokenBucket"/> instance per the provided controls.
/// The provided controls will be null when
/// </summary>
private static ITokenBucket CreateTokenBucket(LeakyBucketControlParameters controls)
{
if (controls == null)
{
// this will only be null when the AlgorithmManager is being initialized outside of LEAN
// for example, in unit tests that don't provide a job package as well as from Research
// in each of the above cases, it seems best to not enforce the leaky bucket restrictions
return TokenBucket.Null;
}
Log.Trace("AlgorithmManager.CreateTokenBucket(): Initializing LeakyBucket: " +
$"Capacity: {controls.Capacity} " +
$"RefillAmount: {controls.RefillAmount} " +
$"TimeInterval: {controls.TimeIntervalMinutes}"
);
// these parameters view 'minutes' as the resource being rate limited. the capacity is the total
// number of minutes available for burst operations and after controls.TimeIntervalMinutes time
// has passed, we'll add controls.RefillAmount to the 'minutes' available, maxing at controls.Capacity
return new LeakyBucket(
controls.Capacity,
controls.RefillAmount,
TimeSpan.FromMinutes(controls.TimeIntervalMinutes)
);
}
}
}