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quantconnect--lean/Algorithm.CSharp/BasicTemplateFuturesDailyAlgorithm.cs
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Martin-Molinero 27de93f78f
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Market orders wait for fresh data instead of filling on stale prices (#9535)
* Market orders wait for fresh data instead of filling on stale prices

A market order would previously fill immediately on the most recent
available data even when that data was older than StalePriceTimeSpan
(default one hour), only attaching a warning. This is unrealistic for a
coarse resolution asset (hour/daily) where the latest bar is the stale
previous close when the order is placed mid-bar or via an intraday
scheduled event.

The default fill models (FillModel, EquityFillModel, FutureFillModel) now
wait for fresh data instead of filling on a stale price, but only for hour
and daily resolutions; the order fills when the next bar closes. For
minute/second/tick subscriptions the previous behavior is kept (fill on
the stale price with a warning), since stale data there is a genuine gap
rather than a bar still forming.

Adds HourResolutionMarketOrderStalePriceRegressionAlgorithm, updates the
FillOutsideHours daily expectation, and regenerates statistics for the
hour/daily algorithms whose fills change. FutureOptionDaily buys and
liquidates a day apart now (a same-day buy + liquidate cannot fill on
daily data once stale fills are disabled).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* Normalize and correct StalePriceTimeSpan XML docs

The interface and class docs now match and reflect the actual behavior:
the wait-for-fresh-data only applies to hour/daily resolutions, while
minute/second/tick subscriptions still fill on stale data with a warning.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* Fill resting market orders at the bar open instead of the close

A hour/daily market order that was resting before the current bar opened
(it predates the bar - placed after the previous close or while waiting
for fresh data) now fills at the bar open, the price when trading resumed
(like a MarketOnOpen), instead of the bar close. Orders placed during the
bar still fill at the current/close price, so intraday mid-bar fills are
unchanged. Equity fills are unchanged (resting equity orders are already
converted to MarketOnOpen by QCAlgorithm.MarketOrder).

Adds the shared FillModel.GetMarketFillPrice helper used by the base
FillModel and FutureFillModel, a unit test, and regenerates statistics for
the affected daily/hour futures, index and crypto regression algorithms
(order counts unchanged, only fill prices).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* Add regression algorithm asserting resting market orders fill at the bar open

RestingMarketOrderFillsAtBarOpenRegressionAlgorithm buys a daily future on the
bar that delivers it (fills at that bar's close) and submits a liquidation while
the market is closed (overnight pulse, no fresh bar). The liquidation rests and
fills on a later bar at the bar open, not its close - asserting the new
GetMarketFillPrice behavior. The in-bar buy is asserted to fill at the close, for
contrast.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* Carry the bar start time on Prices instead of re-reading the cache

Add Prices.Time (the bar start, mirroring BaseData.Time/EndTime), populated from
the source bar/tick in every GetPrices path. GetMarketFillPrice now uses
prices.Time directly instead of a second asset.Cache.GetData() lookup. Behavior
is unchanged (prices.Time equals the previously read cache time).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* Add regression algorithm asserting in-session hour orders fill at the latest close

HourMarketOrderFillsAtBarCloseRegressionAlgorithm submits an hour resolution
market order mid-bar (via an intraday scheduled event) while the market is open,
using the default one hour StalePriceTimeSpan. It asserts the order fills
immediately at the latest available bar's close - not waiting and not at the bar
open - since the latest bar is within the stale window. Guards the resting-order
open-fill behavior against affecting ordinary in-session fills.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* Regenerate custom fill model algorithm statistics for the open-fill change

CustomModelsAlgorithm and CustomPartialFillModelAlgorithm subscribe SPY at hour
resolution and their custom fill models delegate to base.MarketFill, so resting
orders now fill at the bar open. Regenerate their statistics (C#/Python) and the
inline expected statistics of the PEP8StyleCustomModelsWork test.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-18 11:59:19 -03:00

178 lines
7.1 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 QuantConnect.Data;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Interfaces;
using QuantConnect.Securities;
using QuantConnect.Securities.Future;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// This example demonstrates how to add futures with daily resolution.
/// </summary>
/// <meta name="tag" content="using data" />
/// <meta name="tag" content="benchmarks" />
/// <meta name="tag" content="futures" />
public class BasicTemplateFuturesDailyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
protected virtual Resolution Resolution => Resolution.Daily;
protected virtual bool ExtendedMarketHours => false;
// S&P 500 EMini futures
private const string RootSP500 = Futures.Indices.SP500EMini;
// Gold futures
private const string RootGold = Futures.Metals.Gold;
private Future _futureSP500;
private Future _futureGold;
/// <summary>
/// Initialize your algorithm and add desired assets.
/// </summary>
public override void Initialize()
{
SetStartDate(2013, 10, 08);
SetEndDate(2014, 10, 10);
SetCash(1000000);
_futureSP500 = AddFuture(RootSP500, Resolution, extendedMarketHours: ExtendedMarketHours);
_futureGold = AddFuture(RootGold, Resolution, extendedMarketHours: ExtendedMarketHours);
// set our expiry filter for this futures chain
// SetFilter method accepts TimeSpan objects or integer for days.
// The following statements yield the same filtering criteria
_futureSP500.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
_futureGold.SetFilter(0, 182);
}
/// <summary>
/// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
/// </summary>
/// <param name="slice">The current slice of data keyed by symbol string</param>
public override void OnData(Slice slice)
{
if (!Portfolio.Invested)
{
foreach(var chain in slice.FutureChains)
{
// find the front contract expiring no earlier than in 90 days
var contract = (
from futuresContract in chain.Value.OrderBy(x => x.Expiry)
where futuresContract.Expiry > Time.Date.AddDays(90)
select futuresContract
).FirstOrDefault();
// if found, trade it.
// Also check if exchange is open for regular or extended hours. Since daily data comes at 8PM, this allows us prevent the
// algorithm from trading on friday when there is not after-market.
if (contract != null)
{
MarketOrder(contract.Symbol, 1);
}
}
}
// Same as above, check for cases like trading on a friday night.
else if (Securities.Values.Where(x => x.Invested).All(x => x.Exchange.Hours.IsOpen(Time, true)))
{
Liquidate();
}
foreach (var changedEvent in slice.SymbolChangedEvents.Values)
{
if (Time.TimeOfDay != TimeSpan.Zero)
{
throw new RegressionTestException($"{Time} unexpected symbol changed event {changedEvent}!");
}
}
}
public override void OnSecuritiesChanged(SecurityChanges changes)
{
if (changes.RemovedSecurities.Count > 0 &&
Portfolio.Invested &&
Securities.Values.Where(x => x.Invested).All(x => x.Exchange.Hours.IsOpen(Time, true)))
{
Liquidate();
}
}
/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>
public virtual bool CanRunLocally { get; } = true;
/// <summary>
/// This is used by the regression test system to indicate which languages this algorithm is written in.
/// </summary>
public virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public virtual long DataPoints => 5874;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public virtual int AlgorithmHistoryDataPoints => 0;
/// <summary>
/// Final status of the algorithm
/// </summary>
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "22"},
{"Average Win", "0.61%"},
{"Average Loss", "-0.49%"},
{"Compounding Annual Return", "0.117%"},
{"Drawdown", "0.300%"},
{"Expectancy", "0.124"},
{"Start Equity", "1000000"},
{"End Equity", "1001178.23"},
{"Net Profit", "0.118%"},
{"Sharpe Ratio", "-1.834"},
{"Sortino Ratio", "-0.52"},
{"Probabilistic Sharpe Ratio", "15.902%"},
{"Loss Rate", "50%"},
{"Win Rate", "50%"},
{"Profit-Loss Ratio", "1.25"},
{"Alpha", "-0.007"},
{"Beta", "0.002"},
{"Annual Standard Deviation", "0.004"},
{"Annual Variance", "0"},
{"Information Ratio", "-1.352"},
{"Tracking Error", "0.089"},
{"Treynor Ratio", "-4.239"},
{"Total Fees", "$6.77"},
{"Estimated Strategy Capacity", "$290000000.00"},
{"Lowest Capacity Asset", "GC VOFJUCDY9XNH"},
{"Portfolio Turnover", "0.12%"},
{"Drawdown Recovery", "69"},
{"OrderListHash", "064f8f56389ceecb333b5a4bb79622c1"}
};
}
}