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* Add margin-aware option strategy match selection
OptionStrategyMatcher.MatchOnce greedily matched definitions in
descending leg-count order, never consulting the objective function
hook. Books of overlapping debit spreads were carved into ladders
whose uncovered short leg is charged naked option margin, producing
phantom margin deltas, inconsistent accept/reject decisions and
TotalMarginUsed churn on fully covered, defined-risk books.
MatchOnce now evaluates a second candidate solution that deprioritizes
definitions leaving a short leg uncovered, and selects the best
solution via the objective function. The new default objective
function minimizes the quantity of uncovered short contracts, a
deterministic proxy for the margin required to hold the positions.
Ties preserve the previous grouping, so behavior only changes where
the greedy carve left a short uncovered that another grouping of the
same positions covers.
Fixes#9638
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* Cache strategy definition ordering and skip redundant match pass
Materialize the definition enumerations once per matcher options instead of
re-sorting them on every MatchOnce call, and only evaluate the second candidate
solution when some short contract can actually be covered by a long of the same
right or by the underlying lots held. A book of naked shorts, by far the most
common one reaching that point, now runs a single matching pass.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
* Bound credit-side short coverage and add overlapping spreads regression
The uncovered short proxy treated any same-right long as covering a
short leg. A long on the credit side (higher strike for calls, lower
for puts) caps the risk at the strike width, which for a distant long
can exceed the naked short margin, so preferring it could raise the
margin required instead of lowering it.
Coverage from the debit side stays free, while credit-side coverage
only counts within 10% of the short strike, the price-free stand-in
for the naked short margin floor of the option margin model. Beyond
that width the short counts as uncovered, the candidate solutions tie
and the previous grouping is preserved, so the selection can only ever
lower the margin required to hold the positions.
Also adds a regression algorithm for the reported defect: two
overlapping bull call debit spreads with interleaved strikes resolve
into two margin free spreads instead of a bull call ladder charging
naked call margin plus an unmatched long.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* Skip provably useless match passes and drop scoring allocations
Matching again cannot help once the first solution already leaves no
more shorts uncovered than the positions can possibly cover, since a
long contract covers at most its own quantity of shorts of the same
right, and so does an underlying lot. Checking that bound generalizes
the naked shorts precondition it replaces and removes the second pass
from books holding fewer longs than shorts, such as a plain ladder,
which measured 2.2x slower than a single pass before and is now level
with it.
The credit side width test also subsumes the debit side one, whose
width is never positive, so coverage collapses into a single predicate
and one pass over the legs. Strategies with a single short leg, which
is every spread, butterfly, condor, backspread and covered call, now
take a fast path that needs neither ordering nor allocation, and the
remaining ladders and short butterflies sort a small array in place
instead of allocating lists, objects and sort closures per score.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* Require a covering long to outlive the short it covers
The coverage proxy compared strikes only, so a short calendar spread,
long the near expiration and short the far one at the same strike, read
as fully covered on a zero strike width. The margin models disagree:
once the long expires the short is naked for the rest of its life, and
short calendar spreads are charged the stand-alone naked short margin
while ordinary calendar spreads, whose long outlives the short, require
none. Requiring the covering long to expire no earlier than the short
makes the proxy mirror that distinction exactly, and leaves same expiry
books untouched.
The skip added for provably useless second passes reads the score as a
quantity of uncovered contracts, which only the default objective
function guarantees, so a custom one now always gets both candidates.
Also documents that the definition ordering is cached, freezing the
first output of a user supplied enumerator, and drops the stale claim
that nothing in the options type is consulted by the matcher.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* Apply the uncovered short bound to the default objective function only
A function deriving from the default one is free to score by different
rules, so taking its score for a quantity of uncovered contracts could
skip a second candidate it would have preferred. Match the type exactly
instead, which leaves derived functions always evaluating both.
Also documents that the legacy objective function scores are not
bounded above by zero, so configuring it ends candidate evaluation and
preserves the single matching pass, and describes the regression
algorithm strikes by their order in the chain rather than as the
highest ones, which only held for a chain of exactly four strikes.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
---------
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
* Fix universe subscription exception when option universe is removed and re-added in the same time step
* Remove incorrect issue reference from comments
* Use RegressionTestException in regression algorithm
* Clean up stale universe members when universe is removed and re-added in the same time step
* Convert regression algorithms to C# and centralize universe selection data handling
* Simplify fix by parking colliding universe subscription requests and re-issuing them on removal
* Restore universe subscription request invariant exception
* Report parked universe subscription requests as successfully added
* Fix option assignment trade statistics
Resolve the security from each order event when updating TradeBuilder so physically settled underlying fills use the underlying multiplier and conversion rate.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: 716a0df4-0117-458b-b4ac-7d8aeeb9bf48
* Resolve order event security from the event symbol
Option exercises emit the underlying fill under the option's order id, so
resolving the security from the order symbol handed the option's contract
multiplier and quote currency conversion rate to the underlying fill,
inflating closed trade statistics.
Extend the option assignment regression algorithm, in both C# and Python,
to assert every closed trade's profit and loss against its own security's
contract multiplier.
---------
Co-authored-by: Kapil Yadav <kapyadav@microsoft.com>
Co-authored-by: Jhonathan Abreu <jdabreu25@gmail.com>
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A margin call requiring a partial reduction of an option strategy
position group probes a zero-quantity trial group while solving for the
order quantity. The option strategy margin helpers assume at least one
leg with non-zero quantity and threw InvalidOperationException,
crashing the algorithm. Return zero initial/maintenance margin for
zero-quantity groups so the margin call converges on full liquidation.
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* Improve error message when consolidator period Python object is unsupported
* Make unsupported consolidator period error message more concise
* Apply descriptive Python conversion errors to other user-facing sites and add QuoteBarConsolidator.FromResolution
* List available overloads in unsupported Python argument error messages
* Update QuantConnect.pythonnet to 2.0.61
* Update overload hint test expectations to Python-typed signatures
* Exclude PyObject overloads from error hints and update to Python annotation style
* Move PyObject overload filtering from consumers into MethodSignatureFormatter
* Update Python alpha model name expectations for Python-style enum rendering
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* Allow Python option filter functions to return None
The option filter universe is modified in place by the filter methods
(strikes, expiration, etc.), whose return value is only necessary for
chaining. A Python filter function that returns None would kill the
algorithm with a NullReferenceException.
* Allow C# option filter functions to return null and add regression algorithms
Adds C#/Python regression algorithms asserting that option filter
functions are allowed to mutate the universe in place and return
null/None instead of the universe, which is only necessary for chaining.
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* Set security cache open interest from chain universe data
- The option and future security caches now update the open interest
cache property from stored chain universe data points (OptionUniverse,
FutureUniverse), which the algorithm manager pushes into the security
caches
- Add index option and future option specific security caches, mapped in
the SecurityCacheProvider, which previously fell through to the base
SecurityCache
- Add regression algorithms asserting the behavior for equity options,
index options and futures
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* Guard against empty data lists when updating open interest
StoreData is public API, add an UpdateOpenInterest overload taking the
data list which checks the count before accessing the last data point
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
---------
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
* Add built-in rolling window to all consolidators
* Minor fix
* Add unit tests
* Add Current and Previous properties to consolidators
* Add WindowBase<T> as single source of truth for rolling window logic
* Address review comments on consolidator rolling window
* Fix duplicate window in consolidator wrappers
* Fix Python consolidator equality
* Address review comments
* Make ConsolidatorBase implements IDataConsolidator
* Add IDataConsolidator<T> generic interface to avoid casting Consolidated output
* Revert "Add IDataConsolidator<T> generic interface to avoid casting Consolidated output"
This reverts commit f4bf812f4b26aff2789a8129fb07101962557a2a.
* Address second review round on consolidator rolling window
* Populate consolidator window before firing DataConsolidated events
* Move WindowBase to the Indicators namespace
* Restore original consolidator event ordering
* Recover original Sequential wire-up comment
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* Update QuantConnect.pythonnet to 2.0.57
* Update NoMethodMatch interpreter tests for pythonnet 2.0.57 snake_case method names
pythonnet 2.0.57 renders the method name in the 'No method matches given
arguments' TypeError in snake_case (e.g. 'for set_cash:' / 'for rsi:'),
matching the name Python callers use. The interpreter extracts it correctly;
only the tests' hardcoded PascalCase expectations (SetCash, RSI) were stale.
Assert the snake_case names the API now emits.
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* Use risk-free rate in probabilistic Sharpe ratio
* Extend risk free rate to live report PSR and fix probabilistic sharpe ratio tests
* Update regression statistics
* Update test regression statistics
* Add test asserting Sharpe ratio and PSR consistency
* Use excess returns for live report Sharpe and PSR
---------
Co-authored-by: Kevin-Li-2025 <2242139@qq.com>
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Registering an indicator or consolidator for a symbol that had not been
subscribed to threw 'Please register to receive data for symbol ...'.
Order submission already auto-subscribes the symbol on the user's behalf;
this applies the same behavior to indicator/consolidator registration.
GetSubscription now adds the security automatically when it has no
subscription (guarded by the shared CanAutoAddSecurity check, which is
also used by order submission) before falling back to the error. The
subscription lookup is exposed via a TryGetSubscription out-parameter
helper.
Port the C# regression algorithm demonstrating IndicatorVolatilityModel
usage, including how to reset and warm up the indicator on splits and
dividends to avoid volatility jumps from price discontinuities, and
enable the Python variant in the regression test suite.
Closes#6375
Claude-Session: https://claude.ai/code/session_01R7LGdW3eC9za8WMrtssHGr
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
* Seed runtime-added currency conversion rates immediately
Fixes the spurious 'The conversion rate for <currency> is not available'
runtime error caused by a two-path seeding asymmetry.
The setup path (BaseSetupHandler.SetupCurrencyConversions) wires up a
currency's conversion feed AND seeds its rate via history/last-known-price
so the rate is non-zero right away. The runtime path
(UniverseSelection.EnsureCurrencyDataFeeds, invoked during universe
selection / SetCash mid-run) only created the conversion subscription and
left the rate at 0 until the first bar of the pair arrived. Any conversion
in that gap (classically a midnight scheduled SetHoldings firing before the
day's first conversion-pair bar) threw.
EnsureCurrencyDataFeeds now seeds newly introduced, still-zero-rate
conversion securities and calls cash.Update(), mirroring the setup path.
Seeding is gated behind a seedNewCurrencies flag (default true) so the
setup caller, which performs its own optionally white-listed seeding, can
opt out and not regress white-list semantics. SeedSecurities degrades
gracefully when no history/data is available, leaving the rate at 0 as
before, so live mode and no-history scenarios are safe.
Adds a regression test exercising the runtime path.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Make runtime currency seeding robust and fix regression expectation
CI failures from the runtime currency-conversion seeding change:
1. AlgorithmWarmupTests.WarmUpInternalSubscriptions threw
ArgumentNullException because the new EnsureCurrencyDataFeeds seeding
path ran GetLastKnownPrices in a stub where the conversion security
lacked SymbolProperties. Pre-seeding is best-effort and must never
break the algorithm, so wrap it in try/catch and degrade gracefully
(leave the rate at 0, the pre-fix behavior) - matching the documented
intent. The first conversion-pair bar still updates the rate.
2. ScheduledUniverseSelectionModelRegressionAlgorithm (C# + Python)
asserted AlgorithmHistoryDataPoints == 0. The algorithm runtime-adds
Forex pairs (EURGBP -> GBP cash) via scheduled universe selection;
the fix now correctly seeds that runtime currency's conversion rate
with a last-known-price history request (deterministically 50 points).
The old 0 reflected the buggy unseeded behavior, so update the
expectation to 50. No other statistics changed.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Seed runtime added currency conversion rates
* Seed currencies with no new conversion feed and dedup the seeding helper
---------
Co-authored-by: Martin-Molinero <Martin-Molinero@users.noreply.github.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Wait for first session bar before filling equity market orders at open
EquityFillModel.MarketFill could fill a market order placed right after
market open using data from the previous trading date, because the first
bar of the current session has not been emitted yet. ShouldWaitForFreshData
only covered hour/daily resolutions, so minute/second orders filled on stale
prices.
Add IsWithinFirstResolutionSpanAfterMarketOpen: when the order time is within
the lowest subscribed resolution span after the open and the price is stale,
wait for the first bar instead of filling on the previous date's price.
* Share opening-bar stale-fill wait across fill models
Move IsWithinFirstResolutionSpanAfterMarketOpen to the base FillModel and add
a ShouldWaitForFreshDataOnStale sibling helper that combines it with the
existing coarse-resolution ShouldWaitForFreshData check. The base FillModel,
FutureFillModel and EquityFillModel market fills now share this single wait
decision at their stale-data guards.
ShouldWaitForFreshData is intentionally left untouched at its GetMarketFillPrice
call site, which uses it to choose the bar open vs current price and is not
gated by staleness, so fill prices for finer resolutions are unchanged. The
opening-bar helper is guarded against always-open markets, which have no
session open to wait for.
* Add regression algorithm for stale fill at market open
Reproduces the opening-bar stale fill issue: a market order placed one second
after the open while subscribed to minute resolution. Without the fix the order
fills on the previous trading date's stale price; the algorithm asserts in
OnOrderEvent that a fill never happens within the first minute after the open,
so it errors without the fix and passes with it.
Uses SPY minute data over 2013-10-07 to 2013-10-11, which is available in the
repository Data folder.
* Add unit tests for stale fill wait at market open
Cover the opening-bar stale fill scenario directly at the fill model level:
a market order placed within the first bar after the session open, while only
the previous session's stale bar is available, must wait instead of filling on
the stale price, and fills once the first session bar arrives. EquityFillModel
also asserts the boundary (orders past the first bar still fill on stale data),
and FutureFillModel covers the shared base helper from the future path.
* Generalize stale market-order fill wait to any time of day
Replace the market-open-specific wait with a generic check: a market order
that would be filled on stale data waits for fresh data when the latest
available data is more than one subscribed resolution bar behind the current
time. This no longer considers the market open explicitly; it covers the
opening bar (the first session bar has not been emitted yet) and any intraday
data gap larger than the resolution.
ShouldWaitForFreshDataOnStale now takes the latest data end time and the
current time instead of the order time, and is shared by FillModel,
FutureFillModel and EquityFillModel. Coarse resolutions (hour/daily) still
always wait; tick never waits. Internal configurations are included when
sizing the resolution bar. EquityFillModel's best-effort price helpers now
report the stale data end time so the gap can be measured.
Tests: EquityFillModelTests and FutureFillModelTests cover the market-open and
mid-session stale cases (wait then fill on fresh data) plus the within-one-bar
boundary (fill on stale). The regression algorithm is generalized to assert no
fill happens on data staler than the resolution, with orders at the open and
mid-session. Pre-existing plumbing/data-selection tests that used degenerate
timestamps were given fresh timestamps so they still exercise their original
intent.
* Add sample data and adjust regression algorithms for stale-fill wait
Add minute/daily sample data so market orders that now wait for fresh data
can fill (ES futures gap days, TWX/GOOG equities and options, SPXW weeklies,
GC futures/options copy for 2020-01-06). Adjust a few regression algorithms
to the deferred-fill behavior: cap orders in the extended-market continuous
future test, ignore daily-resolution SPY in the automatic-seed data checks,
and refresh OptionAssignmentStatistics expected constants.
* Update regression expected statistics for stale-fill wait
Regenerate ExpectedStatistics, DataPoints and AlgorithmHistoryDataPoints for
the regression algorithms affected by the wait-for-fresh-data fill change and
the added sample data: futures/options fill-timing shifts, ES data-point count
increases, and GOOG 2015-12-28 outcome changes.
* Trim SPXW sample data to expiries within filter window
The two SPXW algorithms filter with Expiration(0,7), so contracts expiring
more than a week out are never subscribed. Drop those far-dated expiries from
the 2021-01-06/08 minute files (760KB->108KB and 776KB->108KB on the quote
files). Fills, DataPoints and statistics are unchanged; both regression tests
still pass.
* Trim ES minute and GOOG option sample data to order-fill minimum
The ES minute gap-day files source no order fills (daily-resolution algos fill
from es_daily); keep only the front contract used for execution and drop the
unused back-month contracts. Trim the GOOG 2015-12-28 option file (no fill
depends on it) to the morning chain window. Regenerate the back-month futures
statistics affected by the dropped back-month bars. Full CSharp regression
suite passes (722/722).
* Use SMA gap threshold in BasicTemplateContinuousFuture for C#/Python parity
At a fast/slow SMA cross the two averages can coincide to within rounding
noise, where the C# (decimal) and Python (double) comparisons disagree,
producing different orders between languages. Require a minimum gap before
acting on a cross so both languages stay in lockstep, and update the shared
expected statistics accordingly.
* Mirror order cap in Python algorithm and update future history counts
Apply the same pre-2013-11-12/3-order cap to the Python
BasicTemplateContinuousFutureWithExtendedMarket algorithm for C#/Python parity,
and update the QuantBook future-history expected counts to reflect the added ES
sample data.
* Use SMA gap threshold in BasicTemplateContinuousFutureWithExtendedMarket for C#/Python parity
This algorithm had the same fast/slow SMA cross divergence already fixed in
BasicTemplateContinuousFutureAlgorithm (ad8fc33): at the 2013-10-29 cross the two
averages coincide to within rounding noise (C# decimal diff -1e-25, Python double
diff exactly 0.0), so the raw `_fast > _slow` / `_fast < _slow` comparisons disagree
between languages. C# fired a liquidate+rebuild that Python skipped, producing 5
orders in C# vs 3 in Python. Require a minimum 0.001 gap before acting on a cross so
both languages stay in lockstep, and regenerate the shared expected statistics
(Total Orders 5 -> 3).
* Document SMA cross threshold as a C#/Python parity workaround
Add a short note before the fast/slow SMA comparisons in both continuous-future
template algorithms clarifying that the minimum-gap threshold exists only so the
C# and Python versions take the exact same trades on the limited sample data in
the repository, where decimal vs double rounding can disagree at a cross.
* Fetch subscription configs once per equity market fill
MarketFill resolved the subscription configs twice per fill: once via the
best-effort price helpers (GetSubscribedTypes) and again via
ShouldWaitForFreshDataOnStale. Fetch them once and thread them through both
paths via optional parameters, leaving existing callers unchanged.
* Measure stale-fill wait against order submission time
ShouldWaitForFreshDataOnStale compared the latest data end time against the
security current time. Compare against the order submission time instead so the
decision to wait for fresh data reflects how stale the data is relative to when
the order was placed. Realign the stale-price warning fill test accordingly.
* Fix stale market data in SendingNewOrderFromOnOrderEvent test
The market price tick was timestamped a day before the order submission time,
so under the order-time staleness check the market orders waited for fresh data
instead of filling. Use a reference time with the tick one minute before the
order so the data is fresh and the orders fill.
* Centralize internal-inclusive subscription config lookup in fill models
ShouldWaitForFreshDataOnStale re-resolved the subscription configs through
the ShouldWaitForFreshData call it makes first, and GetMarketFillPrice did
the same. Thread the already-fetched configs through ShouldWaitForFreshData
and GetMarketFillPrice so each market fill resolves them at most once.
Add a GetSubscriptionDataConfigs(Security) helper on the base FillModel that
returns the internal-inclusive configs, and route every fill-model call site
through it to remove the duplicated lookup and repeated comment.
* Avoid list allocation in ShouldWaitForFreshData
Replace the Where(...).ToList() + All(...) with a single foreach over the
subscription configs, short-circuiting on the first non-coarse resolution.
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HourResolutionMarketOrderStalePriceRegressionAlgorithm now asserts the order
fills at the next hour bar's close price (not the stale previous bar nor the
open), and that the fill bar is a real, freshly closed 11:00 bar rather than a
fill-forwarded repeat.
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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* 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>
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* Convert daily resolution market orders to MarketOnClose/MarketOnOpen
A market order placed intraday (e.g. through a scheduled event) on an
asset subscribed only at daily resolution has no fresh intraday price to
fill against, so it was filling at the stale previous daily close. This
is common when mixing daily resolution assets with minute resolution
assets or intraday scheduled events.
QCAlgorithm.MarketOrder now converts these orders so they fill at a real
daily open/close instead of the stale previous close:
- market closed (any resolution): MarketOnOpen, as before
- market open, daily-only subscription: MarketOnClose (today's close),
or MarketOnOpen (next open) when already within the MarketOnClose
submission buffer near the close
Assets with intraday data are left untouched, and the conversion is only
applied in backtesting; in live trading an open-market market order fills
at the real current price.
Adds DailyResolutionMarketOrderConversionRegressionAlgorithm covering the
MarketOnClose and MarketOnOpen conversion paths plus a minute resolution
asset that is correctly left as a regular market order.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Minor fix
* Reword conversion warning: "current market price" instead of "real current price"
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Update regression stats affected by daily market order conversion
Daily-resolution market orders placed intraday are now converted to
MarketOnClose/MarketOnOpen so they fill at a real daily open/close
instead of the stale previous close. This shifts the affected fills:
- IndexOptionCall{ITM,OTM}ExpiryDaily: the SPX option entry, placed one
minute after the open, now fills at the daily close. Same economics,
one extra data point and a new order list hash.
- AllShortableSymbols (C# + Python): an intraday order's type changed
from Market to a converted order; identical End Equity, new hash.
- ResolutionSwitchingAlgorithm sampling test: the RemoveSecurity
liquidation (fired at 15:50) previously filled at the stale previous
close; it now converts, shifting the equity/performance samples.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Revert expected data point count change
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* Align OnWarmupFinished time to StartDate when ScheduledUniverse skips midnight
* Align algorithm time to StartDate before OnWarmupFinished fires
* Apply warmup time alignment fix to LiveSynchronizer
* Minor fix
* Skip warmup pulse if algorithm not locked
* Fix OnWarmupFinished timing in live trading
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* Fix DataManager skipping invalid data type subscriptions
* Update regression algorithms
* Use effective resolution when looking up subscription data types
* fix: support BNFCR alternative collateral in CryptoFutureMarginModel for Binance (#9339)
* refactor: use classic switch in BinanceFuturesBrokerageModel.GetBuyingPowerModel
* fix: CryptoFutureMarginModel in BinanceCoinFuturesBrokerageModel
* refactor: simplify BinanceCryptoFutureMarginModel collateral conversion
* fix: restore IsCryptoCoinFuture guard in BinanceCryptoFutureMarginModel
* refactor: simplify BinanceCryptoFutureMarginModel to direct BNFCR lookup
Replace IsStableCoinWithoutPair foreach loop with a single TryGetValue
check for BNFCR. BNFCR is EU/EEA-only (MiCA Credits Trading Mode) so
the lookup is a no-op for all other users. Amount reflects availableBalance
from the Binance API — the total cross-margin pool already aggregated by
Binance — making the > 0 guard correct and avoiding CashBook iteration.
* feat: add regression algorithm for BNFCR as sole collateral on Binance USDⓈ-M futures
Asserts end-to-end that EU/MiCA accounts with zero USDT and BNFCR as
the only collateral can open ADAUSDT positions. Verifies buying power,
holdings AbsoluteHoldingsCost, TotalSaleVolume, TotalMarginUsed,
maintenance margin consistency and TotalUnrealizedProfit accuracy.
* refactor: BNFCR presence gate with CashBook iteration for supplementary collateral
Replace IsStableCoinWithoutPair and hardcoded asset list with CashBook
iteration gated by BNFCR presence. Binance controls which assets are in
the account — all with non-zero walletBalance are valid collateral.
Add tests for BNFCR zero balance and BTC collateral conversion.
* refactor: aggregate all collateral without reference equality check
* fix: shared collateral deduction across quote currencies for EU/MiCA BNFCR mode
- Extract virtual SharesCollateral in CryptoFutureMarginModel
- Override in BinanceCryptoFutureMarginModel: BNFCR present → all USDⓈ-M share pool
- Add BNFCRCurrency const
- Add SharedCollateralDeductsMaintenanceMarginAcrossQuoteCurrencies unit test
- Refactor regression algorithm to assert shared collateral across ADAUSDT/ETHUSDC
* refactor: remove dead IsCryptoCoinFuture guard from BinanceCryptoFutureMarginModel
- Remove IsCryptoCoinFuture() check (coin futures use BinanceCoinFuturesBrokerageModel, not this model)
- Call base.GetTotalCollateralAmount() instead of duplicating primaryCollateral.Amount
- Remove CoinFutureDoesNotIncludeBnfcrAsCollateral test (tested wrong margin model)
* refactor: make GetCollateralCash private in CryptoFutureMarginModel
- No longer accessed by subclasses after removing direct collateral checks from BinanceCryptoFutureMarginModel
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* Add ContractMultiplier setter to Cfd via CfdSymbolProperties
* Fix regression tests
* Solve review comments
* Address new review comments
* Fix regression tests
* Use ContractSymbolProperties as base class
* Minor fix
* Address review comment
* Use universe settings when adding derivatives
Use resolution, fill forward and extended market hours settings from universe settings when adding derivative securities (options, index options, futures and future options)
* Minor python syntax check fix
* Minor change
* Default resolution from universe settings for common lean types securities
* Minor test fix
* Cleanup
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* Implement indicator-based option price model
This model uses IV and Greeks indicators to implement Lean's own option pricing model
* Minor fixes
* Address peer review
* Minor tests fixes
* Make the indicator based price model the default for options
* Address peer review
* Cleanup and minor changes
* Support indicators configuration for new pricing model
* Some cleanup
* Add QL option price model example algorithm
* Return lean models from static helpers
* Minor tests fixes
* Minor test fixes
* Address peer review
* Cleanup
* Fix unit tests
* Move QL models to OptionPriceModels.QuantLib.*
* Add forward tree helper method
* Fix weights calculation in VBaseSignalExport
* fix empty portfolio handling
* Refactored signal export to compute and export weights for all portfolio positions, not just update targets.
* Update BuildCsv XML doc to clarify CSV output details
* Clarify comments on portfolio value and empty weights
* Stamp targets as is; we expect that users send all the weights they want to stamp. Extended the demo algorithm to use two positions to better demonstrate the intended usage of the VBaseSignalExport class.
* Minor changes to address PR review comments.
* Minor fix
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Co-authored-by: vb-vlb <volodymyr@vbase.com>
Co-authored-by: Volodymyr <vb-vlb@users.noreply.github.com>
Alexandre Catarino