All Classes and Interfaces
Class
Description
The full-checklist smart order router: where
SmartOrderRouter
ranks venues purely on fee-adjusted displayed price and HftSor
does the same at tick-path speed, this router prices in everything a
production SOR actually weighs:
Displayed liquidity and fees/rebates — the all-in
price, as before;
Probability of fill / venue reliability — a venue's
VenueScorecard fill rate discounts its quote: expected
cost adds (1 − fillRate) × missPenalty (the spread-ish
cost of re-routing a faded child), and venues below a reliability
floor are vetoed outright;
Latency — slower venues pay latency × urgency: in a
moving market, microseconds of delay are adverse selection.Tunable penalties;
AdaptiveSor.Config.defaults() is a sane starting point.The routed plan:
lit legs cover up to the requested quantity
(best-expected-cost first); probes are additive contingent
dark legs sent alongside; unrouted is the shortfall no
eligible lit venue could absorb (0 on a fully routed order).Almgren-Chriss (2000) optimal execution: the trading trajectory that
minimizes
E[cost] + λ·Var[cost] when liquidating X shares over a
horizon, trading off temporary impact (fast execution is expensive) against
price risk (slow execution is risky).Model inputs.
The optimal schedule:
holdings[j] is the position after
interval j (holdings[0] = X, holdings[N] = 0); trades[j] is
sold in interval j+1.Execution-aware factor backtest: runs a factor through a construction
pipeline into target weights at each rebalance and simulates holding,
trading and financing the book bar by bar.
Backtest settings: decision schedule, costs and capital.
Net and gross curves (one point per close from
startIndex),
the cumulative fraction of equity each cost consumed, and turnover.Risk-model-driven construction for
AlphaBacktester.run(AlphaContext, AlphaFactor, Config, RiskOptions): at each rebalance a FactorRiskModel is rebuilt
from the panel up to the decision bar (AlphaRiskModels) and the
book comes from TurnoverAwareOptimizer started at the drifted
book actually held.A run with its per-bar trace: the book held over each close-to-close
bar, each name's P&L, the cost and the financing, all as fractions
of equity at the start of the bar.
Builds target weights from raw scores at a rebalance (the construction hook).
Combines several alpha factors into one by information-coefficient
weights that match the holding horizon, account for signal decay,
remove redundancy by orthogonalisation and shrink toward equal weights.
Fitted weights and the combined factor.
Combination settings.
The research dataset an alpha factor operates on: an index-aligned panel
of price series over a fixed symbol order, with optional fundamentals and
an optional point-in-time universe.
IC-weighted alpha ensemble — the layer above the individual signals.
A cross-sectional alpha factor: at a bar index, one raw score per symbol,
where higher = more attractive to own (buy high scores, sell low).
Alpha reporting: the diagnostics that explain a factor's P&L rather
than just totalling it.
OLS attribution with standard errors.
Mean IC per cumulative horizon, plus the horizon where it first falls
below half the shortest-horizon value.
Lagged-return IC profile with its exponential fit.
Risk model specification.
Validation for alpha factors, run before any capital-weighted conclusion:
Walk-forward: pick the best candidate on a training window by
in-sample IC, measure it on the next unseen window, roll forward.
Per-block ICs with their dispersion: consistency across regimes.
One walk-forward fold.
Which link the null distribution destroys.
Observed mean IC against its null distribution.
IC across the sweep.
All folds plus the aggregate in-sample vs out-of-sample comparison.
Surveillance anomaly detection over interval-aggregated market activity:
Quote stuffing — message-rate spikes (robust z-score) combined
with an abnormal order-to-trade ratio: lots of quoting, little
trading.
Price spikes — interval returns far outside their recent
distribution.
Anti-gaming randomization for schedule-driven algos — a TWAP that
fires identical children on a metronome is a gift to anyone watching
the tape: predators detect the clock in a handful of intervals and
lean on every child.
Asian (average-price) options — the corporate hedger's option: paying off
on the average of n fixings instead of one closing print kills both the
expiry-day manipulation incentive and most of the vol (an average is
smoother than its endpoints), which is why commodity and FX hedging
programs default to them.
A call auction (open/close/volatility uncross): orders accumulate without
trading, then a single clearing price executes the maximum matchable
volume — the mechanism behind exchange opens, the close every
benchmark-tracking strategy trades, and LULD/volatility-halt reopenings.
Auction outcome: clearing price, matched volume, and leftover imbalance.
Autocallable note pricer, the most common equity structured product: a
note that pays a fat coupon and redeems early ("autocalls") the first
observation date the underlier closes at or above the autocall
barrier.
Bachelier (normal) model for options on a forward: the forward follows
dF = σ_N dW, so it can go negative and σ_N is quoted in absolute rate units
(0.0080 = 80 basis points a year).
P&L attribution of a traced backtest over time: factor, specific,
trading, cost and financing components per bar, with long/short leg and
sector splits.
Backtest execution parameters.
Event-driven, single-instrument, long-only backtesting engine.
A segment's result and the state it ended in.
Book state carried between segments.
Result of a backtest run: full equity curve (one point per bar), completed
trade history, and derived performance metrics.
Immutable OHLCV bar.
Continuously monitored single-barrier options: all eight in/out, up/down,
call/put combinations, regular and reverse, with a cash rebate.
Barrier direction relative to spot.
Whether the barrier activates or extinguishes the option.
Immutable, cache-friendly OHLCV time series backed by primitive arrays
(structure-of-arrays layout, no boxing) so indicators read primitive columns directly.
Benchmark-relative performance — the numbers an allocator actually asks
for.
Strategy statistics relative to a benchmark.
The dynamic benchmark execution algorithm: one stateful executor that
works a parent order toward any of the standard benchmarks (VWAP,
TWAP, Arrival Price, Implementation Shortfall, Closing Price, Opening
Price, and Participation (POV)).
The benchmark this parent is measured against.
A snapshot of the real-time inputs a benchmark algo evaluates.
Execution-quality analytics of the kind a MiFID II best-execution review
starts from: slippage versus arrival mid (simple average per order and
quantity-weighted), latency-to-fill distribution, fraction executed at or
better than arrival, and per-venue slippage.
Best-execution summary.
One parent order outcome.
Perold (1988) implementation shortfall of one order, in currency:
Cox-Ross-Rubinstein binomial tree for European and American options with a
continuous carry yield (dividends / foreign rate).
Black-76 — the Black-Scholes sibling for options on forwards and
futures: rates caps/floors and swaptions, commodity futures options,
bond futures options.
Black-Litterman expected returns: start from the market-implied equilibrium
(reverse optimization of the market portfolio) and blend in investor views
with explicit confidences — the standard cure for mean-variance
optimizers' hypersensitivity to raw return estimates (Black and Litterman
1992; He and Litterman 1999).
Posterior mean, posterior covariance of the mean M, and Σ + M.
Black-Scholes-Merton option pricing and Greeks with a continuous carry
yield
q: set q to the dividend yield for equities or the
foreign interest rate for FX (Garman-Kohlhagen).Full Greek set for one option.
Stationary block bootstrap (Politis-Romano) — the confidence interval
your backtest's Sharpe ratio deserves and almost never gets.
Fixed-coupon bond analytics: price/yield conversion, Macaulay and modified
duration, convexity, and DV01.
Bucketed curve risk from the analytic Jacobian of the bootstrap, instead
of bumping each quote and rebuilding the curves (
MultiCurveRisk).Business-day calendar: weekends plus a holiday set, with the standard roll
conventions, settlement-lag arithmetic, and coupon schedule generation.
Date roll conventions for payment dates landing on non-business days.
Where an irregular (stub) period goes when the dates do not divide
into whole periods (ISDA 2006 definitions, section 4.14 and market
practice).
Calendar anomaly profiles: day-of-week and turn-of-month seasonality
with their t-statistics.
Per-day-of-week profile, indexed Monday = 0 … Sunday = 6.
The turn-of-month split.
Strategy capacity: net Sharpe ratio against book size.
CDS pricing off a
CreditCurve: the two legs, the par spread,
and the upfront that post-2009 standardized contracts actually
exchange.The central risk book — one netted view of the firm's market risk
across desks and products.
Snapshot of the book's exposures.
Multi-day persistence of learned state.
Random access to a loaded checkpoint's sections by name.
A model's state deserializer — typically a
readState reference.A model's state serializer — typically a
writeState reference.Collects named sections and commits them atomically on close.
US-equities trading safeguards, styled after the SEC's Limit Up-Limit Down
plan and the market-wide circuit-breaker rule (not certified
implementations — the regulatory texts govern):
LULD price bands (
CircuitBreakers.luldBandPct(double, boolean, boolean), CircuitBreakers.Luld) —
per-symbol bands around a reference price; quoting at a band edge
enters a limit state, and a limit state that persists 15 seconds
becomes a 5-minute trading pause;
Market-wide circuit breakers (CircuitBreakers.MarketWide) — S&P 500
declines of 7% / 13% halt the market for 15 minutes (each at most
once per day, and not after 15:25), and 20% halts for the day.
MWCB halt decision.
The LULD limit-state machine for one symbol: enters a limit state when
the inside quote pins a band edge, converts to a 5-minute pause when
the limit state persists 15 seconds, and exits the pause after it
elapses.
LULD per-symbol state.
Market-wide circuit-breaker day state: feed it the S&P 500 decline
from the prior close and the time of day; it applies the once-per-day
and not-after-15:25 rules for Levels 1 and 2.
Closing-auction participation model.
Engle-Granger two-step cointegration test: regress one price series on the
other, then run an augmented Dickey-Fuller test (no constant) on the
residual spread.
Commodity futures curve.
Component VaR — the answer to the risk committee's actual question.
Concentration risk metrics over exposures (by asset, counterparty, sector,
currency, ...): Herfindahl-Hirschman index, effective number of positions,
top-N share, and single-name limit breaches.
A configuration that is syntactically wrong or names a value outside its
allowed range: an unknown or repeated key in a limits file, a price collar
above 100 %, a non-positive order-size cap.
Constrained long-only optimiser: per-asset weight bounds (position caps
and floors) and an optional turnover penalty against current holdings,
adjusted return = μ'w − τ·Σ|w − w_current|, so the optimiser
trades expected gain against the cost of getting there.Corporate action adjustment: back-adjusts a raw price series for splits and
cash dividends (CRSP-style multiplicative factors), so returns computed
across ex-dates reflect economics rather than mechanical price drops — the
difference between toy and usable equity backtests.
One corporate action, effective from its ex timestamp.
Position-side treatment of
CorporateEvents: what happens to a
holding's share count, cost basis and cash.One holding of an instrument.
Result of applying an event: the resulting holdings (the original
instrument first, possibly with zero shares) and cash received.
Extended corporate actions and the back-adjustment factors they imply.
Cash-and-stock merger with holder election and proration.
Cash dividend tagged regular or special.
Regular or special cash dividend.
Which dividends enter the back-adjustment.
A corporate event effective from its ex timestamp.
Reverse split:
oldPerNew old shares are consolidated into one.Rights issue:
ratio new shares per old share at subscriptionPrice.Spin-off of a new instrument.
Stock dividend or bonus issue:
rate new shares per share held (0.05 = 5 %).Symbol and/or ISIN change; no economic effect.
Correlation and covariance matrices from a returns matrix laid out as
returns[asset][time].Counterparty credit exposure modeling with netting:
Current exposure — max(0, net mark-to-market) per netting set.
Potential future exposure — notional add-ons by tenor bucket
using the FX/gold factors of the Basel Current Exposure Method
(1988 Accord Annex 3 as amended in 1995: <1y 1%, 1–5y 5%,
>5y 7.5%), applied to every trade whatever its
product.
Ledoit-Wolf covariance shrinkage (2004, "A well-conditioned estimator
for large-dimensional covariance matrices"): the standard fix for the
dirty secret of portfolio optimization.
The central risk book's hedging loop: per-factor exposure bands, a
cost-aware hedge when breached, and a cooldown so the book does not
chase its own hedges.
One instrument's hedge instruction.
The hedge-instrument universe, aligned to a book's factor registry —
because hand-assembling
loadings[factor][instrument] is the
most error-prone step in the whole hedging workflow (one transposed
index and the optimizer confidently hedges the wrong thing).The central risk book's economics ledger — the number the desk head
actually asks for at the close: did the spread we captured by
internalizing pay for the hedging we did?
The central risk book's order router — internal cross first, dark
pools second, lit last, each leg priced at its expected all-in cost:
Internal — crossing against the book's own offsetting
inventory costs zero bps and leaks nothing: the CRB itself is
the firm's first and best dark pool.
Where the notional went.
A dark venue as the router sees it.
Credit curve — piecewise-constant hazard rates bootstrapped from CDS par
spreads, the credit market's exact analogue of
YieldCurve's
bootstrap: walk the quotes from shortest to longest, at each pillar
solving for the one hazard rate that reprices that maturity's CDS to
zero upfront given everything already solved.Bond credit-spread measures — the translation layer between a bond's
price and how much of it is credit.
How two leg prices compose into a cross rate.
Point-in-time cross-sectional momentum — the classic equity factor, built
to demonstrate (and test) universe-aware backtesting: at every rebalance
the strategy ranks only the stocks that are index members at that
bar's timestamp, goes long the best trailing performers and short the
worst.
Momentum strategy settings.
Market conventions for an FX currency pair: quotation precision, pip size,
spot lag, and settlement-date arithmetic against both currencies'
holiday calendars.
A quoted market instrument a
MultiCurveBootstrap fits a curve to.How a
DiscountCurve fills in between its pillars.A discount curve (OIS) and the projection curve of one index, as built by
MultiCurveRisk.buildCurves(LocalDate, List, List, CurveInterpolation).Unilateral CVA — the price of the counterparty in every derivative you
hold: the expected loss from their default before your trades' cash
flows finish arriving.
Bilateral CVA and DVA with first-to-default conditioning.
Midpoint-cross dark pool model: hidden resting orders match at the current
lit-market midpoint, honoring minimum-execution-quantity constraints (a
standard anti-gaming feature).
Day-count conventions: the year fraction between two dates as real term
sheets define it — because finance never agreed on how long a year is,
and the disagreement is worth real money.
Day-type-aware seasonality: not every trading day has the same shape.
Dynamic delta hedging simulator: sell an option, then replicate it by
trading the underlying along a price path, rebalancing whenever the delta
drifts outside a band.
Hedging settings.
Rank-based dependence measures — what Pearson correlation misses.
A cash deposit over
[start, end] at simple rate rate:
1 at start grows to 1 + rate * tau at end, tau from
dayCount.European digital (binary) options under Black-Scholes — the building
blocks of the first-generation FX exotics book.
A dated discount curve
P(t) built from pillar discount factors:
the object both an OIS discount curve and a projection curve (for example
a 3M forwarding curve, a pseudo-discount curve whose ratios give the index
forwards) are made of.Discrete (cash) dividends for equity derivatives — the forward-looking
counterpart to
data.CorporateActions' historical back-adjustment.European and American options on a stock paying discrete cash dividends,
on a recombining Cox-Ross-Rubinstein tree, by the method of Vellekoop and
Nieuwenhuis (2006, "Efficient pricing of derivatives on assets with
discrete dividends", Applied Mathematical Finance 13(3), 265-284).
Drawdown structure — because "max drawdown 18%" hides the number that
actually fires clients: how long the pain lasted.
One peak-to-recovery episode.
Drawdown statistics of an equity curve.
Dupire (1994) local volatility from an implied total-variance surface,
in Gatheral's form (Gatheral 2006, The Volatility Surface,
equation 1.10):
EGARCH(1,1) — Nelson's exponential GARCH, the log-variance dynamics
the plain family cannot express:
Streaming EWMA covariance matrix: the multi-asset risk picture that
single-symbol volatility cannot see.
Exponentially weighted moving average variance (RiskMetrics Technical
Document, J.P.
Two-asset closed forms: Margrabe's exchange option and Kirk's spread
approximation — the workhorse formulas for relative-value option books
(crack spreads, calendar spreads, stock-vs-index switches).
A matched trade (fill) for TCA and venue analytics.
Backtests the dynamic execution stack over bar data.
Execution simulation settings.
The TCA-style verdict for one parent worked over one session.
Execution-aware backtesting engine: strategy signals create parent
orders that are worked through an
ExecutionModel — routed by
SorExecution, sliced by IcebergExecution, or filled
instantly by InstantExecution.Result of an execution-aware backtest: the standard
BacktestResult
(equity curve, trades, performance metrics) plus the full parent-order /
child-fill history, with one-call TCA per parent order.How parent orders turn into fills in an execution-aware backtest
(
ExecutionAwareBacktester).Output of
MultiCurrencyExposureSimulator: per exposure date, the profile
statistics, and per path, the discounted exposures the wrong-way CVA in
CvaApproximator needs.Market factor used as the wrong-way driver.
Extreme value theory via peaks-over-threshold — the statistically
principled way to ask about quantiles beyond the sample.
A fitted POT tail model.
A maximum-likelihood GPD fit with asymptotic standard errors
Var ξ̂ = (1+ξ)²/m, Var β̂ = 2β²(1+ξ)/m (Smith 1987).Dense integer ids for risk-factor names — the
SymbolRegistry
pattern applied to the central risk book's factor space, so exposure
arithmetic runs over primitive arrays while the factor names stay
readable (EQ:AAPL, CCY:EUR, FXVEGA:EURUSD).Factor return streams built from the library's own factors, the input
AlphaReport.attribute(double[], double[][], List) regresses a portfolio on.Fundamental equity factor risk model in the Barra USE4 style: a market
factor, one dummy factor per sector and standardised style factors,
estimated by weighted cross-sectional regression each period.
Ex-ante risk of one portfolio under the model.
Estimation settings.
The standard alpha factor library — nine signal generators covering the
classic technical, factor-investing and defensive families.
Latency-adjusted fair value for rapidly updating order books.
Fama-MacBeth (1973, J.
When an order decided on bar
t is filled.Passive-fill probability for a limit order resting away from the touch —
the placement question
QueueModel alone can't answer.WM/R-style 4pm fix analysis: computes a fix rate from samples inside the
fixing window and screens a participant's flow for the classic "banging
the close" signature — a large share of window volume, a price run-up
aligned with the participant's net flow into the fix, and reversion
afterwards.
The fixed leg of a
VanillaSwap: coupons rate * tau_i paid
on each period's payment date, with the schedule, day count, stub and
payment lag from a LegConvention.Published fixings of one index (for example SOFR), by fixing date.
Analytics for benchmark-fixing exposure — the risk concentrated in the
short calculation window of an official fix (WM/R 4pm London, the RBI
reference rate an NDF settles on, an equity closing auction).
The floating leg of a
VanillaSwap: either a compounded overnight
leg (OvernightLeg, SOFR-style) or a term-rate leg
(TermRateLeg, IBOR-style).Streaming order-flow signals for short-horizon execution decisions: the
three imbalances an execution engine reads before crossing a spread.
Implied FX forward curve from market outright forwards, with
interpolation, implied rate differentials, and covered-interest-parity
checks against deposit rates.
A forward rate agreement on the index period
[start, end] at
fixed rate rate.FRTB standardised default risk charge (DRC) for non-securitisation
positions, styled after BCBS d457 chapter MAR22.
Default risk weights by credit quality (MAR22.24 Table 2, verified).
A net JTD per obligor (signed) and its risk weight.
FRTB standardised default risk charge (DRC) for securitisations, both
outside the correlation trading portfolio (non-CTP, MAR22.27 to
MAR22.35) and inside it (CTP, MAR22.36 to MAR22.45).
The 11 asset classes of MAR22.31(2)(a), plus the corporates bucket of MAR22.31(1).
Long-term rating grades of SEC-ERBA Tables 2 and 4 (CRE42.4, CRE42.13).
Short-term rating grades of SEC-ERBA Tables 1 and 3 (CRE42.2, CRE42.12).
A net JTD of one tranche (signed, positive long) and its DRC risk weight per unit of JTD.
A non-CTP bucket (MAR22.31, MAR22.32).
A net tranche JTD tagged with its bucket key (a
FrtbDrcSecuritisation.NonCtpBucket, or an index name for the CTP).The four regions of MAR22.31(2)(b).
FRTB Internal Models Approach expected shortfall — the market-risk
capital measure that replaced 10-day VaR: ES at 97.5%, computed on a
base 10-day horizon and scaled up across liquidity horizons (how long
each risk factor class realistically takes to exit under stress: 10
days for major FX and rates, up to 120 for exotic credit), then
anchored to a stressed period:
The Basel backtesting traffic light over 250 days of 99% VaR
exceptions: GREEN ≤ 4 (model fine), AMBER 5-9 (capital multiplier
rises), RED ≥ 10 (model presumed wrong).
Capital for non-modellable risk factors (NMRF) under the FRTB internal
models approach, styled after BCBS d457 chapter MAR33.
FRTB residual risk add-on, styled after BCBS d457 chapter MAR23.
FRTB standardised approach, sensitivities-based method (SBM), styled
after BCBS d457 (January 2019) chapter MAR21.
One bucket: weighted sensitivities and the medium-scenario
intra-bucket correlation matrix (diagonal ignored).
Bucket-level result.
Commodity parameters, buckets 1-11.
Credit spread risk, non-securitisation (MAR21.51 to MAR21.57).
Equity (spot) parameters, buckets 1-13.
FX parameters.
General interest rate risk parameters.
One risk class: delta, vega and curvature inputs (any may be empty).
Correlation scenarios of MAR21.
CSR securitisation (non-CTP), buckets 1-25 (MAR21.62 to MAR21.71).
Fundamental screening filters.
Fundamental data for one instrument.
Point-in-time fundamentals: every record is keyed by the time it became
public, and
FundamentalsHistory.asOf(String, long) returns only what was published by then.One published record.
The futures roll: the trade every futures position must do and most
do badly.
FX exposure hedging with forwards: nets currency exposures across a book,
computes the variance-minimizing hedge ratio for a foreign-asset position,
and prices the carry cost of the forward hedge from forward points.
One currency exposure, signed, in base-currency terms.
An FX swap: two offsetting FX exchanges (buy, or sell, base currency on
the near date; sell, or buy, it back on the far date).
Tiered multi-LP FX book: the depth structure e-FX actually has.
FX volatility surface built from the market's delta-quoted smile: ATM,
25-delta risk reversal and butterfly, optionally 10-delta wings.
Which strike the ATM vol refers to.
Accumulates per-expiry delta quotes, then solves strikes once in
FxVolSurface.Builder.build().What the quoted butterfly is.
How the quoted deltas are defined (Reiswich and Wystup 2010, table 1).
One expiry's solved smile: absolute strikes and vols, low to high strike.
GARCH(1,1) volatility model (Bollerslev 1986, J.
A fitted model with its uncertainty.
Gaussian and Student-t copula samplers — dependence separated from
marginals, which is the entire point of copula modeling: "these five
factors co-move like this" (the copula) is a different statement from
"each factor's own distribution looks like THAT" (the marginals), and
gluing arbitrary marginals to a chosen dependence structure is how
joint risk scenarios get built.
GJR-GARCH(1,1,1) — GARCH with the leverage term equity markets demand:
Gradient-boosted regression over decision stumps (XGBoost-style additive
boosting with squared-error loss), implemented in pure Java with no
dependencies.
Greek-neutralization: solves the hedge quantities that flatten a
portfolio's option Greeks using available hedge instruments — the standard
delta-gamma and delta-gamma-vega hedging recipes, plus a general linear
solver for arbitrary greek/instrument combinations.
Per-unit Greeks of a hedge instrument (the underlying is delta=1, gamma=0, vega=0).
Exhaustive strategy parameter search: backtests every grid combination and
ranks by an objective (e.g.
One grid point: its parameters, metrics, objective and equity curve.
HAR-RV (Corsi's Heterogeneous AutoRegressive realized-volatility
model) — the forecasting benchmark GARCH papers have to beat, and it
is three regressors and an intercept:
Fitted coefficients with Newey-West standard errors (order: intercept,
daily, weekly, monthly), residual variance and the regression size.
Fitted coefficients:
rv⁺ = c + βd·d + βw·w + βm·m.Self-exciting (Hawkes) event intensity — the model behind the trader's
observation that "activity breeds activity": one trade raises the
probability of the next, so order flow arrives in bursts, not as a
steady Poisson drizzle.
A maximum-likelihood calibration.
Cost-aware minimum-variance hedging of the central risk book's
residual — the question is never "how do we flatten this" (sell
everything) but "what is the cheapest basket of liquid instruments
that takes the risk below the limit".
Distribution of delta-hedging P&L across Monte Carlo paths: how well the
hedge replicates the option, where the tail risk sits, and what the hedging
itself costs.
Monte Carlo delta-hedging engine: runs
DeltaHedger across thousands
of GBM paths in parallel to produce the full hedging-error distribution —
replication error, tail risk (hedging VaR/CVaR), and cost/rebalance
statistics.Heston (1993) stochastic-volatility pricing — the canonical answer to
Black-Scholes' one visible lie, the flat smile.
Model parameters.
Calibrates the five
Heston.Params to a grid of Black-Scholes implied
volatilities by Levenberg-Marquardt (Levenberg 1944; Marquardt 1963, with
Marquardt's diagonal scaling).Calibration outcome.
Heston European options by the COS method of Fang and Oosterlee (2008, "A
novel pricing method for European options based on Fourier-cosine series
expansions", SIAM J.
Hot-lane smart order router: the zero-allocation sibling of
SmartOrderRouter, for when the routing decision sits on the
tick-to-order path.Hidden-liquidity / iceberg detection from the lit tape.
The second-order Greeks a vol book actually hedges with — analytic
Black-Scholes forms, the risk-side complement to
BlackScholes.greeks(BlackScholes.OptionType, double, double, double, double, double, double):
Vanna ∂²V/∂S∂σ — how delta drifts when vol moves
(equivalently, how vega drifts when spot moves).Rule-based holiday calendars for four settlement centres, generated as
BusinessCalendar objects for a range of years.The settlement centres with rule-based calendars.
Iceberg execution: wraps another
ExecutionModel and caps each bar's
execution at the IcebergOrder state machine's visible tranche
(optionally randomized), plus an optional participation cap versus the
bar's volume.Iceberg order state machine: shows only a small display tranche of the full
quantity and reloads automatically when the visible portion fills.
Sampling error of an exponentially weighted correlation, used to gate
learned signals on significance rather than on the sign of a noisy IC.
Marks a class whose instances cannot change after construction: all fields
are final, referenced arrays and collections are private copies that never
escape, and every method that sounds like a mutator (
add...,
with...) returns a new value instead.Implementation-shortfall (arrival-price) schedule: turns the
AlmgrenChriss optimal trajectory into executable Slices.Black (lognormal) implied volatility by a safeguarded Newton iteration on
the normalised Black function.
Tick-frequency Greek estimation without tick-frequency repricing: a full
Black-Scholes evaluation anchors the position, and every tick updates
price/delta by the delta-gamma Taylor expansion (a handful of multiplies,
zero allocation) while the anchor is refreshed off the hot path.
Index construction — the arithmetic behind "the market was up 1%".
Technical Indicator Engine: implementations of the standard
technical analysis toolkit.
Ichimoku lines.
direction: +1 = uptrend (value is support), -1 = downtrend (value is resistance).
AIC and BIC information criteria for model selection.
Distribution of the standardised innovation
z_t = r_t / √h_t in
the GARCH-family likelihoods.Baseline execution model: the full quantity fills at the bar close with
commission and slippage folded into the all-in price — equivalent to the
classic
Backtester fill assumption.A vanilla fixed-for-floating interest rate swap in the multi-curve
framework: the floating coupons are projected off a projection curve
(for example 3M) and both legs are discounted on the OIS curve
(collateralised pricing; Bianchetti 2010, "Two curves, one price", Risk
23(8); Ametrano and Bianchetti 2013, "Everything you always wanted to
know about multiple interest rate curve bootstrapping but were afraid to
ask", SSRN 2219548).
The internalize-or-route decision — the economics that justify a
central risk book's existence.
Where one flow went, and what the client got for it.
Intraday liquidity forecasting: accumulates per-bucket volumes across days
into a seasonal profile (e.g. 24 hourly buckets) to predict when liquidity
peaks — London open, the London/New York overlap, etc.
The ISDA CDS Standard Model: the pricing conventions every post-2009
standard CDS is quoted and settled with, beside the textbook quarterly
grid of
CdsPricer.One CDS contract's dates and terms.
Model conventions beyond the contract terms.
One premium period of the coupon schedule.
A curve of the kind the ISDA CDS Standard Model works on: continuously
compounded zero rates r_i at node times t_i (years, ACT/365F from the
curve's base date), interpolated linearly in
r(t) * t.Builds the discount curve of the ISDA CDS Standard Model from par swap
rates (the swap-only RFR curve used by the SOFR-era test grids).
One par swap quote.
Jump-robust streaming volatility.
Time-varying regression by Kalman filter — the pairs desk's upgrade
over a static OLS hedge ratio.
Key-rate durations: where on the curve a bond's rate risk lives.
Kyle's lambda: market impact learned from the tape instead of assumed
from a formula.
Last-look execution model — the missing realism for FX backtests: on ECN
and single-dealer FX liquidity, the provider holds your order briefly and
may reject it if the price moves against them during the hold.
Streaming cross-asset lead-lag estimation: does instrument A's return
now predict instrument B's return a few intervals from now?
The schedule and accrual conventions of one swap leg: how often it pays,
how a period's year fraction is measured, which calendar and roll adjust
the dates, where a stub goes, and how many business days after the accrual
end the payment is made.
One accrual period.
Dense linear algebra on
double[][] row-major matrices: dot and
matrix-vector products, the quadratic form, Cholesky, a linear solve and
the inverse.Liquidity estimated from bars alone — the estimators for every
market where you have prices but no quotes: history before your tick
capture started, less-developed markets, bonds marked once a day, or
a 20-year backtest that would otherwise pretend spreads were zero.
The opportunistic execution archetype, counterpart to
BenchmarkExecutor's schedule-driven family.Algorithm settings.
Monte Carlo under Dupire local volatility, log-Euler scheme:
Price and its Monte Carlo standard error.
Finite-difference pricer for European options under Dupire local
volatility.
Last-look-aware LP router: chooses where to send an FX clip by
expected all-in price, not displayed price.
Streaming per-LP execution quality: the taker-side answer to last look.
A data file or text record that does not follow its format: a CSV with no
header or missing required columns, a universe file line with the wrong
column count, an unparseable timestamp.
A file or saved state that this library cannot read because its contents
are wrong, not because the read failed: a bad magic number, an unknown
format version, a duplicate checkpoint section, a journal that is not a
FIX journal.
Temporary / permanent market impact models for large trades, parameterized
by average daily volume (ADV) and daily volatility:
Square-root law (empirical standard):
impact = Y * sigma_daily * sqrt(Q / ADV).
Almgren-Chriss style decomposition: linear temporary impact in
participation rate and linear permanent impact in size, with the
expected cost of an execution schedule
E[cost] = permanent/2 + temporary.
All results in basis points of the arrival price.ML market impact prediction: learns realized impact (bps) from order and
book features using gradient-boosted trees, and estimates the probability a
marketable order sweeps through the visible top of book.
Market quality indices used in execution-quality and venue-quality
reporting: quoted / effective / realized spread, price impact, and
order-to-trade ratio.
Mid-rate pegging model: tracks the target price of a mid-pegged order with
an offset and optional limit cap, and decides when the peg has drifted far
enough to justify a reprice (each reprice costs queue priority and a
message, so small moves are ignored).
Minimum-variance and beta hedging with futures or a correlated proxy:
Optimal hedge ratio
h* = cov(asset, hedge) / var(hedge)
— the classic OLS/minimum-variance ratio.
Hedge effectiveness — the fraction of variance removed at the
optimal ratio (= correlation², the standard 80%+ effectiveness test).
Futures contract sizing — contracts to move a portfolio from
its current beta to a target beta.
Monte Carlo simulation of geometric Brownian motion, single- and
multi-asset, in parallel; results are deterministic for a given seed
regardless of thread scheduling (each scenario has its own
SplittableRandom stream derived from the seed).Monte Carlo estimate: mean, its standard error, and the number of independent samples.
Payoff of one simulated path.
Monte Carlo trade reshuffling: the answer to "was my equity curve's
shape luck?".
Drawdown distribution across trade-order shuffles.
Monte Carlo exposure generator for a netting set of multi-curve swaps
and FX forwards on several currency pairs, each foreign currency with
its own stochastic short rate.
Stochastic projection-discount basis for domestic swaps that carry a
projection curve (added in 2.3).
Collateral agreement terms (two-way, symmetric).
A discount function
t -> P(0,t), t in years, P(0,0) = 1.Domestic Hull-White short rate.
One foreign currency: its Hull-White short rate and the spot against
the domestic currency (domestic per foreign).
A swap in a foreign currency (added in 2.3).
An FX forward on one pair.
FX forward: buy
foreignNotional units of foreign currency at
strike domestic per foreign at maturityYears; a
negative notional sells.The market: domestic rate, foreign currencies, and the correlation of
the factors
[W_d, W_1, W_S1, W_2, W_S2, ...].A domestic swap with an optional projection curve for its floating leg.
Vanilla fixed-for-floating swap.
Multi-curve bootstrap: an OIS discount curve fitted to its own
instruments, then projection curves (3M, 6M, ...) fitted with the OIS
curve held fixed for discounting (Ametrano and Bianchetti 2013, SSRN
2219548, sections 3-4).
Curve risk on a bootstrapped OIS + projection curve pair by bumping the
market quotes and rebuilding: the sensitivities a desk hedges with,
because they are expressed in the instruments it can trade.
A non-deliverable forward: the FX forward for restricted currencies (INR,
KRW, TWD, BRL, CNY, ...) where the local currency never moves.
Derivative-free minimisation by the Nelder-Mead simplex method with the
standard coefficients (reflection 1, expansion 2, contraction 1/2, shrink
1/2), following Lagarias, Reeds, Wright and Wright, "Convergence
properties of the Nelder-Mead simplex method in low dimensions", SIAM J.
Result: argmin, minimum, objective evaluations used.
Nelson-Siegel yield-curve fit — the parametric answer to "what shape is
the curve", where
YieldCurve is the exact-repricing answer to
"what IS the curve".Fitted parameters plus the fit's root-mean-square error.
Heteroskedasticity and autocorrelation consistent (HAC) standard errors
with Bartlett weights (Newey and West 1987, Econometrica 55(3), eq. 2).
Small array and scalar helpers: clamping, NaN-filled arrays, the
half-life decay factor and an allocation-free paired sort.
An overnight indexed swap: fixed rate against the daily-compounded
overnight rate (SOFR, ESTR, SONIA), same schedule on both legs, payment
on the accrual end date (no payment lag).
Ordinary least squares by Householder QR, with classical and
Newey-West HAC standard errors.
Online alpha-weight learning: upgrades
SignalEngine.alpha(int)'s fixed
composite weights to weights learned from realized returns — an
online ridge regression (SGD with L2 shrinkage) from the four
dimensionless signal ingredients (queue imbalance, trade imbalance,
normalized OFI, momentum-Z) to the next-interval return.An options book on one underlying: aggregate Greeks across positions,
spot×vol scenario grids, and delta-gamma-vega-theta P&L explain — the
risk view a desk runs, not a single option.
Aggregated book value and Greeks.
One option position;
quantity in option units (contract multiplier applied by caller).Taylor attribution of a P&L move: delta, gamma, vega, vanna
(
∂²V/∂S∂σ · dS·dσ), volga (½·∂²V/∂σ² · dσ²) and theta,
with the remainder in unexplained.The post-or-cross decision — the smallest and most repeated choice in
execution, made explicit as expected-cost arithmetic instead of
habit.
The decision plus the arithmetic that made it.
The fill-probability region where posting beats crossing.
Ornstein-Uhlenbeck estimation — the mean-reversion engine under every
pairs trade and basis position:
dx = κ(θ − x)dt + σ dW.Fitted process parameters.
Probability of backtest overfitting via combinatorially symmetric
cross-validation — CSCV (Bailey, Borwein, Lopez de Prado & Zhu 2015,
"The probability of backtest overfitting").
How a compounded-in-arrears overnight coupon (SOFR, ESTR, SONIA) reads its
daily fixings: lookback, observation shift and lockout, as described in
the ISDA 2021 Interest Rate Derivatives Definitions (section 6.9,
overnight rate compounding) and the ARRC SOFR conventions.
A compounded-in-arrears overnight floating leg (SOFR, ESTR, SONIA) with
payment lag, lookback, observation shift, lockout, stubs and realised
fixings for seasoned trades.
Statistical (pairs) hedging: regresses one price series on another to get
the hedge ratio, builds the spread, and characterizes its mean reversion —
z-score for entry/exit signals and half-life (from an AR(1) fit of spread
changes on spread levels) for expected holding time.
A named parameter grid for strategy optimization;
ParameterGrid.combinations()
enumerates the cartesian product in deterministic order.One parent order worked by the
ExecutionAwareBacktester: the signal
that created it, the arrival price (close at signal time — the TCA
benchmark), and the child fills with the bar index each filled on.Principal component analysis of a covariance matrix: the risk-factor
compressor.
Computes
PerformanceMetrics from an equity curve and trade history.Strategy performance analytics.
FRTB P&L attribution test (PLAT), the exam a risk model must pass
to keep internal-model approval.
The PLAT verdict for one desk over one window.
Point-in-time universe membership — the engine-side half of
survivorship-bias-free backtesting.
How a security's life ends.
A security's terminal event.
Multi-asset portfolio of positions with live price updates.
Multi-asset, long/short portfolio backtester: rebalances positions (possibly
fractional and negative) toward the strategy's target weights at a
configurable cadence, charging commission on traded notional.
costModel, when set, supersedes the flat commissionRate
for every trade (rebalances and forced index-drop sales alike), the
shared TradeCostModel seam that makes a run survivorship-aware
and execution-aware at once.Financing terms, all annual.
Participation cap: each symbol trades at most
maxFractionOfAdv × ADV shares per bar, with ADV the mean
volume of the advWindow bars before the fill bar (fewer at the
start of the data; none on bar 0, so nothing trades there).dividendCashCredited and lifecycleEventsApplied are
populated by the survivorship-aware overload (zero otherwise).Turns raw factor scores into tradeable weight vectors, as a
chain of small, composable, pure functions so a construction pipeline
reads as what it does:
A constructed book with what it actually achieved.
True multi-symbol portfolio-level scheduling: a basket (rebalance,
transition, program trade) executed as one coordinated schedule rather
than N independent parents.
Execution limits for the portfolio.
Long-only, fully invested mean-variance optimisation (Markowitz 1952),
solved exactly as convex quadratic programs by
QuadraticProgram:
minimum variance: min w'Σw s.t.An optimized allocation with its risk/return profile (same periodicity as the inputs).
Portfolio-level risk engine: portfolio VaR/CVaR/volatility, asset-level
risk, exposure analysis, correlation analysis, and risk decomposition
(marginal contribution to risk).
Full risk report.
A multi-asset, weight-based strategy for the
PortfolioBacktester.Position sizing rules: Kelly, fixed-fractional risk, inverse-volatility
weighting, and volatility targeting — the building blocks for
PortfolioStrategy weight construction.POV (percentage-of-volume) execution tracker: the streaming counterpart of
the precomputed
TwapScheduler/VwapScheduler schedules.Pre-trade risk gate: validates every order against configured limits before
it reaches the market — order size, notional, resulting position, price
collar versus a reference mid, restricted symbols, and counterparty credit
headroom.
Private-market analytics — the toolkit for the asset class where the
usual machinery fails on purpose: no daily prices, cash flows the
manager (not the investor) times, and NAVs that are appraisals rather
than trades.
Factorisation and repair of symmetric positive semi-definite matrices:
the one place in the risk, simulation and copula code that decides what a
"valid covariance" is.
Eigenvalues (descending) and matching unit eigenvectors
vectors[k].Purged K-fold cross-validation splits with an embargo — the fix for the
quiet leak that ordinary K-fold has on financial data (Lopez de Prado,
Advances in Financial Machine Learning, ch. 7).
One fold: test on
[testFrom, testTo), train on
trainIndices (ascending, purged and embargoed).Convex quadratic programming by the primal active-set method (Nocedal and
Wright, Numerical Optimization, 2nd ed., Algorithm 16.3):
Solution, its objective value, and the active-set iterations used.
Marks an exception raised by this library for a fault in what it was
given: a broken wire frame, a malformed data file or an invalid
configuration.
Quanto vanilla: a payoff on a foreign asset S (quoted in foreign currency)
paid in domestic currency at a fixed conversion rate, for example a Nikkei
call paying
max(S_T - K, 0) US dollars per index point.Queue positioning and priority analytics: how position in the price-time
queue (and small latency differences in reaching it) translates into
fill probability.
Queue position estimation from L2 data — for when you don't have
the L3 feed that
marketdata.L3BookBuilder needs to track position
exactly.Range-based volatility estimators — the free lunch hiding inside every
OHLC bar: the high-low range carries far more information about the
day's variance than the close alone, so a range estimator reaches a
given precision with several times fewer bars than close-to-close.
Ranking engine: scores stocks by a weighted blend of min-max-normalized
criteria and sorts them best-first.
A short-term interest rate future (3M SOFR/Euribor style) on the index
period
[start, end], quoted by its futures rate
rate = (100 - price)/100.Rates volatility products priced off the curve: the bridge between
YieldCurve (where forwards and discount factors live) and the
option models on a forward rate, pricing.Black76 (lognormal and
shifted lognormal) and pricing.Bachelier (normal).A vol type together with its displacement (0 unless shifted lognormal).
Which vol a quote is: lognormal (Black-76), shifted lognormal
(Black-76 on forward + shift and strike + shift) or normal (Bachelier).
Two-state Gaussian Markov-switching model (hidden Markov model) fitted by
Baum-Welch EM with scaled forward-backward recursions (Rabiner 1989,
Proc.
Pluggable risk metric over a periodic return series.
Custom Risk Metrics Framework: registry of built-in and user-defined risk
metrics, evaluated together over a return series.
Core quantitative risk metrics.
Risk parity: the portfolio where every asset contributes a set share of
total risk (
w_i (Σw)_i / w'Σw = b_i; equal shares by default).SABR stochastic volatility model: the Hagan, Kumar, Lesniewski and
Woodward (2002) lognormal implied-vol expansion ("Managing smile risk",
Wilmott, eq. 2.17a), and calibration of (α, ρ, ν) with β fixed.
Calibrated SABR parameters.
Standardised approach for counterparty credit risk, SA-CCR (Basel
Committee, "The standardised approach for measuring counterparty
credit risk exposures", BCBS 279, March 2014, Annex 4).
The five SA-CCR asset classes.
The four commodity hedging sets (para 161).
Credit rating buckets and their supervisory factors (Table 2).
Hedging-set kind of a trade (paras 162-163) and its multiplier on
the supervisory factor.
Margin agreement terms for a margined netting set.
SA-CCR outputs for one netting set.
One part of a netting set for
SaCcr.subNettingSets(List): the trades
under one margin agreement (or the unmargined trades when
margin is null) and the haircut collateral that belongs to
them.Supervisory haircuts for the collateral C and the NICA that enter
SA-CCR.
Collateral kinds of the supervisory haircut table.
Issue rating buckets for debt collateral.
Debt classes of the CRE22.50 table (jurisdictions without external ratings).
Which supervisory haircut table to use.
One derivative as the SA-CCR sees it (BCBS 279, March 2014, Annex 4):
the asset class, the hedging-set key, the inputs to the trade-level
adjusted notional and the supervisory delta.
Composable screening predicate over a
StockSnapshot.Aligns multi-asset bar series onto one shared timeline — the bridge from
raw vendor files (
io.CsvBarLoader) to the index-aligned input the
PortfolioBacktester requires.Settlement (Herstatt) risk: the exposure created when you pay away one
currency before receiving the other leg.
One settlement instruction pair: we pay one leg and receive the other.
Sharpe ratio significance tests (Bailey & López de Prado):
Probabilistic Sharpe Ratio — the probability the true Sharpe
exceeds a benchmark, adjusting for track length and non-normal
returns (skew, kurtosis).
Deflated Sharpe Ratio — PSR against the Sharpe you'd expect
from the best of N random trials: the multiple-testing haircut
for a strategy picked from a parameter grid.
The three classic short-rate models, each answering "what is a
zero-coupon bond worth if the short rate follows this SDE?"
Order side.
Trading signal emitted by a strategy for a single bar.
The unified streaming signal engine: one multi-symbol, hot-lane component
that turns raw top-of-book quotes and trade prints into the five signal
families a trading decision reads — for equities and FX alike (prices are
doubles; equity integer ticks are exact in a double, FX rates feed in
directly):
Imbalance — order-flow imbalance (Cont-Kukanov-Stoikov,
time-decayed), inside queue imbalance and signed trade-flow
imbalance, via a per-symbol
FlowSignals;
Fair value — the size-weighted microprice
(FairValueEngine.microprice);
Volatility: a streaming EWMA realized-variance rate over
irregular tick arrivals.Half-lives (all in nanos) for the decayed estimators, plus the
composite weights.
Signal evaluation: the metrics that decide whether a factor is worth
building a portfolio from, computed before any backtest so weak signals
die cheaply.
Mean forward return per score quantile:
meanReturns()[0] is the
lowest-scored names' average forward return, the last entry the
highest-scored.The evaluation scorecard;
SignalEvaluator.Report.format() renders it.Analytics over Monte Carlo terminal portfolio values: probabilities,
VaR/CVaR, confidence intervals and scenario extremes.
Inventory-skewed two-way pricing — the central risk book's quoting
face.
A shaded two-way price.
One child slice of an execution schedule.
Smart Order Router: splits a marketable order across venues to minimize
the all-in (fee-adjusted) execution price, respecting each venue's
displayed/estimated size.
One child order of the routing plan.
Smart-order-routed execution over a synthetic fragmented market.
One venue's fee, liquidity share and lit or dark status.
Normal density, distribution and quantile, log-gamma, the regularized
incomplete beta function and the Student-t distribution function.
Two-legged spread execution with legging-risk control — pairs trades,
cash-vs-futures basis, stub-vs-hedge: the trade is the spread, and
the risk is the moment you own one leg without the other.
This interval's child quantities, per leg.
Short-term spread prediction.
Surface SVI (Gatheral and Jacquier 2014, "Arbitrage-free SVI volatility
surfaces", Quantitative Finance 14(1), definition 4.1):
Descriptive statistics on primitive arrays, with every convention named.
Professional Stock Screener: applies technical and fundamental filters to a
universe, optionally ranks matches, and exports results to CSV.
One screening candidate: symbol, price history, and fundamentals.
Builds a strategy instance from one parameter combination.
Incremental O(1)-per-tick indicators for live/HFT strategies: update state
with each new value instead of recomputing arrays.
Exponential moving average seeded with the SMA of the first
period values.MACD line, signal and histogram, matching the batch seeding exactly.
Wilder RSI; NaN until
period price changes have been observed.Simple moving average over a fixed window; NaN until the window fills.
Cumulative volume-weighted average price.
Stress testing and scenario analysis — the risk numbers VaR cannot
give you, because VaR is calibrated to the recent past and a stress
test is not.
The reverse-stress answer: the most-probable shock vector and its distance.
Structured notes — the retail shelf, priced by
decomposition into the vanilla pieces this library already prices.
Svensson (Nelson-Siegel-Svensson) yield-curve fit —
NelsonSiegel
with a second curvature hump, the form most central banks actually
publish (the ECB's daily curve is exactly this):Fitted parameters plus the fit's root-mean-square error.
One expiry of the raw SVI parametrisation (Gatheral 2004, "A parsimonious
arbitrage-free implied volatility parameterization", Global Derivatives;
Gatheral and Jacquier 2014, "Arbitrage-free SVI volatility surfaces",
Quantitative Finance 14(1), equation 3.1):
A surface of raw SVI slices (
SviSlice), one per pillar expiry,
interpolated linearly in total variance at fixed log-moneyness
k = ln(K/F(t)).FX forward (swap-points) curve: the market's quoted forward points per
tenor, turned into outright forwards for any settlement date.
Accumulates tenor/points quotes, then freezes them into a curve.
Direct-versus-synthetic cross execution arithmetic: an FX cross (EURJPY)
can be dealt directly or replicated through its liquid legs (buy EURUSD,
buy USDJPY), and the cheaper route changes with every quote — direct
cross books are thin outside London hours while the USD legs stay tight.
Empirical value-at-risk and expected shortfall of a loss sample, with one
tail definition shared by every class in the library that reports them.
VaR and ES of one sample, both in loss units.
Technical screening filters evaluated on the most recent bar.
A term-rate floating leg (IBOR-style, or a term SOFR leg): each coupon is
the index rate fixed
fixingLagDays business days before the
accrual start, plus a spread, paid with the leg's payment lag.Price-banded tick sizes — the MiFID II / ESMA RTS 11 regime where the
minimum price increment depends on the instrument's price (and liquidity
band), rather than being one flat number.
Accumulates (floor price, tick) bands; floors may arrive in any order.
An implied volatility surface expressed as total implied variance
w(T, k) = σ_BS(T, K)²·T against log-moneyness k = ln(K/F(T)), on a market
with flat continuously compounded rate
r and carry (dividend or
foreign) yield q, so F(T) = S·e^{(r−q)T}.One-touch and no-touch options (pay-at-expiry) under continuously
monitored geometric Brownian motion — with the barrier-hitting
probability itself exposed, since desks quote one-touches as
(roughly) discounted hit probabilities.
A completed round-trip trade.
Trade-level analytics — the numbers a discretionary reviewer asks for
that a Sharpe ratio hides.
Trade-level statistics.
Trade aggressor classification (Lee-Ready, 1991): the missing glue for
feeds that print trades without saying who initiated.
A pluggable per-trade cost model — the one definition of "what a trade
costs" shared by the backtest engines, so an execution-aware number and a
survivorship-aware number can come out of the same run:
TradeCostModel.flat(double) — a fixed all-in bps (the classic commission
assumption, and the exact equivalent of the legacy
commissionRate configs);
TradeCostModel.institutional(double, double, double, int): commission + half-spread + slippage +
square-root market impact, with per-symbol ADV/vol estimated from
the trailing bars via MarketImpactModel.estimate(BarSeries, int, int).A bar-driven trading strategy.
Transaction Cost Analysis: benchmarks matched trades against the arrival
mid, the interval market VWAP, and the prevailing mid at each fill
(effective spread).
Triangular arbitrage checks over three related FX pairs, using dealable
bid/ask quotes (not mids), so a positive result is executable edge before
fees.
Turnover-penalised, constrained mean-variance optimiser solved by ADMM.
Optimiser settings.
TWAP (time-weighted average price) schedule design: splits a parent order
into evenly spaced child slices, optionally with randomized sizes to reduce
schedule predictability (anti-gaming).
UCB1 multi-armed bandit: principled selection among venues, LPs or
algo variants when the scorecards are still thin.
Defensive-copy helpers for immutable result types.
A fixed-for-floating swap built from two convention-driven legs: the
replacement for the single-curve, annual,
tau = 1 methods of the
SwapPricer (removed in 4.0).Vanna-volga pricing: the FX desk's standard smile-consistent adjustment
built from exactly three market pillars (in practice the 25Δ put, ATM and
25Δ call that
fx.FxVolSurface solves from broker RR/BF quotes).Vanna-volga adjusted one-touch (pays at expiry), the FX market
convention for smile-consistent touch prices (Wystup 2006, FX Options
and Structured Products, section 1.5 on vanna-volga pricing;
Bossens, Rayée, Skantzos and Deelstra 2010, "Vanna-volga methods applied
to FX derivatives", IJTAF 13(8)).
VaR model validation: do the exceptions (losses beyond VaR) occur at the
promised rate, and independently?
Result of the Basel traffic-light test.
Backtesting zones of the Basel internal models approach (MAR32.8).
Portfolio Value-at-Risk, all four classic flavors over one input
shape: factor exposures (currency P&L per unit factor return — a
delta vector) against a factor covariance matrix or a factor-return
history.
Revalues the book under one scenario's factor moves.
VaR and ES from Gaussian Monte Carlo factor scenarios.
The Lo-MacKinlay variance ratio test — the question that comes before
every strategy choice: is this series trending, mean-reverting, or a
random walk?
Variance ratio and its z statistic.
Variance swap analytics: the cleanest pure-volatility trade there is.
Venue benchmarking from execution outcomes: fill rate, latency-to-fill,
effective spread paid, and post-trade markout (adverse selection) per
venue, ranked by execution quality.
One routing outcome.
A venue's dealable top of book for routing.
Streaming per-venue execution quality — the equities counterpart of
fx.LpScorecard: displayed prices tell you where a venue claims
you'll trade; the scorecard tells you what actually happens when you send
there.Intraday volatility seasonality — the third leg of the seasonality trio
beside
VolumeCurve and SpreadForecaster: volatility is
U-shaped through an equity day (wild open, quiet lunch, busy close) and
session-humped through an FX day (London open, NY overlap), so "is the
market volatile right now?"Systematic vs idiosyncratic volatility — the decomposition behind
"how much of this stock's risk is the market, and how much is the
company?"
Systematic and idiosyncratic split of an asset's variance.
Machine Learning Risk Forecasting: predicts forward realized volatility from
a return series using gradient-boosted trees over engineered features
(multi-horizon realized vol, momentum, and shock magnitude), and maps the
forecast to a 0-100 risk score.
Out-of-sample comparison: RMSE (per-period vol units) of the model and
of the two baselines over the same forecast dates.
A VIX-style market volatility index — the "fear gauge": the market's
own 30-day volatility expectation, read model-free out of an option
chain.
Implied volatility surface built from (expiry, strike, vol) pillar quotes —
or directly from market option prices via implied-vol inversion.
Total variance falls between two expiries at this log-moneyness.
Dynamic intraday volume prediction — the model that makes a VWAP schedule
live instead of historical.
VPIN (Volume-synchronized Probability of INformed trading; Easley,
López de Prado & O'Hara): the flow-toxicity gauge a market maker
watches to decide when quoting is no longer a business.
VWAP schedule design: allocates child slices proportionally to an expected
intraday volume profile (e.g. from
com.quantfinlib.ml.IntradayLiquidityForecaster), so participation
tracks the market's own volume curve.Walk-forward analysis.
Whalley-Wilmott optimal hedge bands — the answer to the question
every band hedger otherwise guesses: how wide should the no-trade
band around delta be?
The rebalancing decision: trade (to the nearest edge) or hold.
A byte stream that breaks its wire protocol's framing: a FIX BodyLength
that is missing or not a number, an SBE header with an unknown schema or
template.
Benchmark-fixing execution schedule, WMR-style: orders benchmarked to a
fixing (the WM/Refinitiv 4pm London fix and its cousins) are executed by
spreading the parent evenly across the fixing's calculation window, so
realized cost tracks the benchmark rather than betting against it — the
window is 5 minutes for major pairs, and the benchmark is computed from
observations inside it, so TWAP-in-window is the neutral replication.
Zero-coupon yield curve.