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SkillsMP has collected 99 skills from QuantConnect/Documentation. Open a skill to review its source and details.
QuantConnect/DocumentationShowing 40 of 99 collected skills.
Use whenever a signal needs a technical indicator or rolling statistic (moving average, momentum/rate-of-change, RSI, ATR, rolling volatility, etc.) — OR any custom per-symbol statistic computed from a trailing window of prices/returns (weighted sums of past…
Use for any cross-sectional strategy that ranks a large universe and trades only a subset (e.g. long-short deciles/quintiles). The principle — narrow to a bounded set as early as you can, store the target weights, and subscribe to only that bounded set (never…
Use when selecting a QuantConnect/LEAN universe based on per-symbol indicators. Triggers — code uses `add_universe(...)` with a selection callback that builds per-symbol `SimpleMovingAverage`/`ExponentialMovingAverage`/`BollingerBands`/`RSI`/`ATR` etc., often…
Use whenever a signal needs a technical indicator or rolling statistic (moving average, momentum/rate-of-change, RSI, ATR, rolling volatility, etc.) — OR any custom per-symbol statistic computed from a trailing window of prices/returns (weighted sums of past…
Use for any cross-sectional strategy that ranks a large universe and trades only a subset (e.g. long-short deciles/quintiles). The principle — narrow to a bounded set as early as you can, store the target weights, and subscribe to only that bounded set (never…
Use when an algorithm trades options on a SINGLE named underlying Equity — subscribing (py`add_option`cs`AddOption` vs py`add_option_contract`cs`AddOptionContract`), reading the chain (the slice's py`option_chains`cs`OptionChains` vs the…
Use when an algorithm trades options on a SINGLE named underlying Equity — subscribing (`AddOption` vs `AddOptionContract`), reading the chain (the slice's `OptionChains` vs the `OptionChain()` method), greeks/IV data freshness, strike/expiry filters, price…
Use when an algorithm trades options on a SINGLE named underlying Equity — subscribing (`add_option` vs `add_option_contract`), reading the chain (the slice's `option_chains` vs the `option_chain()` method), greeks/IV data freshness, strike/expiry filters,…
Use when placing or managing MULTI-LEG option positions and the option lifecycle in QuantConnect/LEAN — the `OptionStrategies` factory + py`buy/sell`cs`Buy/Sell` route, combo orders (py`combo_market_order`cs`ComboMarketOrder`,…
Use when placing or managing MULTI-LEG option positions and the option lifecycle in QuantConnect/LEAN — the `OptionStrategies` factory + `Buy/Sell` route, combo orders (`ComboMarketOrder`, `ComboLimitOrder`, `ComboLegLimitOrder`), position-group margin, early…
Use when placing or managing MULTI-LEG option positions and the option lifecycle in QuantConnect/LEAN — the `OptionStrategies` factory + `buy/sell` route, combo orders (`combo_market_order`, `combo_limit_order`, `combo_leg_limit_order`), position-group…
Creates a custom indicator class in QuantConnect/LEAN. Invoke for "create a custom indicator", "implement [name] indicator", "I need an indicator LEAN doesn't have", py`PythonIndicator`cs`ComputeNextValue`, "custom indicator class". Skip for LEAN built-ins…
Creates a custom indicator class in QuantConnect/LEAN. Invoke for "create a custom indicator", "implement [name] indicator", "I need an indicator LEAN doesn't have", `ComputeNextValue`, "custom indicator class". Skip for LEAN built-ins (SMA, EMA, RSI).
Creates a custom indicator class in QuantConnect/LEAN. Invoke for "create a custom indicator", "implement [name] indicator", "I need an indicator LEAN doesn't have", `PythonIndicator`, "custom indicator class". Skip for LEAN built-ins (SMA, EMA, RSI).
Use whenever a strategy depends on the market calendar — market closures/holidays, trading-day counting, the Nth trading day before/after a date, or whether a date is a trading day. Use QuantConnect's built-in calendar; do not hand-roll a holiday calendar or…
Use whenever building a CRYPTO universe (a dynamic set of coins on an exchange), ranking coins by dollar volume, or trading crypto long/short — including short-selling crypto and which venues support margin.
Use when a backtest blows up or an asset shows obviously corrupted data (a price spiking orders of magnitude and snapping back within a few bars, or a long flat-line / missing-price stretch). Applies to ANY asset class (equities, futures, crypto). Covers…
Use whenever a strategy needs US macroeconomic survey data — CPI/inflation, nonfarm payrolls and earnings (CES), producer prices (PPI), or job openings (JOLTS). Covers the point-in-time BLS Economic Surveys datasets, their release-date semantics, the field…
Use whenever a strategy trades futures — position sizing (notional/contracts), continuous-contract history and its py`MultiIndex DataFrame`cs`IEnumerable<TradeBar>`, and warm-up. Load it for any futures sizing, history, or warm-up step.
Use when an equity-options strategy needs HISTORICAL option data — implied volatility, greeks, prices, open interest — for PAST dates. E.g. a historical implied-volatility series, or backfilling option IV/greeks over a period for a signal or model. Triggers —…
Use whenever you reach for a py`history()`cs`History()` request — a startup seed, a one-off lookback, or a recent past value like the previous daily close. For a rolling statistic recomputed every bar, prefer a streaming indicator (see indicators).
Use whenever a strategy depends on the market calendar — market closures/holidays, trading-day counting, the Nth trading day before/after a date, or whether a date is a trading day. Use QuantConnect's built-in calendar; do not hand-roll a holiday calendar or…
Use whenever building a CRYPTO universe (a dynamic set of coins on an exchange), ranking coins by dollar volume, or trading crypto long/short — including short-selling crypto and which venues support margin.
Use when a backtest blows up or an asset shows obviously corrupted data (a price spiking orders of magnitude and snapping back within a few bars, or a long flat-line / missing-price stretch). Applies to ANY asset class (equities, futures, crypto). Covers…
Use whenever a strategy needs US macroeconomic survey data — CPI/inflation, nonfarm payrolls and earnings (CES), producer prices (PPI), or job openings (JOLTS). Covers the point-in-time BLS Economic Surveys datasets, their release-date semantics, the field…
Use whenever a strategy trades futures — position sizing (notional/contracts), continuous-contract history and its `IEnumerable<TradeBar>`, and warm-up. Load it for any futures sizing, history, or warm-up step.
Use when an equity-options strategy needs HISTORICAL option data — implied volatility, greeks, prices, open interest — for PAST dates. E.g. a historical implied-volatility series, or backfilling option IV/greeks over a period for a signal or model. Triggers —…
Use whenever you reach for a `History()` request — a startup seed, a one-off lookback, or a recent past value like the previous daily close. For a rolling statistic recomputed every bar, prefer a streaming indicator (see indicators).
Use whenever a strategy depends on the market calendar — market closures/holidays, trading-day counting, the Nth trading day before/after a date, or whether a date is a trading day. Use QuantConnect's built-in calendar; do not hand-roll a holiday calendar or…
Use whenever building a CRYPTO universe (a dynamic set of coins on an exchange), ranking coins by dollar volume, or trading crypto long/short — including short-selling crypto and which venues support margin.
Use when a backtest blows up or an asset shows obviously corrupted data (a price spiking orders of magnitude and snapping back within a few bars, or a long flat-line / missing-price stretch). Applies to ANY asset class (equities, futures, crypto). Covers…
Use whenever a strategy needs US macroeconomic survey data — CPI/inflation, nonfarm payrolls and earnings (CES), producer prices (PPI), or job openings (JOLTS). Covers the point-in-time BLS Economic Surveys datasets, their release-date semantics, the field…
Use whenever a strategy trades futures — position sizing (notional/contracts), continuous-contract history and its `MultiIndex DataFrame`, and warm-up. Load it for any futures sizing, history, or warm-up step.
Use when an equity-options strategy needs HISTORICAL option data — implied volatility, greeks, prices, open interest — for PAST dates. E.g. a historical implied-volatility series, or backfilling option IV/greeks over a period for a signal or model. Triggers —…
Use whenever you reach for a `history()` request — a startup seed, a one-off lookback, or a recent past value like the previous daily close. For a rolling statistic recomputed every bar, prefer a streaming indicator (see indicators).
Use when adding a custom or external data source to a QuantConnect/LEAN algorithm. Triggers: custom data reader, external dataset, `BaseData`, CSV, JSON, XML, ZIP, REST endpoint, Object Store, linked data, unlinked signals, custom universes, or local files…
Use when adding a custom or external data source to a QuantConnect/LEAN algorithm. Triggers: custom data reader, external dataset, `PythonData`, CSV, JSON, XML, ZIP, REST endpoint, Object Store, linked data, unlinked signals, custom universes, or local files…
Use when writing, reviewing, or refactoring QuantConnect/LEAN algorithm code for style correctness. Triggers: new algorithm code, code review, cleanup, "fix code style", "review code quality", "clean up the algorithm", redundant imports, subscription variable…
Use when writing, reviewing, or refactoring QuantConnect/LEAN algorithm code for style correctness. Triggers: new algorithm code, code review, cleanup, "fix code style", "review code quality", "clean up the algorithm", redundant imports, subscription variable…
Use when adding a custom or external data source to a QuantConnect/LEAN algorithm. Triggers: custom data reader, external dataset, py`PythonData`cs`BaseData`, CSV, JSON, XML, ZIP, REST endpoint, Object Store, linked data, unlinked signals, custom universes,…