NexusTrade guide

Build and backtest an algorithmic long strangle

A momentum trigger buys an OTM call and put. Both premiums are at risk if the subsequent move is too small.

As of 2026-10-10

Follow the example

Choose a step to follow the example. Opening a request lets you review it; it does not submit a job or change your account.

Read the signal and every leg: authored process map
Authored task map. It describes what to inspect; it is not an account screenshot or a measured result.
Step 1 of 3

Read the signal and every leg

Inspect the exact entry, position guard, strike selector, DTE range, leg ratio, allocation and exits below. A spread name alone does not define a strategy.

Entry
Saved candidate: RSI(SPY,14,Day) > 60 AND zero matching option positions
Position sizing
Saved candidate: One strategy unit; leg ratios apply. Buying power, collateral and liquidity can restrict orders.
Signal exit
Saved candidate: RSI(SPY,14,Day) <= 50; close whole matching spread at 14 or fewer DTE
Starting capital
Saved candidate: $10000.00
What you should see

A complete opening and closing contract, with an explicit underlying and matching-position scope.

Long strangle: completed 2024 backtest12.99K9.35K2024-01-022024-12-31
Long strangleFull-capital SPY buy and holdHistorical simulation
This exact saved candidate completed its fixed 2024 Day simulation on 2026-10-10. Starting capital was $10000.00. The request enabled detailed events and cash dividends. The curve below contains all 519 exported history points. The SPY comparison invests the full starting balance, reinvests dividends and applies no strategy commission. This strategy requests one spread unit with its declared fees. Use the cash, position value and collateral history to explore how each deploys capital.
Step 2 of 3

Completed historical backtest

This exact saved candidate completed its fixed 2024 Day simulation on 2026-10-10. Starting capital was $10000.00. The request enabled detailed events and cash dividends. The curve below contains all 519 exported history points. The SPY comparison invests the full starting balance, reinvests dividends and applies no strategy commission. This strategy requests one spread unit with its declared fees. Use the cash, position value and collateral history to explore how each deploys capital.

What you should see

The exact stored history shown here, with its source's period, comparisons and limits. Opening the walkthrough does not rerun it.

Preview the same rules in Aurora: authored process map
Authored task map. It describes what to inspect; it is not an account screenshot or a measured result.
Step 3 of 3

Preview the same rules in Aurora

Open the reviewed request, check its selectors and exits, and keep automated trading off. Review any test cost separately before submission.

What you should see

An inspectable draft of this example. Historical synthetic pricing is visible, not a promise of available live quotes or identical execution.

The algorithm and its purpose

A momentum trigger buys an OTM call and put. Both premiums are at risk if the subsequent move is too small.

The rules below trade SPY options. The completed 2024 backtest includes the portfolio curve, contract-resolution records and any recorded fills.

EntryRSI(SPY,14,Day) > 60 AND zero matching option positions
Position sizingOne strategy unit; leg ratios apply. Buying power, collateral and liquidity can restrict orders.
Signal exitRSI(SPY,14,Day) <= 50; close whole matching spread at 14 or fewer DTE
Starting capital$10000.00
Spread typestrangle
ExecutionMarket; $0.65 commission per option contract, default 0.5 half-spread fraction plus applicable liquidity impact.

Contract selectors and ratios

Strike distances are percentages of the underlying price, not fixed market strikes or delta targets. Positive distance means out of the money: a higher strike for calls and a lower strike for puts. Negative distance means in the money; zero targets at the money (ATM). Days to expiration (DTE) measures the time remaining until a contract expires. Nearest expiration must lie within each leg's DTE range. Inspect the resolved contracts rather than assuming the authored offsets produce exact strike widths.

All option legs use the same requested expiry window. Verify actual shared expiration and the resulting quantities in the contract-resolution and fill records.

1longcall5%130 to 45 DTE
2longput5%130 to 45 DTE

Create the exact inactive draft

Ask Aurora to build the rules above, review the preview, then save the draft while keeping automated trading off. A chat draft is inspected in Portfolio > Drafts or Aurora; the native Strategies editor belongs to a paper or live portfolio.

In an inactive native portfolio, use Open Options Position, choose the matching structure preset and verify each leg above. Under Allocation, set Type Contracts and Amount 1. Add the entry conditions, including zero matching option positions. Add both Close Options Position rules separately, matching SPY and the spread type with close scope spread and quantity all. A preset adds contract legs; it does not supply the complete entry or exit algorithm.

Create, test and iterate in Aurora

Start this worked example in the NexusTrade app. Review the filled-in request, open it in Aurora, then send it when ready. Continue in the same conversation through these steps.

  1. Create the exact strategy

    Ask: "Review Long strangle. Entry: RSI(SPY,14,Day) > 60 AND zero matching option positions. Exit: RSI(SPY,14,Day) <= 50; close whole matching spread at 14 or fewer DTE. Show the resolved rules and selectors before saving." The request includes this example's complete draft.

  2. Run the 2024 development comparison

    Ask: "Backtest the saved rules from January 1 through December 31, 2024, daily, starting with $10,000. Keep the displayed fees and capture detailed events." Compare the completed curve with SPY buy and hold.

  3. Explain what happened

    Ask: "Explain one entry signal and its Filled orders using the recorded indicator values, comparisons, allocation, prices, quantity and fees. Then follow the largest drawdown through trades, cash and holdings."

  4. Create one variant, then test unseen dates

    Ask: "Change only the timed close trigger from 14 DTE to 10 DTE. Show the rule diff and compare both candidates on the 2024 development period with every other setting fixed." After choosing, freeze the rules and select another test period you have not inspected. The displayed 2024 results already make 2024 a viewed development period. Keep any later revisions in a new research cycle.

Create and backtest with Python

Python SDK 1.42.0. Save the runner below as run_long_strangle.py.

Install and download

Shell
python3 -m pip install nexustrade==1.42.0
export NEXUSTRADE_API_KEY="YOUR_API_KEY"
curl --fail --output long_strangle.py https://nexustrade.io/seo/strategy-examples/long-strangle.py

Create, test and inspect

Python
from long_strangle import create_long_strangle, backtest_long_strangle

book = create_long_strangle()
completed = backtest_long_strangle()
print(completed["result"])

Run

Shell
python3 run_long_strangle.py

Python strategy and backtest functions

View complete Python SDK functions

The backtest function submits the 2024 test with SPY as its benchmark, records events and waits for the result. Use a new request key when changing rules, dates or fees.

Python
import nexustrade as nt


def create_long_strangle():
    asset = nt.stock_asset("SPY")
    return nt.portfolio(
        "Public SEO example - Long strangle",
        [
            nt.strategy(
                "Open Long strangle",
                ((nt.RSI(asset, 14, "Day") > nt.Value(60)) & (nt.OptionPositionCount("SPY", "call", "long", "strangle") == nt.Value(0))),
                nt.open_option(
                    builder=nt.options_builder(
                        legs=[
                            nt.leg(
                                option_type="call",
                                direction="long",
                                min_days_to_expiration=30,
                                max_days_to_expiration=45,
                                preference="nearest",
                                distance=5,
                                ratio=1
                            ),
                            nt.leg(
                                option_type="put",
                                direction="long",
                                min_days_to_expiration=30,
                                max_days_to_expiration=45,
                                preference="nearest",
                                distance=5,
                                ratio=1
                            )
                        ],
                        underlying_symbol="SPY",
                        spread_type="strangle"
                    ),
                    allocation={'type': 'contracts', 'amount': 1}
                )
            ),
            nt.strategy(
                "Close when signal invalidates",
                (nt.RSI(asset, 14, "Day") <= nt.Value(50)),
                nt.close_option(
                    underlyings=['SPY'],
                    spread_type="strangle",
                    close_scope="spread",
                    quantity={'type': 'all'}
                )
            ),
            nt.strategy(
                "Close at 14 DTE",
                (nt.Value(1) > nt.Value(0)),
                nt.close_option(
                    underlyings=['SPY'],
                    spread_type="strangle",
                    close_scope="spread",
                    quantity={'type': 'all'},
                    triggers=[nt.dte_trigger(max_dte=14)]
                )
            ),
        ],
        initial_value=10000,
        supports_fractional_shares=False,
        alerts_enabled=False,
        dividend_policy='cash',
    )


def backtest_long_strangle(client=None):
    client = client or nt.NexusTradeClient.from_environment()
    operation = client.create_backtest(
        nt.backtest(
            create_long_strangle(),
            start_date="2024-01-01", end_date="2024-12-31",
            interval="Day", baseline_symbol="SPY",
            initial_value=10000, generate_events=True,
            dividend_policy="cash",
            fee_config={"Stock": {"type": "percent", "amount": 0.1},
                        "Cryptocurrency": {"type": "percent", "amount": 0.7},
                        "Option": {"type": "dollars", "amount": 0.65}},
        ),
        idempotency_key="explore-long-strangle-2024-spy-v1",
    )
    return client.wait_for_backtest(operation["id"])


# Build locally: book = create_long_strangle()
# Run and inspect: completed = backtest_long_strangle(); print(completed["result"])

Create and backtest with TypeScript

TypeScript SDK 1.42.0. Save the runner below as run-long-strangle.ts.

Install and download

Shell
npm install nexustrade@1.42.0
npm install --save-dev tsx
export NEXUSTRADE_API_KEY="YOUR_API_KEY"
curl --fail --output long-strangle.ts https://nexustrade.io/seo/strategy-examples/long-strangle.ts

Create, test and inspect

TypeScript
import { createLongStrangle, backtestLongStrangle } from "./long-strangle";

async function main() {
  const book = createLongStrangle();
  const completed = await backtestLongStrangle();
  console.log(completed.result);
}

main().catch((error: unknown) => {
  console.error(error);
  process.exitCode = 1;
});

Run

Shell
npx tsx run-long-strangle.ts

TypeScript strategy and backtest functions

View complete TypeScript SDK functions

The same rules, dates and fees are used in both SDKs. The backtest function keeps its request key across retries.

TypeScript
import * as nt from "nexustrade";

export function createLongStrangle() {
  const asset = nt.stockAsset("SPY");
  return nt.portfolio(
    "Public SEO example - Long strangle",
    [
      nt.strategy(
          "Open Long strangle",
          nt.and(
              nt.gt(nt.RSI(asset, 14, "Day"), nt.Value(60)),
              nt.eq(nt.OptionPositionCount("SPY", "call", "long", "strangle"), nt.Value(0))
          ),
          nt.openOption({ builder: nt.optionsBuilder({ legs: [nt.leg({ optionType: "call", direction: "long", minDaysToExpiration: 30, maxDaysToExpiration: 45, preference: "nearest", distance: 5, ratio: 1 }), nt.leg({ optionType: "put", direction: "long", minDaysToExpiration: 30, maxDaysToExpiration: 45, preference: "nearest", distance: 5, ratio: 1 })], underlyingSymbol: "SPY", spreadType: "strangle" }), allocation: {"type": "contracts", "amount": 1} })
      ),
      nt.strategy(
          "Close when signal invalidates",
          nt.lte(nt.RSI(asset, 14, "Day"), nt.Value(50)),
          nt.closeOption({ underlyings: ["SPY"], spreadType: "strangle", closeScope: "spread", quantity: {"type": "all"} })
      ),
      nt.strategy(
          "Close at 14 DTE",
          nt.gt(nt.Value(1), nt.Value(0)),
          nt.closeOption({ underlyings: ["SPY"], spreadType: "strangle", closeScope: "spread", quantity: {"type": "all"}, triggers: [nt.dteTrigger({ maxDte: 14 })] })
      ),
    ],
    { initialValue: 10000, supportsFractionalShares: false, alertsEnabled: false, dividendPolicy: "cash" }
  );
}

export async function backtestLongStrangle(client = new nt.NexusTradeClient()) {
  const operation = await client.createBacktest(
    nt.backtest(createLongStrangle(), {
      startDate: "2024-01-01", endDate: "2024-12-31",
      interval: "Day", baselineSymbol: "SPY",
      initialValue: 10000, generateEvents: true,
      dividendPolicy: "cash",
      feeConfig: {
        Stock: { type: "percent", amount: 0.1 },
        Cryptocurrency: { type: "percent", amount: 0.7 },
        Option: { type: "dollars", amount: 0.65 },
      },
    }),
    { idempotencyKey: "explore-long-strangle-2024-spy-v1" }
  );
  if (typeof operation.id !== "string") throw new Error("Missing backtest ID");
  return client.waitForBacktest(operation.id);
}

// Build locally: const book = createLongStrangle();
// Run and inspect: const completed = await backtestLongStrangle(); console.log(completed.result);

Completed historical backtest

This exact saved candidate completed its fixed 2024 Day simulation on 2026-10-10. Starting capital was $10000.00. The request enabled detailed events and cash dividends. The curve below contains all 519 exported history points.

The SPY comparison invests the full starting balance, reinvests dividends and applies no strategy commission. This strategy requests one spread unit with its declared fees. Use the cash, position value and collateral history to explore how each deploys capital.

StatusCOMPLETE
Requested period2024-01-01 through 2024-12-31
Starting capital$10000.00
Modeled return-5.98%
Reported maximum drawdown7.49%
Full-capital SPY comparator return25.30%
Recorded commissions$65.00
Engine closed-trade count50
Peak reserved collateral$6396.00
Median reserved collateral while holding positions$2485.00
Pricing contract version8
Observed / synthetic half-spread calls131 / 102
Unknown-timing quote accesses6957
Missing-current-quote checks0
Rejected fill groups / marks0 / 0
Stale basket / single-option marks1 / 0
Long strangle: completed 2024 backtest12.99K9.35K2024-01-022024-12-31
Long strangleFull-capital SPY buy and holdHistorical simulation

Inspect a captured opening and close

These Filled orders show one captured position from the run. Its recorded opening and closing cash flows sum to $31.92 after commissions. Inspect every leg and ratio; the engine's closed-trade count can count option legs rather than whole spread round trips.

Follow this position's Filled events by contract, side and time. Compare opening and closing premiums, quantities and commissions to understand its P&L. This example comes from the captured excerpt of the most recent 50 Filled orders.

2024-12-24 18:00:00SPY250124P00571000Buy to open1$1.7067$0.65
2024-12-24 18:00:00SPY250124C00630000Buy to open1$0.3357$0.65
2024-12-27 21:00:00SPY250124P00571000Sell to close1$2.2654$0.65
2024-12-27 21:00:00SPY250124C00630000Sell to close1$0.1223$0.65

Inspect a contract-resolution audit

This is the latest retained resolution attempt, which can belong to a different position than the matched trade above. Its outcome, capital and risk codes explain what the resolver accepted or rejected at that decision. Follow the resulting Order events to see its fill status.

JSON
{
  "time": "2024-12-24T18:00:00.000Z",
  "status": "success",
  "reason": null,
  "riskAudit": {
    "rulesetVersion": 1,
    "outcome": "allowed",
    "longSharesAvailable": 0,
    "unhedgedShortCallContractsPerSpread": 0,
    "buyingPowerEffective": 3189.671766492289,
    "allocationRequested": 1,
    "allocation": {
      "type": "contracts",
      "amount": 1
    },
    "portfolioValue": 9369.671766492289,
    "underlyingPrice": 601.2999877929688,
    "maxLossPerUnit": 216,
    "finalContractQuantity": 1,
    "collateralReserved": 216,
    "committedCostBefore": 0
  }
}

Inspect the largest decline in the exported history

The exported grid's largest peak-to-trough decline was 7.49%, from $10101.42 at 2024-01-29T21:00:00.000Z to $9345.13 at 2024-12-24T18:00:00.000Z. The engine reported maximum drawdown of 7.49%. Compare the history snapshots with the reported statistic and inspect the events around this period.

2024-01-29T21:00:00.000Z$9772.42$329.00$355.00
2024-12-24T18:00:00.000Z$9164.13$181.00$6396.00

Explain this options decision with Aurora

Ask Aurora to connect the recorded signal, contract choice, allocation and fills. It receives this page's captured decision and order fields, so you can follow its explanation back to each value.

Download the result and explore the events

Download the exact strategy inputs, completed result, full history, pricing counters and captured events. You can use these records to follow the strategy from its signal to its closing fill. Detailed events remain available in the product for 3 days; this saved example stays readable.

Explore this strategy further

Inspect matched quantities, actual strike widths, expirations and all close orders. For sold options, review collateral and exercise or assignment exposure separately from premium income. A condition firing can emit zero close orders; look at its evaluation and the Filled-order records.

Try another date range or change one rule, then compare the new backtest with this saved 2024 result. Inspect which trades and periods explain the difference.

Continue exploring

Aurora · AI research assistant

Try this in Aurora

Edit the request, then open it in Aurora. You choose when to send it.