Build and backtest an algorithmic bear put spread

TL;DR

Build a bear put spread in four steps: describe it to Aurora, check the saved rules, backtest it, follow a trade. Start from the worked example below: copy its rules, then change the ticker, dates or exits and test your version. On SPY in 2024 it returned -13.34% against 25.30% for SPY, and its maximum drawdown was 23.74%.

How to build a bear put spread

Animation: the bear put spread strategy as built in the AI chat (Price(SPY) < SMA(SPY,50,Day); Price(SPY) >= SMA(SPY,50,Day); 14 DTE) is saved as 3 rules. Its legs (sell 1 put at -5% resolving to $557, buy 1 put at ATM resolving to $586; nearest expiry 30 to 45 days out, Jan 17, 2025) appear on a strike line. Then the expiration payoff of the recorded bear put spread (Sell the SPY $557 put, buy the $586 put; both expire Jan 17, 2025) draws as the SPY price sweeps from $537 to $606: max profit $2,235.79; max loss $664.21; breakeven $579.36; per contract before commissions. Then the same position's profit or loss is drawn at each session close from Dec 18, 2024 to Dec 24, 2024, ending at -$487.82 after commissions. — The algorithmic strategy held this position from Dec 18 to Dec 24, 2024 in its backtest and lost $487.82 after commissions.

Step 1 of 4

1. Describe it to Aurora

Open the prepared request. Aurora receives the exact rules shown here and checks them without saving a portfolio. Review its preview before choosing whether to save or test your own version.

What you should see

A preview of the rules and their validation result. Any invalid inputs are identified before you decide what to save.

Step 2 of 4

2. Check the saved rules

Start with the actual rules used in this example. Days to expiration means the days remaining until the option expires. The complete editor inputs and SDK functions are available below.

Entry: Open when SPY’s price is below its 50-day simple moving average and no matching option position is open.
Position sizing: One strategy unit; leg ratios apply. Buying power, collateral and liquidity can restrict orders.
Signal exit: Close all matching option legs when SPY rises to its 50-day average or above, or when 14 or fewer days remain until expiration.
Starting capital: $10,000.00
Leg 1: Buy 1 put contract per unit, targeting a strike nearest SPY’s price. Choose the nearest available expiry 30 to 45 days away.
Leg 2: Sell 1 put contract per unit, targeting a strike 5% below SPY’s price. Choose the nearest available expiry 30 to 45 days away.

What you should see

The entry decides when to open. The leg selectors choose contracts. The allocation sets size, and the exit decides when to close. Keep these parts together in your draft.

Bear put spread 2024-12-31, 21:00:00 UTC: 8,665.52
Full-capital SPY buy and hold 2024-12-31, 21:00:00 UTC: 12,530.29

Bear put spreadFull-capital SPY buy and holdHistorical simulation

Completed 2024 historical simulation. The plotted observations and comparison series are preserved.

Step 3 of 4

3. Backtest it

Compare the two recorded curves and the result below. SPY invests the full starting balance; this options candidate uses its saved allocation. Their fees and invested capital differ.

Candidate vs full-capital SPY: -13.34% vs 25.30%

What you should see

The requested period was 2024-01-01 through 2024-12-31. The candidate’s largest reported decline was 23.74%, with $22.10 in recorded commissions. Quote coverage is not certified for strategy comparison; inspect the retained quote checks before comparing these strategies.

Step 4 of 4

4. Follow one trade

Buying to open purchases an option; selling to open writes it. Closing reverses that position. Multiply each premium below by 100 shares per contract and its quantity, then subtract the recorded fees to follow the cash flow.

Put · $586 strike: Dec 18, 2024 21:00 UTC: buy to open 1 at $11.0660 per share; $0.65 fee. Dec 24, 2024 18:00 UTC: sell to close 1 at $2.5195 per share; $0.65 fee.
Put · $557 strike: Dec 18, 2024 21:00 UTC: sell to open 1 at $4.4239 per share; $0.65 fee. Dec 24, 2024 18:00 UTC: buy to close 1 at $0.7297 per share; $0.65 fee.

What you should see

These Filled orders show one captured position from the run. Its recorded opening and closing cash flows sum to $-487.82 after commissions. Inspect every leg and ratio; the engine's closed-trade count can count option legs rather than whole spread round trips.

Four steps take a bear put spread from an idea to a tested strategy. Each step uses the SPY worked example.

The rules that define it

Entry
Price(SPY) < SMA(SPY,50,Day) AND zero matching option positions
Position sizing
One strategy unit; leg ratios apply. Buying power, collateral and liquidity can restrict orders.
Signal exit
Price(SPY) >= SMA(SPY,50,Day); close whole matching spread at 14 or fewer DTE
Starting capital
$10000.00
Spread type
vertical
Execution
Market; $0.65 commission per option contract, default 0.5 half-spread fraction plus applicable liquidity impact.

Show the table · 6 rows, 2 columns

Rule	Saved candidate
Entry	Price(SPY) < SMA(SPY,50,Day) AND zero matching option positions
Position sizing	One strategy unit; leg ratios apply. Buying power, collateral and liquidity can restrict orders.
Signal exit	Price(SPY) >= SMA(SPY,50,Day); close whole matching spread at 14 or fewer DTE
Starting capital	$10000.00
Spread type	vertical
Execution	Market; $0.65 commission per option contract, default 0.5 half-spread fraction plus applicable liquidity impact.

Contract selectors and ratios

Inspect 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.

Filter rows

Scroll sideways to compare all columns. Select a heading to sort.


1	long	put	0%	1	30 to 45 DTE
2	short	put	5%	1	30 to 45 DTE

Save it as a draft

Show how to save the 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 and backtest with Python

Use the Python SDK instead of Aurora

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

Install and download

Shell

python3 -m pip install nexustrade==1.42.0
export NEXUSTRADE_API_KEY="YOUR_API_KEY"
curl --fail --output bear_put_spread.py https://nexustrade.io/seo/strategy-examples/bear-put-spread.py

Create, test and inspect

Python

from bear_put_spread import create_bear_put_spread, backtest_bear_put_spread

book = create_bear_put_spread()
completed = backtest_bear_put_spread()
print(completed["result"])

Run

Shell

python3 run_bear_put_spread.py

Download Python example ↗Python SDK setup and backtesting ↗

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_bear_put_spread():
    asset = nt.stock_asset("SPY")
    return nt.portfolio(
        "Public SEO example - Bear put spread",
        [
            nt.strategy(
                "Open Bear put spread",
                ((nt.Price(asset) < nt.SMA(asset, 50, "Day")) & (nt.OptionPositionCount("SPY", "put", "long", "vertical") == nt.Value(0))),
                nt.open_option(
                    builder=nt.options_builder(
                        legs=[
                            nt.leg(
                                option_type="put",
                                direction="long",
                                min_days_to_expiration=30,
                                max_days_to_expiration=45,
                                preference="nearest",
                                distance=0,
                                ratio=1
                            ),
                            nt.leg(
                                option_type="put",
                                direction="short",
                                min_days_to_expiration=30,
                                max_days_to_expiration=45,
                                preference="nearest",
                                distance=5,
                                ratio=1
                            )
                        ],
                        underlying_symbol="SPY",
                        spread_type="vertical"
                    ),
                    allocation={'type': 'contracts', 'amount': 1}
                )
            ),
            nt.strategy(
                "Close when signal invalidates",
                (nt.Price(asset) >= nt.SMA(asset, 50, "Day")),
                nt.close_option(
                    underlyings=['SPY'],
                    spread_type="vertical",
                    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="vertical",
                    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_bear_put_spread(client=None):
    client = client or nt.NexusTradeClient.from_environment()
    operation = client.create_backtest(
        nt.backtest(
            create_bear_put_spread(),
            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-bear-put-spread-2024-spy-v1",
    )
    return client.wait_for_backtest(operation["id"])


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

Create and backtest with TypeScript

Use the TypeScript SDK instead of Aurora

TypeScript SDK 1.42.0. Save the runner below as run-bear-put-spread.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 bear-put-spread.ts https://nexustrade.io/seo/strategy-examples/bear-put-spread.ts

Create, test and inspect

TypeScript

import { createBearPutSpread, backtestBearPutSpread } from "./bear-put-spread";

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

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

Run

Shell

npx tsx run-bear-put-spread.ts

Download TypeScript example ↗TypeScript SDK setup and backtesting ↗

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

export async function backtestBearPutSpread(client = new nt.NexusTradeClient()) {
  const operation = await client.createBacktest(
    nt.backtest(createBearPutSpread(), {
      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-bear-put-spread-2024-spy-v1" }
  );
  if (typeof operation.id !== "string") throw new Error("Missing backtest ID");
  return client.waitForBacktest(operation.id);
}

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

Start from this example

The worked example below is a starting point for you to copy. Open its exact rules in Aurora, then change the ticker, dates, legs or exits and backtest your own version.

Worked example to copy: SPY, 2024

Bear put spread 2024-12-31, 21:00:00 UTC: 8,665.52
Full-capital SPY buy and hold 2024-12-31, 21:00:00 UTC: 12,530.29

Bear put spreadFull-capital SPY buy and holdHistorical simulation

Return: -13.34%
SPY buy and hold: 25.30%
Max drawdown: 23.74%
Closed option legs: 16
Commissions: $22.10

Show the table · 16 rows, 2 columns

Filter rows

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Status	COMPLETE
Requested period	2024-01-01 through 2024-12-31
Starting capital	$10000.00
Modeled return	-13.34%
Reported maximum drawdown	23.74%
Full-capital SPY comparator return	25.30%
Recorded commissions	$22.10
Engine closed-trade count	16
Peak reserved collateral	$892.00
Median reserved collateral while holding positions	$596.00
Pricing contract version	8
Observed / synthetic half-spread calls	42 / 26
Unknown-timing quote accesses	2505
Missing-current-quote checks	0
Rejected fill groups / marks	0 / 0
Stale basket / single-option marks	0 / 0

How the example did on SPY, 2024-01-01 to 2024-12-31, starting with $10,000.

One trade from the example

One position from the worked example, opened Dec 18, 2024 and closed Dec 24, 2024.

Long $586 put: −$854.65
Short $557 put: +$369.42
Commissions: −$2.60
Net: −$487.82

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.

Inspect the worked example's records

The example trade's fills

2024-12-18 21:00:00
Contract
SPY250117P00586000
Action
Buy to open
Contracts
1
Premium per share
$11.0660
Fee
$0.65
2024-12-18 21:00:00
Contract
SPY250117P00557000
Action
Sell to open
Contracts
1
Premium per share
$4.4239
Fee
$0.65
2024-12-24 18:00:00
Contract
SPY250117P00557000
Action
Buy to close
Contracts
1
Premium per share
$0.7297
Fee
$0.65
2024-12-24 18:00:00
Contract
SPY250117P00586000
Action
Sell to close
Contracts
1
Premium per share
$2.5195
Fee
$0.65

Recorded rows in source order; spacing does not represent elapsed time.

Show the table · 4 rows, 6 columns

Filter rows

Scroll sideways to compare all columns. Select a heading to sort.


2024-12-18 21:00:00	SPY250117P00586000	Buy to open	1	$11.0660	$0.65
2024-12-18 21:00:00	SPY250117P00557000	Sell to open	1	$4.4239	$0.65
2024-12-24 18:00:00	SPY250117P00557000	Buy to close	1	$0.7297	$0.65
2024-12-24 18:00:00	SPY250117P00586000	Sell to close	1	$2.5195	$0.65

Each premium is per share; one contract is 100 shares.

Inspect the candidate book

This is the indicative selected-candidate snapshot from the opening size decision. Compare the selected symbols and ratios with the actual Filled orders. Use the candidate bid, ask and mid to follow the sizing calculation, then compare the recorded execution premium.

Filter rows

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SPY250117P00586000	$586.00	2025-01-17	30	$11.02	$11.08	$11.05	1	949; sessionVolume
SPY250117P00557000	$557.00	2025-01-17	30	$4.40	$4.52	$4.46	1	98; sessionVolume

JSON

{
  "modelVersion": 2,
  "enforced": true,
  "chosenIndex": 0,
  "path": "targetKept",
  "reason": "target size limit 24 covers 1",
  "requestedQuantity": 1,
  "quantity": 1,
  "sizingChain": [
    {
      "kind": "allocationImplied",
      "bound": 1,
      "quantity": 1,
      "binding": true
    },
    {
      "kind": "buyingPowerCap",
      "bound": 13,
      "quantity": 1,
      "binding": false
    },
    {
      "kind": "volumeLimit",
      "bound": 24,
      "quantity": 1,
      "binding": false
    },
    {
      "kind": "finalPriceRecap",
      "bound": 1,
      "quantity": 1,
      "binding": false
    }
  ],
  "pricing": {
    "mid": 15.510000000000002,
    "halfSpread": 0.08999999999999986,
    "participation": 0.01020408163265306,
    "impactCost": 0.7034756477055026
  }
}

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": "2024-12-27T14:31:00.000Z",
  "status": "success",
  "reason": null,
  "riskAudit": {
    "rulesetVersion": 1,
    "outcome": "allowed",
    "longSharesAvailable": 0,
    "unhedgedShortCallContractsPerSpread": 0,
    "buyingPowerEffective": 8210.239390131885,
    "allocationRequested": 1,
    "allocation": {
      "type": "contracts",
      "amount": 1
    },
    "portfolioValue": 8210.239390131885,
    "underlyingPrice": 597.5399780273438,
    "maxLossPerUnit": 595.9999999999999,
    "finalContractQuantity": 1,
    "collateralReserved": 595.9999999999999,
    "committedCostBefore": 0
  }
}

Inspect the largest decline in the exported history

Scale: 0 to 9.4K USD · zero baseline

Cash

2024-04-19T20:00:00.000Z$9398.84
2024-12-24T18:00:00.000Z$8210.24

Scale: 0 to 1.36K USD · zero baseline

Position value

2024-04-19T20:00:00.000Z$1361.00
2024-12-24T18:00:00.000Z$0.00

Scale: 0 to 554 USD · zero baseline

Reserved collateral

2024-04-19T20:00:00.000Z$554.00
2024-12-24T18:00:00.000Z$0.00

Inspect the largest decline in the exported history

Filter rows

Scroll sideways to compare all columns. Select a heading to sort.


2024-04-19T20:00:00.000Z	$9398.84	$1361.00	$554.00
2024-12-24T18:00:00.000Z	$8210.24	$0.00	$0.00

The exported grid's largest peak-to-trough decline was 23.70%, from $10759.84 at 2024-04-19T20:00:00.000Z to $8210.24 at 2024-12-24T18:00:00.000Z. The engine reported maximum drawdown of 23.74%. Compare the history snapshots with the reported statistic and inspect the events around this period.

Plan a separate variant and later test

Review the optional next experiment

After reviewing the recorded example, use the prepared request above for the original rules. This optional plan covers a separate variant and a later test.

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.

Plan development and unseen tests ↗

Explore this strategy further

Inspect 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

All options strategies and guides ↗Create complete strategy rules ↗Backtest a saved strategy ↗

Discussion

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Build and backtest an algorithmic bear put spread

TL;DR

How to build a bear put spread

1. Describe it to Aurora

2. Check the saved rules

3. Backtest it

4. Follow one trade

The rules that define it

Entry

Position sizing

Signal exit

Starting capital

Spread type

Execution

Contract selectors and ratios

Save it as a draft

Create and backtest with Python

Install and download

Create, test and inspect

Run

Python strategy and backtest functions

Create and backtest with TypeScript

Install and download

Create, test and inspect

Run

TypeScript strategy and backtest functions

Start from this example

Worked example to copy: SPY, 2024

One trade from the example

Explain this options decision with Aurora

The example trade's fills

2024-12-18 21:00:00

2024-12-18 21:00:00

2024-12-24 18:00:00

2024-12-24 18:00:00

Inspect the candidate book

Inspect a contract-resolution audit

Inspect the largest decline in the exported history

Cash

Position value

Reserved collateral

Plan a separate variant and later test

Create one variant, then test unseen dates

Explore this strategy further

Continue exploring

Discussion