Build and backtest BTC trend pullback

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.

Step 1 of 3

Read this pair's entry and exit

Inspect the exact pair, indicator windows, position guard and allocation below. Weekly accumulation has a purchase cadence and no invented sale rule.

Entry: Saved rule: Price > SMA(200, Day) AND RSI(14, Day) < 40 AND position value = 0
Exit: Saved rule: RSI(14, Day) >= 60 OR Price <= SMA(200, Day) AND position value > 0
Allocation: Saved rule: 95% of buying power per entry; sell 100% of held units on exit
Pair: Saved rule: BTC-USD

What you should see

The full saved condition/action book with fractional units and an explicit Cryptocurrency target.

BTC trend pullbackSPY buy and holdBTC buy and holdHistorical simulation

This saved algorithm completed a Day backtest from 2024-01-01 through 2024-12-31, with $10000.00 starting capital. The chart includes all 744 exported history points. Compare the strategy with SPY and BTC buy and hold. Each benchmark invests the full $10000.00 starting balance over the same 2024 period. SPY follows its trading sessions; BTC includes weekends. This algorithm follows its own allocation and entry/exit rules, with 0.7% of traded notional charged on each fill. Explore cash and position values to see how capital was deployed.

Step 2 of 3

Completed 2024 backtest

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.

Step 3 of 3

Preview this strategy in Aurora

Review the provided strategy request without changing its pair or sizing. Ask for a draft preview before any saved candidate or paid test.

What you should see

An inspectable candidate. New dates or a changed rule define another experiment, not the published result.

The algorithm

Buy an RSI pullback within a 200-day uptrend; exit on RSI recovery or a trend break.

This example trades BTC-USD as a spot Cryptocurrency asset. The saved rules were read back and verified with automated trading off.

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Entry	Price > SMA(200, Day) AND RSI(14, Day) < 40 AND position value = 0
Exit	RSI(14, Day) >= 60 OR Price <= SMA(200, Day) AND position value > 0
Allocation	95% of buying power per entry; sell 100% of held units on exit
Pair	BTC-USD
Execution	Market; fractional units enabled
Starting capital	$10,000; no additional deposits

Create the same strategy

Ask Aurora to build the rules above, review the preview, then save the draft with automated trading off. Confirm the Cryptocurrency pair, allocation and entry and exit conditions in the saved rules.

In the native Strategies editor, use Buy and Sell actions with the same Cryptocurrency pair. Add the indicator and position-value conditions shown above. The weekly accumulation example uses a single Buy rule with a seven-day DaysSinceOrder condition.

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.

Create the exact strategy
Ask: "Review BTC trend pullback. Entry: Price > SMA(200, Day) AND RSI(14, Day) < 40 AND position value = 0. Exit: RSI(14, Day) >= 60 OR Price <= SMA(200, Day) AND position value > 0. Show the resolved rules and selectors before saving." The request includes this example's complete draft.
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 strategy with SPY and BTC buy and hold. Use SPY as the backtest baseline and a separate BTC buy-and-hold backtest with matching dates and starting capital.
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."
Create one variant, then test unseen dates
Ask: "Change only the entry allocation from 95% to 75% of buying power. 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 ↗

Create and backtest with Python

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

Install and download

Shell

python3 -m pip install nexustrade==1.42.0
export NEXUSTRADE_API_KEY="YOUR_API_KEY"
curl --fail --output btc_trend_pullback.py https://nexustrade.io/seo/strategy-examples/btc-trend-pullback.py

Create, test and inspect

Python

from btc_trend_pullback import create_btc_trend_pullback, backtest_btc_trend_pullback

book = create_btc_trend_pullback()
completed = backtest_btc_trend_pullback()
print(completed["result"])

Run

Shell

python3 run_btc_trend_pullback.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_btc_trend_pullback():
    asset = nt.crypto_asset("BTC-USD")
    return nt.portfolio(
        "Public SEO crypto example - BTC trend pullback",
        [
            nt.strategy(
                "Enter BTC trend pullback",
                (((nt.Price(asset) > nt.SMA(asset, 200, "Day")) & (nt.RSI(asset, 14, "Day") < nt.Value(40))) & (nt.PositionValue(asset) == nt.Value(0))),
                nt.buy(asset, 95, "percent of buying power")
            ),
            nt.strategy(
                "Exit BTC trend pullback",
                (((nt.RSI(asset, 14, "Day") >= nt.Value(60)) | (nt.Price(asset) <= nt.SMA(asset, 200, "Day"))) & (nt.PositionValue(asset) > nt.Value(0))),
                nt.sell(asset, 100, "percent of current positions")
            ),
        ],
        initial_value=10000,
        supports_crypto=True,
        supports_fractional_shares=True,
        alerts_enabled=False,
        dividend_policy='cash',
    )


def backtest_btc_trend_pullback(client=None):
    client = client or nt.NexusTradeClient.from_environment()
    operation = client.create_backtest(
        nt.backtest(
            create_btc_trend_pullback(),
            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-btc-trend-pullback-2024-spy-v1",
    )
    return client.wait_for_backtest(operation["id"])


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

Create and backtest with TypeScript

TypeScript SDK 1.42.0. Save the runner below as run-btc-trend-pullback.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 btc-trend-pullback.ts https://nexustrade.io/seo/strategy-examples/btc-trend-pullback.ts

Create, test and inspect

TypeScript

import { createBtcTrendPullback, backtestBtcTrendPullback } from "./btc-trend-pullback";

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

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

Run

Shell

npx tsx run-btc-trend-pullback.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 createBtcTrendPullback() {
  const asset = nt.cryptoAsset("BTC-USD");
  return nt.portfolio(
    "Public SEO crypto example - BTC trend pullback",
    [
      nt.strategy(
          "Enter BTC trend pullback",
          nt.and(
              nt.and(
                  nt.gt(nt.Price(asset), nt.SMA(asset, 200, "Day")),
                  nt.lt(nt.RSI(asset, 14, "Day"), nt.Value(40))
              ),
              nt.eq(nt.PositionValue(asset), nt.Value(0))
          ),
          nt.buy(asset, 95, "percent of buying power")
      ),
      nt.strategy(
          "Exit BTC trend pullback",
          nt.and(
              nt.or(
                  nt.gte(nt.RSI(asset, 14, "Day"), nt.Value(60)),
                  nt.lte(nt.Price(asset), nt.SMA(asset, 200, "Day"))
              ),
              nt.gt(nt.PositionValue(asset), nt.Value(0))
          ),
          nt.sell(asset, 100, "percent of current positions")
      ),
    ],
    { initialValue: 10000, supportsCrypto: true, supportsFractionalShares: true, alertsEnabled: false, dividendPolicy: "cash" }
  );
}

export async function backtestBtcTrendPullback(client = new nt.NexusTradeClient()) {
  const operation = await client.createBacktest(
    nt.backtest(createBtcTrendPullback(), {
      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-btc-trend-pullback-2024-spy-v1" }
  );
  if (typeof operation.id !== "string") throw new Error("Missing backtest ID");
  return client.waitForBacktest(operation.id);
}

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

Completed 2024 backtest

This saved algorithm completed a Day backtest from 2024-01-01 through 2024-12-31, with $10000.00 starting capital. The chart includes all 744 exported history points.

Compare the strategy with SPY and BTC buy and hold. Each benchmark invests the full $10000.00 starting balance over the same 2024 period. SPY follows its trading sessions; BTC includes weekends. This algorithm follows its own allocation and entry/exit rules, with 0.7% of traded notional charged on each fill. Explore cash and position values to see how capital was deployed.

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Status	COMPLETE
Backtest return	-6.43%
Reported maximum drawdown	20.62%
SPY buy-and-hold return	25.30%
BTC buy-and-hold return	119.27%
Total recorded trading fees	$2011.18
Engine closed-trade count	31
Starting capital	$10000.00
Ending portfolio value	$9357.49
Ending cash	$438.95
Ending position value	$8918.53

BTC trend pullbackSPY buy and holdBTC buy and holdHistorical simulation

Inspect the recorded trades

Follow the Filled events by pair, side and time. Compare the submitted price, filled price, fractional quantity and fee. This table shows up to eight orders from the captured excerpt (47 Filled events); the download includes the entire excerpt.

For a percentage fee, multiply the traded notional by 0.007. To follow a position, start with a purchase and inspect subsequent sale quantities, remaining holdings and cash flows. For the weekly accumulation example, follow each purchase and the resulting position value.

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2024-01-12T21:00:00.000Z	BTC-USD	Buy	0.21733968539544338	$43710.38	$43710.38	$66.50
2024-01-26T21:00:00.000Z	BTC-USD	Sell	0.21581830759767529	$41979.10	$41979.10	$63.42
2024-01-27T14:30:00.000Z	BTC-USD	Sell	0.001521377797768092	$41771.50	$41771.50	$0.44
2024-03-15T13:30:00.000Z	BTC-USD	Buy	0.1337200380577867	$67442.34	$67442.34	$63.13
2024-03-25T20:00:00.000Z	BTC-USD	Sell	0.1327839977913822	$71160.50	$71160.50	$66.14
2024-03-26T13:30:00.000Z	BTC-USD	Sell	0.0009360402664045087	$70730.99	$70730.99	$0.46
2024-04-02T13:30:00.000Z	BTC-USD	Buy	0.14444388277913411	$64849.37	$64849.37	$65.57
2024-04-07T13:30:00.000Z	BTC-USD	Sell	0.14343277559968018	$69402.56	$69402.56	$69.68

Understand this entry with Aurora

At 2024-12-18T21:00:00.000Z, the recorded rule was: BTC-USD last price > 200 Day BTC-USD SMA and 14 Day BTC-USD RSI < Constant 40 and Position market value (BTC-USD) = Constant 0. Its overall result was true. Read the individual comparisons below, then ask Aurora to explain how they led to the action.

The signal requested 95 percent of buying power at a submitted price of 100,844.8672. 1 captured Filled order shares this timestamp; Aurora receives those fields with the signal.

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BTC-USD price > BTC-USD 200 day SMA	100,844.8672	>	69,711.9228	True
BTC-USD 14 day RSI < constant	39.8636	<	40	True
BTC-USD position value = constant	0	=	0	True

Inspect the original signal record

View captured signal JSON

JSON

{
  "eventType": "BuySignal",
  "event": {
    "eventType": "BuySignal",
    "timestamp": "2024-12-18T21:00:00.000Z",
    "signals": [
      {
        "conditionName": "BTC-USD last price > 200 Day BTC-USD SMA and 14 Day BTC-USD RSI < Constant 40 and Position market value (BTC-USD) = Constant 0",
        "audit": {
          "type": "minimal",
          "results": {
            "0.0.1": {
              "isTrue": true,
              "lhsValue": 39.86359799892766,
              "rhsValue": 40,
              "lhsError": null,
              "rhsError": null,
              "comparison": "lessThan"
            },
            "0.0.0": {
              "isTrue": true,
              "lhsValue": 100844.8671875,
              "rhsValue": 69711.92284665516,
              "lhsError": null,
              "rhsError": null,
              "comparison": "greaterThan"
            },
            "0.1": {
              "isTrue": true,
              "lhsValue": 0,
              "rhsValue": 0,
              "lhsError": null,
              "rhsError": null,
              "comparison": "equal"
            }
          },
          "failuresOnly": false
        },
        "isTrue": true,
        "actionName": "Buy",
        "actionMetadata": {
          "buyOrSell": {
            "targetAsset": {
              "name": "BTC-USD",
              "symbol": "BTC-USD",
              "type": "Cryptocurrency",
              "underlyingSymbol": null,
              "optionType": null,
              "expirationDate": null,
              "strikePrice": null,
              "multiplier": null
            },
            "allocation": {
              "type": "percent of buying power",
              "amount": 95
            },
            "price": 100844.8671875,
            "orderType": "Market Order"
          }
        },
        "orderExecution": {
          "type": "Market"
        }
      }
    ]
  },
  "timestamp": 1734555600000
}

Explore a drawdown period

The largest decline between exported snapshots was 19.30%, from $10511.34 at 2024-06-13T13:30:00.000Z to $8482.89 at 2024-10-23T20:00:00.000Z. The reported maximum drawdown is 20.62%. Explore the trades and holdings around those dates.

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2024-06-13T13:30:00.000Z	$10511.34	$453.37	$10057.97
2024-10-23T20:00:00.000Z	$8482.89	$370.19	$8112.69

Download and explore the result

Download the exact strategy inputs, completed receipt, full history, fee settings and captured events. Detailed events remain available in the product for 3 days; this saved example stays readable.

Download public backtest JSON ↗Inspect signals, pricing and fills ↗Explore trading costs ↗

Test another version

Change one rule or choose a different date range, then compare the resulting curve and trade events with this saved experiment. Explore which trades, fees and periods explain the difference.

Backtest the saved rules ↗

Continue exploring

All cryptocurrency resources ↗Create a crypto strategy ↗Backtest a crypto strategy ↗

Build and backtest BTC trend pullback

Follow the example

Read this pair's entry and exit

Completed 2024 backtest

Preview this strategy in Aurora

The algorithm

Create the same strategy

Create, test and iterate in Aurora

Create the exact strategy

Run the 2024 development comparison

Explain what happened

Create one variant, then test unseen dates

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

Completed 2024 backtest

Inspect the recorded trades

Understand this entry with Aurora

Inspect the original signal record

Explore a drawdown period

Download and explore the result

Test another version

Continue exploring