W07 · example_weights_07_intraday_rsi_15m.py

W07 Intraday RSI15m

Use yfinance-backed 15-minute bars from /bt/prepare and hold an equal weight basket when RSI(14) is oversold.

Review the source on GitHub or return to all strategies.

What this example shows

This example shows how to build a 15m-bar RSI mean-reversion weight-mode example with intraday signal generation, execution timing, cost assumptions and reporting at non-daily granularity.

The goal is educational: to demonstrate the full workflow for universe definition, signal generation, weight construction, risk overlays, execution assumptions, diagnostics and reproducible reporting.

Short-window execution example. Short-window intraday execution example. The dashboard emphasizes raw total return and drawdown; annualized CAGR and Sharpe are intentionally omitted because this sample is too short for a credible annual comparison.

Run setup

The ordinary configuration used by the published run—kept visible here and in the Python source.

UniverseSPY · QQQ · IWM

Configured period2026-06-19 → 2026-07-11

BenchmarkSPY · SPDR S&P 500 ETF Trust

Initial capital$100,000

Data sourceyfinance

Engine / snapshot0.10.0 · db63d014b5511a46

Weight ModeMode

15mGranularity

3Instruments

21Published plots

passedRun status

Dashboard

Compact evidence view built from the same run packet: metrics, plots and run metadata.

-1.07% Max DD

2.64% Total return

$2,635 Net profit

Selected plot gallery

21 published PNG artifacts selected for raw short-window interpretation. Charts marked Pro are generated by the hosted platform report pack; the rest come from the open-source engine output.

W07 Intraday RSI15m Cumulative Returns — Cumulative Returns PNG

W07 Intraday RSI15m Portfolio Drawdown — Portfolio Drawdown PNG

W07 Intraday RSI15m Nav Composition — Nav Composition Pro PNG

W07 Intraday RSI15m Percentage Weights — Percentage Weights PNG

W07 Intraday RSI15m Blotter Trade Pnl — Blotter Trade Pnl Pro PNG

W07 Intraday RSI15m Blotter Cumulative Pnl — Blotter Cumulative Pnl Pro PNG

W07 Intraday RSI15m Blotter Costs — Blotter Costs Pro PNG

W07 Intraday RSI15m Blotter Frequency — Blotter Frequency Pro PNG

W07 Intraday RSI15m Blotter Holding Periods — Blotter Holding Periods Pro PNG

W07 Intraday RSI15m Blotter Instrument Pnl — Blotter Instrument Pnl Pro PNG

Execution

W07 Intraday RSI15m Blotter Trade Size — Blotter Trade Size Pro PNG

W07 Intraday RSI15m Blotter Trade Timeline — Blotter Trade Timeline Pro PNG

Portfolio accounting

W07 Intraday RSI15m Composition — Composition PNG

Performance

W07 Intraday RSI15m Cumulative Log Returns — Cumulative Log Returns PNG

Drawdown

W07 Intraday RSI15m Time Underwater — Time Underwater PNG

Distribution and optimization

W07 Intraday RSI15m Return Quantiles — Return Quantiles PNG

W07 Intraday RSI15m Returns Distribution — Returns Distribution Pro PNG

Strategy traces

W07 Intraday RSI15m Strategy Trace IWM — Strategy Trace IWM Pro PNG

W07 Intraday RSI15m Strategy Trace QQQ — Strategy Trace QQQ Pro PNG

W07 Intraday RSI15m Strategy Trace SPY — Strategy Trace SPY Pro PNG

Metrics

Raw short-window KPIs are shown above; annualized ratios are intentionally not promoted.

Artifacts

Stable links that can be referenced from GitHub README files or external docs.

Run log run.log Raw text report performance_report.txt Published source snapshot strategy.py Structured report performance_report.json GitHub source example_weights_07_intraday_rsi_15m.py

Run log

Tail of the execution log for this packet.

Running strategy: example_weights_07_intraday_rsi_15m
File: <QJ_BACKTESTER_REPO>/strategies/example_weights_07_intraday_rsi_15m.py
Python: <QJ_BACKTESTER_REPO>/.venv/bin/python
Backtester: v0.10.0
Theme: quantjourney
Plot DPI: 300
Log Level: ERROR
Output: reports/canonical-suite-20260711

2026-07-11 12:11:00,661 - quantjourney_ti._utils - WARNING - 2026-07-11 12:11:00,661 - quantjourney_ti._utils - WARNING - Series contains NaN values; they will be handled in calculations
2026-07-11 12:11:00,666 - quantjourney_ti._utils - WARNING - 2026-07-11 12:11:00,666 - quantjourney_ti._utils - WARNING - Series contains NaN values; they will be handled in calculations
[2026-07-11 12:11:03] [ERROR] [backtester] Failed to compute r_squared: Benchmark overlap 0.00% is below required 95.00%
[2026-07-11 12:11:03] [ERROR] [backtester] Failed to compute beta: Benchmark overlap 0.00% is below required 95.00%
[2026-07-11 12:11:03] [ERROR] [backtester] Failed to compute tracking_error: Benchmark overlap 0.00% is below required 95.00%
[2026-07-11 12:11:03] [ERROR] [backtester] Failed to compute up_capture: Benchmark overlap 0.00% is below required 95.00%
[2026-07-11 12:11:03] [ERROR] [backtester] Failed to compute alpha: Benchmark overlap 0.00% is below required 95.00%
[2026-07-11 12:11:03] [ERROR] [backtester] Failed to compute down_capture: Benchmark overlap 0.00% is below required 95.00%
[2026-07-11 12:11:03] [ERROR] [backtester] Failed to generate cumulative_returns_with_regime plot: Insufficient data for regime cumulative returns.
[2026-07-11 12:11:04] [ERROR] [backtester] Failed to generate portfolio_drawdown_with_regime plot: Insufficient data for regime drawdown plot.
<QJ_BACKTESTER_REPO>/backtester/portfolio/portfolio_plots.py:203: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
  regime = regime.reindex(target_index).ffill()
<QJ_BACKTESTER_REPO>/backtester/portfolio/portfolio_plots.py:203: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
  regime = regime.reindex(target_index).ffill()
[2026-07-11 12:11:06] [ERROR] [backtester] Failed to generate rolling_asset_correlations plot: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
[2026-07-11 12:11:06] [ERROR] [backtester] Failed to generate rolling_beta plot: No valid beta values calculated.
[2026-07-11 12:11:06] [ERROR] [backtester] Failed to generate rolling_beta_with_regime plot: No valid beta values calculated.
[2026-07-11 12:11:06] [ERROR] [backtester] Failed to generate rolling_alpha plot: index -1 is out of bounds for axis 0 with size 0
[2026-07-11 12:11:06] [ERROR] [backtester] Failed to generate rolling_alpha_with_regime plot: index -1 is out of bounds for axis 0 with size 0
[2026-07-11 12:11:06] [ERROR] [backtester] Failed to generate rolling_information_ratio plot: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
[2026-07-11 12:11:06] [ERROR] [backtester] Failed to generate rolling_information_ratio_with_regime plot: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
[2026-07-11 12:11:06] [ERROR] [backtester] Failed to generate relative_performance plot: Insufficient data for relative performance plot.
[2026-07-11 12:11:06] [ERROR] [backtester] Failed to generate factor_exposure plot: Insufficient data for factor exposure proxy.
[2026-07-11 12:11:06] [ERROR] [backtester] Failed to generate benchmark_regime_analysis plot: Insufficient data for benchmark regime analysis.
<QJ_BACKTESTER_REPO>/backtester/portfolio/portfolio_plots.py:203: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
  regime = regime.reindex(target_index).ffill()
[2026-07-11 12:11:08] [ERROR] [backtester] Failed to generate asset_risk_contribution plot: Portfolio variance is non-positive.

============================================================
  Strategy: ExampleWeights07_IntradayRSI15m
  Backtester: v0.10.0
  Period:   2026-06-22 → 2026-07-10
  Assets:   SPY, QQQ, IWM
────────────────────────────────────────────────────────────
  Initial NAV:  $    100,000.00
  Final NAV:    $    102,635.04
  Total Return:          2.64%
  Ann. Volatility:       6.35%
  Max Drawdown:         -1.07%
  Sharpe Ratio:        7.0947
────────────────────────────────────────────────────────────
  Runtime Total:        16.32s
  Data Fetch:            1.82s
  Data Prep:             0.16s
  Calculation:           0.87s
  Reporting:            13.45s
────────────────────────────────────────────────────────────
  Rebalance Policy: RebalancePolicy(freq=None, signal_change)
  Rebalances:              47
  Avg Days Btw:          19.1
============================================================

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