How to Backtest an SPX 0-DTE Expected Range

Backtest the published SPX 0-DTE expected range as a model scorecard: grade containment, breach direction and size, width, and regime dependence before modeling any options strategy.

An SPX 0-DTE expected-range backtest should first evaluate the range itself. Alphanume's S&P 500 0-DTE Strike Band dataset provides a lower strike and upper strike at 10:30 AM Eastern for each trading date. Join those published boundaries to the SPX path from publication through the close, then measure post-publication containment, close containment, breach magnitude, and band width.

The S&P 500 strike-band guide explains the model range, while Alphanume's proof material provides broader evidence context. The band is an expected range, never a guaranteed boundary or personalized strike recommendation. A model scorecard is also not the same as an option-strategy backtest.

Freeze the daily band before outcomes

Use the served date, lower strike, upper strike, and instrument as the immutable forecast record. Preserve the raw response or a dated extract. Do not rebuild old bands from revised inputs and combine them with realized outcomes. The evaluation must use what was published for that session.

State whether exact boundary touches count as contained. Use an inclusive rule consistently. Keep upper and lower misses separate because their frequency and tail behavior can differ.

Join verified SPX outcomes and regimes

The band endpoint does not serve realized high, low, or close, so source intraday bars independently for the same SPX cash index session. Use bars at or after 10:30 AM Eastern for the primary score. For regime analysis, join the daily point-in-time S&P 500 Risk Regime dataset under the availability rule in the Risk Regime documentation. Zero is risk-on and one is risk-off.

GET /v1/spx-0dte-strike-band
date_gte=2024-01-01
date_lte=2025-12-31

GET /v1/sp500-risk-regime
date_gte=2024-01-01
date_lte=2025-12-31

post_1030 = spx_intraday_bars where local_time >= 10:30
score = band JOIN post_1030_summary ON date
score = score JOIN risk_regime ON date
calculate post_publication_containment,
          upper_breach, lower_breach,
          width_points, width_pct, relative_breach
retain missing joins and reasons

Align holidays, early closes, and instrument definitions. If a proxy such as an ETF is used for outcomes, label it as a proxy and do not compare its price levels directly with SPX strike boundaries. Missing market or regime rows belong in an exclusion table.

Grade containment, misses, width, and regime

Report overall and rolling containment, upper and lower breach rates, median and tail miss size, and band-width distribution. Then split by prespecified risk regime and width bucket. Include event counts and confidence intervals so a small regime cell is not mistaken for stable evidence.

• Show post-publication and close results, with full-session results labeled descriptive.
• Publish worst misses with their daily widths.
• Compare narrow and wide bands on normalized width.
• Report regime cell sizes and missing joins.

A wider band can achieve higher containment mechanically. Evaluate containment together with normalized width and a proper loss or calibration score if one is defined. Comparing hit rates alone rewards ranges that become uninformatively wide.

Rolling analysis should use fixed, prespecified windows and show the number of scored sessions. A twenty-session rate can move sharply after one breach, while an annual rate can hide recent deterioration. Report both without selecting the window that makes the model look best. If a change-point or recalibration date is studied, define it independently of realized misses or reserve a later period for validation.

Regime dependence can also be confounded by width. Risk-off sessions may receive wider bands and still show different containment. Within each regime, compare normalized-width buckets or model containment with width as a covariate. Keep this descriptive unless the design supports causal claims. A small risk-off sample should be labeled uncertain rather than smoothed into the larger risk-on population.

Separate model accuracy from option PnL

The main failure mode is treating a contained session as a profitable iron condor or other 0-DTE trade. PnL depends on exact strikes, premium, bid-ask spread, intraday path, stop logic, settlement, commissions, and tail loss. A breached band does not automatically mean maximum loss, and a contained band does not guarantee enough premium to cover costs.

Regime labels also have an availability time. Do not condition the 10:30 AM score on a regime observation published later. Either use the prior available regime or define a later decision time. State the rule and run sensitivity to an additional-session lag. Likewise, never present full-session high and low as the outcome of a decision made after 10:30 AM.

Build a published-band scorecard

As a concrete next action, retrieve a completed year of bands, verified SPX bars from 10:30 AM through the close, and point-in-time regime labels. Produce one row per session with post-publication and close containment, normalized width, breach direction and magnitude, regime, proper loss or calibration score, and exclusion status. Summarize rates, widths, tail misses, and prespecified regime-by-width cells. Only after that model scorecard is frozen should a separate contract-level strategy simulation add premiums, paths, execution rules, and costs.