How Historacle turns scenarios into evidence

Historacle helps you stress-test macro views by combining two complementary approaches: real historical precedent and structured statistical relationships. The goal is to turn a scenario into evidence: matched episodes, calibrated ranges, and regime context.

When you define a macro scenario, Historacle generates forward paths using two lenses. It shows its work: matched episodes, regime context, and explicit ranges. The output supports judgment by making the evidence behind the scenario visible.

When you define a macro scenario, Historacle generates forward paths using two lenses:

• Historical Analog Approach. We identify past periods that most closely match the conditions you've set (changes in rates, oil, inflation, the dollar, unemployment, and broader context like recession or stagflation). We then show the actual paths markets and the economy took in those periods. This answers: “What happened the last times the world looked similar to this?”
• Statistical Relationships Approach. We also estimate how individual macro drivers have historically influenced markets, then combine those relationships with the current regime environment. This helps fill in gaps when there isn't a perfect historical match.

These two perspectives are blended into a single set of forward paths. When strong historical matches exist, the view leans more on what actually happened. When the scenario is more unusual, it leans more on the statistical relationships.

In the tool, these approaches are presented as the analog and statistical (decomposed) projections, with a blended result shown by default.

Historacle maintains a library of historical episodes spanning several decades. For any scenario you run, the system scores past episodes for similarity across the dimensions you care about and surfaces the closest ones.

Each match includes a clear explanation of why that period qualified, so you can judge for yourself how relevant it feels. You can review the actual historical outcomes and see how they compare to the forward paths being shown.

This transparency lets you accept, question, or dig deeper into the specific precedents that are influencing the results.

Macro relationships are not constant. The same shock (for example, a rise in oil prices or a shift in Fed policy) tends to play out differently depending on the broader economic and market environment.

Historacle incorporates regime awareness so that historical responses are weighted according to the type of environment we appear to be in. It also shows how the normalized semantic weights across regimes may evolve over the next 24 months under your scenario.

The forward paths include ranges that reflect uncertainty. These ranges are derived from the variation seen across the matched historical episodes and the statistical relationships. They are designed to show a plausible band of outcomes rather than a single point forecast.

We draw on established public data sources, including:

• Federal Reserve Economic Data (FRED) for historical economic and financial series
• U.S. Energy Information Administration (EIA) for energy forecasts
• Additional inputs from professional forecaster surveys and market data providers

All data is used for analytical purposes. Historacle is not affiliated with or endorsed by any of these providers.

Historacle is strongest when its evidence is read the way the product presents it: as scenario intelligence with ranges, analogs, and confidence context. The main boundaries to keep in view are:

• The future can diverge from the past, especially during major structural shifts.
• Some combinations of conditions are rare, which means the set of good historical matches can be limited.
• Data revisions, gaps, and measurement differences exist in any long-term dataset.
• The output is designed for scenario judgment: ranges, evidence, and regime context that help users compare plausible paths.

Clear boundaries make the evidence more useful: users can see where history is strong, where the match is thin, and when to treat the range as the main insight. See the full disclaimer.

Historacle is built for people who want to think carefully about macro conditions and their implications. We aim to surface relevant history and structured analysis in a way that strengthens your own judgment with visible evidence, matched history, and calibrated ranges.

If you have questions about how a specific result was generated, you can review the matched episodes and their explanations directly in the tool.

The chart layers historical reality, published consensus, and your scenario. The shaded band is the plausible range (10th–90th percentile) reflecting uncertainty across matched episodes and statistical relationships. The solid line shows the scenario median path. A thin dashed line shows published consensus where one exists, and a distinct futures-implied curve appears for certain markets. Below the chart, a stacked strip shows scenario-conditioned semantic regime weights over the horizon.

The stock panel shows a conditional 12-month path distribution by applying posterior beta and shrunk alpha to the selected market paths, then adding company-residual history and any selected company-event assumptions. Hand-set sector sensitivities remain separate research diagnostics. You get an expected average, typical median, 10–90 modeled range, share of paths below entry, and historical market-response context (beta, volatility, R²).

Analog cone

Projection built by replaying the actual paths of matched historical episodes, anchored to today's level and delta-corrected toward your inputs.

Decomposed cone

Projection built from kernel-regression estimates of each macro driver's independent marginal effect on the indicator.

Blended cone

A weighted mix of the analog and decomposed cones — analog-heavy when you have direct historical precedent, decomposed-heavy in novel scenarios.

Regime weights

Normalized semantic weights over six cycle phases inferred by the Hamilton filter; these are context labels, not calibrated probabilities.

Percentile band

The 10th–90th percentile range of outcomes from bootstrap resamples across matched episodes — a measure of scenario uncertainty.

Consensus forecast

Published professional forecasts (Fed SEP, EIA STEO, Philly Fed SPF, Wall Street strategist aggregate), shown for comparison against your scenario.

Futures-implied curve

The market's risk-neutral forward expectation from futures prices — bundles consensus with risk premia and carry; shown distinctly from surveyed forecasts.

Condition flag

A binary scenario context — e.g. recession, stagflation, energy crisis — used to refine which historical episodes are eligible to match.