MORPHIQLABS

FerroSpread

Getting started

Construct, rank, and explain a first defined-risk spread.

Product site API reference

FerroSpread turns enriched equity, option, and eligibility rows into explained spread candidates. Pricing and volatility assumptions come from upstream analytics; FerroSpread owns construction, candidate summaries, scenario analytics, and leg-level accounting.

Construct

use spread_builder::{build_spread_candidates, SpreadBuilderInput};
 
let input = SpreadBuilderInput::legacy(
    snapshot_date,
    &equity_rows,
    &option_rows,
    &eligibility_rows,
);
 
let output = build_spread_candidates(&config.spread_builder, &input)?;
 
for summary in &output.summaries {
    println!(
        "{} {} {} {:?}",
        summary.symbol,
        summary.strategy_family,
        summary.strategy_code,
        summary.tradeable_resolution_reason
    );
}
# Ok::<(), Box<dyn std::error::Error>>(())

Analyze

use spread_analytics::{compute_candidate_analytics, CandidateAnalytics};
 
let analytics: CandidateAnalytics = compute_candidate_analytics(&candidate_inputs)?;
 
println!(
    "pop={} expected_value={} stress_loss={}",
    analytics.probability_of_profit,
    analytics.expected_value,
    analytics.stress_loss
);
# Ok::<(), Box<dyn std::error::Error>>(())

Every output should be treated as an explainable candidate: construction inputs, leg rows, analytics inputs, and scenario assumptions stay separate so the application layer can rank or filter without hiding provenance.

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