The Oyamori Edge Catalog

A strategy catalog and an edge catalog are different things. A strategy catalog lists rules — entry conditions, exit conditions, parameters. An edge catalog maps the underlying inefficiency each strategy is designed to exploit. The distinction matters because strategies degrade. The underlying inefficiencies they are built on degrade more slowly, and recognizing one lets you rebuild a strategy when the current implementation stops working.

The Oyamori edge catalog is organized around inefficiency classes: statistical arbitrage, momentum and trend, news and sentiment, and structural market mechanics. Each entry names the inefficiency explicitly, identifies the market regime where it performs best, and states the typical holding period for strategies built around it.

This is not a complete list of all edges that exist in markets. It is a list of edges that meet Oyamori's standard: there is a documented behavioral or structural explanation for why the mispricing occurs, and there is consistent empirical evidence that it has persisted across market cycles.

How to Read the Catalog

Each table contains four columns:

• Edge — the name of the specific inefficiency
• Inefficiency — the behavioral or structural cause of the mispricing
• Regime — the market condition where the edge performs best (ranging, trending, volatile, any)
• Holding Period — typical time a position based on this edge is held

Complexity is noted inline for edges that require advanced tooling or significant data infrastructure. Where a detailed explainer article exists, the edge name links to it.

Not every entry has a published explainer yet. The catalog is a living inventory — edges are added as documentation is completed, not held until the full catalog is written.

Statistical Arbitrage Edges

Statistical arbitrage edges exploit temporary pricing divergences between related instruments. The underlying hypothesis is that prices are mean-reverting over some time horizon — deviations from equilibrium are eventually corrected.

Mean reversion and pairs trading are the most accessible entry points. Cointegration spread strategies require identifying cointegrated pairs statistically — the Engle-Granger or Johansen test is the standard approach. Index and ETF arbitrage require sub-second execution infrastructure and are not accessible to retail systematic traders without direct market access.

Momentum and Trend Edges

Momentum edges exploit the persistence of price movement. The behavioral source is well-documented: investors underreact to information in the short run (anchoring, attention limitations), and then overreact as the trend becomes obvious (herding, FOMO). The result is price movement that continues longer than fundamentals alone would predict.

Momentum edges fail in ranging or mean-reverting markets. A momentum strategy that runs without regime detection will give back gains during consolidation phases. Volume confirmation is the primary filter — strong momentum without volume support is more likely to reverse.

Cross-sectional momentum (buying the top 10% of performers and shorting the bottom 10%) is a portfolio construction approach rather than a single-stock strategy. It requires sufficient capital to hold a diversified long/short book.

News and Sentiment Edges

News-driven edges exploit the time lag between information becoming available and that information being fully priced into the market. The behavioral cause is processing speed: most market participants cannot parse news at the speed that creates an opportunity, and even when they can, position-taking has friction.

The Newsvibe API provides structured sentiment scoring — numeric scores, confidence intervals, urgency tiers — rather than raw text, which is what makes these edges accessible to systematic traders without NLP infrastructure. The explainer at How Newsvibe Works covers the signal format and validation methodology.

Overnight sentiment edges require pre-market or after-hours routing. Not all brokers provide this; Alpaca and Interactive Brokers are the standard options for systematic retail traders.

Structural Edges

Structural edges arise from the mechanics of how markets operate rather than from behavioral patterns. These are more persistent than behavioral edges because they are anchored to market structure rather than investor psychology, but they also change when market structure changes.

Structural edges tend to be more robust across market regimes because the underlying mechanism is the structure of the market itself rather than investor behavior. Gap trading works in bull and bear markets because gaps are a function of overnight price formation, not market direction. Options theta decay works in any volatility regime as long as IV is elevated relative to historical RV — which it nearly always is, on average.

Order flow imbalance requires Level 2 data and execution speed. It is available to retail traders but requires proper data subscriptions and low-latency routing.

How Edges Decay

Every edge in this catalog has decayed to some degree since it was first documented in academic literature. Mean reversion on individual stocks is less profitable at daily frequency than it was in the 1990s — increased algorithmic participation has made markets more efficient at that time horizon. Pairs trading spreads are tighter than they were before HFT.

This is not a reason to abandon the catalog. It is a reason to monitor performance continuously and adjust. An edge that returns 0.8% per trade instead of 1.5% per trade is still an edge. An edge that returns 0.0% or negative is not.

Edges decay for three reasons: arbitrage capital removes the inefficiency, structural changes alter the underlying mechanism, or regulatory changes eliminate the opportunity. Monitoring which edges are working and which are degrading is an ongoing operational responsibility.

The pattern of decay: academic publication → hedge fund adoption → retail adoption → crowding → compression → further compression until edge is too thin to cover transaction costs. The catalog is most valuable in the early and middle stages.

The Oyamori Approach

The catalog is not static. New edges are added when they meet the documentation standard: a plausible behavioral or structural explanation and consistent empirical evidence across at least one full market cycle. Edges are retired when monitored performance suggests the underlying inefficiency has been arbitraged away.

The platform's live monitoring system tracks edge performance metrics across the active catalog. When a previously reliable edge enters a drawdown period that is anomalous relative to its history, the system flags it for review. This is not automatic de-listing — drawdowns happen in the normal course — but it is a signal that the regime may have changed or that the edge has attracted enough capital to compress the opportunity.

Developers building on the Oyamori platform can see which edges are currently active, what their recent performance metrics show, and where in the catalog each edge sits in terms of complexity and infrastructure requirements. The goal is a catalog that is honest about what it is: a set of probabilistic opportunities, each with known failure modes, held with appropriate position sizing and monitored continuously.

Next: What Is a Trading Edge? →