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Volatility Engine

The volatility engine is Tracera’s core differentiator — bringing institutional-grade financial analytics to the CS2 skin market.

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Why Volatility?

Most skin tracking tools show price and price history. Tracera goes further by computing quantitative volatility metrics that answer harder questions:
  • Is this price move normal or unusual? (Bollinger bands)
  • How risky is this item to hold? (Standard deviation, CoV)
  • Is the price trending up or down? (Trend score)
  • How does this item’s volatility compare to others? (Coefficient of variation)

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Metrics

All calculations run in Go for speed. Pre-aggregated data from TimescaleDB continuous aggregates feeds into these computations.

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Rolling Standard Deviation

The core volatility measure. Computed over sliding windows (1h, 24h, 7d). 
σ = √(Σ(xi - μ)² / N)
Higher σ = more volatile = more risk/opportunity.

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Percentage Change

Quick trend indicator showing the price movement from the previous period. 
% change = (current - previous) / previous × 100

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Bollinger Bands

Classic technical analysis indicator for detecting overbought/oversold conditions. 
Upper Band = SMA + (k × σ)    where k = 2
Middle Band = SMA (Simple Moving Average)
Lower Band = SMA - (k × σ)
When the price breaks above the upper band, the item may be overbought. Below the lower band, it may be oversold.

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Coefficient of Variation (CoV)

Normalized volatility that enables comparison across different price ranges. 
CoV = σ / μ
A 10itemwithσ=2anda10 item with σ=2 and a 1000 item with σ=20 both have CoV=0.2, meaning they’re equally volatile relative to their price.

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Trend Score

Linear regression slope on the recent price window. Positive values indicate an uptrend, negative values a downtrend. The magnitude indicates the strength of the trend.

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Data Pipeline

TimescaleDB Continuous Aggregates (1h, 24h, 7d)
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    │  Pre-aggregated: avg, min, max, stddev, volume
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    ▼
Volatility Engine (Go)
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    │  Computes: all metrics per item
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    ├──▶ Redis Cache (latest metrics)
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    └──▶ Redis Pub/Sub (broadcast to WebSocket clients)

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Vision: Portfolio Volatility Score

Phase 7 extends the volatility engine to portfolios:
  • Compute a single-number portfolio volatility score across all holdings
  • Similar to portfolio beta in traditional finance
  • Percentile ranking — see how your portfolio’s risk compares to other users
  • Informs the What-If Trade Simulator (Phase 9) — simulate trades and see how your portfolio score changes

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Vision: Market Sentiment Index

Phase 11 aggregates volatility signals into a market-wide indicator:
  • Fear/greed index derived from:
    • Volume spikes across items
    • Listing count changes (supply pressure)
    • Price velocity (rate of price change)
  • Historical comparison for trend analysis