Exp Score — Expected Value Score Parameter

Byadmin-dcmm-page

What is Exp Score?

Exp Score (Expected Score) is a composite parameter that quantifies the expected value of a trading setup by combining two independent signals: the probability of a winning outcome and the reward-to-risk ratio. It is one of the most actionable parameters in the DCMM Deep Access tier, serving as the primary ranking metric for prioritizing setups.

The Formula

The Exp Score is calculated using a modified expected value formula applied to the DCMM setup parameters:

Exp_Score = P_win × TP_year / SLm × 100

Where:

  • P_win = Probability of a winning outcome (based on Historical Twins, expressed as a decimal, e.g., 0.60 for 60%)
  • TP_year = Take-profit target (annual, as a percentage of current price)
  • SLm = Smart Stop loss (as a percentage of current price, positive value)
  • The multiplication by 100 scales the result to a readable index

In essence, Exp Score captures: “If I take this trade, what is my expected return as a multiple of my risk, weighted by the probability of success?”

Interpreting Exp Score Values

  • Exp Score > 70 — Excellent setup. High probability combined with favorable R/R. Prioritize these setups.
  • Exp Score 50–70 — Good setup. Solid edge present.
  • Exp Score 30–50 — Acceptable setup. Meets minimum criteria but not a high-conviction trade.
  • Exp Score < 30 — Weak setup. Either low probability or poor R/R (or both). Avoid unless other strong confirmations exist.

In the example from the DCMM Deep dashboard, LYB (LyondellBasell) with DD=5 shows Exp Score of 48.75 — reflecting its 50% P_win combined with its R/R ratio of 0.57. PPG Industries with DD=4 shows 88.49, reflecting a strong combination of 77.8% P_win and 0.65 R/R.

Why Exp Score is Superior to Using P_win or R/R Alone

Many traders focus exclusively on either probability (“I want a 70%+ win rate”) or reward/risk (“I need 2:1 R/R”). Both approaches miss the complete picture:

  • A 70% win rate with a 0.1 R/R ratio has negligible expected value
  • A 2:1 R/R with only 30% probability is a losing strategy long-term

Exp Score synthesizes both into a single ranking metric, allowing direct comparison across different setups regardless of their individual P_win or R/R characteristics.

Exp Score in the Context of Kelly Criterion

While Exp Score is primarily a ranking tool, it is closely related to the Kelly Criterion for position sizing:

Kelly % = P_win - (1 - P_win) / (TP_year / SLm)

A higher Exp Score generally corresponds to a higher Kelly percentage, indicating that both the position ranking and the optimal position sizing point to the same high-quality setups.

Using Exp Score in Practice

  1. After filtering by DD (primary setup filter), sort by Exp Score descending
  2. Focus on the top 3–5 setups by Exp Score for any given day
  3. Cross-check with Z-Score (avoid extreme negative values) and Vol Ratio (confirm elevated volume)
  4. Use the Exp Score ranking to allocate capital: higher Exp Score → larger position (within Kelly limits)

Availability

Exp Score is available in the DCMM Deep Access tier. It represents the full QDSF Engine Level 3 analytical output, combining all available data layers (Historical Twins, P_win, TP/SL levels) into a single actionable score.

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