Energy Stock Rankings

Updated 2026-10-15 16:18 UTC · 56 tickers · mode: signals

Market Pulse

17
Risk On
25
Transitional
14
Risk Off

Top 5 This Week

MPC
100.0
transitional
VLO
99.7
risk on
PSX
99.2
risk on
XOM
95.3
risk on
COP
95.2
transitional

This Week in Energy

Sector Context

Across the 56-name universe, the per-ticker regime classifier currently labels 17 risk-on and 14 risk-off.

Company Spotlights

Four names each week, rotating deterministically through the full universe (about 14 weeks per complete pass) — not picked by score, so the laggards and the boring-but-instructive names get their turn too. Nothing here is a recommendation: no stock-selection signal in this project has passed validation, and the scores below are shown to be understood, not acted on.

SLB Traditional Energy

Oilfield services (global)

Levered to: international and offshore capex cycles

Filings (FY2025): net debt/EBITDA 1.1x (conservative); capex 5% of revenue; free cash flow +$4.8B.

Composite 26.8 (0–100, normalized across this universe), ranked 15 of 17 in its sub-sector; momentum component 0.46. The regime classifier labels it risk-on (99% confidence). Sizing model currently allocates nothing here — the return/risk profile doesn't clear the bar at these prices.

SMR Nuclear / Hydrogen

Small modular reactor developer

Levered to: pre-revenue: NRC licensing, first-plant milestones

Filings (FY2025): capex 2% of revenue; free cash flow −$0.5B.

Composite 0.0 (0–100, normalized across this universe), ranked 14 of 14 in its sub-sector; momentum component 0.11. The regime classifier labels it transitional (88% confidence). Sizing model currently allocates nothing here — the return/risk profile doesn't clear the bar at these prices.

SQM Critical Minerals

Lithium and potassium producer (Chile)

Levered to: lithium prices, Chilean policy/royalties

Composite 19.5 (0–100, normalized across this universe), ranked 5 of 13 in its sub-sector; momentum component 0.36. The regime classifier labels it transitional (63% confidence). Sizing model currently allocates nothing here — the return/risk profile doesn't clear the bar at these prices.

STEM Solar / Wind / Storage

AI-driven battery storage software

Levered to: storage deployment rates, software attach

Composite 1.8 (0–100, normalized across this universe), ranked 12 of 12 in its sub-sector; momentum component 0.14. The regime classifier labels it transitional (92% confidence). Sizing model currently allocates nothing here — the return/risk profile doesn't clear the bar at these prices.

Score Calibration — tracking started

20 spotlighted names are being tracked against XLE over 13-week windows; none have closed yet, so there is nothing to report. The first measurable result lands around 13 Dec 2026. Because spotlights rotate on a schedule that ignores the composite score, what accumulates here is an unbiased forward sample — it will eventually answer whether higher-scored names beat the benchmark more often than lower-scored ones. Four signal families have failed that test in backtest; this is the live version, and it is meant to take months.

#TickerScore RegimeConfidenceMomentumKellySector
1MPC100.0transitional82%+0.8810.0%traditional_energy
2VLO99.7risk on88%+0.8810.0%traditional_energy
3PSX99.2risk on89%+0.8710.0%traditional_energy
4XOM95.3risk on100%+0.8210.0%traditional_energy
5COP95.2transitional65%+0.8210.0%traditional_energy
6XLE94.1transitional54%+0.8110.0%traditional_energy
7CVX92.4transitional56%+0.7910.0%traditional_energy
8DVN89.6transitional82%+0.7510.0%traditional_energy
9AES88.1transitional100%+0.7310.0%solar_wind_storage
10BE80.9transitional97%+0.6410.0%nuclear_hydrogen
11NEM78.9risk on95%+0.6110.0%critical_minerals
12FCX78.3risk on56%+0.6010.0%critical_minerals
13PR74.0risk off50%+0.834.5%traditional_energy
14COPX69.6transitional98%+0.4910.0%critical_minerals
15OXY63.6risk off89%+0.714.2%traditional_energy
16CPER53.6transitional92%+0.564.7%critical_minerals
17EOG53.2risk off46%+0.741.1%traditional_energy
18CEG50.6risk on93%+0.2510.0%nuclear_hydrogen
19KMI44.2transitional79%+0.68—traditional_energy
20FANG41.3risk on98%+0.64—traditional_energy
21FCEL31.4risk off95%+0.52—nuclear_hydrogen
22ET31.0risk on99%+0.51—traditional_energy
23SLB26.8risk on99%+0.46—traditional_energy
24WMB24.7transitional81%+0.43—traditional_energy
25HAL23.6transitional99%+0.41—traditional_energy
26NXE20.8risk off70%+0.272.2%nuclear_hydrogen
27SHLS20.5risk on80%+0.38—solar_wind_storage
28SQM19.5transitional63%+0.36—critical_minerals
29VST19.2transitional76%+0.36—nuclear_hydrogen
30NEE17.9risk on99%+0.34—solar_wind_storage
31VALE17.0risk on94%+0.33—critical_minerals
32AA14.7transitional93%+0.30—critical_minerals
33BEP14.2transitional84%+0.29—solar_wind_storage
34ALB13.9risk off43%+0.29—critical_minerals
35LIT13.6risk off80%+0.29—critical_minerals
36CWEN12.0risk on85%+0.27—solar_wind_storage
37SEDG11.2risk off96%+0.26—solar_wind_storage
38FLNC10.7risk off99%+0.25—solar_wind_storage
39CCJ10.7transitional84%+0.25—nuclear_hydrogen
40FSLR10.6risk off78%+0.25—solar_wind_storage
41PLUG10.3transitional91%+0.24—nuclear_hydrogen
42DNN9.6transitional98%+0.24—nuclear_hydrogen
43REMX8.4risk off96%+0.22—critical_minerals
44BWXT8.0risk on99%+0.21—nuclear_hydrogen
45HYSR7.1risk off99%+0.20—nuclear_hydrogen
46ENPH6.5risk on99%+0.20—solar_wind_storage
47RUN5.5transitional99%+0.18—solar_wind_storage
48UUUU5.2transitional65%+0.18—nuclear_hydrogen
49LAC4.8transitional82%+0.17—critical_minerals
50UEC4.0transitional81%+0.16—nuclear_hydrogen
51ARRY3.5risk on87%+0.16—solar_wind_storage
52MP3.4risk on98%+0.16—critical_minerals
53NMG2.0risk off99%+0.14—critical_minerals
54STEM1.8transitional92%+0.14—solar_wind_storage
55OKLO0.8risk off78%+0.12—nuclear_hydrogen
56SMR0.0transitional88%+0.11—nuclear_hydrogen

Glossary & Model Reference

How the Ranking Works

Each stock receives a Composite Score (0–100) combining two independent analytical engines. Higher score = stronger combined signal. The score is relative — it ranks stocks against each other, not against an absolute threshold.

Damodaran Engine — Fundamentals

DCF valuation and relative multiples (EV/EBITDA, P/E, P/FCF) have both been built and backtested (2026-08-22 and 2026-08-27) — neither showed statistically significant predictive power on this universe. Fundamentals currently contribute 0% weight to the composite score pending a signal that actually validates; ratios are still computed and shown for reference, not because they're proven to predict returns.

Lo Adaptive Markets Engine — Signals

Hidden Markov Model regime detection, cross-sectional momentum, trend alignment, RSI, and Kelly-based position sizing. Answers: is the market currently rewarding buyers of this stock? Runs daily Mon–Fri.

Column Definitions

Composite Score

Weighted average of the Damodaran fundamental score and the Lo Adaptive signals score, normalized to 0–100. Currently 0% fundamentals / 100% signals — the fundamentals weight is gated behind a validation test (see FUNDAMENTALS_VALIDATED) that neither DCF nor relative multiples has passed yet, so despite the "composite" name this is presently a pure Lo Adaptive score. Scores are cross-sectional — a stock ranked #1 at 75 is the best in the universe today, not an absolute buy signal.

Regime  risk on transitional risk off

The current market state for this stock as detected by a Gaussian Hidden Markov Model (HMM) fitted on 2 years of daily log-returns and volume. The HMM identifies 3 latent states and labels them post-hoc by their return distribution:

  • Risk On — positive mean return state; market is rewarding buyers. Momentum strategies tend to work here.
  • Transitional — near-zero mean return state; regime is shifting or ambiguous. Reduce position sizing, wait for confirmation.
  • Risk Off — negative mean return state; sellers in control. Even strong momentum names should be sized down.

Important: Regime is per-stock, not market-wide. A stock can be risk on during a broad market selloff if it is rotating into favor (e.g. defensive energy names during equity drawdowns).

Confidence

The posterior probability that the HMM assigns to the current regime state — how certain the model is about its regime classification. A regime label with <60% confidence is unreliable; treat it as transitional regardless of the label. High score + high confidence is the strongest combined signal. High score + low confidence (e.g. REMX at 42%) warrants caution even if the label says risk on.

Momentum

A composite of three signals, weighted 50/30/20:

  • Cross-sectional momentum (50%) — rank-based z-score of 12-1 month returns across the universe. Captures which stocks are outperforming peers over the past year, skipping the most recent month to avoid short-term reversal. Based on Jegadeesh & Titman (1993).
  • Trend alignment (30%) — price vs. 50-day and 200-day moving averages. Scores 0, 0.33, 0.67, or 1.0 based on how many of: price>MA50, price>MA200, MA50>MA200 (golden cross) are true.
  • RSI normalized (20%) — 14-day Wilder RSI rescaled to [0,1] between oversold (30) and overbought (70). Not used as a contrarian signal here — higher RSI = stronger trend confirmation.

Kelly Size — Is This Relevant?

Yes — but treat it as a relative conviction signal, not a literal portfolio weight.

The Kelly Criterion (J.L. Kelly, 1956) is the mathematically optimal fraction of capital to bet on a wager with known odds and win probability, maximizing long-run geometric growth. Formula: f* = p/|loss| − q/gain

Here it is applied to stocks using:

  • Win probability — fraction of positive daily returns over the past 63 days
  • Expected gain — annualized mean return over 63 days
  • Max loss — 2× annualized volatility (2-sigma drawdown proxy)

Three practical adjustments are applied:

  • Quarter-Kelly (÷4) — full Kelly is theoretically optimal but brutal in practice; most practitioners use ¼ Kelly to reduce variance
  • Regime multiplier — risk on: 1.0×, transitional: 0.5×, risk off: 0.25×
  • 10% cap — no single name exceeds 10% of portfolio regardless of Kelly output

A Kelly of 0% means the raw Kelly formula returned zero or negative — the stock's return/risk profile doesn't justify a position at current prices even before regime adjustment. This is common for high-volatility names with inconsistent returns (UUUU, UEC, FLNC). High momentum + zero Kelly = interesting name but wait for a better entry.

Decision Framework — How to use this dashboard

The ranking is a screen, not a trade signal. Use it to narrow the universe, then apply your own fundamental research to top-ranked names.

Signal combination Interpretation
Score >65 + Risk On + Kelly >5% Strongest signal — trend, regime, and sizing all aligned
Score >65 + Risk On + Kelly = 0% High momentum, but volatility too high for Kelly to size — watch for consolidation entry
Score >55 + Transitional Regime shifting — reduce size, wait for risk on confirmation
Any score + Risk Off Avoid new positions; if held, review stop-loss levels
Score <35 Underperforming peers on momentum — consider underweighting vs. sector benchmark
Model limitations & known caveats
  • Backward-looking: The HMM is fitted on historical returns. It detects regimes in hindsight and can lag real-time regime changes by several days.
  • Fundamentals are not currently weighted in at all: DCF and relative multiples have both been built and backtested, and neither showed statistically significant predictive power on this universe (research_log.md, 2026-08-22 and 2026-08-27). The composite is presently 100% the Lo Adaptive signals score, not a blend.
  • Kelly inputs are estimates: Win probability and return estimates come from 63 days of price history — a short window. The true forward distribution is unknown.
  • No macro overlay: The model ranks stocks in isolation. A risk-on regime for an energy stock during a broad recession may still result in losses — sector dynamics and macro conditions (FRED data) are supplementary context, not yet integrated into the score.
  • Rebalancing frequency: Daily signals change frequently. The composite score is designed for weekly review cadence, not daily trading.

Damodaran (2012) Investment Valuation · Lo (2004) The Adaptive Markets Hypothesis · Kelly (1956) A New Interpretation of Information Rate · Jegadeesh & Titman (1993) Returns to Buying Winners and Selling Losers