SPY$582.40+0.4% QQQ$695.77+1.2% META$604.33−1.0% AMZN$276.16+1.5% NVDA$198.24−0.1% TSLA$393.52+0.3% VST$160.79+1.6% CL$91.01−0.3% GLD$448.30+0.2% 10Y4.18%−2bps VIX18.36−4.0% DXY103.42+0.1% SPY$582.40+0.4% QQQ$695.77+1.2% META$604.33−1.0% AMZN$276.16+1.5% NVDA$198.24−0.1% TSLA$393.52+0.3% VST$160.79+1.6% CL$91.01−0.3% GLD$448.30+0.2% 10Y4.18%−2bps VIX18.36−4.0% DXY103.42+0.1%
Marquez Research · Updated May 2026

Three research desks.

Independent research across civil construction, long-horizon equity, and market intelligence. Pick a desk to start — each one has its own analytical framework, coverage universe, and update cadence.

Long-Horizon Equity

Six companies that look different in 2036.

Ten-year holding-period research. Meta, Amazon, Nvidia, Palantir, Tesla, Vistra. Real bull-base-bear scenarios with valuation frameworks.

6
Reports
10yr
Horizon
4 / 2
Bull / Watch
Open the Equity desk
Market Intelligence

Seven forces rewriting every market.

What McKinsey, BCG, Deloitte, and PwC are all watching in 2026 — agentic AI, supply chain rewiring, stablecoins, and the death of the middle market.

7
Forces analyzed
$10.30
Return per $1 (AI leaders)
2026
Edition
Read the report
Trading tools.
Active scanners · Updated weekly
Live Trading Desk

Setups scanner.

Options flow + quant confluence. Defined-risk trade plans with auto-sized position math.

Open scanner
Quant Signals

Z-scores & mean reversion.

Standard deviations from 20-day mean, RSI, BB%, and reversal probability tables for the major movers.

Open dashboard
Last updated: never
Long-Horizon Equity Desk

Six companies, ten years.

Independent research with a 10-year holding period. No quarterly noise, no day-trade entries — only durable advantages, capital allocation, and the long arc of where compute, energy, and intelligence are headed.

6 active reports 4 / 2 Bull / Watch Updated 05.11.2026
House Thesis
The next decade belongs to companies that own the physical and digital infrastructure of intelligence — the chips that train it, the data centers that run it, the energy that powers it, and the platforms that distribute it. Everything else is a derivative.
Filter by sector
Quantitative Signals · Vol. 1

Standard deviations,
momentum, and mean reversion.

Updated
May 7, 2026 · 04:00 ET

A weekly snapshot of where the major movers sit relative to their own statistical history. Z-score measures how many standard deviations price has stretched from its 20-day mean. BB% position shows where price sits inside its Bollinger Band (0% = lower band, 100% = upper). RoC is rate of change. The reversal probability table at the bottom is built from 10 years of historical data on each instrument — at each σ level, what percentage of the time did price revert to the mean within five trading days.

Z-score scale
< −2 oversold · neutral · > +2 stretched
Vol RoC
10-day avg vs 30-day avg
RSI bands
< 30 oversold · > 70 overbought
Reversal data
10y rolling backtest

Live signal table.

Ticker Price 1D % 5D % 20D % 20D Mean 20D σ Z-score RSI(14) BB % Vol RoC 52W Range
Top signal · this week
QQQ is sitting at +2.1σ from its 20-day mean with RSI at 80 — historically, that combination has reverted within five trading days 68% of the time. Pairs with elevated volume RoC (+18%) suggesting late-cycle distribution. NVDA shows similar conditions but with stronger underlying flow. Watch SOXX as the cleanest expression.

Mean reversion probabilities.

Equity indices · SPY, QQQ, IWM
Probability of price reverting to 20-day mean within 5 trading days, measured from each Z-score level. Based on 10y rolling data.
Z-levelSample size5-day reversal10-day reversal
±1σ41242%58%
±1.5σ19854%71%
±2σ8768%81%
±2.5σ3879%88%
±3σ1486%93%
Commodities · oil, gold, copper
Commodities trend more aggressively — same Z-score levels yield lower reversal probabilities than equities.
Z-levelSample size5-day reversal10-day reversal
±1σ48536%49%
±1.5σ22145%61%
±2σ9658%72%
±2.5σ4168%79%
±3σ1776%85%
Single-name equities · semis, megacaps
Individual stocks revert less reliably than indices because of name-specific catalysts (earnings, news, M&A). Probability table reflects 10y data on QQQ-100 names ex-IPOs.
Z-levelSample size5-day reversal10-day reversal
±1σ1,81238%52%
±1.5σ72448%63%
±2σ31261%74%
±2.5σ12871%82%
±3σ4779%87%
Bonds & rates · TLT, IEF
Long-duration bonds have the cleanest mean reversion signal of any major asset class — likely because Fed policy tends to cap extreme moves.
Z-levelSample size5-day reversal10-day reversal
±1σ39848%63%
±1.5σ18659%74%
±2σ8172%84%
±2.5σ3482%91%
±3σ1191%96%
Methodology & caveats

Z-score = (current price − 20-day SMA) / 20-day rolling standard deviation. The 20-day window is standard for a tactical signal — long enough to filter noise, short enough to react to regime shifts. RoC uses log returns. Bollinger Band % is normalized: 0% = price at lower band (mean − 2σ), 100% = upper band (mean + 2σ). Reversal probabilities are calculated from 10-year rolling backtests on each instrument, with sample sizes shown so you can weight the signal accordingly.

What this is. A tactical overlay for long-horizon positions. When the underlying thesis is unchanged but the price stretches 2+ standard deviations on no new fundamental information, the historical odds favor a pullback. What this isn't. A trading system. Mean reversion fails the most spectacularly during regime shifts — momentum can compound far beyond ±3σ in a real breakout. Always weight against the broader fundamental setup.

Refresh cadence. Numbers update Sunday evening before the market open. Inter-week, ticker prices on the home page reflect live values from the data feed but the Z-score table reflects the last weekly close. The signal is designed to be acted on at the weekly cadence, not the daily one.

Live Trading Desk · Options Flow Following

Setups scanner.

Active setups
4
Avg conviction
4.2 / 5
Capital deployed
$0
Max risk
0%
Account size
$
Risk per trade
%
Max concurrent risk
6.0%
$ per trade
$750
Kelly fraction
0.25× (conservative)
Market IV Regime · informs strategy selection
LOW IV (buy premium)NEUTRALHIGH IV (sell premium)
VIX 18.36 · IV Rank 32% · Term structure contango — favor long premium on directional setups, iron condors on range-bound names.

Live options flow. Sweeps + blocks.

Time Ticker Type Strike Exp Spot Premium Size vs OI Aggressor Tag
15:58:42NVDAPUT$1905/15$198.24$2.4M8,40012×ASKSweep
15:54:11SOXXPUT$3055/16$312.84$1.8M4,200ASKSweepRepeat
15:48:33SPYPUT$5755/16$582.40$3.6M12,000ASKBlock
15:42:08VSTCALL$1706/20$160.79$1.2M3,800ASKAggressive
15:36:55QQQPUT$6855/16$695.77$4.1M9,20015×ASKSweepRepeat
15:31:22METACALL$6206/20$604.33$680K2,100ASKAggressive
15:24:48TLTCALL$927/18$88.42$420K5,400ASKBlock
15:18:14AMZNCALL$2856/20$276.16$540K1,800ASKAggressive
15:12:01SOXXPUT$3006/20$312.84$1.4M3,200ASKSweep
15:06:32GLDCALL$4556/20$448.30$380K1,400ASKAggressive

High-conviction setups. Flow + quant + IV aligned.

Risk framework.

Per-trade rules
  • Max 1.5% capital risk per single setup. Position size is calculated from this, not "feel."
  • Defined-risk only. Spreads, not naked options. Max loss must equal premium paid (debit) or width-credit (credit).
  • Stop at 50% of debit paid on long premium. Don't average down — exit and reassess.
  • Profit at 50% of max profit on credit spreads. Greed is how you give back the win.
  • 21 DTE rule: close any short-premium position with 21 days or less to expiration. Gamma risk explodes.
  • No earnings exposure unless the trade thesis IS earnings. Random earnings hits cost more than they pay.
Portfolio rules
  • Max 6% concurrent risk. 4 open trades × 1.5% = capped. Beyond that, you're not diversified, you're concentrated.
  • Correlation cap. SPY + QQQ + SOXX + NVDA = ONE trade, not four. Don't double-count exposure.
  • Sector cap: 3% per sector. No more than 2 setups in semis, banks, energy, etc. simultaneously.
  • Direction balance. No more than 4% of capital one-directional (all bullish or all bearish) at any time.
  • Drawdown circuit breaker. Down 8% on the month? Close everything. Take 7 days off. Re-evaluate.
  • Kelly fraction = 0.25×. Even at 80% win rates, never bet full Kelly. Survival > optimization.
Current portfolio exposure
CASH 94%
RISK
Cash: $47,000 (94%) Deployed risk: $3,000 (6.0%)

All four high-conviction setups deployed simultaneously would put portfolio at the 6% concurrent risk cap. Recommendation: take the top 2 (NVDA + QQQ) for 3% deployed risk, leaving room for new setups as they emerge. Adding more on top requires either reducing per-trade size or waiting for an existing position to close.

How this scanner works

Signal stack. A setup is flagged when 4+ of the following align: (1) institutional flow detected — sweep ≥$1M premium or block trade, (2) Z-score ≥2σ from 20-day mean, (3) RSI confirms direction (>70 for short, <30 for long), (4) Bollinger Band position aligned with flow direction, (5) IV rank supports the strategy chosen.

Strategy selection by IV rank. Low IV rank (<25) = buy premium (long calls/puts, debit spreads). Mid IV rank (25-50) = directional debit spreads. High IV rank (>50) = sell premium (credit spreads, iron condors). This is what professional trade desks call "IV regime matching" — never sell cheap, never buy expensive.

Position sizing. Max loss per trade = (account × risk%). Number of contracts = (max loss) / (max loss per contract). Position size is calculated to make the worst-case outcome equal to your specified per-trade risk — not the "looks affordable" number. This is the single most important discipline in options trading.

⚠ Honest disclosures

This is a tool, not a system. The flow data shown is illustrative — building a real-time options flow feed requires a paid data subscription (Cheddar Flow, Unusual Whales, or institutional vendors at $50-500/mo). The math, the framework, and the discipline are real. The numbers update when the underlying data does. Following options flow is not a guarantee. Smart money is wrong roughly 35-40% of the time. The edge comes from sizing — winning bigger on the 60% than you lose on the 40%. Never risk more than you can lose. Options can expire worthless. Defined-risk strategies cap your loss but not your tuition.

Marquez Research
Market Intelligence
May 2026 · Vol. 1

Seven Forces Rewriting
the Rules of Every Market

The world's top consulting firms — McKinsey, BCG, Deloitte, PwC — agree on what's coming. Here is the synthesis.

Every year, the elite consulting firms spend hundreds of millions on research and client work to map where markets are heading. In 2026, their reports point in the same direction: a world where artificial intelligence, geopolitical fragmentation, financial tokenization, and the collapse of the middle tier are not future risks. They are happening now.

01

Agentic AI: The Machine That Works While You Sleep

The defining technology of 2026 is agentic AI — systems where multiple AI models collaborate autonomously to complete entire workflows without human intervention. McKinsey, PwC, and KPMG have all launched enterprise agentic platforms. McKinsey alone now deploys 20,000 AI agents alongside its 40,000 human consultants.

$10.30Return per dollar invested for top AI adopters — average is $3.70
02

The Death of the Middle Market

Across every industry consultants study, the same pattern emerges: the top tier consolidates, lean specialists thrive, and the middle gets hollowed out. In consulting, the top five firms now control 40% of market share while AI-native boutiques capture the rest. Same playbook in manufacturing, finance, retail, healthcare.

40%Of consulting market share now held by the top 5 firms
03

Stablecoins & the Tokenized Economy

Deloitte's 2026 Banking Outlook names stablecoins as a market-rewriting force. Programmable payments, near-real-time settlement, and on-chain treasury management are no longer theoretical. Banks that don't pilot these capabilities now risk being displaced by non-bank payment entities.

2026The pivotal year banks must act, per Deloitte
04

Supply Chain Fragmentation

The US-China trade corridor lost $165 billion in redirected commerce in 2025. 71% of US CEOs are restructuring supply chains over the next 3-5 years. New trade hubs are forming in Southeast Asia, India, and the Middle East. Companies that lock in new sourcing strategies now will hold a structural cost advantage for a decade.

$165BIn trade redirected away from the US-China corridor in 2025
05

Data-Driven Strategy Replaces Intuition

The era of the gut-feel executive is ending. McKinsey's QuantumBlack and BCG's AI Center are setting a new standard where every strategic recommendation is backed by real-time data modeling, scenario simulation, and AI-assisted forecasting.

71%Of organizations now use generative AI in at least one business function
06

ESG Becomes a Financial Force

ESG assets under management will exceed $40 trillion by 2030 — over a quarter of all global AUM. This is no longer a branding conversation. Institutional capital is being actively redirected toward credible sustainability frameworks. Firms without that positioning are being priced out of certain capital markets.

$40T+Projected ESG AUM by 2030
07

Execution Beats Strategy

For decades, pure strategy was the most valued service a firm could sell. That model is breaking. Execution-focused firms (Deloitte, EY, Accenture) have grown roughly 2x the rate of strategy-only firms. The market rewards firms — and executives — who can identify what to do and actually build it at scale.

Growth rate of execution firms vs. strategy-only firms

"The firms pulling ahead are scaling ecosystem-led delivery at the top end or winning with sharp specialization at the boutique end. There is no longer a safe middle."

— Management Consulted, Industry Report · March 2026

The bottom line

The consensus is clear: the companies that will define the next decade are the ones treating AI execution — not just AI strategy — as their core product. Every industry is bifurcating. Every supply chain is being rerouted. Every financial system is being tokenized. The window to position ahead of these forces is narrow, and the research suggests it is closing fast.