Brad Gerstner
Cross-pod book · Gerstner

Brad on every pod, one portfolio.

15 All-In appearances + 58 BG2 episodes, deduped to 59 unique calls over ~4 years. The unified book runs from his first INITIATE on All-In to his most recent BG2 release. Following him on one pod only captures part of his thesis arc; combining them is the full picture.

Beat SPY by
+11.7pp
cross-pod · default engine
Brad's return
+82%
SPY same window: +71%
$100K became
$182K
vs SPY $171K
Active window
2022-03 →
through 2026-06-25
Why combining matters
 
All-In only
2022-03 → 2026-05
Brad: +86%
SPY: +73%
+13.2pp
15 calls · BALANCED preset
BG2 only
2024-02 → 2025-10
Brad: +62%
SPY: +38%
+24.0pp
58 calls · Let It Ride
Cross-pod
2022-03 → 2026-05
Brad: +152%
SPY: +73%
+11.7pp
59 calls combined
Wait — 13 + 24 ≠ 79. How?

These aren't additive. They're three different portfolios with three different windows + deployment levels. The pp gap is just Brad's return minus SPY's same-window return for each book.

  • All-In only: 15 calls scattered across 4 years. His $100K bucket sits mostly idle in SPY between INITIATEs, so the portfolio tracks SPY closely. Brad returns +86%, SPY returns +73%, gap = +13pp.
  • BG2 only: 58 calls but a shorter 21-month window. SPY only ran +38% in that period (no COVID-recovery tailwind). Brad +62%, gap = +24pp.
  • Cross-pod: 71 deduped calls compressed into the longer 4-year window. Now the $100K bucket is actively rotated into Brad's actual picks (AI compounders NVDA/META/TSLA) most of the time, not just hanging out in SPY. Brad returns +152% (vs +86% solo), SPY benchmark still +73%, gap = +79pp.

The cross-pod book isn't the sum of two outperformances. It's a fundamentally different portfolio with more deployment, more of his strongest conviction calls, compounding over more time.

Cross-pod book under each methodology

Defaults to BALANCED — the same published default every book on this site runs. Swap presets to see how Brad's unified book reacts to different harvest/stop rules. Same caveat as BG2: his long-runway compounders punish aggressive trim, so Let It Ride and Concentrated both beat the default here (at the cost of variance).

Methodology

Data-driven default. 18mo hold, -10% stop, gain-harvest +50/+100, time-decay last 9mo.

Beat SPY by
+11.7pp
Cross-pod (All-In + BG2) · selected methodology
Net P&L
+$12K
vs SPY · $100K starting
Host return
+82%
SPY in same window: +71%
History
2020 →
updated 2026-06-25
Methodology shape

Data-optimal default: moderate stop, medium hold, stepped gain harvest.

The cohort numbers above are the result of running the engine with this preset's exact parameters (stop loss, hold window, gain harvest schedule, conviction floor, portfolio mode). The recipe itself isn't published. Subscribers can see the full parameter readout and replicate the methodology end-to-end.

Cross-Pod Portfolio vs SPY 1064 trading days · raw engine book · Brad's combined All-In + BG2

Daily walk-forward · matched-pairs SPY mirror · deduped to one position per (ticker, week)

Host portfolio$NaNSPY mirror$NaN$NaN (NaN%)
$NaN$NaN$NaN$NaN$NaN

Current Cross-Pod Book 3 open positions · 82% return on $100K · BALANCED book

SPY: $9,403 (5.2%)GOOGL: $8,378 (4.6%)NVDA: $2,986 (1.6%)Cash: $161,580 (88.6%)TOTAL$182,347
Top Holdings · 4 slices
SPY$9,4035.2%
GOOGL$8,3784.6%
NVDA$2,9861.6%
Cash$161,58088.6%
Sample INITIATEs (audit trail)
Date
Ticker
cs
Pod / context
Direction
2022-03-26
SNOW
69
All-In: E73: Late-stage VC markdowns and mistakes, market strategy,
bull
2023-06-16
GOOGL
65
All-In: E133: Market melt-up, IPO update, AI startups overheat, Redd
bull
2024-02-22
AAPL
57
BG2: NVDA, Chips, AI Compute Build Out, Impact of AI on Big Tech,
bull
2024-03-07
TSLA
71
BG2: Tesla FSD 12, Imitation Learning, Open vs Closed AI, Delawar
bull
2024-11-21
TSLA
68
BG2: Ep20. AI Scaling Laws, DOGE, FSD 13, Trump Markets
bull
2025-04-04
SPX
52
BG2: Liberation Day, Tariffs, US v China Open Source, OpenAI Fund
bull
2025-05-22
SPX
68
BG2: AI, Middle East, China, Tariffs, Recon Bill, Invest America
bull
2026-05-08
TSLA
68
All-In: Elon's Anthropic Deal, The Next AI Monopoly?, "FDA for AI" P
bull
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