XAnalytics · Backtest audit File @ren_stocks · 23 Jun 2026

@ren_stocks · 128 verified calls backtested

Marginal

@ren_stocks's calls have beaten their sector by 5.2% per month, winning 55% of the time.

+5.2%
Avg. return vs its sector
per call · over the timeframe it called (or 1 month)
-0.4%
1 day
+7.7%
1 month
3 months
the same calls held a fixed 1 day / 1 month / 3 months
55%
Calls that beat the market
based on 42 deduplicated bets
55% beat their sector 45% didn't

A slight edge — promising, but not decisive.

What “return vs sector” means
Each call's stock vs its own sector — beating the sector, not just going up, is the fair test of skill. Averaged across 42 deduplicated bets. Calls that named their own timeframe are judged over that window (as a per-month rate); the rest over 1 month.
Not yet conclusive

Across 42 bets, @ren_stocks's average call beat its sector by 5.2% per month, each bet judged on its author's own timeframe (1 month when unstated, or as far into it as the data reaches) — t = 1.6, but not decisive yet.

could be luckt = 2almost certain

t = 1.6 — the strength of the evidence. Above 2, there's under a 5% chance it's luck.

How the t-value works

Each call is one bet, scored by how much it beat its own sector (fairer than the whole market). The t-value is the average beat divided by its uncertainty:

t = x̄ ⁄ ( s ⁄ √M ) x̄ = avg beat · s = how much the bets vary · M = number of bets

Same-week, same-sector calls ride one move, so they prove less than fully independent wins — the 42 bets count as 42 effective ones. That's why the honest t is 1.6, not the raw 1.3. Full breakdown on the analysis page.

Performance over time

Aftervs sectorvs S&P 500Hit rateCalls
1 day -0.4% -0.6% 43% 68
1 month +7.7% +14.6% 57% 42

“vs sector” compares each call to the stock's own industry — the fairest test of skill.

What drives the signal

Does conviction matter?

High conviction71 calls · 52% hit
+6.7%
Low conviction6 calls · 67% hit
+1.0%

Return by post type

Prediction13 calls · 54% hit
+8.1%
Analysis34 calls · 56% hit
+6.6%
Position Disclosure29 calls · 48% hit
+4.1%

Long vs short

Long76 calls · 54% hit
+6.5%
Short1 calls · 0% hit
-12.6%

The evidence — best & worst calls

Biggest wins (after 1 month)

Exhibit A · 2026-05-04 POET
“저는 안 팔았어요. 저한테는 기술이 너무 좋아서 포기할 수가 없어요. MRVL은 단 하나의 고객사일 뿐이고, 제품이 정말 그들이 말하는 것만큼 좋다면 앞으로 더 많은 고객사가 생길 수밖에 없을 거예요”
Long · high conviction · View on X ↗
Full post
@Sofigoodboy 팔았어요? 저는 안 팔았어요. 저한테는 기술이 너무 좋아서 포기할 수가 없어요. MRVL은 단 하나의 고객사일 뿐이고, 제품이 정말 그들이 말하는 것만큼 좋다면 앞으로 더 많은 고객사가 생길 수밖에 없을 거예요.
+69.6%vs sector
Exhibit B · 2026-05-04 MU
“$MU since November”
Long · high conviction · View on X ↗
Full post
@babyfolio My port is 30% memory $SNDK since October $MU since November $SK Hynix since January One has been better than the others --- @babyfolio I just follow the money, SK Square is too good. I’ll try to lock in some other SK Stock. So many to choose from.
+59.8%vs sector
Exhibit C · 2026-05-03 NBIS
“Bullish for $NBIS”
Long · high conviction · View on X ↗
Full post
$NBIS JPMorgan’s observability expert flagged OpenAI moving logs to ClickHouse (28% owned by $NBIS) as a notable defection from Datadog at hyperscale. OpenAI defects from Datadog to ClickHouse because log ingestion + retention at scale is too expensive on third-party platforms. Nebius rips the Bullish for $NBIS
+49.9%vs sector

Biggest misses (after 1 month)

Exhibit D · 2026-05-13 P4O
“It only gets better from here. … Long $P4O”
Long · high conviction · View on X ↗
Full post
$P4O is finally getting the recognition it deserves, and it’s trading at ATH, after an unsustained peak back in March. It only gets better from here. Management own guidance says: series ramps ups from 2027 onwards are expected to result in a further significant increase in group revenue. Long $P4O
-35.8%vs sector
Exhibit E · 2026-05-05 3105.TWO
Long Win Semi (3105.TWO) on CPO/InP bottleneck exposure, 30x EPS growth, and market not yet fully pricing it in. summary
Long · high conviction · View on X ↗
Full post
Win Semi (3105.TWO) is one of the easiest trades you can do this year. Embedded in the CPO buildout alongside $SIVE. Sits on the foundry side of the III-V/InP bottleneck, supplying high-power InP laser arrays for CPO, LiDAR, and sensing. Then the earnings hit. EPS up 30x YoY. That’s 3000% growth. Not something you see every quarter. Revenue +28% YoY. Q2 guidance up 14-16% QoQ. The market hasn’t fully priced it in yet. ‘Only up 200% YTD.’ Classic sleeper build. Set it, sleep well, let it compound. I’m long Win Semi --- Win Semi is available in IBKR as 3105 on TPEX https://t.co/5kVFUnpFJV
-29.2%vs sector
Exhibit F · 2026-05-08 MXL
“The re-rate is real. Bullish.”
Long · high conviction · View on X ↗
Full post
$MXL is up 415% in one month and 20% today. The market is re-pricing the scale-up play. Every optical transceiver in every AI datacenter – every 800G module connecting GPU to GPU, rack to rack, building to building – needs a DSP. A Digital Signal Processor. It’s the chip that takes the raw optical signal and makes it usable. Without it, the transceiver doesn’t work. MaxLinear has shipped millions of units of their Keystone DSP platform, now in production at multiple major hyperscalers across the US and Asia supporting 400G and 800G deployments. Today, about 30% of the optical transceiver TAM is scale-up and 70% is scale-out. MaxLinear was mostly a scale-out play. Now they’re both. Annapurna – the 1.6T AEC and 3.2T onboard electrical retimer platform for scale-up applications. Foundational to the next wave of data center optical architectures including LPO, LRO, AECs, XPO, and co-packaged optics. Only 3 companies make DSPs for 1.6T optical interconnects: $MRVL, $AVGO, and $MXL. The first two are $50B+ giants. MXL just crossed $2B market cap. When $AAOI announced they’re ramping 800G to 550K units per month and 1.6T to 380K units per month by end of 2027 – every one of those modules needs a DSP. MaxLinear is one of three companies that can supply it. The market is paying a premium for scale-up exposure. MXL just proved it has it. The re-rate is real. Bullish.
-26.2%vs sector

Their strongest setups — best combination at each horizon

  • 1 day long position disclosures +1.1% vs -0.4% overall · 29 bets
  • 1 month long predictions +11.6% vs +7.7% overall · 3 bets

Step behind the counter — every call, every chart, every time horizon. Filter by conviction or direction and chart any single trade.

Open the data room →
THE RECEIPTS
@ren_stocks · audited 23 Jun 2026

calls found128
independent bets42
beat the market55%
avg edge / month+5.2%
best callPOET +69.6%
worst callP4O -35.8%

VERDICT: MARGINAL
SCORE 8/10

Watch out for
their long predictions · +11.6% after 1 month

getxanalysis.net · run the receipts on anyone
Share the receipts on X ↗ Download all calls (CSV) ↓

Help shape XAnalytics

Was this report useful?

How we measured this · download the raw data

We pull @ren_stocks's posts, use AI to extract each call (ticker, direction, conviction), and backtest it against real prices. A call wins only if it beat its own sector over the month after — not just if the stock rose. Headline numbers use deduplicated bets.

Download the full backtest data (JSONL)

Backtested results are computed from historical price data and do not predict future performance. Every signal here is extracted automatically from public posts and may misread intent, sarcasm, or context. This is not investment advice — verify everything independently before acting on it.