AI Research PLTRPLTR_earnings

PLTR daily-return tails over the last ~3 years: upside melt-ups vs downside crashes

PLTR’s largest single-day shocks over the past roughly three years have tended to be melt-ups, not crashes. Measuring close-to-close returns across 751 trading days, the return series shows a positive Fisher-Pearson skew of about +0.42; the biggest up day was +24.51% while the largest down day was −15.08%. That tilt shows up in the extremes: a majority of the largest absolute moves and a slight edge in |return| ≥ 5% days are on the upside.

The dataset and methods are straightforward — resampled minute bars to daily closes, 36-month trailing returns, and tail checks using skewness, 1st/99th percentiles and a top-10 up vs top-10 down comparison (with earnings days flagged). The edge is real but modest: a few outsized events, including earnings-linked moves, do a lot of the work. Full numbers, charts and the head-to-head breakdown follow below.

The research question

For PLTR over the past ~3 years, does the 'stocks take the stairs up and the elevator down' cliché actually hold — are its largest single-day moves skewed to the downside, or does this momentum darling deliver its biggest lurches to the UPSIDE on breakouts and earnings? Thesis: PLTR's daily-return distribution is positively skewed with its fattest tail pointing up, so its biggest one-day shocks have been melt-ups rather than crashes, flipping the folk wisdom on its head.

How this was measured

Resampled PLTR minute bars to daily closes and computed close-to-close returns over the trailing 36 months (bounded by the available data range). Assessed tail asymmetry via Fisher-Pearson skewness, extreme quantiles (1st/99th percentiles), and a head-to-head comparison of the top-10 positive vs top-10 negative one-day moves by magnitude. Ranked the largest absolute daily moves and flagged whether each fell on the first trading day on/after an earnings reported_date (earnings often catalyze outsized moves).

The key numbers

Trading days analyzed
751
2023-06-30 to 2026-06-30
Mean daily return
0.3531%
Median daily return
0.3472%
Daily return std
4.0729%
Skewness (Fisher-Pearson)
0.420
Largest up day
24.5109%
Date: 2025-02-03
Largest down day
-15.0790%
Date: 2025-03-10
99th percentile return
11.1765%
1st percentile return
-10.0995%
Share of top-20 absolute moves that were UP
55.00%
N=20 events
Mean of top-10 UP moves
14.8813%
N=10
Mean magnitude of top-10 DOWN moves
11.9199%
N=10
Top-10 tail edge (UP − |DOWN|)
2.9614%
Days with |return| ≥ 5%
124
Share UP among |return| ≥ 5% days
58.06%
Threshold=5%

Reading the numbers

Across 751 trading days PLTR shows a small positive bias and modest positive skew (skewness ≈0.420). Its single biggest day was a +24.51% up move versus a largest down day of -15.08%, and 55% of the top-20 absolute moves were upward.

The charts

PLTR daily returns (trailing ~36 months)
What this chart says

The histogram piles most daily returns close to zero with a slight tilt to the right — the mean daily return is about 0.35% and the median is about 0.347%. Look at the center cluster (many small moves) and then the longer right tail stretching to the max near +24.51% vs the left extreme at -15.08%; given a daily std of ~4.07%, those extremes are much larger than a typical day. In plain terms, routine days are small, but the distribution has a fatter positive tail, consistent with more extreme up days than down days.

Top 10 one-day move magnitudes — UP vs DOWN tails
What this chart says

This bar chart lines up the top-10 absolute moves and shows the UP bars exceed the DOWN bars at every rank: the largest up is 24.51% versus the largest down at 15.08%, and at ranks 2–10 the upside magnitudes (e.g., 21.48%, 16.54%, 14.02%) are consistently higher than their downside counterparts. The mean of the top-10 UP moves is about 14.88% versus about 11.92% for the top-10 DOWN moves, so the biggest shocks have been larger on the upside. That pattern directly supports flipping the 'stairs up, elevator down' cliché for this sample period: PLTR's biggest one-day lurches have tended to be melt-ups, not crashes.

Top 15 absolute one-day moves (earnings-flagged)

datereturndirectionabs_rankearnings_day
2025-02-030.2451Up1Yes
2025-04-090.2148Up2No
2023-11-020.1654Up3Yes
2025-03-10-0.1508Down4No
2025-02-19-0.1491Down5No
2024-08-080.1402Up6No
2024-02-050.1375Up7Yes
2023-07-280.135Up8No
2025-04-04-0.1344Down9No
2025-02-24-0.1243Down10No
2024-11-040.1236Up11Yes
2025-02-060.1185Up12No
2023-08-24-0.1176Down13No
2025-08-19-0.1132Down14No
2024-02-060.105Up15No

The takeaway

Yes — over the trailing ~36 months PLTR's biggest single-day moves lean to the upside. The return series shows a positive skew of about +0.42, the largest up day was +24.51% (2025-02-03) while the largest down day was -15.08% (2025-03-10). Looking at extremes, 55% of the top-20 absolute moves were up, the mean of the top-10 up days was 14.88% versus 11.92% for the top-10 down days (a tail-edge of +2.96%), and of 124 days with |return| ≥ 5% about 58% closed higher. This is a real, modest tilt rather than a slam-dunk: with 751 trading days the signal is suggestive but narrow, and a few outsized events (including earnings-linked moves such as 2025-02-03) do a lot of the heavy lifting. Practical takeaway: don’t assume PLTR’s shocks are mainly crashes — over this window melt-ups dominate slightly, but the margin is small and sensitive to a handful of extreme days.

The fine print