Rank | Ticker | Consecutive Days Below 10-Day SMA |
---|---|---|
1 | QUBT π | 29 |
2 | AEO π | 27 |
3 | KNX | 25 |
4 | SYF | 25 |
5 | TGT | 25 |
6 | SQ | 22 |
7 | CRM | 21 |
8 | AMZN | 20 |
9 | AMZU | 20 |
10 | CCL | 20 |
11 | AAL | 19 |
12 | DAL | 19 |
13 | DJT π | 19 |
14 | AI π | 18 |
15 | BTDR π | 18 |
16 | IONQ π | 18 |
17 | RCAT π | 18 |
18 | RKLB π | 18 |
19 | WULF π | 18 |
20 | TSM | 17 |
21 | VRT | 17 |
22 | ARM π | 15 |
23 | RETL | 15 |
24 | SERV π | 15 |
25 | AVGO | 14 |
26 | META | 14 |
27 | NU | 14 |
28 | OKLO π | 14 |
29 | RIOT | 14 |
30 | BBAI π | 13 |
31 | GLW | 13 |
32 | IWM | 13 |
33 | NET | 13 |
34 | PLTR π | 13 |
35 | PLTU π | 13 |
36 | RBRK | 13 |
37 | SNAP | 13 |
38 | TNA | 13 |
39 | AFRM | 12 |
40 | BA | 12 |
41 | BB | 12 |
42 | C | 12 |
43 | CRWD | 12 |
44 | CVNA | 12 |
45 | ET | 12 |
46 | FFTY | 12 |
47 | GS | 12 |
48 | HOOD | 12 |
49 | IREN π | 12 |
50 | JPM | 12 |
51 | MRVL π | 12 |
52 | ORCL π | 12 |
53 | PTEN | 12 |
54 | PTON π | 12 |
55 | SHOP π | 12 |
56 | TSLL π | 12 |
57 | UAL π | 12 |
58 | VST | 12 |
59 | WMT | 12 |
60 | AA | 11 |
61 | ACHR π | 11 |
62 | AMD | 11 |
63 | AMDL π | 11 |
64 | APA | 11 |
65 | APP | 11 |
66 | BP | 11 |
67 | CLF π | 11 |
68 | COF | 11 |
69 | DKNG | 11 |
70 | EVGO π | 11 |
71 | GUSH | 11 |
72 | HPE | 11 |
73 | LCID π | 11 |
74 | LUNR π | 11 |
75 | MDB π | 11 |
76 | NBIS π | 11 |
77 | NVDA | 11 |
78 | NVDL π | 11 |
79 | PANW | 11 |
80 | PINS | 11 |
81 | PYPL | 11 |
82 | QQQ | 11 |
83 | RIVN | 11 |
84 | SOFI | 11 |
85 | SPY | 11 |
86 | TQQQ | 11 |
87 | TSLA | 11 |
88 | UPST π | 11 |
89 | AMC π | 10 |
90 | CART | 10 |
91 | DELL | 10 |
92 | GME π | 10 |
93 | MU | 10 |
94 | QS π | 10 |
95 | SOXL π | 10 |
96 | APLD π | 9 |
97 | DVN | 9 |
98 | INTC π | 9 |
99 | OXY | 9 |
100 | QBTS π | 9 |
101 | ROKU | 9 |
102 | RUN π | 9 |
103 | UTSL | 9 |
104 | AAPL | 8 |
105 | AAPU | 8 |
106 | DOW | 8 |
107 | PBR | 8 |
108 | BBWI | 7 |
109 | NTAP | 7 |
110 | SMCI π | 7 |
A 10βday Simple Moving Average (SMA) is the unweighted average of a securityβs closing prices over the most recent ten trading days. To calculate it, you sum those 10 closing prices and divide by ten. As each new trading day closes, the oldest price drops off and the newest closes replaces it, creating a rolling average line - this smoothed curve highlights shortβterm trends while reducing daily noise. Traders use the 10βday SMA for shortβterm trend analysis and trade timing. When prices stay consistently above the 10βday SMA, it often signals upward momentum; when below, it suggests a shortβterm downtrend. Common strategies involve watching price crossovers or combining the 10βday SMA with longer averages - like the 50βday - for βfaster versus slowerβ confirmation. This indicator is also used as dynamic support or resistance: prices often bounce around the SMA line. For traders with holding periods of only a few days to two weeks, the 10βday SMA delivers relevant insight into recent trend shifts, market noise, and momentum. However, the 10βday SMA is a lagging indicator - it reflects past prices rather than predicting future moves. During sideways or choppy markets, it may yield false signals. Therefore, many traders pair it with momentum indicators like the RSI or Bollinger Bands and follow disciplined risk management with stopβloss levels or confirmation rules.