MARKET COMPOSITE
Chinese Tech Stocks19-30-2024 20:30:00 PM
Price
$85.85
-1.20%
The list of companies include CALX-Calix Inc, CBAT-CBAK Energy Technology Inc, LKCO-Luokung Technology Corp, PBTS-Powerbridge Technologies Co Ltd, SEED-Origin Agritech Ltd., TAOP-Taoping Inc., TKAT-Takung Art Co Ltd, WAFU-Wah Fu Education Group Ltd
* Latest intraday update before market close @ 19:45:45 PM 04/19/2024
Summary
:
Average return is down -1.4%
Median return is down -0.8%
11 out of 42 stocks are up (limited to those with intraday pricing feeds).
Top Movers
:
CAN -16.8%LI -10.0%NIO -5.4%NIU -4.2%XPEV -4.1%IQ -3.5%BZUN -3.2%FENG -2.9%WB -2.6%SY -2.5%HUYA -2.4%

Aggregated price index with volume information

Summary:

  • Chinese Tech stocks down 1.2% on average while median return down 0.5% in a day
  • Chinese Tech stocks down 4.9% on average while median return down 3.1% in a week
  • Chinese Tech stocks down 6.9% on average while median return down 8.5% in a month
  • When average return is significantly different from median return, this implies an asymmetry - composite return is driven by some outliners.

Aggregated price index (close) is based on equal weighted constituencies returns. Average short volume and average total volumes are averaged across all volume data among constituencies.

Related Stocks
Ticker
1d
7d
30d
PE Ratio
PE/G
P/B (mrq)
P/S (ttm)
Earning Growth
MarketCap
Short %
Held By Institutions %
RSI
Price Pattern
Resist Support
Days Since Channel Change
Channel Slope (daily rate %)
MOGU5.9%
-6.1%
4.7%
0.120.3716.3M24%52\Above resistance144-0.0%
CMCM5.0%
-23.2%
44.5%
-11.180.080.2634M13%53-\/Above resistance560.6%
SEED4.1%
0.0%
0.0%
2.5920.8M4%3%\/591.8%
SECO2.2%
18.6%
-2.9%
0.080.03-64%2.4M20%53
YI2.0%
-7.3%
-33.3%
3.090.0849M15%38-\51-0.4%
QD1.3%
-5.8%
-9.2%
5.37-5.10.060.21368M32%38\/1260.2%
DADA1.1%
-2.6%
-24.4%
4.581.13649.8M20%39/\-\194-0.4%
NTES1.1%
1.5%
-12.9%
16.492.120.840.9725%60.3B39%39/-\-/At support2200.1%
PT0.9%
-0.9%
0.9%
0.1115.5M1%45/-102-0.0%
LX0.6%
-8.0%
-24.3%
18.990.380.19209.4M38%37\/\220-0.1%
UXIN0.6%
-11.2%
-21.3%
-0.47-3.79774.9M38%35\109-1.0%
SOHU0.5%
-4.0%
10.5%
-0.121.870.92363.2M46%55/\At resistance657-0.1%
BABA0.3%
-3.1%
-6.9%
12.8641.610.610.80177.2B36%37/\/\220-0.1%
JD0.2%
0.5%
-9.3%
11.9881.580.590.14237%40.2B42%46-\146-0.2%
ATHM0.1%
-3.8%
-7.3%
73.010.420.904%703.4M55%35/\-\220-0.0%
VIPS0.1%
-6.7%
-14.7%
8.7641.710.420.12126%7B58%31/\/2200.1%
XNET0.0%
-2.6%
-2.7%
1.101.7295.1M15%44\284-0.1%
PDD-0.2%
-1.7%
-14.1%
25.6837.852.502.09157.9B29%39/-2200.3%
KC-0.4%
-1.9%
-29.1%
1.10669.7M31%40/\/-198-0.3%
YRD-0.4%
-6.2%
-11.0%
0.120.11843%428M3%47/-/750.9%
* P/E and MarketCap are refreshed daily using IEX Cloud service. P/B, P/S, PEG, growth, short%, HelbyInstitute are refreshed weekly using Yahoo feeds. For latest stock stats please visit Yahoo Finance.
* Price Patter: / is upward trend, \ is downward trend, - is sideway. Click on the ticker to go to stock page to see Bayesian Trend model plot of the time series.
* Channel and change points are derived from Bayesian Trend model, where the channel slope is the growth rate while change points are those the model partition the time series.

Related ETFs (click on ticker for stock detail page)

Detail Performance Summary
  • 1M winners are : Winners for past month are $CMCM 44.5%, $NIU 12.3%, $SY 11.0%, $SOHU 10.5%, $FENG 9.1%
  • 1M losers are : Losers for past month are $NIO -25.5%, $XPEV -27.1%, $KC -29.1%, $YI -33.3%, $CAN -53.0%
  • 1W winners are : Winners for past week are $MOMO 5.5%, $WB 3.5%, $NTES 1.5%, $FXI 0.7%, $JD 0.5%
  • 1W losers are : Losers for past week are $LI -10.3%, $FENG -11.8%, $NIU -12.7%, $CMCM -23.2%, $CAN -37.3%
Pick two stocks to compare:

Correlation Analysis

Index correlation analysis

Correlation for the past month is 25.5%, for the past 3 months is 26.4%

In the past month for a 5 days rolling window, the highest corrrelation is 41.4%, the lowest correlation is 5.6%, the latest correlation is 19.4%

When a correlation deviated from the normal level and goes lower or even negative, it indicates some of stocks have deviated from the normal direction of the group. The deviation could reverse if long term level of correlation was at a higher level. It creates trading opportunities and deserves study whether the deviation is idiosyncratic or systematic.

Among pairwise correlation, the highest correlation is 99.8% between CWEB and KWEB

The lowest correlation is -44.7% between MOGU and MOMO

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