Aggregated price index
Aggregated price index with volume information
- IoT stocks up 1.5% on average while median return up 0.0% in a day
- IoT stocks up 2.0% on average while median return up 0.8% in a week
- IoT stocks down 8.0% on average while median return down 4.6% 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.
Click on + to show price series and click on ticker for stock detail page
* 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.
- 1M winners are : Winners for past month are $DXCM 20.7%, $FTNT 14.3%, $SMSI 8.4%, $DGII 2.8%, $SWIR 1.8%
- 1M losers are : Losers for past month are $PI -10.8%, $CETX -15.2%, $UCL -28.7%, $TAOP -28.8%, $BSQR -34.0%
- 1W winners are : Winners for past week are $DXCM 11.9%, $BSQR 11.7%, $PI 6.4%, $SWIR 5.2%, $WKEY 4.6%
- 1W losers are : Losers for past week are $SMSI -0.4%, $FTNT -1.3%, $SPCB -3.1%, $TAOP -5.5%, $UCL -8.9%
Index correlation analysis
Correlation for the past month is 21.5%, for the past 3 months is 16.4%
In the past month for a 5 days rolling window, the highest corrrelation is 34.7%, the lowest correlation is -2.9%, the latest correlation is 24.8%
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 80.5% between CAMP and DGII
The lowest correlation is -34.4% between DXCM and RNET