TACHLIT INDICES (Israel) Technical Analysis

TCH-F71 -- Israel ETF  

ILA 268.00  5.60  2.13%

As of the 28th of February TACHLIT INDICES owns Standard Deviation of 0.5878, Mean Deviation of 0.5229 and Market Risk Adjusted Performance of (3.01). Macroaxis technical analysis interface makes it possible for you to check helpful technical drivers of TACHLIT INDICES MU as well as the relationship between them. Strictly speaking you can use this information to find out if the entity will indeed mirror its model of historical prices and volume patterns or the prices will eventually revert. We found nineteen technical drivers for TACHLIT INDICES, which can be compared to its peers in the sector. Please validate TACHLIT INDICES MU Downside Deviation, Standard Deviation, Information Ratio, as well as the relationship between Coefficient Of Variation and Variance to decide if TACHLIT INDICES MU is priced fairly providing market reflects its prevailing price of 268.0 per share.


Use this graph to draw trend lines for TACHLIT INDICES MU. You can use it to identify possible trend reversals for TACHLIT INDICES as well as other signals and approximate when it will take place. Remember, you need at least two touches of the trend line with actual TACHLIT INDICES price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.

TACHLIT INDICES Best Fit Change Line

The following chart estimates an ordinary least squares regression model for TACHLIT INDICES MU applied against its price change over selected period. The best fit line has a slop of   1.17  which means TACHLIT INDICES MU will continue generating value for investors. It has 18 observation points and a regression sum of squares at 164.27, which is the sum of squared deviations for the predicted TACHLIT INDICES price change compared to its average price change.

TACHLIT INDICES February 28, 2020 Technical Indicators

Additionally, take a look at World Market Map. Please also try Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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