Seeing Machines Correlations

SEEMF Stock  USD 0.06  0  2.30%   
The current 90-days correlation between Seeing Machines and Tenet Fintech Group is 0.02 (i.e., Significant diversification). The correlation of Seeing Machines is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.

Seeing Machines Correlation With Market

Good diversification

The correlation between Seeing Machines Limited and DJI is -0.03 (i.e., Good diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding Seeing Machines Limited and DJI in the same portfolio, assuming nothing else is changed.
  
The ability to find closely correlated positions to Seeing Machines could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Seeing Machines when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Seeing Machines - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Seeing Machines Limited to buy it.

Moving against Seeing Pink Sheet

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Related Correlations Analysis

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Correlation Matchups

Over a given time period, the two securities move together when the Correlation Coefficient is positive. Conversely, the two assets move in opposite directions when the Correlation Coefficient is negative. Determining your positions' relationship to each other is valuable for analyzing and projecting your portfolio's future expected return and risk.
High positive correlations   
OSPNIMXI
EVCMIMXI
EVCMOSPN
EVCMNTCT
IMXINTCT
OSPNNTCT
  
High negative correlations   
IMXIFOBIF
EVCMFOBIF
OSPNFOBIF
NTCTFOBIF
FOBIFPKKFF
RPAYFOBIF

Risk-Adjusted Indicators

There is a big difference between Seeing Pink Sheet performing well and Seeing Machines Company doing well as a business compared to the competition. There are so many exceptions to the norm that investors cannot definitively determine what's good or bad unless they analyze Seeing Machines' multiple risk-adjusted performance indicators across the competitive landscape. These indicators are quantitative in nature and help investors forecast volatility and risk-adjusted expected returns across various positions.
Mean DeviationJensen AlphaSortino RatioTreynor RatioSemi DeviationExpected ShortfallPotential UpsideValue @RiskMaximum Drawdown
AMPDF  0.00  0.00  0.00  0.00  0.00 
 0.00 
 0.00 
PKKFF  7.67  0.37  0.04 (0.30) 7.80 
 19.05 
 79.19 
FOBIF  14.18  1.98  0.09 (0.73) 14.53 
 50.00 
 109.17 
VRAR  9.12  3.24  0.43 (1.48) 5.43 
 31.58 
 118.45 
RPAY  1.80 (0.03) 0.00 (0.50) 0.00 
 4.33 
 15.69 
NTCT  1.49  0.06  0.02  0.19  1.65 
 3.29 
 11.69 
SPSC  1.45 (0.02) 0.00 (0.15) 0.00 
 3.01 
 13.74 
IMXI  1.29  0.17  0.10  0.49  1.42 
 2.74 
 15.73 
OSPN  2.00  0.25  0.09  0.52  2.52 
 3.99 
 21.05 
EVCM  1.47  0.10  0.04  0.66  2.08 
 3.22 
 13.03 

Be your own money manager

Our tools can tell you how much better you can do entering a position in Seeing Machines without increasing your portfolio risk or giving up the expected return. As an individual investor, you need to find a reliable way to track all your investment portfolios. However, your requirements will often be based on how much of the process you decide to do yourself. In addition to allowing all investors analytical transparency into all their portfolios, our tools can evaluate risk-adjusted returns of your individual positions relative to your overall portfolio.

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Seeing Machines Corporate Management

Susan DallistonG SecProfile
Anthony BorgoChief OfficerProfile
Mike LenneChief OfficerProfile
Sebastian RougeauxChief Scientific Officer and Principal Research ScientistProfile
Nicolas DifioreVP AutomotiveProfile
Martin IveChief OfficerProfile