MCB GROUP math transform tool provides the execution environment for running the Price Common Logarithm transformation and other technical functions against MCB GROUP. MCB GROUP value trend is the prevailing direction of the price over some defined period of time. The concept of trend is an important idea in technical analysis, including the analysis of math transform indicators. As with most other technical indicators, the Price Common Logarithm transformation function is designed to identify and follow existing trends. Analysts that use price transformation techniques rely on the belief that biggest profits from investing in MCB GROUP can be made when MCB GROUP shifts in price trends from positive to negative or vice versa.
The output start index for this execution was zero with a total number of output elements of sixty-one. MCB GROUP LIMITED Price Common Logarithm is logarithm with base 10 applied on the entire pricing series.
MCB GROUP Technical Analysis Modules
Most technical analysis of MCB GROUP help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for MCB from various momentum indicators to cycle indicators. When you analyze MCB charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.
As an individual investor, you need to find a reliable way to track all your investment portfolios' performance accurately. However, your requirements will often be based on how much of the process you decide to do yourself. In addition to allowing you full analytical transparency into your positions, our tools can tell you how much better you can do without increasing your risk or reducing expected return.
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Fundamentals Comparison
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One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if MCB GROUP position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in MCB GROUP will appreciate offsetting losses from the drop in the long position's value.
MCB GROUP Pair Trading
MCB GROUP LIMITED Pair Trading Analysis
The ability to find closely correlated positions to MCB GROUP could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace MCB GROUP 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 MCB GROUP - 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 MCB GROUP LIMITED to buy it.
The correlation of MCB GROUP 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 perfect positive correlation (i.e., a correlation coefficient of +1) implies that as MCB GROUP moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if MCB GROUP LIMITED moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for MCB GROUP can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.