Doosan Fuel statistic functions tool provides the execution environment for running the Pearson Correlation Coefficient function and other technical functions against Doosan Fuel. Doosan Fuel 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 statistic functions indicators. As with most other technical indicators, the Pearson Correlation Coefficient function function is designed to identify and follow existing trends. Doosan Fuel statistical functions help analysts to determine different price movement patterns based on how price series statistical indicators change over time. Please specify Time Period to run this model.
The output start index for this execution was thirteen with a total number of output elements of fourty-eight. The Pearsons Correlation Coefficient is one of the most common measures of correlation in financial statistics. It shows the linear relationship between price series of Doosan Fuel Cell and its benchmark or peer.
Doosan Fuel Technical Analysis Modules
Most technical analysis of Doosan Fuel 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 Doosan from various momentum indicators to cycle indicators. When you analyze Doosan 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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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 Doosan Fuel 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 Doosan Fuel will appreciate offsetting losses from the drop in the long position's value.
Doosan Fuel Pair Trading
Doosan Fuel Cell Pair Trading Analysis
The ability to find closely correlated positions to Doosan Fuel could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Doosan Fuel 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 Doosan Fuel - 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 Doosan Fuel Cell to buy it.
The correlation of Doosan Fuel 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 Doosan Fuel moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Doosan Fuel Cell 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 Doosan Fuel 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.