WIG 30 momentum indicators tool provides the execution environment for running the Stochastic indicator and other technical functions against WIG 30. WIG 30 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 momentum indicators indicators. As with most other technical indicators, the Stochastic indicator function is designed to identify and follow existing trends. Momentum indicators of WIG 30 are pattern recognition functions that provide distinct formation on WIG 30 potential trading signals or future price movement. Analysts can use these trading signals to identify current and future trends and trend reversals to provide buy and sell recommendations. Please specify the following input to run this model: Fast-K Period, Slow-K Period, Slow-K MA, Slow-D Period, and Slow-D MA.
The output start index for this execution was eight with a total number of output elements of fifty-three. The Stochastic indicator compares WIG 30 closing price to its price range over a given period of time.
WIG 30 Technical Analysis Modules
Most technical analysis of WIG 30 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 WIG from various momentum indicators to cycle indicators. When you analyze WIG 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 WIG 30 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 WIG 30 will appreciate offsetting losses from the drop in the long position's value.
WIG 30 Pair Correlation
Correlation Analysis For Tax-loss Harvesting
The ability to find closely correlated positions to WIG 30 could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace WIG 30 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 WIG 30 - 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 WIG 30 to buy it.
The correlation of WIG 30 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 WIG 30 moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if WIG 30 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 WIG 30 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.