Strats Sm Trust Stock Overlap Studies Parabolic SAR Extended

GJP Stock  USD 24.99  0.10  0.40%   
STRATS SM overlap studies tool provides the execution environment for running the Parabolic SAR Extended study and other technical functions against STRATS SM. STRATS SM 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 overlap studies indicators. As with most other technical indicators, the Parabolic SAR Extended study function is designed to identify and follow existing trends. STRATS SM overlay technical analysis usually involve calculating upper and lower limits of price movements based on various statistical techniques. Please specify the following input to run this model: Start Value, Offset on Reverse, AF Init Long, AF Long, AF Max Long, AF Init Short, AF Short, and AF Max Short.

Study
Start Value
Offset on Reverse
AF Init Long
AF Long
AF Max Long
AF Init Short
AF Short
AF Max Short
Execute Study
The output start index for this execution was one with a total number of output elements of sixty. The Extended Parabolic SAR indicator is used to determine the direction of STRATS SM's momentum and the point in time when it has higher than normal probability of directional change. It has more input parameters than standard Parabolic SAR indicator.

STRATS SM Technical Analysis Modules

Most technical analysis of STRATS SM 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 STRATS from various momentum indicators to cycle indicators. When you analyze STRATS 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.

About STRATS SM Predictive Technical Analysis

Predictive technical analysis modules help investors to analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of STRATS SM Trust. We use our internally-developed statistical techniques to arrive at the intrinsic value of STRATS SM Trust based on widely used predictive technical indicators. In general, we focus on analyzing STRATS Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build STRATS SM's daily price indicators and compare them against related drivers, such as overlap studies and various other types of predictive indicators. Using this methodology combined with a more conventional technical analysis and fundamental analysis, we attempt to find the most accurate representation of STRATS SM's intrinsic value. In addition to deriving basic predictive indicators for STRATS SM, we also check how macroeconomic factors affect STRATS SM price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
Hype
Prediction
LowEstimatedHigh
24.2924.9925.69
Details
Intrinsic
Valuation
LowRealHigh
23.0323.7327.49
Details
Naive
Forecast
LowNextHigh
24.4525.1525.85
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
24.7424.9525.15
Details

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Additional Tools for STRATS Stock Analysis

When running STRATS SM's price analysis, check to measure STRATS SM's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy STRATS SM is operating at the current time. Most of STRATS SM's value examination focuses on studying past and present price action to predict the probability of STRATS SM's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move STRATS SM's price. Additionally, you may evaluate how the addition of STRATS SM to your portfolios can decrease your overall portfolio volatility.