Lanvin Group Holdings Stock Statistic Functions Pearson Correlation Coefficient

LANV Stock   1.56  0.03  1.89%   
Lanvin Group statistic functions tool provides the execution environment for running the Pearson Correlation Coefficient function and other technical functions against Lanvin Group. Lanvin 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 statistic functions indicators. As with most other technical indicators, the Pearson Correlation Coefficient function function is designed to identify and follow existing trends. Lanvin Group 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.

Function
Time Period
Execute Function
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 Lanvin Group Holdings and its benchmark or peer.

Lanvin Group Technical Analysis Modules

Most technical analysis of Lanvin 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 Lanvin from various momentum indicators to cycle indicators. When you analyze Lanvin 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 Lanvin Group 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 Lanvin Group Holdings. We use our internally-developed statistical techniques to arrive at the intrinsic value of Lanvin Group Holdings based on widely used predictive technical indicators. In general, we focus on analyzing Lanvin Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Lanvin Group's daily price indicators and compare them against related drivers, such as statistic functions 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 Lanvin Group's intrinsic value. In addition to deriving basic predictive indicators for Lanvin Group, we also check how macroeconomic factors affect Lanvin Group price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
 2021 2022 2023 2024 (projected)
Days Sales Outstanding47.0242.2439.132.95
PTB Ratio1.742.932.072.62
Hype
Prediction
LowEstimatedHigh
0.081.557.44
Details
Intrinsic
Valuation
LowRealHigh
0.122.388.27
Details
Naive
Forecast
LowNextHigh
0.031.597.48
Details
1 Analysts
Consensus
LowTargetHigh
4.595.045.59
Details

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Additional Tools for Lanvin Stock Analysis

When running Lanvin Group's price analysis, check to measure Lanvin Group'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 Lanvin Group is operating at the current time. Most of Lanvin Group's value examination focuses on studying past and present price action to predict the probability of Lanvin Group's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Lanvin Group's price. Additionally, you may evaluate how the addition of Lanvin Group to your portfolios can decrease your overall portfolio volatility.