BNP Paribas Fund Forward View - Triple Exponential Smoothing

OBAM Fund  EUR 25.60  -0.34  -1.31%   
This page provides reference data for BNP Paribas using Triple Exponential Smoothing forecasting. The projected value and error metrics are calculated from available daily price observations.
The Triple Exponential Smoothing forecasted value of BNP Paribas Obam on the next trading day is expected to be 25.51 with a mean absolute deviation of 0.17 and the sum of the absolute errors of 10.23.As with simple exponential smoothing, in triple exponential smoothing models past BNP Paribas observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older BNP Paribas Obam observations. This Triple Exponential Smoothing reference page for BNP Paribas presents model-generated projections from historical price data for informational purposes.
Triple exponential smoothing for BNP Paribas - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When BNP Paribas prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any trend in BNP Paribas price movement. However, neither of these exponential smoothing models address any seasonality of BNP Paribas Obam.

Triple Exponential Smoothing Price Forecast For the 22nd of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of BNP Paribas Obam on the next trading day is expected to be 25.51 with a mean absolute deviation of 0.17 , mean absolute percentage error of 0.05 , and the sum of the absolute errors of 10.23 .
Please note that although there have been many attempts to predict BNP Fund prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that BNP Paribas' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Fund Forecast Pattern

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Forecasted Value

For the next trading day, Macroaxis evaluates BNP Paribas' predictive range by looking for statistically meaningful downside and upside boundaries. Investors should still remember that no empirical framework consistently proves that one family of forecasting models will outperform all other approaches in live markets.
Market Value
25.60
25.51
Expected Value
26.29
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of BNP Paribas fund data series using in forecasting. Note that when a statistical model is used to represent BNP Paribas fund, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.
AICAkaike Information CriteriaHuge
BiasArithmetic mean of the errors 0.0364
MADMean absolute deviation0.1706
MAPEMean absolute percentage error0.0063
SAESum of the absolute errors10.2343
As with simple exponential smoothing, in triple exponential smoothing models past BNP Paribas observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older BNP Paribas Obam observations.

Other Forecasting Options for BNP Paribas

For investors considering BNP, BNP Paribas' price movement is the most direct driver of investment returns. Noise in BNP Fund price charts can make identifying meaningful trends difficult without dedicated analytical tools.

BNP Paribas Related Equities

The following equities are related to BNP Paribas within the Global Large-Cap Growth Equity space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing BNP Paribas against peers on metrics such as P/E, margins, and return on equity helps contextualize its positioning and identify relative strengths or weaknesses.
 Risk & Return  Correlation

BNP Paribas Market Strength Events

Market strength indicators for BNP Paribas provide investors with a view of how the fund performs across different market environments. By analyzing these indicators, traders can determine the best moments to enter or exit positions in BNP Paribas Obam.

BNP Paribas Risk Indicators

A structured analysis of BNP Paribas' risk indicators is one of the most reliable ways to improve the accuracy of price forecasts. Understanding the risk embedded in BNP Paribas' allows investors to decide whether to accept, reduce, or hedge their exposure.
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.

Story Coverage note for BNP Paribas

Coverage intensity for BNP Paribas Obam matters because narrative visibility can influence sentiment, participation, and volatility around the name. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.

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