BOSTON PARTNERS Mutual Fund Forward View - Simple Regression

BPSIX Fund  USD 25.44  -0.35  -1.36%   
The Simple Regression forecast shown here for BOSTON PARTNERS is reference data produced from its historical price series. The projected value and error measures below serve as reference information. This data is provided for reference and analytical review. The Simple Regression output serves as one input among many for analytical review.
The Simple Regression forecasted value of Boston Partners Small on the next trading day is expected to be 26.73 with a mean absolute deviation of 0.58 and the sum of the absolute errors of 35.26.In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as Boston Partners Small historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data. This Simple Regression reference page for BOSTON PARTNERS presents model-generated projections from historical price data for informational purposes.
Simple Regression model is a single variable regression model that attempts to put a straight line through BOSTON PARTNERS price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

Simple Regression Price Forecast For the 23rd of March

Given 90 days horizon, the Simple Regression forecasted value of Boston Partners Small on the next trading day is expected to be 26.73 with a mean absolute deviation of 0.58 , mean absolute percentage error of 0.44 , and the sum of the absolute errors of 35.26 .
Please note that although there have been many attempts to predict BOSTON Mutual 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 BOSTON PARTNERS's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Mutual Fund Forecast Pattern

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Forecasted Value

For the next trading day, Macroaxis evaluates BOSTON PARTNERS's predictive range by looking for statistically meaningful downside and upside boundaries. At the moment, the model places downside around 25.73 and upside around 27.73 for the forecasting period.
Market Value
25.44
26.73
Expected Value
27.73
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of BOSTON PARTNERS mutual fund data series using in forecasting. Note that when a statistical model is used to represent BOSTON PARTNERS mutual 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 Criteria117.293
BiasArithmetic mean of the errors None
MADMean absolute deviation0.5781
MAPEMean absolute percentage error0.0216
SAESum of the absolute errors35.2625
In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as Boston Partners Small historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Other Forecasting Options for BOSTON PARTNERS

The distribution of BOSTON PARTNERS's daily returns is typically non-normal, with fatter tails than a Gaussian model predicts. This can reveal hidden support and resistance zones in BOSTON PARTNERS's chart that simple price charts miss. The slope of BOSTON PARTNERS's linear regression channel quantifies trend direction and strength over a chosen lookback period. Divergences between OBV and price can foreshadow trend changes in BOSTON.

BOSTON PARTNERS Related Equities

These firms work in a similar space as BOSTON PARTNERS within the Small Value space and serve as useful points for comparison. Checking BOSTON PARTNERS against peers on P/E, margins, and return on equity helps put its position in context.
 Risk & Return  Correlation

BOSTON PARTNERS Market Strength Events

Market strength indicators for BOSTON PARTNERS give insight into the mutual fund's responsiveness to broader forces. These indicators are useful for traders seeking optimal timing for positions in Boston Partners Small. Market strength analysis for Boston Partners Small works best when combined with volume and volatility data. For BOSTON PARTNERS, strength indicators are a practical complement to price and fundamental analysis.

BOSTON PARTNERS Risk Indicators

A thorough review of BOSTON PARTNERS's risk indicators is an important first step in forecasting its price. Quantifying the risk involved in BOSTON PARTNERS's allows investors to make better decisions about entry, sizing, and hedging. The assessment of BOSTON PARTNERS's risk indicators plays a key role in managing investment exposure. Identifying the magnitude of risk in BOSTON PARTNERS's provides context to choose between accepting or hedging 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 BOSTON PARTNERS

A coverage review of Boston Partners Small shows when the security is attracting above-average attention from contributors and market observers. A disciplined read of coverage separates durable relevance from temporary noise.

Other Macroaxis Stories

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