STERLING CAPITAL Mutual Fund Forward View - Simple Regression
| STRBX Fund | USD 20.24 0.22 1.10% |
STERLING CAPITAL's Simple Regression reference data reflects the model's output when applied to available daily price observations. This page summarizes the model output and key accuracy metrics for reference. The projected value and error metrics are calculated from available daily price observations.
The Simple Regression forecasted value of Sterling Capital Behavioral on the next trading day is expected to be 20.64 with a mean absolute deviation of 0.45 and the sum of the absolute errors of 27.66.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 Sterling Capital Behavioral historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data. The Simple Regression reference values for STERLING CAPITAL are derived from publicly available price data and should be used for informational purposes only. Simple Regression Price Forecast For the 26th of March
Given 90 days horizon, the Simple Regression forecasted value of Sterling Capital Behavioral on the next trading day is expected to be 20.64 with a mean absolute deviation of 0.45 , mean absolute percentage error of 0.27 , and the sum of the absolute errors of 27.66 .Please note that although there have been many attempts to predict STERLING 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 STERLING CAPITAL'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
This next-day forecast for Sterling Capital Behavioral uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. No forecasting approach has been shown to beat all others over time. Investors should treat any model output as a guide, not a guarantee.
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 STERLING CAPITAL mutual fund data series using in forecasting. Note that when a statistical model is used to represent STERLING CAPITAL 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.| AIC | Akaike Information Criteria | 118.6428 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.4461 |
| MAPE | Mean absolute percentage error | 0.0218 |
| SAE | Sum of the absolute errors | 27.6577 |
Other Forecasting Options for STERLING CAPITAL
Relative Strength Index values for STERLING measure the speed and magnitude of recent price changes. Recognizing these clusters in STERLING CAPITAL's returns helps calibrate position size and stop-loss levels. Candlestick pattern analysis of STERLING Mutual Fund daily data can reveal short-term reversal or continuation signals.STERLING CAPITAL Related Equities
These related stocks within the Small Value space give benchmarks for judging STERLING CAPITAL's results, margins, and growth trend. Market cap and total value checks frame STERLING CAPITAL's size within the competitive field. Identifying peers that steadily beat or lag STERLING CAPITAL across many periods highlights durable competitive gaps. Peer review is one of the most widely used methods in stock research and portfolio building.
| Risk & Return | Correlation |
STERLING CAPITAL Market Strength Events
Market strength indicators provide a structured view of how STERLING CAPITAL mutual fund is positioned relative to trends. These indicators are valuable tools for identifying when to enter or exit positions in Sterling Capital Behavioral. These signals help validate or refine position timing for STERLING CAPITAL.
| Rate Of Daily Change | 1.01 | |||
| Day Median Price | 20.24 | |||
| Day Typical Price | 20.24 | |||
| Price Action Indicator | 0.11 | |||
| Period Momentum Indicator | 0.22 |
STERLING CAPITAL Risk Indicators
The analysis of STERLING CAPITAL's risk metrics is one of the most important steps in projecting its future price. This process quantifies the risk associated with STERLING CAPITAL's and helps determine how to manage it. A structured analysis of STERLING CAPITAL's risk indicators is one of the most reliable ways to improve forecast accuracy.
| Mean Deviation | 0.7864 | |||
| Semi Deviation | 0.9457 | |||
| Standard Deviation | 1.02 | |||
| Variance | 1.04 | |||
| Downside Variance | 0.9671 | |||
| Semi Variance | 0.8943 | |||
| Expected Short fall | -0.85 |
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 STERLING CAPITAL
Story coverage around Sterling Capital Behavioral often expands when market conditions, narrative momentum, or risk-adjusted performance make the security more visible to investors. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.
Other Macroaxis Stories
Macroaxis story coverage is designed for a broad investing audience that ranges from self-directed traders to advisers, researchers, and institutional market participants. The content is intended to support people who want a more structured path from headline information to portfolio action.