Orange County Stock Forward View - Simple Regression

Orange County Additional Predictive Modules

Most predictive techniques to examine Orange price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Orange using various technical indicators. When you analyze Orange 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. Simple Regression model is a single variable regression model that attempts to put a straight line through Orange County 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.

Orange County Simple Regression Price Forecast For the 10th of March

Given 90 days horizon, the Simple Regression forecasted value of Orange County Bancorp on the next trading day is expected to be 34.47 with a mean absolute deviation of 1.16 , mean absolute percentage error of 1.99 , and the sum of the absolute errors of 70.85 .

Orange County Stock Forecast Pattern

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Orange County Price Prediction

Research Analysis

Orange County Forecasted Value

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 Orange County stock data series using in forecasting. Note that when a statistical model is used to represent Orange County stock, 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. 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 Orange County Bancorp historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Hype Prediction Low Estimated High 29.68 31.46 33.24 Details

Intrinsic Valuation Low Real High 27.45 29.23 34.61 Details

Bollinger Band Projection (param) Low Middle High 31.25 33.72 36.19 Details

3 Analysts Consensus Low Target High 34.58 38.00 42.18 Details

Analyzing Orange County in isolation is insufficient for informed investment decisions. Placing Orange County's results in the context of its peer group reveals whether its performance is company-specific or simply a function of industry-wide trends.

Orange County After-Hype Price Density Analysis

Orange County Estimiated After-Hype Price Volatility

Orange County Stock Price Outlook Analysis

Expected Return	Period Volatility	Hype Elasticity	Related Elasticity	News Density	Related Density	Expected Hype
0.24	1.78	0.04	0.02	8 Events	7 Events	In 8 days

Latest traded price	Expected after-news price	Potential return on next major news	Average after-hype volatility
31.61	31.46	0.00	988.89

Notes

Orange County Hype Timeline

On the 9th of March Orange County Bancorp is traded for 31.61. The entity has historical hype elasticity of 0.04, and average elasticity to hype of competition of 0.02. Orange is forecasted not to react to the next headline, with the price staying at about the same level, and average media hype impact volatility is over 100%. The immediate return on the next news is forecasted to be very small, whereas the daily expected return is now at 0.24%. %. The volatility of related hype on Orange County is about 2000.0%, with the expected price after the next announcement by competition of 31.63. About 13.0% of the company outstanding shares are owned by corporate insiders. The company has price-to-book ratio of 1.48. Typically companies with comparable Price to Book (P/B) are able to outperform the market in the long run. Orange County Bancorp last dividend was issued on the 4th of March 2026. The entity completed a 2:1 stock split on 13th of January 2025. Considering the 90-day investment horizon the next forecasted press release will be in 8 days. Use Historical Fundamental Analysis of Orange County to cross-verify projections for Orange County. The analysis adds historical context for the projection set.

Orange County Related Hype Analysis

Other Forecasting Options for Orange County

For investors of all experience levels considering Orange, understanding Orange County's price movement is fundamental to making sound investment decisions. Orange Stock price charts contain significant noise that can obscure meaningful trends.

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Risk & Return

Correlation

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Story Coverage note for Orange County

Orange County Short Properties

Additional Tools for Orange Stock Analysis