Cabot Stock Forward View - Simple Exponential Smoothing
| CBT Stock | USD 68.45 -0.01 -0.01% |
Cabot's Simple Exponential Smoothing 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 Exponential Smoothing forecasted value of Cabot on the next trading day is expected to be 68.43 with a mean absolute deviation of 1.00 and the sum of the absolute errors of 60.18.This simple exponential smoothing model begins by setting Cabot forecast for the second period equal to the observation of the first period. In other words, recent Cabot observations are given relatively more weight in forecasting than the older observations. The Simple Exponential Smoothing reference values for Cabot are derived from publicly available price data and should be used for informational purposes only. Simple Exponential Smoothing Price Forecast For the 25th of March
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Cabot on the next trading day is expected to be 68.43 with a mean absolute deviation of 1.00 , mean absolute percentage error of 2.22 , and the sum of the absolute errors of 60.18 .Please note that although there have been many attempts to predict Cabot Stock 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 Cabot's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Stock Forecast Pattern
| Backtest Cabot | Cabot Price Prediction | Research Analysis |
Forecasted Value
This next-day forecast for Cabot uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. Used properly, these levels provide context around forecast dispersion rather than certainty about the next closing print.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Cabot stock data series using in forecasting. Note that when a statistical model is used to represent Cabot 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.| AIC | Akaike Information Criteria | 117.0711 |
| Bias | Arithmetic mean of the errors | -0.0582 |
| MAD | Mean absolute deviation | 1.0031 |
| MAPE | Mean absolute percentage error | 0.0139 |
| SAE | Sum of the absolute errors | 60.1837 |
Other Forecasting Options for Cabot
Relative Strength Index values for Cabot measure the speed and magnitude of recent price changes. Recognizing these clusters in Cabot's returns helps calibrate position size and stop-loss levels. Candlestick pattern analysis of Cabot Stock daily data can reveal short-term reversal or continuation signals.Cabot Related Equities
These stocks are related to Cabot within the Materials space and can be used for peer review, pricing, or spreading risk. Market cap and total value checks frame Cabot's size within the competitive field.
| Risk & Return | Correlation |
Cabot Market Strength Events
Market strength indicators provide a structured view of how Cabot stock is positioned relative to trends. These indicators are valuable tools for identifying when to enter or exit positions in Cabot. These signals help validate or refine position timing for Cabot.
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 68.45 | |||
| Day Typical Price | 68.45 | |||
| Price Action Indicator | -0.01 | |||
| Period Momentum Indicator | -0.01 | |||
| Relative Strength Index | 45.49 |
Cabot Risk Indicators
The analysis of Cabot's risk metrics is one of the most important steps in projecting its future price. This process quantifies the risk associated with Cabot's and helps determine how to manage it. A structured analysis of Cabot's risk indicators is one of the most reliable ways to improve forecast accuracy.
| Mean Deviation | 1.34 | |||
| Semi Deviation | 1.75 | |||
| Standard Deviation | 2.07 | |||
| Variance | 4.28 | |||
| Downside Variance | 3.31 | |||
| Semi Variance | 3.07 | |||
| Expected Short fall | -1.38 |
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 Cabot
Coverage intensity for Cabot matters because narrative visibility can influence sentiment, participation, and volatility around the name. The stronger process compares story flow with performance, theme classification, and the level of short-term market interest.
Contributor Headline
Latest Perspective From Macroaxis
Cabot Short Properties
Reviewing short-oriented indicators for Cabot is useful because long and short participants often create very different signals for timing and volatility. Used correctly, these measures can help investors decide when hedging or timing discipline may matter more than conviction alone.
| Common Stock Shares Outstanding | 54.2 M | |
| Cash And Short Term Investments | 258 M |
Additional Tools for Cabot Stock Analysis
| Technical Analysis Check basic technical indicators and analysis based on most latest market data | |
| Positions Ratings Determine portfolio positions ratings based on digital equity recommendations. Macroaxis instant position ratings are based on combination of fundamental analysis and risk-adjusted market performance | |
| Companies Directory Evaluate performance of over 100,000 Stocks, Funds, and ETFs against different fundamentals | |
| Sign In To Macroaxis Sign in to explore Macroaxis' wealth optimization platform and fintech modules | |
| Portfolio Volatility Check portfolio volatility and analyze historical return density to properly model market risk | |
| Risk-Return Analysis View associations between returns expected from investment and the risk you assume | |
| Options Analysis Analyze and evaluate options and option chains as a potential hedge for your portfolios | |
| Share Portfolio Track or share privately all of your investments from the convenience of any device | |
| FinTech Suite Use AI to screen and filter investment opportunities |