BMC Stock Forward View - Double Exponential Smoothing

BMC Stock   86.10  0.10  0.12%   
BMC's Double Exponential Smoothing reference page covers the model's projected value and error measures from recent price data. The forecast output and associated deviation metrics are shown for informational use. The model is fitted to available historical daily prices for BMC. This page is updated as new daily closing prices become available for BMC.
The Double Exponential Smoothing forecasted value of BMC on the next trading day is expected to be 84.57 with a mean absolute deviation of 1.69 and the sum of the absolute errors of 99.67.When BMC 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 BMC trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent BMC observations are given relatively more weight in forecasting than the older observations. All Double Exponential Smoothing forecast figures shown for BMC are reference data reflecting model output based on available historical prices.
Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for BMC works best with periods where there are trends or seasonality.

Double Exponential Smoothing Price Forecast For the 25th of March

Given 90 days horizon, the Double Exponential Smoothing forecasted value of BMC on the next trading day is expected to be 84.57 with a mean absolute deviation of 1.69 , mean absolute percentage error of 4.57 , and the sum of the absolute errors of 99.67 .
Please note that although there have been many attempts to predict BMC 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 BMC's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Stock Forecast Pattern

Forecasted Value

This next-day forecast for BMC uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. The current forecast range spans downside near 82.82 and upside near 86.31.
Market Value
86.10
84.57
Expected Value
86.31
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of BMC stock data series using in forecasting. Note that when a statistical model is used to represent BMC 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.
AICAkaike Information CriteriaHuge
BiasArithmetic mean of the errors 0.3734
MADMean absolute deviation1.6893
MAPEMean absolute percentage error0.0163
SAESum of the absolute errors99.6664
When BMC 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 BMC trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent BMC observations are given relatively more weight in forecasting than the older observations.

Other Forecasting Options for BMC

Bollinger Bands applied to BMC Stock price data measure how far BMC has deviated from its recent average relative to its own volatility. This distinction drives the choice of forecasting model applied to BMC's price data. On-balance volume for BMC Stock creates a running indicator of buying versus selling pressure in BMC. Price departures from the channel boundary often mean-revert, offering tactical signals for BMC's.

BMC Related Equities

These firms work in a similar space as BMC and serve as useful points for comparison. Looking at BMC's pricing multiples next to these peers shows if the stock trades at a premium or discount. How BMC ranks within this group can shift over time as the competitive picture changes. This type of review is most useful when done often to track how positions shift over time.
 Risk & Return  Correlation

BMC Market Strength Events

For investors tracking BMC, market strength indicators offer quantitative evaluation of stock behavior. These indicators add context to timing decisions around BMC positions. These indicators capture shifts in momentum that may precede significant price moves in BMC. These metrics provide actionable context for both entry and risk management decisions around BMC.

BMC Risk Indicators

Analyzing BMC's basic risk indicators provides investors with a structured view of the risk-return trade-off for bmc stock. By identifying the level of risk embedded in BMC's investment, investors can make informed decisions about position sizing. Analyzing BMC's risk indicators gives investors important context for price forecasting. Understanding the risk in BMC's investment allows investors to make informed choices about mitigating 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 BMC

Story coverage around BMC often expands when market conditions, narrative momentum, or risk-adjusted performance make the security more visible to investors. Used properly, this context can help investors judge whether visibility is reinforcing the thesis or attracting more speculative pressure.

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.

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