First Mining Stock Forward View - Triple Exponential Smoothing
| FF Stock | CAD 0.43 0.03 7.50% |
The Triple Exponential Smoothing forecast reference data for First Mining Gold is based on the equity's recent trading history. Forecast values and accuracy indicators are summarized on this page for reference. This reference information is provided for analytical context.
The Triple Exponential Smoothing forecasted value of First Mining Gold on the next trading day is expected to be 0.42 with a mean absolute deviation of 0.03 and the sum of the absolute errors of 1.62.As with simple exponential smoothing, in triple exponential smoothing models past First Mining observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older First Mining Gold observations. The Triple Exponential Smoothing projections for First Mining Gold are reference data based on historical daily prices and are provided as informational context. Triple Exponential Smoothing Price Forecast For the 24th of March
Given 90 days horizon, the Triple Exponential Smoothing forecasted value of First Mining Gold on the next trading day is expected to be 0.42 with a mean absolute deviation of 0.03 , mean absolute percentage error of 0.0012 , and the sum of the absolute errors of 1.62 .Please note that although there have been many attempts to predict First 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 First Mining's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Stock Forecast Pattern
| Backtest First Mining | First Mining Price Prediction | Research Analysis |
Forecasted Value
The next-day forecast for First Mining Gold focuses on identifying predictive downside and upside bands that can frame a realistic trading range. 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 Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of First Mining stock data series using in forecasting. Note that when a statistical model is used to represent First Mining 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 | Huge |
| Bias | Arithmetic mean of the errors | -0.0078 |
| MAD | Mean absolute deviation | 0.0275 |
| MAPE | Mean absolute percentage error | 0.0455 |
| SAE | Sum of the absolute errors | 1.62 |
Other Forecasting Options for First Mining
Volatility clustering is a well-documented feature of First Stock price data where periods of large moves tend to follow other large moves. When First Mining's RSI reaches extreme levels, it often precedes a short-term price correction or consolidation. Seasonal patterns in First Mining's returns can persist when driven by structural factors like earnings calendars or index rebalancing.First Mining Related Equities
The stocks listed below are peers of First Mining within the Materials space and offer context for ranking and strength. Checking cash flow across this peer set helps gauge First Mining's relative financial strength. Falling behind peers on key ratios may signal headwinds or execution issues worth looking into. The data below allows side-by-side review across the most common financial metrics.
| Risk & Return | Correlation |
First Mining Market Strength Events
Analyzing market strength indicators for First Mining enables investors to understand relative stock momentum. Investors use these tools to determine the best times to initiate or close positions in First Mining Gold. Market strength indicators support more precise timing of First Mining Gold positions across market cycles.
First Mining Risk Indicators
Identifying and analyzing First Mining's key risk indicators is a foundational step in projecting how its price may evolve. This process involves measuring the level of investment risk in First Mining's and determining how best to manage it. Studying First Mining's risk indicators helps investors understand the risk level of first stock.
| Mean Deviation | 4.35 | |||
| Standard Deviation | 5.41 | |||
| Variance | 29.22 |
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 First Mining
Coverage intensity for First Mining Gold matters because narrative visibility can influence sentiment, participation, and volatility around the name. A disciplined read of coverage separates durable relevance from temporary noise.
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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First Mining Short Properties
Reviewing short-oriented indicators for First Mining Gold is useful because long and short participants often create very different signals for timing and volatility. The practical goal is to identify when the balance between long and short participation may be changing the quality of the setup.
| Common Stock Shares Outstanding | 971.5 M | |
| Cash And Short Term Investments | 13.7 M |
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Other Information on Investing in First Stock
These ratios describe connections between financial data points for First Mining. The format ensures data can be compared on a consistent basis.