Cipher Pharmaceuticals Stock Forward View - Triple Exponential Smoothing
| CPH Stock | CAD 16.57 -0.13 -0.78% |
The Triple Exponential Smoothing reference data for Cipher Pharmaceuticals is derived from the equity's published trading history. The resulting forecast and deviation statistics are presented as reference data for informational context. Forecast values and accuracy statistics are presented for informational purposes.
The Triple Exponential Smoothing forecasted value of Cipher Pharmaceuticals on the next trading day is expected to be 16.69 with a mean absolute deviation of 0.28 and the sum of the absolute errors of 16.60.As with simple exponential smoothing, in triple exponential smoothing models past Cipher Pharmaceuticals 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 Cipher Pharmaceuticals observations. The forecast reference data presented here for Cipher Pharmaceuticals reflects Triple Exponential Smoothing model output and is intended as reference material for analytical use. Triple Exponential Smoothing Price Forecast For the 24th of March
Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Cipher Pharmaceuticals on the next trading day is expected to be 16.69 with a mean absolute deviation of 0.28 , mean absolute percentage error of 0.17 , and the sum of the absolute errors of 16.60 .Please note that although there have been many attempts to predict Cipher 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 Cipher Pharmaceuticals' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Stock Forecast Pattern
| Backtest Cipher Pharmaceuticals | Cipher Pharmaceuticals Price Prediction | Research Analysis |
Forecasted Value
Forecasting Cipher Pharmaceuticals for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. 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 Cipher Pharmaceuticals stock data series using in forecasting. Note that when a statistical model is used to represent Cipher Pharmaceuticals 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 | 0.0858 |
| MAD | Mean absolute deviation | 0.2814 |
| MAPE | Mean absolute percentage error | 0.0184 |
| SAE | Sum of the absolute errors | 16.5998 |
Other Forecasting Options for Cipher Pharmaceuticals
Fibonacci retracement levels applied to Cipher Stock price swings identify potential support and resistance zones. Extreme price moves in Cipher occur more frequently than standard risk models assume. Support and resistance levels derived from Cipher Pharmaceuticals' historical data identify zones where buying or selling pressure has stalled moves.Cipher Pharmaceuticals Related Equities
Checking Cipher Pharmaceuticals against related firms within the Health Care space helps investors see where the stock stands among peers. Looking at Cipher Pharmaceuticals' pricing multiples next to these peers shows if the stock trades at a premium or discount.
| Risk & Return | Correlation |
Cipher Pharmaceuticals Market Strength Events
Tracking market strength indicators for Cipher Pharmaceuticals provides context for understanding stock momentum dynamics. Tracking these indicators helps identify periods where trading Cipher Pharmaceuticals is likely to be most rewarding. These tools are essential for timing trades in Cipher Pharmaceuticals with a quantitative framework.
Cipher Pharmaceuticals Risk Indicators
Properly assessing Cipher Pharmaceuticals' risk indicators is a prerequisite for building reliable price forecasts. This analysis provides context for determining the appropriate level of risk to accept when holding Cipher Pharmaceuticals'. Analyzing Cipher Pharmaceuticals' risk indicators provides a critical input for investment risk management.
| Mean Deviation | 1.71 | |||
| Semi Deviation | 1.34 | |||
| Standard Deviation | 2.8 | |||
| Variance | 7.82 | |||
| Downside Variance | 2.49 | |||
| Semi Variance | 1.8 | |||
| Expected Short fall | -2.40 |
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 Cipher Pharmaceuticals
A coverage review of Cipher Pharmaceuticals shows when the security is attracting above-average attention from contributors and market observers. Used properly, this context can help investors judge whether visibility is reinforcing the thesis or attracting more speculative pressure.
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Cipher Pharmaceuticals Short Properties
Short-interest signals around Cipher Pharmaceuticals can help investors judge whether skeptical positioning is starting to pressure price predictability and market tone. The stronger read compares short sentiment with trend behavior, volume, and the broader market narrative.
| Common Stock Shares Outstanding | 26 M | |
| Cash And Short Term Investments | 7.5 M |
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Other Information on Investing in Cipher Stock
Financial ratios for Cipher Pharmaceuticals organize key financial data into structured relationships. This format maintains consistency across different reporting periods.