PolyPid Stock Forward View - Triple Exponential Smoothing

PYPD Stock  USD 4.15  -0.01  -0.24%   
PolyPid's Triple 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 Triple Exponential Smoothing forecasted value of PolyPid on the next trading day is expected to be 4.15 with a mean absolute deviation of 0.10 and the sum of the absolute errors of 6.18.As with simple exponential smoothing, in triple exponential smoothing models past PolyPid 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 PolyPid observations. All Triple Exponential Smoothing forecast figures shown for PolyPid are reference data reflecting model output based on available historical prices.
Triple exponential smoothing for PolyPid - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When PolyPid 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 trend in PolyPid price movement. However, neither of these exponential smoothing models address any seasonality of PolyPid.

Triple Exponential Smoothing Price Forecast For the 24th of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of PolyPid on the next trading day is expected to be 4.15 with a mean absolute deviation of 0.10 , mean absolute percentage error of 0.02 , and the sum of the absolute errors of 6.18 .
Please note that although there have been many attempts to predict PolyPid 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 PolyPid's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Stock Forecast Pattern

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Forecasted Value

The next-day forecast for PolyPid 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.
Market Value
4.15
4.15
Expected Value
7.06
Upside

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 PolyPid stock data series using in forecasting. Note that when a statistical model is used to represent PolyPid 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 0.0211
MADMean absolute deviation0.1048
MAPEMean absolute percentage error0.0234
SAESum of the absolute errors6.1845
As with simple exponential smoothing, in triple exponential smoothing models past PolyPid 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 PolyPid observations.

Other Forecasting Options for PolyPid

Bollinger Bands applied to PolyPid Stock price data measure how far PolyPid has deviated from its recent average relative to its own volatility. This distinction drives the choice of forecasting model applied to PolyPid's price data.

PolyPid Related Equities

PolyPid's market space within the Health Care space is best grasped by looking at the firms listed below. Key comparison metrics include price-to-earnings, profit margin, and revenue growth across PolyPid's peer group. When PolyPid breaks from its peer group on a key metric, it often signals a firm-level change worth exploring.
 Risk & Return  Correlation

PolyPid Market Strength Events

For investors tracking PolyPid, market strength indicators offer quantitative evaluation of stock behavior. By using these indicators, traders can make more informed decisions about when to buy or sell PolyPid.

PolyPid Risk Indicators

Analyzing PolyPid's basic risk indicators provides investors with a structured view of the risk-return trade-off for polypid stock. By identifying the level of risk embedded in PolyPid's investment, investors can make informed decisions about position sizing.
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 PolyPid

Coverage intensity for PolyPid matters because narrative visibility can influence sentiment, participation, and volatility around the name. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.

PolyPid Short Properties

A short-interest review of PolyPid provides context for understanding whether skepticism in the market is becoming more influential. Used correctly, these measures can help investors decide when hedging or timing discipline may matter more than conviction alone.
Common Stock Shares Outstanding16.4 M
Cash And Short Term Investments12.9 M

More Resources for PolyPid Stock Analysis

Initial analysis of PolyPid centers on its financial statements and observed trends. These values are derived from PolyPid's published financial data.