AppYea OTC Stock Forward View - Triple Exponential Smoothing

APYP Stock

USD 0.01 0.0001 0.67%

This reference page presents Triple Exponential Smoothing forecast data for AppYea Inc. The model output shown here is derived from AppYea's historical price series and is provided for informational purposes.

The Triple Exponential Smoothing forecasted value of AppYea Inc on the next trading day is expected to be 0.02 with a mean absolute deviation of 0.0014 and the sum of the absolute errors of 0.08.As with simple exponential smoothing, in triple exponential smoothing models past AppYea 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 AppYea Inc observations. This Triple Exponential Smoothing forecast data for AppYea Inc is sourced from the most recent available trading data and is intended solely as reference information.

Triple exponential smoothing for AppYea - 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 AppYea 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 AppYea price movement. However, neither of these exponential smoothing models address any seasonality of AppYea Inc.

Triple Exponential Smoothing Price Forecast For the 20th of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of AppYea Inc on the next trading day is expected to be 0.02 with a mean absolute deviation of 0.0014 , mean absolute percentage error of 0.00000356 , and the sum of the absolute errors of 0.08 .

Please note that although there have been many attempts to predict AppYea OTC 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 AppYea's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

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Forecasted Value

For the next trading day, Macroaxis evaluates AppYea's predictive range by looking for statistically meaningful downside and upside boundaries. The current forecast range spans downside near 0.0001 and upside near 9.97.

Market Value

0.01

0.0001

Downside

0.02

Expected Value

Target Odds

Above Odds

Below Odds

9.97

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 AppYea otc stock data series using in forecasting. Note that when a statistical model is used to represent AppYea otc 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	-1.0E-4
MAD	Mean absolute deviation	0.0014
MAPE	Mean absolute percentage error	0.076
SAE	Sum of the absolute errors	0.0814

As with simple exponential smoothing, in triple exponential smoothing models past AppYea 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 AppYea Inc observations.

Other Forecasting Options for AppYea

For every potential investor in AppYea, whether a beginner or expert, AppYea's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better.

AppYea Related Equities

The following equities are related to AppYea within the Software—Application space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing AppYea against peers on metrics such as P/E, margins, and return on equity helps contextualize its positioning and identify relative strengths or weaknesses.

SeaChange International Grow Capital Everything Blockchain Humbl Inc Killi BC Technology Group Elcom International KwikClick ZOO Digital Group RoboGroup TEK American Airlines Group Alcoa Corp Apple Inc Best Buy Co Citigroup

Risk & Return

Correlation

AppYea Market Strength Events

Market strength indicators help investors to evaluate how AppYea otc stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading AppYea shares will generate the highest return on.

	Rate Of Daily Change	1.01
	Day Median Price	0.015
	Day Typical Price	0.015
	Price Action Indicator	1.0E-4
	Period Momentum Indicator	1.0E-4
	Relative Strength Index	47.91

AppYea Risk Indicators

The analysis of AppYea's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in AppYea's investment and either accepting that risk or mitigating it.

	Mean Deviation	7.18
	Semi Deviation	8.08
	Standard Deviation	9.83
	Variance	96.68
	Downside Variance	84.98
	Semi Variance	65.22
	Expected Short fall	-8.49

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 AppYea

Coverage intensity for AppYea Inc 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.

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	Simple Exponential Smoothing
	Double Exponential Smoothing
	Triple Exponential Smoothing
	Simple Regression
	Polynomial Regression
	Simple Moving Average
	4 Period Moving Average
	8 Period Moving Average
	20 Period Moving Average