Monad Crypto Coin Forward View - Simple Moving Average

MON Crypto  USD 0.02  -0.001  -4.46%   
This reference page presents Simple Moving Average forecast data for Monad. The projected values and error metrics are presented below as reference information. The output values and deviation metrics are provided for informational reference.
The Simple Moving Average forecasted value of Monad on the next trading day is expected to be 0.02 with a mean absolute deviation of 0.0011 and the sum of the absolute errors of 0.07.The simple moving average model is conceptually a linear regression of the current value of Monad price series against current and previous (unobserved) value of Monad. In time series analysis, the simple moving-average model is a very common approach for modeling univariate price series models including forecasting prices into the future This Simple Moving Average forecast data for Monad is sourced from the most recent available trading data and is intended solely as reference information.
A two period moving average forecast for Monad is based on an daily price series in which the stock price on a given day is replaced by the mean of that price and the preceding price. This model is best suited to price patterns experiencing average volatility.

Simple Moving Average Price Forecast For the 23rd of March

Given 90 days horizon, the Simple Moving Average forecasted value of Monad on the next trading day is expected to be 0.02 with a mean absolute deviation of 0.0011 , mean absolute percentage error of 0.00000345 , and the sum of the absolute errors of 0.07 .
Please note that although there have been many attempts to predict Monad Crypto Coin 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 Monad's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Crypto Coin Forecast Pattern

Forecasted Value

Forecasting Monad 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.
Market Value
0.02
0.0002
Downside
0.02
Expected Value
8.58
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Moving Average forecasting method's relative quality and the estimations of the prediction error of Monad crypto coin data series using in forecasting. Note that when a statistical model is used to represent Monad crypto coin, 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 Criteria101.8569
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0011
MAPEMean absolute percentage error0.0509
SAESum of the absolute errors0.066
The simple moving average model is conceptually a linear regression of the current value of Monad price series against current and previous (unobserved) value of Monad. In time series analysis, the simple moving-average model is a very common approach for modeling univariate price series models including forecasting prices into the future

Other Forecasting Options for Monad

Monad's daily price returns can be decomposed into trend, seasonal, and residual components. Divergence between short-term and long-term averages in Monad often signals an upcoming reversal or acceleration. Gap analysis of Monad Crypto Coin data examines overnight jumps between Monad's closing and opening prices.

Monad Related Equities

Investors studying Monad often look at related stocks within the Cryptocurrency space to gauge pricing and results. Profit comparisons show whether Monad earns above or below average returns next to its peers.
 Risk & Return  Correlation

Monad Market Strength Events

Market strength indicators help investors evaluate how Monad crypto coin reacts to evolving market conditions. These indicators help determine optimal entry and exit points for trading Monad. These indicators can identify periods when trading Monad may offer more favorable risk-reward conditions.

Monad Risk Indicators

The analysis of Monad's basic risk indicators is one of the essential steps in accurately forecasting its future price. Understanding the risk involved in holding Monad's allows investors to make informed decisions about their exposure. The analysis of Monad's basic risk metrics provides a foundation for managing investment risk.
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 Monad

A coverage review of Monad shows when the security is attracting above-average attention from contributors and market observers. 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.

More Resources for Monad Crypto Coin Analysis

Reviewing Monad typically starts with core financial statements and performance trends. All figures are aligned with Monad's latest available data.
Cross-checking projections for Monad against Historical Fundamental Analysis of Monad can provide additional context.
Monad currently shows market cap of 6.72 Million. This analysis of Monad works best as a complementary layer when evaluating how the security fits in a broader portfolio. For Monad, the analytical tools below add portfolio-level context that single-security review alone cannot provide. You can also try the Crypto Correlations module to use cryptocurrency correlation module to diversify your cryptocurrency portfolio across multiple coins.
It is useful to distinguish Monad's network value from its trading price, since each reflects a different lens. Value context can include adoption, utility, network security, and ecosystem activity.