Butterfly Network Stock Forecast - Simple Moving Average

BFLY Stock  USD 3.54  0.07  1.94%   
The Simple Moving Average forecasted value of Butterfly Network on the next trading day is expected to be 3.54 with a mean absolute deviation of 0.11 and the sum of the absolute errors of 6.78. Butterfly Stock Forecast is based on your current time horizon.
  
At this time, Butterfly Network's Receivables Turnover is fairly stable compared to the past year. Fixed Asset Turnover is likely to rise to 3.20 in 2024, whereas Inventory Turnover is likely to drop 0.64 in 2024. . Common Stock Shares Outstanding is likely to drop to about 130.1 M in 2024. Net Loss is likely to drop to about (159.4 M) in 2024.
A two period moving average forecast for Butterfly Network 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.

Butterfly Network Simple Moving Average Price Forecast For the 14th of December 2024

Given 90 days horizon, the Simple Moving Average forecasted value of Butterfly Network on the next trading day is expected to be 3.54 with a mean absolute deviation of 0.11, mean absolute percentage error of 0.03, and the sum of the absolute errors of 6.78.
Please note that although there have been many attempts to predict Butterfly Stock prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Butterfly Network's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Butterfly Network Stock Forecast Pattern

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Butterfly Network Forecasted Value

In the context of forecasting Butterfly Network's Stock value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Butterfly Network's downside and upside margins for the forecasting period are 0.04 and 9.40, respectively. We have considered Butterfly Network's daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Market Value
3.54
3.54
Expected Value
9.40
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 Butterfly Network stock data series using in forecasting. Note that when a statistical model is used to represent Butterfly Network 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 Criteria112.6112
BiasArithmetic mean of the errors -0.0406
MADMean absolute deviation0.1131
MAPEMean absolute percentage error0.0487
SAESum of the absolute errors6.785
The simple moving average model is conceptually a linear regression of the current value of Butterfly Network price series against current and previous (unobserved) value of Butterfly Network. 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

Predictive Modules for Butterfly Network

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Butterfly Network. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.
Hype
Prediction
LowEstimatedHigh
0.193.799.65
Details
Intrinsic
Valuation
LowRealHigh
0.173.319.18
Details
3 Analysts
Consensus
LowTargetHigh
3.193.503.89
Details
Earnings
Estimates (0)
LowProjected EPSHigh
-0.09-0.07-0.06
Details

Other Forecasting Options for Butterfly Network

For every potential investor in Butterfly, whether a beginner or expert, Butterfly Network's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Butterfly Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Butterfly. Basic forecasting techniques help filter out the noise by identifying Butterfly Network's price trends.

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 Risk & Return  Correlation

Butterfly Network Technical and Predictive Analytics

The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Butterfly Network's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Butterfly Network's current price.

Butterfly Network Market Strength Events

Market strength indicators help investors to evaluate how Butterfly Network stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Butterfly Network shares will generate the highest return on investment. By undertsting and applying Butterfly Network stock market strength indicators, traders can identify Butterfly Network entry and exit signals to maximize returns.

Butterfly Network Risk Indicators

The analysis of Butterfly Network'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 Butterfly Network's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting butterfly stock prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
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.

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Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.

Additional Tools for Butterfly Stock Analysis

When running Butterfly Network's price analysis, check to measure Butterfly Network's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Butterfly Network is operating at the current time. Most of Butterfly Network's value examination focuses on studying past and present price action to predict the probability of Butterfly Network's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Butterfly Network's price. Additionally, you may evaluate how the addition of Butterfly Network to your portfolios can decrease your overall portfolio volatility.