Sellas Life Stock Forecast - Naive Prediction

SLS Stock  USD 1.17  0.05  4.10%   
The Naive Prediction forecasted value of Sellas Life Sciences on the next trading day is expected to be 1.15 with a mean absolute deviation of 0.03 and the sum of the absolute errors of 2.00. Sellas Stock Forecast is based on your current time horizon.
  
Asset Turnover is likely to gain to 0.07 in 2024, despite the fact that Inventory Turnover is likely to grow to (0.02). . Common Stock Shares Outstanding is likely to gain to about 29.2 M in 2024, whereas Net Loss is likely to drop (49.9 M) in 2024.
Forecasting cash, or other financial indicators, requires analysts to apply different statistical methods, techniques, and algorithms to find hidden patterns within the Sellas Life's financial statements to predict how it will affect future prices.
 
Cash  
First Reported
2006-12-31
Previous Quarter
9.2 M
Current Value
21.1 M
Quarterly Volatility
13.6 M
 
Housing Crash
 
Credit Downgrade
 
Yuan Drop
 
Covid
A naive forecasting model for Sellas Life is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Sellas Life Sciences value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period.

Sellas Life Naive Prediction Price Forecast For the 27th of November

Given 90 days horizon, the Naive Prediction forecasted value of Sellas Life Sciences on the next trading day is expected to be 1.15 with a mean absolute deviation of 0.03, mean absolute percentage error of 0, and the sum of the absolute errors of 2.00.
Please note that although there have been many attempts to predict Sellas 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 Sellas Life's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Sellas Life Stock Forecast Pattern

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Sellas Life Forecasted Value

In the context of forecasting Sellas Life'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. Sellas Life's downside and upside margins for the forecasting period are 0.01 and 4.26, respectively. We have considered Sellas Life'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
1.17
1.15
Expected Value
4.26
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Sellas Life stock data series using in forecasting. Note that when a statistical model is used to represent Sellas Life 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 Criteria111.7435
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0327
MAPEMean absolute percentage error0.0266
SAESum of the absolute errors1.9977
This model is not at all useful as a medium-long range forecasting tool of Sellas Life Sciences. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict Sellas Life. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights.

Predictive Modules for Sellas Life

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Sellas Life Sciences. 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
0.061.174.29
Details
Intrinsic
Valuation
LowRealHigh
0.122.345.46
Details
3 Analysts
Consensus
LowTargetHigh
5.466.006.66
Details

Other Forecasting Options for Sellas Life

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

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 Risk & Return  Correlation

Sellas Life Sciences 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 Sellas Life'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 Sellas Life's current price.

Sellas Life Market Strength Events

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

Sellas Life Risk Indicators

The analysis of Sellas Life'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 Sellas Life's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting sellas 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.

Thematic Opportunities

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Additional Tools for Sellas Stock Analysis

When running Sellas Life's price analysis, check to measure Sellas Life'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 Sellas Life is operating at the current time. Most of Sellas Life's value examination focuses on studying past and present price action to predict the probability of Sellas Life's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Sellas Life's price. Additionally, you may evaluate how the addition of Sellas Life to your portfolios can decrease your overall portfolio volatility.