Clean Science Stock Forecast - Simple Exponential Smoothing
| CLEAN Stock | 1,284 0.50 0.04% |
The Simple Exponential Smoothing forecasted value of Clean Science and on the next trading day is expected to be 1,284 with a mean absolute deviation of 20.78 and the sum of the absolute errors of 1,247. Clean Stock Forecast is based on your current time horizon. Although Clean Science's naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of Clean Science's systematic risk associated with finding meaningful patterns of Clean Science fundamentals over time.
Clean |
Clean Science Simple Exponential Smoothing Price Forecast For the 30th of November
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Clean Science and on the next trading day is expected to be 1,284 with a mean absolute deviation of 20.78, mean absolute percentage error of 809.14, and the sum of the absolute errors of 1,247.Please note that although there have been many attempts to predict Clean 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 Clean Science's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Clean Science Stock Forecast Pattern
| Backtest Clean Science | Clean Science Price Prediction | Buy or Sell Advice |
Clean Science Forecasted Value
In the context of forecasting Clean Science'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. Clean Science's downside and upside margins for the forecasting period are 1,282 and 1,286, respectively. We have considered Clean Science'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.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Clean Science stock data series using in forecasting. Note that when a statistical model is used to represent Clean Science 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 | 122.9686 |
| Bias | Arithmetic mean of the errors | 3.7058 |
| MAD | Mean absolute deviation | 20.7825 |
| MAPE | Mean absolute percentage error | 0.0139 |
| SAE | Sum of the absolute errors | 1246.95 |
Predictive Modules for Clean Science
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Clean Science. 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.Other Forecasting Options for Clean Science
For every potential investor in Clean, whether a beginner or expert, Clean Science's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Clean Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Clean. Basic forecasting techniques help filter out the noise by identifying Clean Science's price trends.Clean Science Related Equities
One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with Clean Science stock to make a market-neutral strategy. Peer analysis of Clean Science could also be used in its relative valuation, which is a method of valuing Clean Science by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Clean Science 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 Clean Science'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 Clean Science's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Clean Science Market Strength Events
Market strength indicators help investors to evaluate how Clean Science stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Clean Science shares will generate the highest return on investment. By undertsting and applying Clean Science stock market strength indicators, traders can identify Clean Science and entry and exit signals to maximize returns.
| Accumulation Distribution | 3093.15 | |||
| Daily Balance Of Power | 0.0181 | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 1292.4 | |||
| Day Typical Price | 1289.67 | |||
| Market Facilitation Index | 2.0E-4 | |||
| Price Action Indicator | (7.95) | |||
| Period Momentum Indicator | 0.5 |
Clean Science Risk Indicators
The analysis of Clean Science'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 Clean Science's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting clean 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.
| Mean Deviation | 1.38 | |||
| Standard Deviation | 1.84 | |||
| Variance | 3.39 |
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.
Also Currently Popular
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.Other Information on Investing in Clean Stock
Clean Science financial ratios help investors to determine whether Clean Stock is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Clean with respect to the benefits of owning Clean Science security.