Synthetic Products Stock Forecast - Naive Prediction
| SPEL Stock | 45.22 4.11 10.00% |
The Naive Prediction forecasted value of Synthetic Products Enterprises on the next trading day is expected to be 46.46 with a mean absolute deviation of 1.39 and the sum of the absolute errors of 84.74. Synthetic Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Synthetic Products stock prices and determine the direction of Synthetic Products Enterprises's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Synthetic Products' historical fundamentals, such as revenue growth or operating cash flow patterns.
Synthetic |
Synthetic Products Naive Prediction Price Forecast For the 16th of December 2024
Given 90 days horizon, the Naive Prediction forecasted value of Synthetic Products Enterprises on the next trading day is expected to be 46.46 with a mean absolute deviation of 1.39, mean absolute percentage error of 3.07, and the sum of the absolute errors of 84.74.Please note that although there have been many attempts to predict Synthetic 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 Synthetic Products' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Synthetic Products Stock Forecast Pattern
| Backtest Synthetic Products | Synthetic Products Price Prediction | Buy or Sell Advice |
Synthetic Products Forecasted Value
In the context of forecasting Synthetic Products' 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. Synthetic Products' downside and upside margins for the forecasting period are 42.06 and 50.85, respectively. We have considered Synthetic Products' 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 Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Synthetic Products stock data series using in forecasting. Note that when a statistical model is used to represent Synthetic Products 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 | 119.2335 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 1.3893 |
| MAPE | Mean absolute percentage error | 0.0366 |
| SAE | Sum of the absolute errors | 84.745 |
Predictive Modules for Synthetic Products
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Synthetic Products. 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 Synthetic Products
For every potential investor in Synthetic, whether a beginner or expert, Synthetic Products' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Synthetic Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Synthetic. Basic forecasting techniques help filter out the noise by identifying Synthetic Products' price trends.Synthetic Products 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 Synthetic Products stock to make a market-neutral strategy. Peer analysis of Synthetic Products could also be used in its relative valuation, which is a method of valuing Synthetic Products by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Synthetic Products 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 Synthetic Products' 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 Synthetic Products' current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Synthetic Products Market Strength Events
Market strength indicators help investors to evaluate how Synthetic Products stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Synthetic Products shares will generate the highest return on investment. By undertsting and applying Synthetic Products stock market strength indicators, traders can identify Synthetic Products Enterprises entry and exit signals to maximize returns.
Synthetic Products Risk Indicators
The analysis of Synthetic Products' 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 Synthetic Products' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting synthetic 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 | 3.16 | |||
| Semi Deviation | 3.33 | |||
| Standard Deviation | 4.36 | |||
| Variance | 19.02 | |||
| Downside Variance | 11.98 | |||
| Semi Variance | 11.09 | |||
| Expected Short fall | (3.97) |
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.
Pair Trading with Synthetic Products
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Synthetic Products position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Synthetic Products will appreciate offsetting losses from the drop in the long position's value.Moving against Synthetic Stock
The ability to find closely correlated positions to Synthetic Products could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Synthetic Products when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Synthetic Products - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Synthetic Products Enterprises to buy it.
The correlation of Synthetic Products is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Synthetic Products moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Synthetic Products moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Synthetic Products can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Other Information on Investing in Synthetic Stock
Synthetic Products financial ratios help investors to determine whether Synthetic 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 Synthetic with respect to the benefits of owning Synthetic Products security.