Kingfa Science Stock Forecast - Triple Exponential Smoothing
| KINGFA Stock | 3,112 135.30 4.55% |
The Triple Exponential Smoothing forecasted value of Kingfa Science Technology on the next trading day is expected to be 3,116 with a mean absolute deviation of 56.53 and the sum of the absolute errors of 3,335. Kingfa Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Kingfa Science stock prices and determine the direction of Kingfa Science Technology's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Kingfa Science's historical fundamentals, such as revenue growth or operating cash flow patterns.
Kingfa |
Kingfa Science Triple Exponential Smoothing Price Forecast For the 2nd of December
Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Kingfa Science Technology on the next trading day is expected to be 3,116 with a mean absolute deviation of 56.53, mean absolute percentage error of 5,016, and the sum of the absolute errors of 3,335.Please note that although there have been many attempts to predict Kingfa 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 Kingfa Science's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Kingfa Science Stock Forecast Pattern
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Kingfa Science Forecasted Value
In the context of forecasting Kingfa 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. Kingfa Science's downside and upside margins for the forecasting period are 3,114 and 3,118, respectively. We have considered Kingfa 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 Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Kingfa Science stock data series using in forecasting. Note that when a statistical model is used to represent Kingfa 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 | Huge |
| Bias | Arithmetic mean of the errors | -13.5763 |
| MAD | Mean absolute deviation | 56.5289 |
| MAPE | Mean absolute percentage error | 0.0178 |
| SAE | Sum of the absolute errors | 3335.2062 |
Predictive Modules for Kingfa 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 Kingfa Science Technology. 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 Kingfa Science
For every potential investor in Kingfa, whether a beginner or expert, Kingfa Science's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Kingfa Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Kingfa. Basic forecasting techniques help filter out the noise by identifying Kingfa Science's price trends.Kingfa 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 Kingfa Science stock to make a market-neutral strategy. Peer analysis of Kingfa Science could also be used in its relative valuation, which is a method of valuing Kingfa Science by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Kingfa Science Technology 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 Kingfa 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 Kingfa Science's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Kingfa Science Market Strength Events
Market strength indicators help investors to evaluate how Kingfa 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 Kingfa Science shares will generate the highest return on investment. By undertsting and applying Kingfa Science stock market strength indicators, traders can identify Kingfa Science Technology entry and exit signals to maximize returns.
| Accumulation Distribution | 0.0767 | |||
| Daily Balance Of Power | 0.5612 | |||
| Rate Of Daily Change | 1.05 | |||
| Day Median Price | 3023.45 | |||
| Day Typical Price | 3053.0 | |||
| Market Facilitation Index | 241.1 | |||
| Price Action Indicator | 156.3 | |||
| Period Momentum Indicator | 135.3 |
Kingfa Science Risk Indicators
The analysis of Kingfa 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 Kingfa Science's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting kingfa 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 | 1.74 | |||
| Standard Deviation | 2.22 | |||
| Variance | 4.93 |
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 Kingfa Stock
Kingfa Science financial ratios help investors to determine whether Kingfa 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 Kingfa with respect to the benefits of owning Kingfa Science security.