The Triple Exponential Smoothing forecasted value of Li FT Power on the next trading day is expected to be 2.02 with a mean absolute deviation of 0.11 and the sum of the absolute errors of 6.67. Investors can use prediction functions to forecast Li-FT Power's stock prices and determine the direction of Li FT Power's future trends based on various well-known forecasting models. However, exclusively looking at the historical price movement is usually misleading. We recommend always using this module together with an analysis of Li-FT Power's historical fundamentals, such as revenue growth or operating cash flow patterns. Check out Your Current Watchlist to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in board of governors.
Li-FT
Triple exponential smoothing for Li-FT Power - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When Li-FT Power prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any trend in Li-FT Power price movement. However, neither of these exponential smoothing models address any seasonality of Li FT Power.
Li-FT Power Triple Exponential Smoothing Price Forecast For the 19th of January
Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Li FT Power on the next trading day is expected to be 2.02 with a mean absolute deviation of 0.11, mean absolute percentage error of 0.03, and the sum of the absolute errors of 6.67.
Please note that although there have been many attempts to predict Li-FT 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 Li-FT Power's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Li-FT Power Stock Forecast Pattern
Li-FT Power Forecasted Value
In the context of forecasting Li-FT Power'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. Li-FT Power's downside and upside margins for the forecasting period are 0.02 and 8.49, respectively. We have considered Li-FT Power'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.
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 Li-FT Power stock data series using in forecasting. Note that when a statistical model is used to represent Li-FT Power 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
0.0163
MAD
Mean absolute deviation
0.113
MAPE
Mean absolute percentage error
0.0536
SAE
Sum of the absolute errors
6.6688
As with simple exponential smoothing, in triple exponential smoothing models past Li-FT Power observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Li FT Power observations.
Predictive Modules for Li-FT Power
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Li FT Power. 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 Li-FT Power
For every potential investor in Li-FT, whether a beginner or expert, Li-FT Power's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Li-FT Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Li-FT. Basic forecasting techniques help filter out the noise by identifying Li-FT Power's price trends.
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 Li-FT Power stock to make a market-neutral strategy. Peer analysis of Li-FT Power could also be used in its relative valuation, which is a method of valuing Li-FT Power by comparing valuation metrics with similar companies.
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 Li-FT Power'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 Li-FT Power's current price.
Market strength indicators help investors to evaluate how Li-FT Power stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Li-FT Power shares will generate the highest return on investment. By undertsting and applying Li-FT Power stock market strength indicators, traders can identify Li FT Power entry and exit signals to maximize returns.
The analysis of Li-FT Power'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 Li-FT Power's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting li-ft 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.