Panda Financial Stock Forecast - Triple Exponential Smoothing

600599 Stock   14.32  0.62  4.53%   
The Triple Exponential Smoothing forecasted value of Panda Financial Holding on the next trading day is expected to be 14.29 with a mean absolute deviation of 0.33 and the sum of the absolute errors of 19.58. Panda Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Panda Financial stock prices and determine the direction of Panda Financial Holding's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Panda Financial's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
At present, Panda Financial's Total Current Liabilities is projected to decrease significantly based on the last few years of reporting. The current year's Cash is expected to grow to about 410.4 M, whereas Total Assets are forecasted to decline to about 727.5 M.
Triple exponential smoothing for Panda Financial - 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 Panda Financial 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 Panda Financial price movement. However, neither of these exponential smoothing models address any seasonality of Panda Financial Holding.

Panda Financial Triple Exponential Smoothing Price Forecast For the 27th of November

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Panda Financial Holding on the next trading day is expected to be 14.29 with a mean absolute deviation of 0.33, mean absolute percentage error of 0.16, and the sum of the absolute errors of 19.58.
Please note that although there have been many attempts to predict Panda 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 Panda Financial's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Panda Financial Stock Forecast Pattern

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Panda Financial Forecasted Value

In the context of forecasting Panda Financial'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. Panda Financial's downside and upside margins for the forecasting period are 11.14 and 17.44, respectively. We have considered Panda Financial'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
14.32
14.29
Expected Value
17.44
Upside

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 Panda Financial stock data series using in forecasting. Note that when a statistical model is used to represent Panda Financial 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 CriteriaHuge
BiasArithmetic mean of the errors -0.1142
MADMean absolute deviation0.3319
MAPEMean absolute percentage error0.0271
SAESum of the absolute errors19.58
As with simple exponential smoothing, in triple exponential smoothing models past Panda Financial 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 Panda Financial Holding observations.

Predictive Modules for Panda Financial

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Panda Financial Holding. 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
11.6214.7717.92
Details
Intrinsic
Valuation
LowRealHigh
8.0611.2114.36
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Panda Financial. Your research has to be compared to or analyzed against Panda Financial's peers to derive any actionable benefits. When done correctly, Panda Financial's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Panda Financial Holding.

Other Forecasting Options for Panda Financial

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

Panda Financial 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 Panda Financial stock to make a market-neutral strategy. Peer analysis of Panda Financial could also be used in its relative valuation, which is a method of valuing Panda Financial by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Panda Financial Holding 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 Panda Financial'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 Panda Financial's current price.

Panda Financial Market Strength Events

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

Panda Financial Risk Indicators

The analysis of Panda Financial'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 Panda Financial's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting panda 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.

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Other Information on Investing in Panda Stock

Panda Financial financial ratios help investors to determine whether Panda 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 Panda with respect to the benefits of owning Panda Financial security.