Four Leaf Stock Forecast - Naive Prediction

FORLU Stock   11.03  0.00  0.00%   
The Naive Prediction forecasted value of Four Leaf Acquisition on the next trading day is expected to be 11.03 with a mean absolute deviation of 0 and the sum of the absolute errors of 0. Four Stock Forecast is based on your current time horizon.
  
Forecasting cash, or other financial indicators, requires analysts to apply different statistical methods, techniques, and algorithms to find hidden patterns within the Four Leaf's financial statements to predict how it will affect future prices.
 
Cash  
First Reported
2010-12-31
Previous Quarter
10.6 K
Current Value
6.5 K
Quarterly Volatility
2.7 K
 
Credit Downgrade
 
Yuan Drop
 
Covid
A naive forecasting model for Four Leaf is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Four Leaf Acquisition value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period.

Four Leaf Naive Prediction Price Forecast For the 3rd of December

Given 90 days horizon, the Naive Prediction forecasted value of Four Leaf Acquisition on the next trading day is expected to be 11.03 with a mean absolute deviation of 0, mean absolute percentage error of 0, and the sum of the absolute errors of 0.
Please note that although there have been many attempts to predict Four 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 Four Leaf's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Four Leaf Stock Forecast Pattern

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Four Leaf Forecasted Value

In the context of forecasting Four Leaf'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. Four Leaf's downside and upside margins for the forecasting period are 11.03 and 11.03, respectively. We have considered Four Leaf'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
11.03
11.03
Expected Value
11.03
Upside

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 Four Leaf stock data series using in forecasting. Note that when a statistical model is used to represent Four Leaf 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 Criteria55.9303
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0
MAPEMean absolute percentage error0.0
SAESum of the absolute errors0.0
This model is not at all useful as a medium-long range forecasting tool of Four Leaf Acquisition. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict Four Leaf. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights.

Predictive Modules for Four Leaf

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Four Leaf Acquisition. 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
11.0311.0311.03
Details
Intrinsic
Valuation
LowRealHigh
11.0311.0311.03
Details
Bollinger
Band Projection (param)
LowMiddleHigh
11.0311.0311.03
Details

Other Forecasting Options for Four Leaf

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

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

Four Leaf Acquisition 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 Four Leaf'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 Four Leaf's current price.

Four Leaf Market Strength Events

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

Thematic Opportunities

Explore Investment Opportunities

Build portfolios using Macroaxis predefined set of investing ideas. Many of Macroaxis investing ideas can easily outperform a given market. Ideas can also be optimized per your risk profile before portfolio origination is invoked. Macroaxis thematic optimization helps investors identify companies most likely to benefit from changes or shifts in various micro-economic or local macro-level trends. Originating optimal thematic portfolios involves aligning investors' personal views, ideas, and beliefs with their actual investments.
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Additional Tools for Four Stock Analysis

When running Four Leaf's price analysis, check to measure Four Leaf's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Four Leaf is operating at the current time. Most of Four Leaf's value examination focuses on studying past and present price action to predict the probability of Four Leaf's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Four Leaf's price. Additionally, you may evaluate how the addition of Four Leaf to your portfolios can decrease your overall portfolio volatility.