Burlington Stores Stock Forecast - Naive Prediction
| BUI Stock | EUR 274.00 2.00 0.72% |
The Naive Prediction forecasted value of Burlington Stores on the next trading day is expected to be 265.73 with a mean absolute deviation of 4.03 and the sum of the absolute errors of 245.91. Burlington Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Burlington Stores' historical fundamentals, such as revenue growth or operating cash flow patterns.
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Burlington Stores Naive Prediction Price Forecast For the 13th of December 2024
Given 90 days horizon, the Naive Prediction forecasted value of Burlington Stores on the next trading day is expected to be 265.73 with a mean absolute deviation of 4.03, mean absolute percentage error of 29.10, and the sum of the absolute errors of 245.91.Please note that although there have been many attempts to predict Burlington 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 Burlington Stores' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Burlington Stores Stock Forecast Pattern
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Burlington Stores Forecasted Value
In the context of forecasting Burlington Stores' 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. Burlington Stores' downside and upside margins for the forecasting period are 263.51 and 267.95, respectively. We have considered Burlington Stores' 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 Burlington Stores stock data series using in forecasting. Note that when a statistical model is used to represent Burlington Stores 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 | 121.4811 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 4.0314 |
| MAPE | Mean absolute percentage error | 0.0165 |
| SAE | Sum of the absolute errors | 245.9129 |
Predictive Modules for Burlington Stores
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Burlington Stores. 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 Burlington Stores
For every potential investor in Burlington, whether a beginner or expert, Burlington Stores' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Burlington Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Burlington. Basic forecasting techniques help filter out the noise by identifying Burlington Stores' price trends.Burlington Stores 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 Burlington Stores stock to make a market-neutral strategy. Peer analysis of Burlington Stores could also be used in its relative valuation, which is a method of valuing Burlington Stores by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Burlington Stores 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 Burlington Stores' 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 Burlington Stores' current price.| Cycle Indicators | ||
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| Math Transform | ||
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| Overlap Studies | ||
| Pattern Recognition | ||
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| Volume Indicators |
Burlington Stores Market Strength Events
Market strength indicators help investors to evaluate how Burlington Stores stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Burlington Stores shares will generate the highest return on investment. By undertsting and applying Burlington Stores stock market strength indicators, traders can identify Burlington Stores entry and exit signals to maximize returns.
| Daily Balance Of Power | (9,223,372,036,855) | |||
| Rate Of Daily Change | 0.99 | |||
| Day Median Price | 274.0 | |||
| Day Typical Price | 274.0 | |||
| Price Action Indicator | (1.00) | |||
| Period Momentum Indicator | (2.00) | |||
| Relative Strength Index | 65.17 |
Burlington Stores Risk Indicators
The analysis of Burlington Stores' 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 Burlington Stores' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting burlington 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 | 1.6 | |||
| Semi Deviation | 1.8 | |||
| Standard Deviation | 2.22 | |||
| Variance | 4.93 | |||
| Downside Variance | 5.61 | |||
| Semi Variance | 3.23 | |||
| Expected Short fall | (2.14) |
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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Additional Information and Resources on Investing in Burlington Stock
When determining whether Burlington Stores is a strong investment it is important to analyze Burlington Stores' competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact Burlington Stores' future performance. For an informed investment choice regarding Burlington Stock, refer to the following important reports:Check out Historical Fundamental Analysis of Burlington Stores to cross-verify your projections. For more detail on how to invest in Burlington Stock please use our How to Invest in Burlington Stores guide.You can also try the Portfolio Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.