Online Brands Stock Forecast - Naive Prediction

OBAB Stock  SEK 10.55  0.30  2.76%   
The Naive Prediction forecasted value of Online Brands Nordic on the next trading day is expected to be 12.16 with a mean absolute deviation of 0.56 and the sum of the absolute errors of 34.41. Online Stock Forecast is based on your current time horizon.
  
A naive forecasting model for Online Brands is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Online Brands Nordic 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.

Online Brands Naive Prediction Price Forecast For the 23rd of November

Given 90 days horizon, the Naive Prediction forecasted value of Online Brands Nordic on the next trading day is expected to be 12.16 with a mean absolute deviation of 0.56, mean absolute percentage error of 0.49, and the sum of the absolute errors of 34.41.
Please note that although there have been many attempts to predict Online 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 Online Brands' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Online Brands Stock Forecast Pattern

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Online Brands Forecasted Value

In the context of forecasting Online Brands' 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. Online Brands' downside and upside margins for the forecasting period are 7.20 and 17.13, respectively. We have considered Online Brands' 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
10.55
12.16
Expected Value
17.13
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 Online Brands stock data series using in forecasting. Note that when a statistical model is used to represent Online Brands 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 Criteria117.3876
BiasArithmetic mean of the errors None
MADMean absolute deviation0.5642
MAPEMean absolute percentage error0.048
SAESum of the absolute errors34.4141
This model is not at all useful as a medium-long range forecasting tool of Online Brands Nordic. 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 Online Brands. 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 Online Brands

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Online Brands Nordic. 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
5.9010.8515.80
Details
Intrinsic
Valuation
LowRealHigh
4.929.8714.82
Details
Bollinger
Band Projection (param)
LowMiddleHigh
9.4011.1412.89
Details

Other Forecasting Options for Online Brands

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

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

Online Brands Nordic 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 Online Brands' 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 Online Brands' current price.

Online Brands Market Strength Events

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

Online Brands Risk Indicators

The analysis of Online Brands' 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 Online Brands' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting online 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.

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 Online Stock Analysis

When running Online Brands' price analysis, check to measure Online Brands' 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 Online Brands is operating at the current time. Most of Online Brands' value examination focuses on studying past and present price action to predict the probability of Online Brands' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Online Brands' price. Additionally, you may evaluate how the addition of Online Brands to your portfolios can decrease your overall portfolio volatility.