Novartis Stock Forecast - Polynomial Regression

NOVN Stock  CHF 89.50  0.50  0.56%   
The Polynomial Regression forecasted value of Novartis AG on the next trading day is expected to be 89.13 with a mean absolute deviation of  0.95  and the sum of the absolute errors of 57.71. Novartis Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Novartis stock prices and determine the direction of Novartis AG's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Novartis' historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Novartis to cross-verify your projections.
  
Most investors in Novartis cannot accurately predict what will happen the next trading day because, historically, stock markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the Novartis' time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Novartis' price structures and extracts relationships that further increase the generated results' accuracy.
Novartis polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Novartis AG as well as the accuracy indicators are determined from the period prices.

Novartis Polynomial Regression Price Forecast For the 30th of April

Given 90 days horizon, the Polynomial Regression forecasted value of Novartis AG on the next trading day is expected to be 89.13 with a mean absolute deviation of 0.95, mean absolute percentage error of 1.35, and the sum of the absolute errors of 57.71.
Please note that although there have been many attempts to predict Novartis 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 Novartis' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Novartis Stock Forecast Pattern

Backtest NovartisNovartis Price PredictionBuy or Sell Advice 

Novartis Forecasted Value

In the context of forecasting Novartis' 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. Novartis' downside and upside margins for the forecasting period are 88.02 and 90.24, respectively. We have considered Novartis' 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
89.50
89.13
Expected Value
90.24
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Novartis stock data series using in forecasting. Note that when a statistical model is used to represent Novartis 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 Criteria118.411
BiasArithmetic mean of the errors None
MADMean absolute deviation0.946
MAPEMean absolute percentage error0.0109
SAESum of the absolute errors57.707
A single variable polynomial regression model attempts to put a curve through the Novartis historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm

Predictive Modules for Novartis

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Novartis AG. 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.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Novartis' price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Hype
Prediction
LowEstimatedHigh
88.3989.5090.61
Details
Intrinsic
Valuation
LowRealHigh
87.2788.3898.45
Details
Bollinger
Band Projection (param)
LowMiddleHigh
83.9786.8189.64
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Novartis. Your research has to be compared to or analyzed against Novartis' peers to derive any actionable benefits. When done correctly, Novartis' 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 Novartis AG.

Other Forecasting Options for Novartis

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

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

Novartis AG 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 Novartis' 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 Novartis' current price.

Novartis Market Strength Events

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

Novartis Risk Indicators

The analysis of Novartis' 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 Novartis' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting novartis 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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Check out Historical Fundamental Analysis of Novartis to cross-verify your projections.
You can also try the Aroon Oscillator module to analyze current equity momentum using Aroon Oscillator and other momentum ratios.

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When running Novartis' price analysis, check to measure Novartis' 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 Novartis is operating at the current time. Most of Novartis' value examination focuses on studying past and present price action to predict the probability of Novartis' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Novartis' price. Additionally, you may evaluate how the addition of Novartis to your portfolios can decrease your overall portfolio volatility.
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Please note, there is a significant difference between Novartis' value and its price as these two are different measures arrived at by different means. Investors typically determine if Novartis is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Novartis' price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.