Macquarie Bank Stock Forecast - Polynomial Regression

MBLPD Stock   104.01  0.01  0.01%   
The Polynomial Regression forecasted value of Macquarie Bank Limited on the next trading day is expected to be 103.08 with a mean absolute deviation of 0.39 and the sum of the absolute errors of 24.24. Macquarie Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Macquarie Bank stock prices and determine the direction of Macquarie Bank Limited's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Macquarie Bank's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
Macquarie Bank polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Macquarie Bank Limited as well as the accuracy indicators are determined from the period prices.

Macquarie Bank Polynomial Regression Price Forecast For the 1st of December

Given 90 days horizon, the Polynomial Regression forecasted value of Macquarie Bank Limited on the next trading day is expected to be 103.08 with a mean absolute deviation of 0.39, mean absolute percentage error of 0.28, and the sum of the absolute errors of 24.24.
Please note that although there have been many attempts to predict Macquarie 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 Macquarie Bank's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Macquarie Bank Stock Forecast Pattern

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Macquarie Bank Forecasted Value

In the context of forecasting Macquarie Bank'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. Macquarie Bank's downside and upside margins for the forecasting period are 102.60 and 103.55, respectively. We have considered Macquarie Bank'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
104.01
102.60
Downside
103.08
Expected Value
103.55
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 Macquarie Bank stock data series using in forecasting. Note that when a statistical model is used to represent Macquarie Bank 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 Criteria118.6921
BiasArithmetic mean of the errors None
MADMean absolute deviation0.391
MAPEMean absolute percentage error0.0038
SAESum of the absolute errors24.2403
A single variable polynomial regression model attempts to put a curve through the Macquarie Bank 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 Macquarie Bank

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Macquarie Bank. 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 Macquarie Bank's 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
103.49103.97104.45
Details
Intrinsic
Valuation
LowRealHigh
103.13103.61104.09
Details
Bollinger
Band Projection (param)
LowMiddleHigh
101.99103.05104.11
Details

Other Forecasting Options for Macquarie Bank

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

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

Macquarie Bank 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 Macquarie Bank'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 Macquarie Bank's current price.

Macquarie Bank Market Strength Events

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

Macquarie Bank Risk Indicators

The analysis of Macquarie Bank'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 Macquarie Bank's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting macquarie 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

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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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Other Information on Investing in Macquarie Stock

Macquarie Bank financial ratios help investors to determine whether Macquarie 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 Macquarie with respect to the benefits of owning Macquarie Bank security.