John Hancock Etf Forecast - Double Exponential Smoothing
| JHML Etf | USD 73.25 0.33 0.45% |
The Double Exponential Smoothing forecasted value of John Hancock Multifactor on the next trading day is expected to be 73.45 with a mean absolute deviation of 0.42 and the sum of the absolute errors of 25.48. John Etf Forecast is based on your current time horizon.
John |
John Hancock Double Exponential Smoothing Price Forecast For the 1st of December
Given 90 days horizon, the Double Exponential Smoothing forecasted value of John Hancock Multifactor on the next trading day is expected to be 73.45 with a mean absolute deviation of 0.42, mean absolute percentage error of 0.31, and the sum of the absolute errors of 25.48.Please note that although there have been many attempts to predict John Etf 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 John Hancock's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
John Hancock Etf Forecast Pattern
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John Hancock Forecasted Value
In the context of forecasting John Hancock's Etf 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. John Hancock's downside and upside margins for the forecasting period are 72.76 and 74.15, respectively. We have considered John Hancock'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.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of John Hancock etf data series using in forecasting. Note that when a statistical model is used to represent John Hancock etf, 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 | Huge |
| Bias | Arithmetic mean of the errors | -0.0471 |
| MAD | Mean absolute deviation | 0.4246 |
| MAPE | Mean absolute percentage error | 0.0061 |
| SAE | Sum of the absolute errors | 25.4759 |
Predictive Modules for John Hancock
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as John Hancock Multifactor. Regardless of method or technology, however, to accurately forecast the etf market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the etf 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 John Hancock
For every potential investor in John, whether a beginner or expert, John Hancock's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. John Etf price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in John. Basic forecasting techniques help filter out the noise by identifying John Hancock's price trends.John Hancock 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 John Hancock etf to make a market-neutral strategy. Peer analysis of John Hancock could also be used in its relative valuation, which is a method of valuing John Hancock by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
John Hancock Multifactor Technical and Predictive Analytics
The etf market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of John Hancock'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 John Hancock's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
John Hancock Market Strength Events
Market strength indicators help investors to evaluate how John Hancock etf reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading John Hancock shares will generate the highest return on investment. By undertsting and applying John Hancock etf market strength indicators, traders can identify John Hancock Multifactor entry and exit signals to maximize returns.
John Hancock Risk Indicators
The analysis of John Hancock'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 John Hancock's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting john etf 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 | 0.5314 | |||
| Semi Deviation | 0.5496 | |||
| Standard Deviation | 0.727 | |||
| Variance | 0.5285 | |||
| Downside Variance | 0.5019 | |||
| Semi Variance | 0.3021 | |||
| Expected Short fall | (0.59) |
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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The market value of John Hancock Multifactor is measured differently than its book value, which is the value of John that is recorded on the company's balance sheet. Investors also form their own opinion of John Hancock's value that differs from its market value or its book value, called intrinsic value, which is John Hancock's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because John Hancock's market value can be influenced by many factors that don't directly affect John Hancock's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between John Hancock's value and its price as these two are different measures arrived at by different means. Investors typically determine if John Hancock is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, John Hancock's 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.