Morgan Stanley Fund Forecast - Polynomial Regression
| CAF Fund | USD 12.28 0.05 0.41% |
The Polynomial Regression forecasted value of Morgan Stanley China on the next trading day is expected to be 12.19 with a mean absolute deviation of 0.47 and the sum of the absolute errors of 28.94. Morgan Fund Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Morgan Stanley's historical fundamentals, such as revenue growth or operating cash flow patterns.
Morgan |
Morgan Stanley Polynomial Regression Price Forecast For the 27th of November
Given 90 days horizon, the Polynomial Regression forecasted value of Morgan Stanley China on the next trading day is expected to be 12.19 with a mean absolute deviation of 0.47, mean absolute percentage error of 0.45, and the sum of the absolute errors of 28.94.Please note that although there have been many attempts to predict Morgan Fund 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 Morgan Stanley's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Morgan Stanley Fund Forecast Pattern
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Morgan Stanley Forecasted Value
In the context of forecasting Morgan Stanley's Fund 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. Morgan Stanley's downside and upside margins for the forecasting period are 9.35 and 15.02, respectively. We have considered Morgan Stanley'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 Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Morgan Stanley fund data series using in forecasting. Note that when a statistical model is used to represent Morgan Stanley fund, 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 | 117.308 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.4745 |
| MAPE | Mean absolute percentage error | 0.0368 |
| SAE | Sum of the absolute errors | 28.9436 |
Predictive Modules for Morgan Stanley
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Morgan Stanley China. Regardless of method or technology, however, to accurately forecast the fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the fund 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 Morgan Stanley
For every potential investor in Morgan, whether a beginner or expert, Morgan Stanley's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Morgan Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Morgan. Basic forecasting techniques help filter out the noise by identifying Morgan Stanley's price trends.Morgan Stanley 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 Morgan Stanley fund to make a market-neutral strategy. Peer analysis of Morgan Stanley could also be used in its relative valuation, which is a method of valuing Morgan Stanley by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Morgan Stanley China Technical and Predictive Analytics
The fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Morgan Stanley'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 Morgan Stanley's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Morgan Stanley Market Strength Events
Market strength indicators help investors to evaluate how Morgan Stanley fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Morgan Stanley shares will generate the highest return on investment. By undertsting and applying Morgan Stanley fund market strength indicators, traders can identify Morgan Stanley China entry and exit signals to maximize returns.
| Accumulation Distribution | 186.78 | |||
| Daily Balance Of Power | (0.56) | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 12.32 | |||
| Day Typical Price | 12.3 | |||
| Price Action Indicator | (0.06) | |||
| Period Momentum Indicator | (0.05) |
Morgan Stanley Risk Indicators
The analysis of Morgan Stanley'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 Morgan Stanley's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting morgan fund 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 | 1.78 | |||
| Semi Deviation | 2.54 | |||
| Standard Deviation | 2.8 | |||
| Variance | 7.82 | |||
| Downside Variance | 7.64 | |||
| Semi Variance | 6.43 | |||
| Expected Short fall | (1.95) |
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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Other Information on Investing in Morgan Fund
Morgan Stanley financial ratios help investors to determine whether Morgan Fund 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 Morgan with respect to the benefits of owning Morgan Stanley security.
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