UBS IF Fund Forecast - Polynomial Regression
| 0P00019WES | 237.43 0.00 0.00% |
UBS |
UBS IF Polynomial Regression Price Forecast For the 7th of January
Given 90 days horizon, the Polynomial Regression forecasted value of UBS IF Eqs on the next trading day is expected to be 235.63 with a mean absolute deviation of 2.13, mean absolute percentage error of 7.62, and the sum of the absolute errors of 129.66.Please note that although there have been many attempts to predict UBS 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 UBS IF's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
UBS IF Fund Forecast Pattern
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 UBS IF fund data series using in forecasting. Note that when a statistical model is used to represent UBS IF 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 | 120.1413 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 2.1256 |
| MAPE | Mean absolute percentage error | 0.0093 |
| SAE | Sum of the absolute errors | 129.6618 |
Predictive Modules for UBS IF
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as UBS IF Eqs. 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.UBS IF 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 UBS IF fund to make a market-neutral strategy. Peer analysis of UBS IF could also be used in its relative valuation, which is a method of valuing UBS IF by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
UBS IF Market Strength Events
Market strength indicators help investors to evaluate how UBS IF fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading UBS IF shares will generate the highest return on investment. By undertsting and applying UBS IF fund market strength indicators, traders can identify UBS IF Eqs entry and exit signals to maximize returns.
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 237.43 | |||
| Day Typical Price | 237.43 |
UBS IF Risk Indicators
The analysis of UBS IF'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 UBS IF's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting ubs 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 | 0.6634 | |||
| Semi Deviation | 0.8116 | |||
| Standard Deviation | 0.961 | |||
| Variance | 0.9235 | |||
| Downside Variance | 1.08 | |||
| Semi Variance | 0.6587 | |||
| Expected Short fall | (0.70) |
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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