Pimco Municipal Fund Forecast - Simple Exponential Smoothing
| PML Fund | USD 8.88 0.09 1.02% |
The Simple Exponential Smoothing forecasted value of Pimco Municipal Income on the next trading day is expected to be 8.88 with a mean absolute deviation of 0.07 and the sum of the absolute errors of 4.13. Pimco Fund Forecast is based on your current time horizon.
Pimco |
Pimco Municipal Simple Exponential Smoothing Price Forecast For the 30th of November
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Pimco Municipal Income on the next trading day is expected to be 8.88 with a mean absolute deviation of 0.07, mean absolute percentage error of 0.01, and the sum of the absolute errors of 4.13.Please note that although there have been many attempts to predict Pimco 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 Pimco Municipal's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Pimco Municipal Fund Forecast Pattern
| Backtest Pimco Municipal | Pimco Municipal Price Prediction | Buy or Sell Advice |
Pimco Municipal Forecasted Value
In the context of forecasting Pimco Municipal'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. Pimco Municipal's downside and upside margins for the forecasting period are 7.93 and 9.83, respectively. We have considered Pimco Municipal'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 Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Pimco Municipal fund data series using in forecasting. Note that when a statistical model is used to represent Pimco Municipal 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 | 111.3963 |
| Bias | Arithmetic mean of the errors | -0.0018 |
| MAD | Mean absolute deviation | 0.0688 |
| MAPE | Mean absolute percentage error | 0.0077 |
| SAE | Sum of the absolute errors | 4.13 |
Predictive Modules for Pimco Municipal
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Pimco Municipal Income. 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 Pimco Municipal
For every potential investor in Pimco, whether a beginner or expert, Pimco Municipal's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Pimco Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Pimco. Basic forecasting techniques help filter out the noise by identifying Pimco Municipal's price trends.Pimco Municipal 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 Pimco Municipal fund to make a market-neutral strategy. Peer analysis of Pimco Municipal could also be used in its relative valuation, which is a method of valuing Pimco Municipal by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Pimco Municipal Income 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 Pimco Municipal'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 Pimco Municipal's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Pimco Municipal Market Strength Events
Market strength indicators help investors to evaluate how Pimco Municipal fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Pimco Municipal shares will generate the highest return on investment. By undertsting and applying Pimco Municipal fund market strength indicators, traders can identify Pimco Municipal Income entry and exit signals to maximize returns.
Pimco Municipal Risk Indicators
The analysis of Pimco Municipal'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 Pimco Municipal's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting pimco 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 | 0.7171 | |||
| Semi Deviation | 0.8454 | |||
| Standard Deviation | 0.9321 | |||
| Variance | 0.8688 | |||
| Downside Variance | 0.8351 | |||
| Semi Variance | 0.7147 | |||
| Expected Short fall | (0.84) |
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.
Building efficient market-beating portfolios requires time, education, and a lot of computing power!
The Portfolio Architect is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.
Try AI Portfolio ArchitectOther Information on Investing in Pimco Fund
Pimco Municipal financial ratios help investors to determine whether Pimco 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 Pimco with respect to the benefits of owning Pimco Municipal security.
| Companies Directory Evaluate performance of over 100,000 Stocks, Funds, and ETFs against different fundamentals | |
| Portfolio Optimization Compute new portfolio that will generate highest expected return given your specified tolerance for risk | |
| Portfolio Analyzer Portfolio analysis module that provides access to portfolio diagnostics and optimization engine |