PACLIF Forecast - Simple Regression
| 694476AF9 | 99.21 0.00 0.00% |
The Simple Regression forecasted value of PACLIF 54 15 SEP 52 on the next trading day is expected to be 97.83 with a mean absolute deviation of 2.35 and the sum of the absolute errors of 145.78. PACLIF Bond Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast PACLIF stock prices and determine the direction of PACLIF 54 15 SEP 52's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of PACLIF's historical fundamentals, such as revenue growth or operating cash flow patterns.
PACLIF |
PACLIF Simple Regression Price Forecast For the 13th of December 2024
Given 90 days horizon, the Simple Regression forecasted value of PACLIF 54 15 SEP 52 on the next trading day is expected to be 97.83 with a mean absolute deviation of 2.35, mean absolute percentage error of 9.36, and the sum of the absolute errors of 145.78.Please note that although there have been many attempts to predict PACLIF Bond 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 PACLIF's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
PACLIF Bond Forecast Pattern
PACLIF Forecasted Value
In the context of forecasting PACLIF's Bond 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. PACLIF's downside and upside margins for the forecasting period are 95.02 and 100.65, respectively. We have considered PACLIF'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 Regression forecasting method's relative quality and the estimations of the prediction error of PACLIF bond data series using in forecasting. Note that when a statistical model is used to represent PACLIF bond, 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 | 122.185 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 2.3512 |
| MAPE | Mean absolute percentage error | 0.024 |
| SAE | Sum of the absolute errors | 145.7774 |
Predictive Modules for PACLIF
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as PACLIF 54 15. Regardless of method or technology, however, to accurately forecast the bond market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the bond 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 PACLIF
For every potential investor in PACLIF, whether a beginner or expert, PACLIF's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. PACLIF Bond price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in PACLIF. Basic forecasting techniques help filter out the noise by identifying PACLIF's price trends.PACLIF 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 PACLIF bond to make a market-neutral strategy. Peer analysis of PACLIF could also be used in its relative valuation, which is a method of valuing PACLIF by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
PACLIF 54 15 Technical and Predictive Analytics
The bond market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of PACLIF'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 PACLIF's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
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| Volume Indicators |
PACLIF Market Strength Events
Market strength indicators help investors to evaluate how PACLIF bond reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading PACLIF shares will generate the highest return on investment. By undertsting and applying PACLIF bond market strength indicators, traders can identify PACLIF 54 15 SEP 52 entry and exit signals to maximize returns.
PACLIF Risk Indicators
The analysis of PACLIF'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 PACLIF's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting paclif bond 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. One of the essential factors to consider when estimating the risk of default for a bond instrument is its duration, which is the bond's price sensitivity to changes in interest rates. The duration of PACLIF 54 15 SEP 52 bond is primarily affected by its yield, coupon rate, and time to maturity. The duration of a bond will be higher the lower its coupon, lower its yield, and longer the time left to maturity.
| Mean Deviation | 1.46 | |||
| Semi Deviation | 2.4 | |||
| Standard Deviation | 2.89 | |||
| Variance | 8.33 | |||
| Downside Variance | 7.36 | |||
| Semi Variance | 5.75 | |||
| Expected Short fall | (1.65) |
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.
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.Other Information on Investing in PACLIF Bond
PACLIF financial ratios help investors to determine whether PACLIF Bond 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 PACLIF with respect to the benefits of owning PACLIF security.