T Rowe Mutual Fund Forecast - Polynomial Regression

TCELX Mutual Fund Forecast is based on your current time horizon.
  
T Rowe polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for T Rowe Price as well as the accuracy indicators are determined from the period prices.
A single variable polynomial regression model attempts to put a curve through the T Rowe historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm

Predictive Modules for T Rowe

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as T Rowe Price. Regardless of method or technology, however, to accurately forecast the mutual fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the mutual 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.
Hype
Prediction
LowEstimatedHigh
11.7712.5713.37
Details
Intrinsic
Valuation
LowRealHigh
12.0912.8913.69
Details
Bollinger
Band Projection (param)
LowMiddleHigh
11.3712.0112.64
Details

T Rowe 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 T Rowe mutual fund to make a market-neutral strategy. Peer analysis of T Rowe could also be used in its relative valuation, which is a method of valuing T Rowe by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

T Rowe Risk Indicators

The analysis of T Rowe'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 T Rowe's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting tcelx mutual 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.
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 TCELX Mutual Fund

T Rowe financial ratios help investors to determine whether TCELX Mutual 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 TCELX with respect to the benefits of owning T Rowe security.
Pattern Recognition
Use different Pattern Recognition models to time the market across multiple global exchanges
Competition Analyzer
Analyze and compare many basic indicators for a group of related or unrelated entities
Portfolio Optimization
Compute new portfolio that will generate highest expected return given your specified tolerance for risk
Performance Analysis
Check effects of mean-variance optimization against your current asset allocation