Cohen Mutual Fund Forecast - Polynomial Regression

CSRIX Fund  USD 45.87  0.03  0.07%   
The Polynomial Regression forecasted value of Cohen And Steers on the next trading day is expected to be 45.20 with a mean absolute deviation of  0.43  and the sum of the absolute errors of 26.28. Cohen Mutual Fund Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Cohen stock prices and determine the direction of Cohen And Steers's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Cohen's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Cohen to cross-verify your projections.
  
Most investors in Cohen cannot accurately predict what will happen the next trading day because, historically, fund markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the Cohen's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Cohen's price structures and extracts relationships that further increase the generated results' accuracy.
Cohen polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Cohen And Steers as well as the accuracy indicators are determined from the period prices.

Cohen Polynomial Regression Price Forecast For the 29th of March

Given 90 days horizon, the Polynomial Regression forecasted value of Cohen And Steers on the next trading day is expected to be 45.20 with a mean absolute deviation of 0.43, mean absolute percentage error of 0.26, and the sum of the absolute errors of 26.28.
Please note that although there have been many attempts to predict Cohen Mutual 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 Cohen's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Cohen Mutual Fund Forecast Pattern

Backtest CohenCohen Price PredictionBuy or Sell Advice 

Cohen Forecasted Value

In the context of forecasting Cohen's Mutual 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. Cohen's downside and upside margins for the forecasting period are 44.20 and 46.21, respectively. We have considered Cohen'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.
Market Value
45.87
45.20
Expected Value
46.21
Upside

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 Cohen mutual fund data series using in forecasting. Note that when a statistical model is used to represent Cohen mutual 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.
AICAkaike Information Criteria116.7487
BiasArithmetic mean of the errors None
MADMean absolute deviation0.4309
MAPEMean absolute percentage error0.0095
SAESum of the absolute errors26.2831
A single variable polynomial regression model attempts to put a curve through the Cohen 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 Cohen

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Cohen And Steers. 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.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Cohen's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Hype
Prediction
LowEstimatedHigh
44.8645.8746.88
Details
Intrinsic
Valuation
LowRealHigh
44.7245.7346.74
Details
Bollinger
Band Projection (param)
LowMiddleHigh
44.3645.5846.81
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Cohen. Your research has to be compared to or analyzed against Cohen's peers to derive any actionable benefits. When done correctly, Cohen's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Cohen And Steers.

Other Forecasting Options for Cohen

For every potential investor in Cohen, whether a beginner or expert, Cohen's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Cohen Mutual Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Cohen. Basic forecasting techniques help filter out the noise by identifying Cohen's price trends.

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

Cohen And Steers Technical and Predictive Analytics

The mutual fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Cohen'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 Cohen's current price.

Cohen Market Strength Events

Market strength indicators help investors to evaluate how Cohen mutual fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Cohen shares will generate the highest return on investment. By undertsting and applying Cohen mutual fund market strength indicators, traders can identify Cohen And Steers entry and exit signals to maximize returns.

Cohen Risk Indicators

The analysis of Cohen'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 Cohen's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting cohen 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.

Pair Trading with Cohen

One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Cohen position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Cohen will appreciate offsetting losses from the drop in the long position's value.

Moving together with Cohen Mutual Fund

  0.97VGSIX Vanguard Reit IndexPairCorr
  0.97VGSLX Vanguard Reit IndexPairCorr
  0.97VGSNX Vanguard Reit IndexPairCorr
  0.98DFREX Dfa Real EstatePairCorr
  1.0CSCIX Cohen Steers RealPairCorr
The ability to find closely correlated positions to Cohen could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Cohen when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Cohen - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Cohen And Steers to buy it.
The correlation of Cohen is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Cohen moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Cohen And Steers moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Cohen can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.
Pair CorrelationCorrelation Matching
Check out Historical Fundamental Analysis of Cohen to cross-verify your projections.
You can also try the Portfolio Comparator module to compare the composition, asset allocations and performance of any two portfolios in your account.

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Please note, there is a significant difference between Cohen's value and its price as these two are different measures arrived at by different means. Investors typically determine if Cohen is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Cohen's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.