Kayne Anderson Fund Forecast - Polynomial Regression
KMFDelisted Fund | USD 7.49 0.09 1.22% |
The Polynomial Regression forecasted value of Kayne Anderson Midstreamenergy on the next trading day is expected to be 7.56 with a mean absolute deviation of 0.07 and the sum of the absolute errors of 4.35. Kayne Fund Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Kayne Anderson's historical fundamentals, such as revenue growth or operating cash flow patterns.
Kayne |
Kayne Anderson Polynomial Regression Price Forecast For the 6th of December
Given 90 days horizon, the Polynomial Regression forecasted value of Kayne Anderson Midstreamenergy on the next trading day is expected to be 7.56 with a mean absolute deviation of 0.07, mean absolute percentage error of 0.01, and the sum of the absolute errors of 4.35.Please note that although there have been many attempts to predict Kayne 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 Kayne Anderson's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Kayne Anderson Fund Forecast Pattern
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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 Kayne Anderson fund data series using in forecasting. Note that when a statistical model is used to represent Kayne Anderson 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 | 113.4332 |
Bias | Arithmetic mean of the errors | None |
MAD | Mean absolute deviation | 0.0714 |
MAPE | Mean absolute percentage error | 0.0102 |
SAE | Sum of the absolute errors | 4.3536 |
Predictive Modules for Kayne Anderson
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Kayne Anderson Midst. 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.Kayne Anderson 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 Kayne Anderson fund to make a market-neutral strategy. Peer analysis of Kayne Anderson could also be used in its relative valuation, which is a method of valuing Kayne Anderson by comparing valuation metrics with similar companies.
Risk & Return | Correlation |
Kayne Anderson Market Strength Events
Market strength indicators help investors to evaluate how Kayne Anderson fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Kayne Anderson shares will generate the highest return on investment. By undertsting and applying Kayne Anderson fund market strength indicators, traders can identify Kayne Anderson Midstreamenergy entry and exit signals to maximize returns.
Kayne Anderson Risk Indicators
The analysis of Kayne Anderson'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 Kayne Anderson's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting kayne 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 | 0.891 | |||
Semi Deviation | 1.18 | |||
Standard Deviation | 1.15 | |||
Variance | 1.31 | |||
Downside Variance | 1.59 | |||
Semi Variance | 1.39 | |||
Expected Short fall | (0.91) |
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.
Currently Active Assets on Macroaxis
Check out Correlation Analysis to better understand how to build diversified portfolios. Also, note that the market value of any fund could be closely tied with the direction of predictive economic indicators such as signals in population. You can also try the Portfolio Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
Other Consideration for investing in Kayne Fund
If you are still planning to invest in Kayne Anderson Midst check if it may still be traded through OTC markets such as Pink Sheets or OTC Bulletin Board. You may also purchase it directly from the company, but this is not always possible and may require contacting the company directly. Please note that delisted stocks are often considered to be more risky investments, as they are no longer subject to the same regulatory and reporting requirements as listed stocks. Therefore, it is essential to carefully research the Kayne Anderson's history and understand the potential risks before investing.
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