Kkr Income Fund Forecast - Double Exponential Smoothing
| KIO Fund | USD 13.44 0.02 0.15% |
The Double Exponential Smoothing forecasted value of Kkr Income Opportunities on the next trading day is expected to be 13.47 with a mean absolute deviation of 0.07 and the sum of the absolute errors of 4.00. Kkr Fund Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Kkr Income stock prices and determine the direction of Kkr Income Opportunities's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Kkr Income's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Kkr Income to cross-verify your projections. Kkr |
Most investors in Kkr Income 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 Kkr Income's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Kkr Income's price structures and extracts relationships that further increase the generated results' accuracy.
Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for Kkr Income works best with periods where there are trends or seasonality. Kkr Income Double Exponential Smoothing Price Forecast For the 21st of May
Given 90 days horizon, the Double Exponential Smoothing forecasted value of Kkr Income Opportunities on the next trading day is expected to be 13.47 with a mean absolute deviation of 0.07, mean absolute percentage error of 0.01, and the sum of the absolute errors of 4.00.Please note that although there have been many attempts to predict Kkr 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 Kkr Income's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Kkr Income Fund Forecast Pattern
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Kkr Income Forecasted Value
In the context of forecasting Kkr Income'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. Kkr Income's downside and upside margins for the forecasting period are 12.86 and 14.08, respectively. We have considered Kkr Income'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 Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Kkr Income fund data series using in forecasting. Note that when a statistical model is used to represent Kkr Income 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 | Huge |
| Bias | Arithmetic mean of the errors | 0.0183 |
| MAD | Mean absolute deviation | 0.0678 |
| MAPE | Mean absolute percentage error | 0.0051 |
| SAE | Sum of the absolute errors | 4.0 |
Predictive Modules for Kkr Income
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Kkr Income Opportunities. 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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Kkr Income'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.
Other Forecasting Options for Kkr Income
For every potential investor in Kkr, whether a beginner or expert, Kkr Income's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Kkr Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Kkr. Basic forecasting techniques help filter out the noise by identifying Kkr Income's price trends.View Kkr Income Related Equities
| Risk & Return | Correlation |
Kkr Income Opportunities 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 Kkr Income'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 Kkr Income's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Kkr Income Market Strength Events
Market strength indicators help investors to evaluate how Kkr Income fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Kkr Income shares will generate the highest return on investment. By undertsting and applying Kkr Income fund market strength indicators, traders can identify Kkr Income Opportunities entry and exit signals to maximize returns.
Kkr Income Risk Indicators
The analysis of Kkr Income'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 Kkr Income's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting kkr 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 | 0.4835 | |||
| Semi Deviation | 0.4784 | |||
| Standard Deviation | 0.6094 | |||
| Variance | 0.3714 | |||
| Downside Variance | 0.4002 | |||
| Semi Variance | 0.2289 | |||
| Expected Short fall | (0.56) |
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.
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Try AI Portfolio ArchitectCheck out Historical Fundamental Analysis of Kkr Income to cross-verify your projections. You can also try the Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.