Ksm Mutual Etf Forecast - Polynomial Regression
| KSM-F104 | 1,191 56.00 4.93% |
Ksm |
Most investors in Ksm Mutual cannot accurately predict what will happen the next trading day because, historically, etf 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 Ksm Mutual's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Ksm Mutual's price structures and extracts relationships that further increase the generated results' accuracy.
Ksm Mutual polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Ksm Mutual Funds as well as the accuracy indicators are determined from the period prices. Ksm Mutual Polynomial Regression Price Forecast For the 19th of April
Given 90 days horizon, the Polynomial Regression forecasted value of Ksm Mutual Funds on the next trading day is expected to be 1,143 with a mean absolute deviation of 21.87, mean absolute percentage error of 639.22, and the sum of the absolute errors of 1,334.Please note that although there have been many attempts to predict Ksm Etf 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 Ksm Mutual's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Ksm Mutual Etf Forecast Pattern
Ksm Mutual Forecasted Value
In the context of forecasting Ksm Mutual's Etf 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. Ksm Mutual's downside and upside margins for the forecasting period are 1,141 and 1,144, respectively. We have considered Ksm Mutual'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 Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Ksm Mutual etf data series using in forecasting. Note that when a statistical model is used to represent Ksm Mutual etf, 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 | 124.5707 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 21.8691 |
| MAPE | Mean absolute percentage error | 0.0182 |
| SAE | Sum of the absolute errors | 1334.0143 |
Predictive Modules for Ksm Mutual
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Ksm Mutual Funds. Regardless of method or technology, however, to accurately forecast the etf market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the etf 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 Ksm Mutual'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.
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Ksm Mutual. Your research has to be compared to or analyzed against Ksm Mutual's peers to derive any actionable benefits. When done correctly, Ksm Mutual'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 Ksm Mutual Funds.
Other Forecasting Options for Ksm Mutual
For every potential investor in Ksm, whether a beginner or expert, Ksm Mutual's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Ksm Etf price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Ksm. Basic forecasting techniques help filter out the noise by identifying Ksm Mutual's price trends.Ksm Mutual 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 Ksm Mutual etf to make a market-neutral strategy. Peer analysis of Ksm Mutual could also be used in its relative valuation, which is a method of valuing Ksm Mutual by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Ksm Mutual Funds Technical and Predictive Analytics
The etf market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Ksm Mutual'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 Ksm Mutual's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Ksm Mutual Market Strength Events
Market strength indicators help investors to evaluate how Ksm Mutual etf reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Ksm Mutual shares will generate the highest return on investment. By undertsting and applying Ksm Mutual etf market strength indicators, traders can identify Ksm Mutual Funds entry and exit signals to maximize returns.
Ksm Mutual Risk Indicators
The analysis of Ksm Mutual'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 Ksm Mutual's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting ksm etf 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 | 1.32 | |||
| Semi Deviation | 1.41 | |||
| Standard Deviation | 1.74 | |||
| Variance | 3.01 | |||
| Downside Variance | 2.74 | |||
| Semi Variance | 1.99 | |||
| 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.
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Try AI Portfolio ArchitectCheck out Correlation Analysis to better understand how to build diversified portfolios. Also, note that the market value of any etf could be tightly coupled with the direction of predictive economic indicators such as signals in census. Note that the Ksm Mutual Funds information on this page should be used as a complementary analysis to other Ksm Mutual's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Money Flow Index module to determine momentum by analyzing Money Flow Index and other technical indicators.