Columbia Seligman Mutual Fund Forecast - Simple Moving Average
| SCMIX Fund | USD 137.69 1.42 1.04% |
The Simple Moving Average forecasted value of Columbia Seligman Munications on the next trading day is expected to be 137.69 with a mean absolute deviation of 1.58 and the sum of the absolute errors of 94.81. Columbia Mutual Fund Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Columbia Seligman stock prices and determine the direction of Columbia Seligman Munications's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Columbia Seligman's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Columbia Seligman to cross-verify your projections. Columbia |
Most investors in Columbia Seligman 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 Columbia Seligman's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Columbia Seligman's price structures and extracts relationships that further increase the generated results' accuracy.
A two period moving average forecast for Columbia Seligman is based on an daily price series in which the stock price on a given day is replaced by the mean of that price and the preceding price. This model is best suited to price patterns experiencing average volatility. Columbia Seligman Simple Moving Average Price Forecast For the 4th of May
Given 90 days horizon, the Simple Moving Average forecasted value of Columbia Seligman Munications on the next trading day is expected to be 137.69 with a mean absolute deviation of 1.58, mean absolute percentage error of 3.64, and the sum of the absolute errors of 94.81.Please note that although there have been many attempts to predict Columbia 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 Columbia Seligman's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Columbia Seligman Mutual Fund Forecast Pattern
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Columbia Seligman Forecasted Value
In the context of forecasting Columbia Seligman'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. Columbia Seligman's downside and upside margins for the forecasting period are 136.46 and 138.92, respectively. We have considered Columbia Seligman'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 Simple Moving Average forecasting method's relative quality and the estimations of the prediction error of Columbia Seligman mutual fund data series using in forecasting. Note that when a statistical model is used to represent Columbia Seligman 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.| AIC | Akaike Information Criteria | 117.5632 |
| Bias | Arithmetic mean of the errors | -0.0539 |
| MAD | Mean absolute deviation | 1.5801 |
| MAPE | Mean absolute percentage error | 0.0114 |
| SAE | Sum of the absolute errors | 94.805 |
Predictive Modules for Columbia Seligman
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Columbia Seligman. 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 Columbia Seligman'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 Columbia Seligman
For every potential investor in Columbia, whether a beginner or expert, Columbia Seligman's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Columbia Mutual Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Columbia. Basic forecasting techniques help filter out the noise by identifying Columbia Seligman's price trends.Columbia Seligman 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 Columbia Seligman mutual fund to make a market-neutral strategy. Peer analysis of Columbia Seligman could also be used in its relative valuation, which is a method of valuing Columbia Seligman by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Columbia Seligman 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 Columbia Seligman'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 Columbia Seligman's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Columbia Seligman Market Strength Events
Market strength indicators help investors to evaluate how Columbia Seligman 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 Columbia Seligman shares will generate the highest return on investment. By undertsting and applying Columbia Seligman mutual fund market strength indicators, traders can identify Columbia Seligman Munications entry and exit signals to maximize returns.
| Daily Balance Of Power | 9.2 T | |||
| Rate Of Daily Change | 1.01 | |||
| Day Median Price | 137.69 | |||
| Day Typical Price | 137.69 | |||
| Price Action Indicator | 0.71 | |||
| Period Momentum Indicator | 1.42 | |||
| Relative Strength Index | 40.98 |
Columbia Seligman Risk Indicators
The analysis of Columbia Seligman'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 Columbia Seligman's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting columbia 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.
| Mean Deviation | 0.9831 | |||
| Semi Deviation | 1.26 | |||
| Standard Deviation | 1.24 | |||
| Variance | 1.53 | |||
| Downside Variance | 1.74 | |||
| Semi Variance | 1.59 | |||
| Expected Short fall | (0.96) |
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 Historical Fundamental Analysis of Columbia Seligman to cross-verify your projections. You can also try the Price Ceiling Movement module to calculate and plot Price Ceiling Movement for different equity instruments.