INTECH US Mutual Fund Forward View - Simple Exponential Smoothing
| JRSIX Fund | USD 11.55 -0.22 -1.87% |
The Simple Exponential Smoothing forecast shown here for INTECH US is reference data produced from its historical price series. The projected value and error measures below serve as reference information. This data is provided for reference and analytical review. The Simple Exponential Smoothing output serves as one input among many for analytical review.
The Simple Exponential Smoothing forecasted value of Intech Managed Volatility on the next trading day is expected to be 11.56 with a mean absolute deviation of 0.08 and the sum of the absolute errors of 4.91.This simple exponential smoothing model begins by setting Intech Managed Volatility forecast for the second period equal to the observation of the first period. In other words, recent INTECH US observations are given relatively more weight in forecasting than the older observations. This Simple Exponential Smoothing reference page for INTECH US presents model-generated projections from historical price data for informational purposes. Simple Exponential Smoothing Price Forecast For the 28th of March
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Intech Managed Volatility on the next trading day is expected to be 11.56 with a mean absolute deviation of 0.08 , mean absolute percentage error of 0.01 , and the sum of the absolute errors of 4.91 .Please note that although there have been many attempts to predict INTECH Mutual Fund prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that INTECH US's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Mutual Fund Forecast Pattern
| Backtest INTECH US | INTECH US Price Prediction | Research Analysis |
Forecasted Value
Forecasting Intech Managed Volatility for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. Used properly, these levels provide context around forecast dispersion rather than certainty about the next closing print.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of INTECH US mutual fund data series using in forecasting. Note that when a statistical model is used to represent INTECH US 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 | 113.5089 |
| Bias | Arithmetic mean of the errors | 0.0163 |
| MAD | Mean absolute deviation | 0.0804 |
| MAPE | Mean absolute percentage error | 0.0066 |
| SAE | Sum of the absolute errors | 4.9052 |
Other Forecasting Options for INTECH US
The distribution of INTECH US's daily returns is typically non-normal, with fatter tails than a Gaussian model predicts. This can reveal hidden support and resistance zones in INTECH US's chart that simple price charts miss. The slope of INTECH US's linear regression channel quantifies trend direction and strength over a chosen lookback period. Divergences between OBV and price can foreshadow trend changes in INTECH.INTECH US Related Equities
The peer firms below within the Large Blend space can help frame INTECH US's pricing and running costs in context. Revenue and margin checks across this group help investors set expectations for INTECH US's results. Falling behind peers on key ratios may signal headwinds or execution issues worth looking into.
| Risk & Return | Correlation |
INTECH US Market Strength Events
Market strength indicators for INTECH US give insight into the mutual fund's responsiveness to broader forces. These indicators are useful for traders seeking optimal timing for positions in Intech Managed Volatility. Market strength analysis for Intech Managed Volatility works best when combined with volume and volatility data. For INTECH US, strength indicators are a practical complement to price and fundamental analysis.
| Rate Of Daily Change | 0.98 | |||
| Day Median Price | 11.55 | |||
| Day Typical Price | 11.55 | |||
| Price Action Indicator | -0.11 | |||
| Period Momentum Indicator | -0.22 | |||
| Relative Strength Index | 37.06 |
INTECH US Risk Indicators
A thorough review of INTECH US's risk indicators is an important first step in forecasting its price. Quantifying the risk involved in INTECH US's allows investors to make better decisions about entry, sizing, and hedging. The assessment of INTECH US's risk indicators plays a key role in managing investment exposure. Identifying the magnitude of risk in INTECH US's provides context to choose between accepting or hedging exposure.
| Mean Deviation | 0.6577 | |||
| Standard Deviation | 0.8193 | |||
| Variance | 0.6712 |
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.
Story Coverage note for INTECH US
A coverage review of Intech Managed Volatility shows when the security is attracting above-average attention from contributors and market observers. Used properly, this context can help investors judge whether visibility is reinforcing the thesis or attracting more speculative pressure.
Other Macroaxis Stories
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