FINANCIAL SERVICES Mutual Fund Forward View - Triple Exponential Smoothing
| RYFIX Fund | USD 97.04 0.12 0.12% |
The Triple Exponential Smoothing forecast shown here for FINANCIAL SERVICES 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 Triple Exponential Smoothing output serves as one input among many for analytical review.
The Triple Exponential Smoothing forecasted value of Financial Services Fund on the next trading day is expected to be 96.65 with a mean absolute deviation of 0.81 and the sum of the absolute errors of 47.88.As with simple exponential smoothing, in triple exponential smoothing models past FINANCIAL SERVICES observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Financial Services Fund observations. This Triple Exponential Smoothing reference page for FINANCIAL SERVICES presents model-generated projections from historical price data for informational purposes. Triple Exponential Smoothing Price Forecast For the 26th of March
Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Financial Services Fund on the next trading day is expected to be 96.65 with a mean absolute deviation of 0.81 , mean absolute percentage error of 0.99 , and the sum of the absolute errors of 47.88 .Please note that although there have been many attempts to predict FINANCIAL 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 FINANCIAL SERVICES's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Mutual Fund Forecast Pattern
| Backtest FINANCIAL SERVICES | FINANCIAL SERVICES Price Prediction | Research Analysis |
Forecasted Value
Forecasting Financial Services Fund for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. At the moment, the model places downside around 95.70 and upside around 97.61 for the forecasting period.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of FINANCIAL SERVICES mutual fund data series using in forecasting. Note that when a statistical model is used to represent FINANCIAL SERVICES 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 | Huge |
| Bias | Arithmetic mean of the errors | -0.1279 |
| MAD | Mean absolute deviation | 0.8116 |
| MAPE | Mean absolute percentage error | 0.0078 |
| SAE | Sum of the absolute errors | 47.884 |
Other Forecasting Options for FINANCIAL SERVICES
The distribution of FINANCIAL SERVICES's daily returns is typically non-normal, with fatter tails than a Gaussian model predicts. This can reveal hidden support and resistance zones in FINANCIAL SERVICES's chart that simple price charts miss. The slope of FINANCIAL SERVICES's linear regression channel quantifies trend direction and strength over a chosen lookback period. Divergences between OBV and price can foreshadow trend changes in FINANCIAL.FINANCIAL SERVICES Related Equities
Sizing up FINANCIAL SERVICES against these stocks within the Financial space shows how it compares on key financial measures. Growth rate gaps between FINANCIAL SERVICES and its peers often explain pricing differences in the market. Identifying peers that steadily beat or lag FINANCIAL SERVICES across many periods highlights durable competitive gaps.
| Risk & Return | Correlation |
FINANCIAL SERVICES Market Strength Events
Market strength indicators for FINANCIAL SERVICES give insight into the mutual fund's responsiveness to broader forces. These indicators are useful for traders seeking optimal timing for positions in Financial Services Fund. Market strength analysis for Financial Services Fund works best when combined with volume and volatility data. For FINANCIAL SERVICES, strength indicators are a practical complement to price and fundamental analysis.
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 97.04 | |||
| Day Typical Price | 97.04 | |||
| Price Action Indicator | 0.06 | |||
| Period Momentum Indicator | 0.12 |
FINANCIAL SERVICES Risk Indicators
A thorough review of FINANCIAL SERVICES's risk indicators is an important first step in forecasting its price. Quantifying the risk involved in FINANCIAL SERVICES's allows investors to make better decisions about entry, sizing, and hedging. The assessment of FINANCIAL SERVICES's risk indicators plays a key role in managing investment exposure. Identifying the magnitude of risk in FINANCIAL SERVICES's provides context to choose between accepting or hedging exposure.
| Mean Deviation | 0.7807 | |||
| Standard Deviation | 0.9565 | |||
| Variance | 0.9149 |
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 FINANCIAL SERVICES
A coverage review of Financial Services Fund 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
Macroaxis story coverage is designed for a broad investing audience that ranges from self-directed traders to advisers, researchers, and institutional market participants. The content is intended to support people who want a more structured path from headline information to portfolio action.