Financial Services Portfolio Fund Technical Analysis
| SFPIX Fund | USD 13.23 0.02 0.15% |
As of the 27th of November, Financial Services shows the Coefficient Of Variation of 490.86, downside deviation of 0.7846, and Mean Deviation of 0.7788. In respect to fundamental indicators, the technical analysis model provides you with a way to check existing technical drivers of Financial Services, as well as the relationship between them.
Financial Services Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Financial, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to FinancialFinancial |
Financial Services technical mutual fund analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, fund market cycles, or different charting patterns.
Financial Services Technical Analysis
The output start index for this execution was twenty-four with a total number of output elements of thirty-seven. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Welles Wilder Directional Movement indicators. The ATR is a measure of Financial Services volatility. High ATR values indicate high volatility, and low values indicate low volatility.
Financial Services Trend Analysis
Use this graph to draw trend lines for Financial Services Portfolio. You can use it to identify possible trend reversals for Financial Services as well as other signals and approximate when it will take place. Remember, you need at least two touches of the trend line with actual Financial Services price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.Financial Services Best Fit Change Line
The following chart estimates an ordinary least squares regression model for Financial Services Portfolio applied against its price change over selected period. The best fit line has a slop of 0.03 , which means Financial Services Portfolio will continue generating value for investors. It has 122 observation points and a regression sum of squares at 39.91, which is the sum of squared deviations for the predicted Financial Services price change compared to its average price change.About Financial Services Technical Analysis
The technical analysis module can be used to analyzes prices, returns, volume, basic money flow, and other market information and help investors to determine the real value of Financial Services Portfolio on a daily or weekly bases. We use both bottom-up as well as top-down valuation methodologies to arrive at the intrinsic value of Financial Services Portfolio based on its technical analysis. In general, a bottom-up approach, as applied to this mutual fund, focuses on Financial Services price pattern first instead of the macroeconomic environment surrounding Financial Services. By analyzing Financial Services's financials, daily price indicators, and related drivers such as dividends, momentum ratios, and various types of growth rates, we attempt to find the most accurate representation of Financial Services's intrinsic value. As compared to a bottom-up approach, our top-down model examines the macroeconomic factors that affect the industry/economy before zooming in to Financial Services specific price patterns or momentum indicators. Please read more on our technical analysis page.
Financial Services November 27, 2024 Technical Indicators
Most technical analysis of Financial help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Financial from various momentum indicators to cycle indicators. When you analyze Financial charts, please remember that the event formation may indicate an entry point for a short seller, and look at different other indicators across different periods to confirm that a breakdown or reversion is likely to occur.
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.1592 | |||
| Market Risk Adjusted Performance | (2.57) | |||
| Mean Deviation | 0.7788 | |||
| Semi Deviation | 0.4951 | |||
| Downside Deviation | 0.7846 | |||
| Coefficient Of Variation | 490.86 | |||
| Standard Deviation | 1.17 | |||
| Variance | 1.37 | |||
| Information Ratio | 0.0921 | |||
| Jensen Alpha | 0.2387 | |||
| Total Risk Alpha | 0.044 | |||
| Sortino Ratio | 0.1372 | |||
| Treynor Ratio | (2.58) | |||
| Maximum Drawdown | 8.49 | |||
| Value At Risk | (1.16) | |||
| Potential Upside | 1.8 | |||
| Downside Variance | 0.6156 | |||
| Semi Variance | 0.2451 | |||
| Expected Short fall | (0.98) | |||
| Skewness | 2.52 | |||
| Kurtosis | 13.1 |
Other Information on Investing in Financial Mutual Fund
Financial Services financial ratios help investors to determine whether Financial Mutual Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Financial with respect to the benefits of owning Financial Services security.
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