Facebook Technical Analysis |
| FB -- USA Stock | Trading Volume Increase |
As of 21 of October Facebook shows Mean Deviation of 1.28. Facebook technical analysis allows you to utilize historical prices and volume patterns in order to determine a pattern that computes the direction of the firm future prices. In plain English you can use this information to find out if the firm will indeed mirror its model of historical prices and volume momentum or the prices will eventually revert. We found nineteen technical drivers for Facebook which can be compared to its rivals. Please confirm Facebook Variance, Maximum Drawdown and the relationship between Coefficient Of Variation and Jensen Alpha to decide if Facebook is priced favorably providing market reflects its regular price of 185.85 per share. Given that Facebook has Jensen Alpha of (0.08), we urge you verify Facebook prevailing market performance to make sure the company can sustain itself at future point.
Facebook current and past analyst recommendations published by number of research institutions as well as average analyst consensus
| Target Price | Advice | # of Analysts | |
| 228.65 | Buy | 31 | Odds |
| Facebook Analyst Advice |
| Horizon | 30 Days Login to change |
Facebook Technical Analysis
The output start index for this execution was twelve with a total number of output elements of fourty-nine. The Normalized Average True Range is used to analyze tradable apportunities for Facebook across different markets. View also all equity analysis or get more info about normalized average true range volatility indicators indicator.
Facebook Trend Analysis
Use this graph to draw trend lines for Facebook. You can use it to identify possible trend reversals for Facebook 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 Facebook price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.Facebook Best Fit Change Line
The following chart estimates an ordinary least squares regression model for Facebook applied against its price change over selected period. The best fit line has a slop of 0.12 which may indicate that the price for Facebook will continue to decline. It has 122 observation points and a regression sum of squares at 537.76, which is the sum of squared deviations for the predicted Facebook price change compared to its average price change.Facebook October 21, 2019 Technical Indicators
| Cycle Indicators | |
| Math Operators | |
| Math Transform | |
| Momentum Indicators | |
| Overlap Studies | |
| Pattern Recognition | |
| Price Transform | |
| Statistic Functions | |
| Volatility Indicators | |
| Volume Indicators |
| Risk Adjusted Performance | (0.06) | ||
| Market Risk Adjusted Performance | (0.08) | ||
| Mean Deviation | 1.28 | ||
| Coefficient Of Variation | (1,535) | ||
| Standard Deviation | 1.6 | ||
| Variance | 2.57 | ||
| Information Ratio | (0.05) | ||
| Jensen Alpha | (0.08) | ||
| Total Risk Alpha | (0.06) | ||
| Treynor Ratio | (0.09) | ||
| Maximum Drawdown | 7.34 | ||
| Value At Risk | (2.38) | ||
| Potential Upside | 2.6 | ||
| Skewness | (0.27) | ||
| Kurtosis | 0.0583 |
Facebook October 21, 2019 Daily Price Condition
| Accumulation Distribution | 614,074 |
| Daily Balance Of Power | (0.60) |
| Rate Of Daily Change | 0.98 |
| Day Median Price | 187.71 |
| Day Typical Price | 187.09 |
| Price Action Indicator | (4.12) |
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