SP BSE (India) Technical Analysis

SB
BSE-POWER -- India Index  

 1,569  43.09  2.67%

As of the 12th of July 2020, SP BSE owns the risk adjusted performance of 1.04, and mean deviation of 3.0. Our technical analysis interface makes it possible for you to check potential technical drivers of SP BSE POWER, as well as the relationship between them. Strictly speaking, you can use this information to find out if the index will indeed mirror its model of historical prices and volume patterns, or the prices will eventually revert. We are able to interpolate and collect nineteen technical drivers for SP BSE, which can be compared to its peers in the sector. Please validate SP BSE POWER jensen alpha, semi variance, and the relationship between the standard deviation and value at risk to decide if SP BSE POWER INDEX is priced correctly, providing market reflects its prevailing price of 1568.85 per share.

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SP BSE technical index 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, stock market cycles, or different charting patterns.
A focus of SP BSE technical analysis is to determine if market prices reflect all relevant information impacting that market. A technical analyst looks at the history of SP BSE trading pattern rather than external drivers such as economic, fundamental, or social events. It is believed that price action tends to repeat itself due to investors' collective, patterned behavior. Hence technical analysis focuses on identifiable price trends and conditions. More Info...

SP BSE POWER Trend Analysis

Use this graph to draw trend lines for SP BSE POWER INDEX. You can use it to identify possible trend reversals for SP BSE 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 SP BSE price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.

SP BSE Best Fit Change Line

The following chart estimates an ordinary least squares regression model for SP BSE POWER INDEX applied against its price change over selected period. The best fit line has a slop of   35.05  , which means SP BSE POWER INDEX will continue producing value for investors. It has 16 observation points and a regression sum of squares at 103188.6, which is the sum of squared deviations for the predicted SP BSE price change compared to its average price change.

About SP BSE 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 SP BSE POWER INDEX 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 SP BSE POWER INDEX based on its technical analysis. In general, a bottom-up approach, as applied to this index, focuses on SP BSE POWER stock first instead of the macroeconomic environment surrounding SP BSE POWER . By analyzing SP BSE'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 SP BSE'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 SP BSE specific price patterns or momentum indicators. Please read more on our technical analysis page.

SP BSE July 12, 2020 Technical Indicators

Most technical analysis of BSE-POWER stock 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 BSE-POWER from various momentum indicators to cycle indicators. When you analyze BSE-POWER 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 Performance1.04
Mean Deviation3.0
Coefficient Of Variation174.36
Standard Deviation3.81
Variance14.49
Information Ratio0.5246
Total Risk Alpha1.8
Maximum Drawdown8.62
Value At Risk(2.67)
Potential Upside8.92
Skewness0.7785
Kurtosis0.5738
Continue to Trending Equities. Please also try Portfolio Comparator module to compare the composition, asset allocations and performance of any two portfolios in your account.
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