Monte Carlo (India) Technical Analysis
| MONTECARLO | 813.25 15.90 1.92% |
As of the 29th of November, Monte Carlo secures the Mean Deviation of 1.96, risk adjusted performance of 0.0748, and Downside Deviation of 2.23. In connection with fundamental indicators, the technical analysis model lets you check existing technical drivers of Monte Carlo Fashions, as well as the relationship between them.
Monte Carlo Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Monte, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to MonteMonte |
Monte Carlo technical stock 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.
Monte Carlo Fashions 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 Monte Carlo Fashions volatility. High ATR values indicate high volatility, and low values indicate low volatility.
Monte Carlo Fashions Trend Analysis
Use this graph to draw trend lines for Monte Carlo Fashions. You can use it to identify possible trend reversals for Monte Carlo 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 Monte Carlo price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.Monte Carlo Best Fit Change Line
The following chart estimates an ordinary least squares regression model for Monte Carlo Fashions applied against its price change over selected period. The best fit line has a slop of 0.18 , which means Monte Carlo Fashions will continue generating value for investors. It has 122 observation points and a regression sum of squares at 1197.28, which is the sum of squared deviations for the predicted Monte Carlo price change compared to its average price change.About Monte Carlo 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 Monte Carlo Fashions 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 Monte Carlo Fashions based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on Monte Carlo Fashions price pattern first instead of the macroeconomic environment surrounding Monte Carlo Fashions. By analyzing Monte Carlo'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 Monte Carlo'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 Monte Carlo specific price patterns or momentum indicators. Please read more on our technical analysis page.
Monte Carlo November 29, 2024 Technical Indicators
Most technical analysis of Monte 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 Monte from various momentum indicators to cycle indicators. When you analyze Monte 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 | 0.0748 | |||
| Market Risk Adjusted Performance | 0.2708 | |||
| Mean Deviation | 1.96 | |||
| Semi Deviation | 1.99 | |||
| Downside Deviation | 2.23 | |||
| Coefficient Of Variation | 1131.01 | |||
| Standard Deviation | 2.6 | |||
| Variance | 6.78 | |||
| Information Ratio | 0.0402 | |||
| Jensen Alpha | 0.1227 | |||
| Total Risk Alpha | (0.17) | |||
| Sortino Ratio | 0.0469 | |||
| Treynor Ratio | 0.2608 | |||
| Maximum Drawdown | 14.59 | |||
| Value At Risk | (3.64) | |||
| Potential Upside | 4.32 | |||
| Downside Variance | 4.99 | |||
| Semi Variance | 3.97 | |||
| Expected Short fall | (2.38) | |||
| Skewness | 0.5913 | |||
| Kurtosis | 1.24 |
Complementary Tools for Monte Stock analysis
When running Monte Carlo's price analysis, check to measure Monte Carlo's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Monte Carlo is operating at the current time. Most of Monte Carlo's value examination focuses on studying past and present price action to predict the probability of Monte Carlo's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Monte Carlo's price. Additionally, you may evaluate how the addition of Monte Carlo to your portfolios can decrease your overall portfolio volatility.
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