MongoDB (Germany) Overlap Studies Triple Exponential Moving Average
| 526 Stock | EUR 304.55 2.60 0.85% |
| Symbol |
The output start index for this execution was twenty-seven with a total number of output elements of thirty-four. MongoDB Triple Exponential Moving Average indicator shows smoothing effect of MongoDB price series composite of a single exponential moving average, a double exponential moving average and a triple exponential moving average.
MongoDB Technical Analysis Modules
Most technical analysis of MongoDB 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 MongoDB from various momentum indicators to cycle indicators. When you analyze MongoDB charts, please remember that the event formation may indicate an entry point for a short seller, and look at 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 |
About MongoDB Predictive Technical Analysis
Predictive technical analysis modules help investors to analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of MongoDB. We use our internally-developed statistical techniques to arrive at the intrinsic value of MongoDB based on widely used predictive technical indicators. In general, we focus on analyzing MongoDB Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build MongoDB's daily price indicators and compare them against related drivers, such as overlap studies and various other types of predictive indicators. Using this methodology combined with a more conventional technical analysis and fundamental analysis, we attempt to find the most accurate representation of MongoDB's intrinsic value. In addition to deriving basic predictive indicators for MongoDB, we also check how macroeconomic factors affect MongoDB price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
Learn to be your own money manager
As an individual investor, you need to find a reliable way to track all your investment portfolios' performance accurately. However, your requirements will often be based on how much of the process you decide to do yourself. In addition to allowing you full analytical transparency into your positions, our tools can tell you how much better you can do without increasing your risk or reducing expected return.Did you try this?
Run Stocks Directory Now
Stocks DirectoryFind actively traded stocks across global markets |
| All Next | Launch Module |
MongoDB pair trading
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if MongoDB position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in MongoDB will appreciate offsetting losses from the drop in the long position's value.MongoDB Pair Trading
MongoDB Pair Trading Analysis
The ability to find closely correlated positions to MongoDB could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace MongoDB when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back MongoDB - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling MongoDB to buy it.
The correlation of MongoDB is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as MongoDB moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if MongoDB moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for MongoDB can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Additional Information and Resources on Investing in MongoDB Stock
When determining whether MongoDB offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of MongoDB's financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Mongodb Stock. Outlined below are crucial reports that will aid in making a well-informed decision on Mongodb Stock:Check out Trending Equities to better understand how to build diversified portfolios, which includes a position in MongoDB. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in board of governors. For more detail on how to invest in MongoDB Stock please use our How to Invest in MongoDB guide.You can also try the Piotroski F Score module to get Piotroski F Score based on the binary analysis strategy of nine different fundamentals.