# MongoDB Stock Volatility

MDB Stock | USD 216.79 3.28 1.49% |

MongoDB appears to be very steady, given 3 months investment horizon. MongoDB has Sharpe Ratio of 0.0745, which conveys that the firm had 0.0745% of return per unit of risk over the last 3 months. Our standpoint towards estimating the volatility of a stock is to use all available market data together with stock-specific technical indicators that cannot be diversified away. We have found twenty-one technical indicators for MongoDB, which you can use to evaluate the future volatility of the firm. Please exercise MongoDB's Mean Deviation of 3.25, risk adjusted performance of 0.0674, and Downside Deviation of 4.3 to check out if our risk estimates are consistent with your expectations.

MongoDB |

MongoDB Stock volatility depicts how high the prices fluctuate around the mean (or its average) price. In other words, it is a statistical measure of the distribution of MongoDB daily returns, and it is calculated using variance and standard deviation. We also use MongoDB's beta, its sensitivity to the market, as well as its odds of financial distress to provide a more practical estimation of MongoDB volatility.

### 30 Days Market Risk

### Chance of Distress

### 30 Days Economic Sensitivity

Since volatility provides investors with entry points to take advantage of stock prices, companies, such as MongoDB can benefit from it. Downward market volatility can be a perfect environment for investors who play the long game. Here, they may decide to buy additional stocks of MongoDB at lower prices. For example, an investor can purchase MongoDB stock that has halved in price over a short period. This will lower your average cost per share, thereby improving your portfolio's performance when the markets normalize. Similarly, when the prices of MongoDB's stock rises, investors can sell out and invest the proceeds in other equities with better opportunities. Investing when markets are volatile with better valuations will accord both investors and companies the opportunity to generate better long-term returns.

## Moving together with MongoDB

+ | 0.67 | ADBE | Adobe Systems Incorp | Fiscal Quarter End 31st of May 2023 | PairCorr | ||

+ | 0.61 | AFRM | Affirm Holdings | Aggressive Push | PairCorr | ||

+ | 0.61 | ALTR | Altair Engineering | Fiscal Quarter End 31st of March 2023 | PairCorr | ||

+ | 0.86 | APPN | Appian Corp | Fiscal Quarter End 31st of March 2023 | PairCorr |

## Moving against MongoDB

- | 0.43 | ATEN | A10 Network | Fiscal Quarter End 31st of March 2023 | PairCorr |

## MongoDB Market Sensitivity And Downside Risk

MongoDB's beta coefficient measures the volatility of MongoDB stock compared to the systematic risk of the entire stock market represented by your selected benchmark. In mathematical terms, beta represents the slope of the line through a regression of data points where each of these points represents MongoDB stock's returns against your selected market. In other words, MongoDB's beta of 1.72 provides an investor with an approximation of how much risk MongoDB stock can potentially add to one of your existing portfolios.

MongoDB exhibits above-average semi-deviation for your current time horizon. We encourage investors to investigate MongoDB individually to make sure intended market timing strategies and available technical indicators are consistent with their estimates about MongoDB future systematic risk. Understanding different market volatility trends often help investors to time the market. Properly using volatility indicators enable traders to measure MongoDB's stock risk against market volatility during both bullish and bearish trends. The higher level of volatility that comes with bear markets can directly impact MongoDB's stock price while adding stress to investors as they watch their shares' value plummet. This usually forces investors to rebalance their portfolios by buying different stocks as prices fall. 3 Months Beta |Analyze MongoDB Demand TrendCheck current 90 days MongoDB correlation with market (NYSE Composite)## MongoDB Beta |

MongoDB standard deviation measures the daily dispersion of prices over your selected time horizon relative to its mean. Typical volatile equity has a high standard deviation, while the deviation of a stable instrument is usually low. As a downside, the standard deviation calculates all uncertainty as risk, even when it is in your favor, such as above-average returns.

## Standard Deviation | 4.12 |

It is essential to understand the difference between upside risk (as represented by MongoDB's standard deviation) and the downside risk, which can be measured by semi-deviation or downside deviation of MongoDB's daily returns or price. Since the actual investment returns on holding a position in mongodb stock tend to have a non-normal distribution, there will be different probabilities for losses than for gains. The likelihood of losses is reflected in the downside risk of an investment in MongoDB.

## Using MongoDB Put Option to Manage Risk

Put options written on MongoDB grant holders of the option the right to sell a specified amount of MongoDB at a specified price within a specified time frame. The put buyer has a limited loss and, while not fully unlimited gains, as the price of MongoDB Stock cannot fall below zero, the put buyer does gain as the price drops. So, one way investors can hedge MongoDB's position is by buying a put option against it. The put option used this way is usually referred to as insurance. If an undesired outcome occurs and loss on holding MongoDB will be realized, the loss incurred will be offset by the profits made with the option trade.

### MongoDB's PUT expiring on 2023-03-31

Profit |

MongoDB Price At Expiration |

### Current MongoDB Insurance Chain

Delta | Gamma | Open Int | Expiration | Current Spread | Last Price | |||

Put | 2023-03-31 PUT at $260.0 | -0.9309 | 0.0052 | 1 | 2023-03-31 | 39.95 - 47.75 | 0.0 | View |

Put | 2023-03-31 PUT at $255.0 | -0.9452 | 0.0052 | 1 | 2023-03-31 | 34.6 - 42.6 | 0.0 | View |

Put | 2023-03-31 PUT at $250.0 | -0.9096 | 0.0074 | 7 | 2023-03-31 | 31.15 - 36.85 | 38.0 | View |

Put | 2023-03-31 PUT at $240.0 | -0.8409 | 0.0116 | 5 | 2023-03-31 | 23.3 - 26.25 | 27.6 | View |

Put | 2023-03-31 PUT at $237.5 | -0.8229 | 0.013 | 2 | 2023-03-31 | 20.7 - 24.2 | 0.0 | View |

Put | 2023-03-31 PUT at $235.0 | -0.7848 | 0.0141 | 3 | 2023-03-31 | 18.3 - 22.75 | 0.0 | View |

Put | 2023-03-31 PUT at $232.5 | -0.7815 | 0.0161 | 10 | 2023-03-31 | 16.6 - 19.0 | 0.0 | View |

Put | 2023-03-31 PUT at $230.0 | -0.7343 | 0.0173 | 19 | 2023-03-31 | 15.0 - 17.05 | 18.3 | View |

Put | 2023-03-31 PUT at $227.5 | -0.6996 | 0.0191 | 13 | 2023-03-31 | 13.2 - 14.65 | 15.85 | View |

Put | 2023-03-31 PUT at $225.0 | -0.652 | 0.0202 | 37 | 2023-03-31 | 11.55 - 12.8 | 14.15 | View |

Put | 2023-03-31 PUT at $222.5 | -0.602 | 0.0211 | 39 | 2023-03-31 | 9.75 - 11.3 | 12.35 | View |

## MongoDB Stock Volatility Analysis

Volatility refers to the frequency at which MongoDB stock price increases or decreases within a specified period. These fluctuations usually indicate the level of risk that's associated with MongoDB's price changes. Investors will then calculate the volatility of MongoDB's stock to predict their future moves. A stock that has erratic price changes quickly hits new highs, and lows are considered highly volatile. A stock with relatively stable price changes has low volatility. A highly volatile stock is riskier, but the risk cuts both ways. Investing in highly volatile security can either be highly successful, or you may experience significant failure. There are two main types of MongoDB's volatility:

### Historical Volatility

This type of stock volatility measures MongoDB's fluctuations based on previous trends. It's commonly used to predict MongoDB's future behavior based on its past. However, it cannot conclusively determine the future direction of the stock.### Implied Volatility

This type of volatility provides a positive outlook on future price fluctuations for MongoDB's current market price. This means that the stock will return to its initially predicted market price. This type of volatility can be derived from derivative instruments written on MongoDB's to be redeemed at a future date.Transformation |

The output start index for this execution was zero with a total number of output elements of sixty-one. Developed by Larry Williams, the Weighted Close is the average of MongoDB high, low and close of a chart with the close values weighted twice. It can be used to smooth an indicator that normally takes only MongoDB closing price as input..

## MongoDB Projected Return Density Against Market

Considering the 90-day investment horizon the stock has the beta coefficient of 1.723 . This indicates as the benchmark fluctuates upward, the company is expected to outperform it on average. However, if the benchmark returns are projected to be negative, MongoDB will likely underperform.Most traded equities are subject to two types of risk - systematic (i.e., market) and unsystematic (i.e., nonmarket or company-specific) risk. Unsystematic risk is the risk that events specific to MongoDB or IT Services sector will adversely affect the stock's price. This type of risk can be diversified away by owning several different stocks in different industries whose stock prices have shown a small correlation to each other. On the other hand, systematic risk is the risk that MongoDB's price will be affected by overall stock market movements and cannot be diversified away. So, no matter how many positions you have, you cannot eliminate market risk. However, you can measure a MongoDB stock's historical response to market movements and buy it if you are comfortable with its volatility direction. Beta and standard deviation are two commonly used measures to help you make the right decision.

The company has an alpha of 0.2866, implying that it can generate a 0.29 percent excess return over NYSE Composite after adjusting for the inherited market risk (beta). Predicted Return Density |

Returns |

## What Drives a MongoDB Price Volatility?

Several factors can influence a stock's market volatility:### Industry

Specific events can influence volatility within a particular industry. For instance, a significant weather upheaval in a crucial oil-production site may cause oil prices to increase in the oil sector. The direct result will be the rise in the stock price of oil distribution companies. Similarly, any government regulation in a specific industry could negatively influence stock prices due to increased regulations on compliance that may impact the company's future earnings and growth.### Political and Economic environment

When governments make significant decisions regarding trade agreements, policies, and legislation regarding specific industries, they will influence stock prices. Everything from speeches to elections may influence investors, who can directly influence the stock prices in any particular industry. The prevailing economic situation also plays a significant role in stock prices. When the economy is doing well, investors will have a positive reaction and hence, better stock prices and vice versa.### The Company's Performance

Sometimes volatility will only affect an individual company. For example, a revolutionary product launch or strong earnings report may attract many investors to purchase the company. This positive attention will raise the company's stock price. In contrast, product recalls and data breaches may negatively influence a company's stock prices.## MongoDB Stock Risk Measures

Most traded equities are subject to two types of risk - systematic (i.e., market) and unsystematic (i.e., nonmarket or company-specific) risk. Unsystematic risk is the risk that events specific to MongoDB or IT Services sector will adversely affect the stock's price. This type of risk can be diversified away by owning several different stocks in different industries whose stock prices have shown a small correlation to each other. On the other hand, systematic risk is the risk that MongoDB's price will be affected by overall stock market movements and cannot be diversified away. So, no matter how many positions you have, you cannot eliminate market risk. However, you can measure a MongoDB stock's historical response to market movements and buy it if you are comfortable with its volatility direction. Beta and standard deviation are two commonly used measures to help you make the right decision. Considering the 90-day investment horizon the coefficient of variation of MongoDB is 1342.3. The daily returns are distributed with a variance of 17.0 and standard deviation of 4.12. The mean deviation of MongoDB is currently at 3.29. For similar time horizon, the selected benchmark (NYSE Composite) has volatility of 0.95

α | Alpha over NYSE Composite | 0.29 | |

β | Beta against NYSE Composite | 1.72 | |

σ | Overall volatility | 4.12 | |

Ir | Information ratio | 0.07 |

## MongoDB Stock Return Volatility

MongoDB historical daily return volatility represents how much of MongoDB stock's daily returns swing around its mean - it is a statistical measure of its dispersion of returns. The company has volatility of**4.123%**on return distribution over 90 days investment horizon. By contrast, NYSE Composite accepts 0.9499% volatility on return distribution over the 90 days horizon.

Performance (%) |

Timeline |

## About MongoDB Volatility

Volatility is a rate at which the price of MongoDB or any other equity instrument increases or decreases for a given set of returns. It is measured by calculating the standard deviation of the annualized returns over a given period of time and shows the range to which the price of MongoDB may increase or decrease. In other words, similar to MongoDB's beta indicator, it measures the risk of MongoDB and helps estimate the fluctuations that may happen in a short period of time. So if prices of MongoDB fluctuate rapidly in a short time span, it is termed to have high volatility, and if it swings slowly in a more extended period, it is understood to have low volatility.

Please read more on our technical analysis page.Last Reported | Projected for 2023 | ||

Market Capitalization | 14.8 B | 15.5 B |

MongoDB's stock volatility refers to the amount of uncertainty or risk involved with the size of changes in its stock's price. It is a statistical measure of the dispersion of returns on MongoDB Stock over a specified period of time, often expressed as the standard deviation of daily returns. In other words, it measures how much MongoDB's price varies over time.

## 3 ways to utilize MongoDB's volatility to invest better

Higher MongoDB's stock volatility means that the price of its stock is changing rapidly and unpredictably, while lower stock volatility indicates that the price of MongoDB stock is relatively stable. Investors and traders use stock volatility as an indicator of risk and potential reward, as stocks with higher volatility can offer the potential for more significant returns but also come with a greater risk of losses. MongoDB stock volatility can provide helpful information for making investment decisions in the following ways:- Measuring Risk: Volatility can be used as a measure of risk, which can help you determine the potential fluctuations in the value of MongoDB investment. A higher volatility means higher risk and potentially larger changes in value.
- Identifying Opportunities: High volatility in MongoDB's stock can indicate that there is potential for significant price movements, either up or down, which could present investment opportunities.
- Diversification: Understanding how the volatility of MongoDB's stock relates to your other investments can help you create a well-diversified portfolio of assets with varying levels of risk.

## MongoDB Investment Opportunity

MongoDB has a volatility of 4.12 and is 4.34 times more volatile than NYSE Composite.**36**of all equities and portfolios are less risky than MongoDB. Compared to the overall equity markets, volatility of historical daily returns of MongoDB is lower than

**36 ()**of all global equities and portfolios over the last 90 days. Use MongoDB to protect your portfolios against small market fluctuations. Benchmarks are essential to demonstrate the utility of optimization algorithms. The stock experiences a somewhat bearish sentiment, but the market may correct it shortly. Check odds of MongoDB to be traded at $210.29 in 90 days.

### Very weak diversification

The correlation between MongoDB and NYA is

**0.4**(i.e., Very weak diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding MongoDB and NYA in the same portfolio, assuming nothing else is changed.## MongoDB Additional Risk Indicators

The analysis of MongoDB's secondary risk indicators is one of the essential steps in making a buy or sell decision. The process involves identifying the amount of risk involved in MongoDB's investment and either accepting that risk or mitigating it. Along with some common measures of MongoDB stock's risk such as standard deviation, beta, or value at risk, we also provide a set of secondary indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.

Risk Adjusted Performance | 0.0674 | |||

Market Risk Adjusted Performance | 0.1525 | |||

Mean Deviation | 3.25 | |||

Semi Deviation | 4.06 | |||

Downside Deviation | 4.3 | |||

Coefficient Of Variation | 1591.12 | |||

Standard Deviation | 4.07 |

Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential stocks, we recommend comparing similar stocks with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.

## MongoDB Suggested Diversification Pairs

Pair trading is one of the very effective strategies used by professional day traders and hedge funds capitalizing on short-time and mid-term market inefficiencies. The approach is based on the fact that the ratio of prices of two correlating shares is long-term stable and oscillates around the average value. If the correlation ratio comes outside the common area, you can speculate with a high success rate that the ratio will return to the mean value and collect a profit.

The effect of pair diversification on risk is to reduce it, but we should note this doesn't apply to all risk types. When we trade pairs against MongoDB as a counterpart, there is always some inherent risk that will never be diversified away no matter what. This volatility limits the effect of tactical diversification using pair trading. MongoDB's systematic risk is the inherent uncertainty of the entire market, and therefore cannot be mitigated even by pair-trading it against the equity that is not highly correlated to it. On the other hand, MongoDB's unsystematic risk describes the types of risk that we can protect against, at least to some degree, by selecting a matching pair that is not perfectly correlated to MongoDB.

Check out Correlation Analysis. For information on how to trade MongoDB Stock refer to our How to Trade MongoDB Stock guide. Note that the MongoDB information on this page should be used as a complementary analysis to other MongoDB's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try Idea Breakdown module to analyze constituents of all Macroaxis ideas. Macroaxis investment ideas are predefined, sector-focused investing themes.

## Complementary Tools for MongoDB Stock analysis

When running MongoDB price analysis, check to measure MongoDB'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 MongoDB is operating at the current time. Most of MongoDB's value examination focuses on studying past and present price action to predict the probability of MongoDB's future price movements. You can analyze the entity against its peers and financial market as a whole to determine factors that move MongoDB's price. Additionally, you may evaluate how the addition of MongoDB to your portfolios can decrease your overall portfolio volatility.

Correlation Analysis Reduce portfolio risk simply by holding instruments which are not perfectly correlated | |

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Instant Ratings Determine any equity ratings based on digital recommendations. Macroaxis instant equity ratings are based on combination of fundamental analysis and risk-adjusted market performance |

Is MongoDB's industry expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of MongoDB. If investors know MongoDB will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about MongoDB listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.

Earnings Share(4.96) | Revenue Per Share18.71 | Quarterly Revenue Growth0.356 | Return On Assets(0.09) | Return On Equity(0.49) |

The market value of MongoDB is measured differently than its book value, which is the value of MongoDB that is recorded on the company's balance sheet. Investors also form their own opinion of MongoDB's value that differs from its market value or its book value, called intrinsic value, which is MongoDB's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because MongoDB's market value can be influenced by many factors that don't directly affect MongoDB's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.

Please note, there is a significant difference between MongoDB's value and its price as these two are different measures arrived at by different means. Investors typically determine MongoDB value by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, MongoDB's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.