Quantitative U S Fund Volatility
| GQLVX Fund | USD 14.56 0.19 1.29% |
At this stage we consider Quantitative Mutual Fund to be very steady. Quantitative U S maintains Sharpe Ratio (i.e., Efficiency) of 0.0794, which implies the entity had a 0.0794% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Quantitative U S, which you can use to evaluate the volatility of the fund. Please check Quantitative's Semi Deviation of 0.4399, coefficient of variation of 799.68, and Risk Adjusted Performance of 0.0947 to confirm if the risk estimate we provide is consistent with the expected return of 0.0584%. Key indicators related to Quantitative's volatility include:
720 Days Market Risk | Chance Of Distress | 720 Days Economic Sensitivity |
Quantitative Mutual Fund 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 Quantitative daily returns, and it is calculated using variance and standard deviation. We also use Quantitative's beta, its sensitivity to the market, as well as its odds of financial distress to provide a more practical estimation of Quantitative volatility.
Quantitative |
Downward market volatility can be a perfect environment for investors who play the long game with Quantitative. They may decide to buy additional shares of Quantitative at lower prices to lower the average cost per share, thereby improving their portfolio's performance when markets normalize.
Moving together with Quantitative Mutual Fund
| 0.92 | NOVIX | Glenmede International | PairCorr |
| 0.9 | GEQIX | Equity Income Portfolio | PairCorr |
| 0.93 | GWILX | Woman In Leadership | PairCorr |
| 0.91 | RESGX | Responsible Esg Equity | PairCorr |
| 0.85 | GLSOX | Secured Options Portfolio | PairCorr |
| 0.76 | GQSCX | Quantitative U S | PairCorr |
| 0.74 | GTAPX | Long/short Portfolio | PairCorr |
| 0.86 | GTCEX | Strategic Equity Por | PairCorr |
Moving against Quantitative Mutual Fund
Quantitative Market Sensitivity And Downside Risk
Quantitative's beta coefficient measures the volatility of Quantitative mutual fund compared to the systematic risk of the entire 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 Quantitative mutual fund's returns against your selected market. In other words, Quantitative's beta of 0.0128 provides an investor with an approximation of how much risk Quantitative mutual fund can potentially add to one of your existing portfolios. Quantitative U S exhibits very low volatility with skewness of 0.89 and kurtosis of 1.82. Understanding different market volatility trends often help investors to time the market. Properly using volatility indicators enable traders to measure Quantitative's mutual fund risk against market volatility during both bullish and bearish trends. The higher level of volatility that comes with bear markets can directly impact Quantitative's mutual fund price while adding stress to investors as they watch their shares' value plummet. This usually forces investors to rebalance their portfolios by buying different financial instruments as prices fall.
3 Months Beta |Analyze Quantitative U S Demand TrendCheck current 90 days Quantitative correlation with market (Dow Jones Industrial)Quantitative Beta |
Quantitative standard deviation measures the daily dispersion of prices over your selected time horizon relative to its mean. A typical volatile entity 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 | 0.74 |
It is essential to understand the difference between upside risk (as represented by Quantitative's standard deviation) and the downside risk, which can be measured by semi-deviation or downside deviation of Quantitative's daily returns or price. Since the actual investment returns on holding a position in quantitative mutual fund 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 Quantitative.
Quantitative U S Mutual Fund Volatility Analysis
Volatility refers to the frequency at which Quantitative fund price increases or decreases within a specified period. These fluctuations usually indicate the level of risk that's associated with Quantitative's price changes. Investors will then calculate the volatility of Quantitative's mutual fund to predict their future moves. A fund that has erratic price changes quickly hits new highs, and lows are considered highly volatile. A mutual fund with relatively stable price changes has low volatility. A highly volatile fund 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 Quantitative's volatility:
Historical Volatility
This type of fund volatility measures Quantitative's fluctuations based on previous trends. It's commonly used to predict Quantitative's future behavior based on its past. However, it cannot conclusively determine the future direction of the mutual fund.Implied Volatility
This type of volatility provides a positive outlook on future price fluctuations for Quantitative's current market price. This means that the fund will return to its initially predicted market price. This type of volatility can be derived from derivative instruments written on Quantitative'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. Quantitative U S Average Price is the average of the sum of open, high, low and close daily prices of a bar. It can be used to smooth an indicator that normally takes just the closing price as input.
Quantitative Projected Return Density Against Market
Assuming the 90 days horizon Quantitative has a beta of 0.0128 . This usually indicates as returns on the market go up, Quantitative average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding Quantitative U S will be expected to be much smaller as well.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 Quantitative or Glenmede 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 Quantitative's price will be affected by overall mutual fund 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 Quantitative fund'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.
Quantitative U S has an alpha of 0.078, implying that it can generate a 0.078 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). Predicted Return Density |
| Returns |
What Drives a Quantitative Price Volatility?
Several factors can influence a fund'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.Quantitative Mutual Fund Risk Measures
Assuming the 90 days horizon the coefficient of variation of Quantitative is 1259.34. The daily returns are distributed with a variance of 0.54 and standard deviation of 0.74. The mean deviation of Quantitative U S is currently at 0.58. For similar time horizon, the selected benchmark (Dow Jones Industrial) has volatility of 0.76
α | Alpha over Dow Jones | 0.08 | |
β | Beta against Dow Jones | 0.01 | |
σ | Overall volatility | 0.74 | |
Ir | Information ratio | -0.03 |
Quantitative Mutual Fund Return Volatility
Quantitative historical daily return volatility represents how much of Quantitative fund's daily returns swing around its mean - it is a statistical measure of its dispersion of returns. The fund shows 0.7351% volatility of returns over 90 . By contrast, Dow Jones Industrial accepts 0.7685% volatility on return distribution over the 90 days horizon. Performance |
| Timeline |
About Quantitative Volatility
Volatility is a rate at which the price of Quantitative 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 Quantitative may increase or decrease. In other words, similar to Quantitative's beta indicator, it measures the risk of Quantitative and helps estimate the fluctuations that may happen in a short period of time. So if prices of Quantitative 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.Under normal market circumstances, the Portfolio invests at least 80 percent of the value of its net assets in common stocks of large cap companies tied economically to the U.S. The Advisor considers a company to be tied economically to the U.S. if the company 1 is organized under the laws of the U.S., 2 maintains its principal place of business in the U.S., 3 is traded principally in the U.S. or 4 at the time of purchase, is included in a U.S. equity index managed by SP Global Ratings or FTSE Russell.
Quantitative'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 Quantitative Mutual Fund over a specified period of time, often expressed as the standard deviation of daily returns. In other words, it measures how much Quantitative's price varies over time.
3 ways to utilize Quantitative's volatility to invest better
Higher Quantitative's fund volatility means that the price of its stock is changing rapidly and unpredictably, while lower stock volatility indicates that the price of Quantitative U S fund 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. Quantitative U S fund 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 Quantitative U S investment. A higher volatility means higher risk and potentially larger changes in value.
- Identifying Opportunities: High volatility in Quantitative's fund 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 Quantitative's fund relates to your other investments can help you create a well-diversified portfolio of assets with varying levels of risk.
Quantitative Investment Opportunity
Dow Jones Industrial has a standard deviation of returns of 0.77 and is 1.04 times more volatile than Quantitative U S. 6 percent of all equities and portfolios are less risky than Quantitative. You can use Quantitative U S to protect your portfolios against small market fluctuations. The mutual fund experiences a somewhat bearish sentiment, but the market may correct it shortly. Check odds of Quantitative to be traded at $14.12 in 90 days.Significant diversification
The correlation between Quantitative U S and DJI is 0.01 (i.e., Significant diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding Quantitative U S and DJI in the same portfolio, assuming nothing else is changed.
Quantitative Additional Risk Indicators
The analysis of Quantitative'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 Quantitative's investment and either accepting that risk or mitigating it. Along with some common measures of Quantitative mutual fund'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 | 0.0947 | |||
| Market Risk Adjusted Performance | 6.2 | |||
| Mean Deviation | 0.5603 | |||
| Semi Deviation | 0.4399 | |||
| Downside Deviation | 0.5751 | |||
| Coefficient Of Variation | 799.68 | |||
| Standard Deviation | 0.7138 |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential mutual funds, we recommend comparing similar funds with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
Quantitative 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 Quantitative 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. Quantitative'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, Quantitative'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 Quantitative U S.
Other Information on Investing in Quantitative Mutual Fund
Quantitative financial ratios help investors to determine whether Quantitative Mutual Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Quantitative with respect to the benefits of owning Quantitative security.
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