Virtus Allianzgi Health Fund Market Value
| AAAEX Fund | USD 30.05 0.18 0.60% |
| Symbol | Virtus |
Virtus Allianzgi 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Virtus Allianzgi's mutual fund what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Virtus Allianzgi.
| 03/19/2024 |
| 04/18/2024 |
If you would invest 0.00 in Virtus Allianzgi on March 19, 2024 and sell it all today you would earn a total of 0.00 from holding Virtus Allianzgi Health or generate 0.0% return on investment in Virtus Allianzgi over 30 days. Virtus Allianzgi is related to or competes with Vanguard Health, T Rowe, Blackrock Health, and Blackrock Health. The fund seeks to achieve its objective by normally investing at least 80 percent of its net assets in health sciences-r... More
Virtus Allianzgi Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Virtus Allianzgi's mutual fund current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Virtus Allianzgi Health upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.8346 | |||
| Information Ratio | (0.06) | |||
| Maximum Drawdown | 4.31 | |||
| Value At Risk | (1.27) | |||
| Potential Upside | 1.34 |
Virtus Allianzgi Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Virtus Allianzgi's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Virtus Allianzgi's standard deviation. In reality, there are many statistical measures that can use Virtus Allianzgi historical prices to predict the future Virtus Allianzgi's volatility.| Risk Adjusted Performance | 0.011 | |||
| Jensen Alpha | (0.04) | |||
| Total Risk Alpha | (0.06) | |||
| Sortino Ratio | (0.05) | |||
| Treynor Ratio | 0.0013 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Virtus Allianzgi's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Virtus Allianzgi Health Backtested Returns
We consider Virtus Allianzgi very steady. Virtus Allianzgi Health owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.0238, which indicates the fund had a 0.0238% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Virtus Allianzgi Health, which you can use to evaluate the volatility of the fund. Please validate Virtus Allianzgi's Coefficient Of Variation of 7111.19, risk adjusted performance of 0.011, and Semi Deviation of 0.7438 to confirm if the risk estimate we provide is consistent with the expected return of 0.0191%. The entity has a beta of 0.96, which indicates possible diversification benefits within a given portfolio. Virtus Allianzgi returns are very sensitive to returns on the market. As the market goes up or down, Virtus Allianzgi is expected to follow.
Auto-correlation | 0.43 |
Average predictability
Virtus Allianzgi Health has average predictability. Overlapping area represents the amount of predictability between Virtus Allianzgi time series from 19th of March 2024 to 3rd of April 2024 and 3rd of April 2024 to 18th of April 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Virtus Allianzgi Health price movement. The serial correlation of 0.43 indicates that just about 43.0% of current Virtus Allianzgi price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.43 | |
| Spearman Rank Test | 0.36 | |
| Residual Average | 0.0 | |
| Price Variance | 0.27 |
Virtus Allianzgi Health lagged returns against current returns
Autocorrelation, which is Virtus Allianzgi mutual fund's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Virtus Allianzgi's mutual fund expected returns. We can calculate the autocorrelation of Virtus Allianzgi returns to help us make a trade decision. For example, suppose you find that Virtus Allianzgi has exhibited high autocorrelation historically, and you observe that the mutual fund is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Virtus Allianzgi regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Virtus Allianzgi mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Virtus Allianzgi mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Virtus Allianzgi mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Virtus Allianzgi Lagged Returns
When evaluating Virtus Allianzgi's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Virtus Allianzgi mutual fund have on its future price. Virtus Allianzgi autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Virtus Allianzgi autocorrelation shows the relationship between Virtus Allianzgi mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Virtus Allianzgi Health.
Regressed Prices |
| Timeline |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Virtus Allianzgi in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Virtus Allianzgi's short interest history, or implied volatility extrapolated from Virtus Allianzgi options trading.
Pair Trading with Virtus Allianzgi
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 Virtus Allianzgi 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 Virtus Allianzgi will appreciate offsetting losses from the drop in the long position's value.Moving together with Virtus Mutual Fund
| 0.65 | VMSSX | Virtus Multi Sector | PairCorr |
| 0.93 | SAGAX | Ridgeworth Innovative | PairCorr |
| 0.65 | SSAGX | Virtus Seix Government | PairCorr |
| 0.69 | SASVX | Ridgeworth Ceredex Small | PairCorr |
| 0.82 | PXSGX | Virtus Kar Small | PairCorr |
The ability to find closely correlated positions to Virtus Allianzgi could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Virtus Allianzgi 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 Virtus Allianzgi - 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 Virtus Allianzgi Health to buy it.
The correlation of Virtus Allianzgi 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 Virtus Allianzgi moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Virtus Allianzgi Health 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 Virtus Allianzgi 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.Check out Virtus Allianzgi Correlation, Virtus Allianzgi Volatility and Virtus Allianzgi Alpha and Beta module to complement your research on Virtus Allianzgi. Note that the Virtus Allianzgi Health information on this page should be used as a complementary analysis to other Virtus Allianzgi'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 the Global Correlations module to find global opportunities by holding instruments from different markets.
Virtus Allianzgi technical mutual fund 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, fund market cycles, or different charting patterns.