Alger Dynamic Opportunities Fund Market Value
| ADOCX Fund | USD 16.16 0.14 0.87% |
| Symbol | Alger |
Alger Dynamic '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 Alger Dynamic'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 Alger Dynamic.
| 04/05/2024 |
| 05/05/2024 |
If you would invest 0.00 in Alger Dynamic on April 5, 2024 and sell it all today you would earn a total of 0.00 from holding Alger Dynamic Opportunities or generate 0.0% return on investment in Alger Dynamic over 30 days. Alger Dynamic is related to or competes with Jhancock Diversified, Delaware Limited-term, Transamerica Asset, Calvert Conservative, American Funds, Aqr Diversified, and Mutual Of. The fund invests in a portfolio of U.S. and foreign equity securities More
Alger Dynamic 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 Alger Dynamic'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 Alger Dynamic Opportunities upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.7664 | |||
| Information Ratio | (0.02) | |||
| Maximum Drawdown | 4.28 | |||
| Value At Risk | (0.92) | |||
| Potential Upside | 1.5 |
Alger Dynamic Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Alger Dynamic's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Alger Dynamic's standard deviation. In reality, there are many statistical measures that can use Alger Dynamic historical prices to predict the future Alger Dynamic's volatility.| Risk Adjusted Performance | 0.0552 | |||
| Jensen Alpha | 0.0127 | |||
| Total Risk Alpha | (0.03) | |||
| Sortino Ratio | (0.02) | |||
| Treynor Ratio | 0.0892 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Alger Dynamic'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.
Alger Dynamic Opport Backtested Returns
We consider Alger Dynamic very steady. Alger Dynamic Opport secures Sharpe Ratio (or Efficiency) of 0.0328, which signifies that the fund had a 0.0328% return per unit of standard deviation over the last 3 months. We have found twenty-eight technical indicators for Alger Dynamic Opportunities, which you can use to evaluate the volatility of the entity. Please confirm Alger Dynamic's mean deviation of 0.5997, and Risk Adjusted Performance of 0.0552 to double-check if the risk estimate we provide is consistent with the expected return of 0.0253%. The fund shows a Beta (market volatility) of 0.64, which signifies possible diversification benefits within a given portfolio. As returns on the market increase, Alger Dynamic's returns are expected to increase less than the market. However, during the bear market, the loss of holding Alger Dynamic is expected to be smaller as well.
Auto-correlation | -0.54 |
Good reverse predictability
Alger Dynamic Opportunities has good reverse predictability. Overlapping area represents the amount of predictability between Alger Dynamic time series from 5th of April 2024 to 20th of April 2024 and 20th of April 2024 to 5th of May 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 Alger Dynamic Opport price movement. The serial correlation of -0.54 indicates that about 54.0% of current Alger Dynamic price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.54 | |
| Spearman Rank Test | -0.2 | |
| Residual Average | 0.0 | |
| Price Variance | 0.02 |
Alger Dynamic Opport lagged returns against current returns
Autocorrelation, which is Alger Dynamic 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 Alger Dynamic's mutual fund expected returns. We can calculate the autocorrelation of Alger Dynamic returns to help us make a trade decision. For example, suppose you find that Alger Dynamic 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 |
Alger Dynamic 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 Alger Dynamic mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Alger Dynamic mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Alger Dynamic mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Alger Dynamic Lagged Returns
When evaluating Alger Dynamic's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Alger Dynamic mutual fund have on its future price. Alger Dynamic 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, Alger Dynamic autocorrelation shows the relationship between Alger Dynamic mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Alger Dynamic Opportunities.
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 Alger Dynamic 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, Alger Dynamic's short interest history, or implied volatility extrapolated from Alger Dynamic options trading.
Pair Trading with Alger Dynamic
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 Alger Dynamic 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 Alger Dynamic will appreciate offsetting losses from the drop in the long position's value.Moving together with Alger Mutual Fund
| 0.93 | AMGAX | Alger Midcap Growth | PairCorr |
| 0.93 | AMGCX | Alger Midcap Growth | PairCorr |
| 0.93 | AMGOX | Alger Mid Cap | PairCorr |
| 0.95 | ACAAX | Alger Capital Apprec | PairCorr |
The ability to find closely correlated positions to Alger Dynamic could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Alger Dynamic 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 Alger Dynamic - 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 Alger Dynamic Opportunities to buy it.
The correlation of Alger Dynamic 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 Alger Dynamic moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Alger Dynamic Opport 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 Alger Dynamic 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 Alger Dynamic Correlation, Alger Dynamic Volatility and Alger Dynamic Alpha and Beta module to complement your research on Alger Dynamic. Note that the Alger Dynamic Opport information on this page should be used as a complementary analysis to other Alger Dynamic'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 AI Portfolio Architect module to use AI to generate optimal portfolios and find profitable investment opportunities.
Alger Dynamic 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.