Alger Smallcap Growth Fund Market Value
| ALSAX Fund | USD 9.37 0.08 0.85% |
| Symbol | Alger |
Alger Smallcap '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 Smallcap'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 Smallcap.
| 03/26/2024 |
| 04/25/2024 |
If you would invest 0.00 in Alger Smallcap on March 26, 2024 and sell it all today you would earn a total of 0.00 from holding Alger Smallcap Growth or generate 0.0% return on investment in Alger Smallcap over 30 days. Alger Smallcap is related to or competes with Fidelity Advisor, HUMANA, Morningstar Unconstrained, High Yield, Thrivent High, Via Renewables, and T Rowe. The fund normally invests at least 80 percent of its net assets, plus any borrowings for investment purposes, in equity ... More
Alger Smallcap 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 Smallcap'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 Smallcap Growth upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.48 | |||
| Information Ratio | (0.03) | |||
| Maximum Drawdown | 6.57 | |||
| Value At Risk | (2.18) | |||
| Potential Upside | 2.0 |
Alger Smallcap Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Alger Smallcap's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Alger Smallcap's standard deviation. In reality, there are many statistical measures that can use Alger Smallcap historical prices to predict the future Alger Smallcap's volatility.| Risk Adjusted Performance | 0.0283 | |||
| Jensen Alpha | (0.1) | |||
| Total Risk Alpha | (0.14) | |||
| Sortino Ratio | (0.03) | |||
| Treynor Ratio | 0.0243 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Alger Smallcap'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 Smallcap Growth Backtested Returns
We consider Alger Smallcap not too volatile. Alger Smallcap Growth secures Sharpe Ratio (or Efficiency) of 0.0105, which signifies that the fund had a 0.0105% return per unit of standard deviation over the last 3 months. We have found twenty-eight technical indicators for Alger Smallcap Growth, which you can use to evaluate the volatility of the entity. Please confirm Alger Smallcap's mean deviation of 1.09, and Risk Adjusted Performance of 0.0283 to double-check if the risk estimate we provide is consistent with the expected return of 0.0144%. The fund shows a Beta (market volatility) of 1.63, which signifies a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, Alger Smallcap will likely underperform.
Auto-correlation | 0.84 |
Very good predictability
Alger Smallcap Growth has very good predictability. Overlapping area represents the amount of predictability between Alger Smallcap time series from 26th of March 2024 to 10th of April 2024 and 10th of April 2024 to 25th 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 Alger Smallcap Growth price movement. The serial correlation of 0.84 indicates that around 84.0% of current Alger Smallcap price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.84 | |
| Spearman Rank Test | 0.55 | |
| Residual Average | 0.0 | |
| Price Variance | 0.07 |
Alger Smallcap Growth lagged returns against current returns
Autocorrelation, which is Alger Smallcap 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 Smallcap's mutual fund expected returns. We can calculate the autocorrelation of Alger Smallcap returns to help us make a trade decision. For example, suppose you find that Alger Smallcap 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 Smallcap 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 Smallcap mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Alger Smallcap 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 Smallcap mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Alger Smallcap Lagged Returns
When evaluating Alger Smallcap's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Alger Smallcap mutual fund have on its future price. Alger Smallcap 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 Smallcap autocorrelation shows the relationship between Alger Smallcap mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Alger Smallcap Growth.
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 Smallcap 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 Smallcap's short interest history, or implied volatility extrapolated from Alger Smallcap options trading.
Pair Trading with Alger Smallcap
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 Smallcap 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 Smallcap will appreciate offsetting losses from the drop in the long position's value.Moving together with Alger Mutual Fund
| 0.9 | AMGAX | Alger Midcap Growth | PairCorr |
| 0.9 | AMGCX | Alger Midcap Growth | PairCorr |
| 0.83 | AMGOX | Alger Mid Cap | PairCorr |
| 0.92 | AOFAX | Alger Small Cap | PairCorr |
| 0.85 | CHUSX | Alger Global Growth | PairCorr |
The ability to find closely correlated positions to Alger Smallcap 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 Smallcap 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 Smallcap - 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 Smallcap Growth to buy it.
The correlation of Alger Smallcap 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 Smallcap moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Alger Smallcap Growth 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 Smallcap 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 Smallcap Correlation, Alger Smallcap Volatility and Alger Smallcap Alpha and Beta module to complement your research on Alger Smallcap. Note that the Alger Smallcap Growth information on this page should be used as a complementary analysis to other Alger Smallcap'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 Instant Ratings module to determine any equity ratings based on digital recommendations. Macroaxis instant equity ratings are based on combination of fundamental analysis and risk-adjusted market performance.
Alger Smallcap 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.