Amg Managers Cadence Fund Market Value
| MECZX Fund | USD 47.99 0.37 0.77% |
| Symbol | Amg |
Amg Managers '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 Amg Managers' 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 Amg Managers.
| 10/26/2022 |
| 04/18/2024 |
If you would invest 0.00 in Amg Managers on October 26, 2022 and sell it all today you would earn a total of 0.00 from holding Amg Managers Cadence or generate 0.0% return on investment in Amg Managers over 540 days. Amg Managers is related to or competes with HUMANA, Barloworld, Thrivent High, Morningstar Unconstrained, High Yield, Via Renewables, and T Rowe. The fund seeks to achieve its investment objective by investing primarily in a portfolio of equity securities issued by ... More
Amg Managers 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 Amg Managers' 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 Amg Managers Cadence upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.913 | |||
| Information Ratio | (0) | |||
| Maximum Drawdown | 3.51 | |||
| Value At Risk | (1.45) | |||
| Potential Upside | 0.8615 |
Amg Managers Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Amg Managers' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Amg Managers' standard deviation. In reality, there are many statistical measures that can use Amg Managers historical prices to predict the future Amg Managers' volatility.| Risk Adjusted Performance | 0.048 | |||
| Jensen Alpha | 0.0044 | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | (0) | |||
| Treynor Ratio | 0.0507 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Amg Managers' 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.
Amg Managers Cadence Backtested Returns
We consider Amg Managers out of control. Amg Managers Cadence secures Sharpe Ratio (or Efficiency) of 0.1, which signifies that the fund had a 0.1% return per unit of standard deviation over the last 3 months. We have found twenty-seven technical indicators for Amg Managers Cadence, which you can use to evaluate the volatility of the entity. Please confirm Amg Managers' risk adjusted performance of 0.048, and Mean Deviation of 0.5619 to double-check if the risk estimate we provide is consistent with the expected return of 0.0707%. The fund shows a Beta (market volatility) of 0.85, which signifies possible diversification benefits within a given portfolio. Amg Managers returns are very sensitive to returns on the market. As the market goes up or down, Amg Managers is expected to follow.
Auto-correlation | -0.05 |
Very weak reverse predictability
Amg Managers Cadence has very weak reverse predictability. Overlapping area represents the amount of predictability between Amg Managers time series from 26th of October 2022 to 23rd of July 2023 and 23rd of July 2023 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 Amg Managers Cadence price movement. The serial correlation of -0.05 indicates that only as little as 5.0% of current Amg Managers price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.05 | |
| Spearman Rank Test | 0.3 | |
| Residual Average | 0.0 | |
| Price Variance | 6.6 |
Amg Managers Cadence lagged returns against current returns
Autocorrelation, which is Amg Managers 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 Amg Managers' mutual fund expected returns. We can calculate the autocorrelation of Amg Managers returns to help us make a trade decision. For example, suppose you find that Amg Managers 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 |
Amg Managers 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 Amg Managers mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Amg Managers mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Amg Managers mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Amg Managers Lagged Returns
When evaluating Amg Managers' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Amg Managers mutual fund have on its future price. Amg Managers 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, Amg Managers autocorrelation shows the relationship between Amg Managers mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Amg Managers Cadence.
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 Amg Managers 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, Amg Managers' short interest history, or implied volatility extrapolated from Amg Managers options trading.
Building efficient market-beating portfolios requires time, education, and a lot of computing power!
The Portfolio Architect is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.
Try AI Portfolio ArchitectCheck out Amg Managers Correlation, Amg Managers Volatility and Amg Managers Alpha and Beta module to complement your research on Amg Managers. Note that the Amg Managers Cadence information on this page should be used as a complementary analysis to other Amg Managers' 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 Share Portfolio module to track or share privately all of your investments from the convenience of any device.
Amg Managers 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.