Aim Etf Products Etf Market Value
| FEBT Etf | 38.76 0.18 0.47% |
| Symbol | AIM |
AIM ETF Products's market price often diverges from its book value, the accounting figure shown on AIM's balance sheet. Smart investors calculate AIM ETF's intrinsic value - its true economic worth - which may differ significantly from both market price and book value. Analysts utilize numerous techniques to assess fundamental value, seeking to purchase shares when trading prices fall beneath estimated intrinsic worth. Since AIM ETF's trading price responds to investor sentiment, macroeconomic conditions, and market psychology, it can swing far from fundamental value.
Please note, there is a significant difference between AIM ETF's value and its price as these two are different measures arrived at by different means. Investors typically determine if AIM ETF is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, AIM ETF's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.
AIM ETF '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 AIM ETF's etf 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 AIM ETF.
| 11/21/2025 |
| 02/19/2026 |
If you would invest 0.00 in AIM ETF on November 21, 2025 and sell it all today you would earn a total of 0.00 from holding AIM ETF Products or generate 0.0% return on investment in AIM ETF over 90 days. AIM ETF is related to or competes with FT Cboe, FT Cboe, First Trust, First Trust, Innovator, FT Cboe, and Innovator. AIM ETF is entity of United States. It is traded as Etf on NYSE ARCA exchange. More
AIM ETF 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 AIM ETF's etf 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 AIM ETF Products upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.5595 | |||
| Information Ratio | 0.0019 | |||
| Maximum Drawdown | 2.3 | |||
| Value At Risk | (0.93) | |||
| Potential Upside | 0.6819 |
AIM ETF Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for AIM ETF's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as AIM ETF's standard deviation. In reality, there are many statistical measures that can use AIM ETF historical prices to predict the future AIM ETF's volatility.| Risk Adjusted Performance | 0.0728 | |||
| Jensen Alpha | 0.0195 | |||
| Total Risk Alpha | 0.0156 | |||
| Sortino Ratio | 0.0016 | |||
| Treynor Ratio | 0.0762 |
AIM ETF February 19, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0728 | |||
| Market Risk Adjusted Performance | 0.0862 | |||
| Mean Deviation | 0.3477 | |||
| Semi Deviation | 0.477 | |||
| Downside Deviation | 0.5595 | |||
| Coefficient Of Variation | 995.31 | |||
| Standard Deviation | 0.4733 | |||
| Variance | 0.224 | |||
| Information Ratio | 0.0019 | |||
| Jensen Alpha | 0.0195 | |||
| Total Risk Alpha | 0.0156 | |||
| Sortino Ratio | 0.0016 | |||
| Treynor Ratio | 0.0762 | |||
| Maximum Drawdown | 2.3 | |||
| Value At Risk | (0.93) | |||
| Potential Upside | 0.6819 | |||
| Downside Variance | 0.313 | |||
| Semi Variance | 0.2275 | |||
| Expected Short fall | (0.33) | |||
| Skewness | (0.36) | |||
| Kurtosis | 1.08 |
AIM ETF Products Backtested Returns
Currently, AIM ETF Products is very steady. AIM ETF Products secures Sharpe Ratio (or Efficiency) of 0.19, which signifies that the etf had a 0.19 % return per unit of return volatility over the last 3 months. We have found twenty-nine technical indicators for AIM ETF Products, which you can use to evaluate the volatility of the entity. Please confirm AIM ETF's Mean Deviation of 0.3477, risk adjusted performance of 0.0728, and Semi Deviation of 0.477 to double-check if the risk estimate we provide is consistent with the expected return of 0.0839%. The etf shows a Beta (market volatility) of 0.49, which signifies possible diversification benefits within a given portfolio. As returns on the market increase, AIM ETF's returns are expected to increase less than the market. However, during the bear market, the loss of holding AIM ETF is expected to be smaller as well.
Auto-correlation | 0.49 |
Average predictability
AIM ETF Products has average predictability. Overlapping area represents the amount of predictability between AIM ETF time series from 21st of November 2025 to 5th of January 2026 and 5th of January 2026 to 19th of February 2026. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of AIM ETF Products price movement. The serial correlation of 0.49 indicates that about 49.0% of current AIM ETF price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.49 | |
| Spearman Rank Test | 0.66 | |
| Residual Average | 0.0 | |
| Price Variance | 0.06 |
Thematic Opportunities
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Check out AIM ETF Correlation, AIM ETF Volatility and AIM ETF Performance module to complement your research on AIM ETF. You can also try the Bond Analysis module to evaluate and analyze corporate bonds as a potential investment for your portfolios..
AIM ETF technical etf 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, etf market cycles, or different charting patterns.