Amplify Transformational Data Etf Market Value
| BLOK Etf | USD 63.72 0.02 0.03% |
| Symbol | Amplify |
Investors evaluate Amplify Transformational using market value (trading price) and book value (balance sheet equity), each telling a different story. Calculating Amplify Transformational's intrinsic value—the estimated true worth—helps identify when the stock trades at a discount or premium to fair value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. External factors like market trends, sector rotation, and investor psychology can cause Amplify Transformational's market price to deviate significantly from intrinsic value.
It's important to distinguish between Amplify Transformational's intrinsic value and market price, which are calculated using different methodologies. Investment decisions regarding Amplify Transformational should consider multiple factors including financial performance, growth metrics, competitive position, and professional analysis. Conversely, Amplify Transformational's market price signifies the transaction level at which participants voluntarily complete trades.
Amplify Transformational '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 Amplify Transformational'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 Amplify Transformational.
| 10/31/2025 |
| 01/29/2026 |
If you would invest 0.00 in Amplify Transformational on October 31, 2025 and sell it all today you would earn a total of 0.00 from holding Amplify Transformational Data or generate 0.0% return on investment in Amplify Transformational over 90 days. Amplify Transformational is related to or competes with Brown Advisory, IShares MSCI, Invesco Exchange, Goldman Sachs, Invesco Exchange, WisdomTree Total, and Aptus Defined. The fund is an actively managed ETF that seeks to provide total return by investing at least 80 percent of its net asset... More
Amplify Transformational 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 Amplify Transformational'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 Amplify Transformational Data upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.06) | |||
| Maximum Drawdown | 10.1 | |||
| Value At Risk | (4.68) | |||
| Potential Upside | 4.13 |
Amplify Transformational Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Amplify Transformational's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Amplify Transformational's standard deviation. In reality, there are many statistical measures that can use Amplify Transformational historical prices to predict the future Amplify Transformational's volatility.| Risk Adjusted Performance | (0.01) | |||
| Jensen Alpha | (0.19) | |||
| Total Risk Alpha | (0.29) | |||
| Treynor Ratio | (0.05) |
Amplify Transformational January 29, 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 | (0.01) | |||
| Market Risk Adjusted Performance | (0.04) | |||
| Mean Deviation | 1.88 | |||
| Coefficient Of Variation | (3,659) | |||
| Standard Deviation | 2.44 | |||
| Variance | 5.97 | |||
| Information Ratio | (0.06) | |||
| Jensen Alpha | (0.19) | |||
| Total Risk Alpha | (0.29) | |||
| Treynor Ratio | (0.05) | |||
| Maximum Drawdown | 10.1 | |||
| Value At Risk | (4.68) | |||
| Potential Upside | 4.13 | |||
| Skewness | (0.07) | |||
| Kurtosis | (0.05) |
Amplify Transformational Backtested Returns
Amplify Transformational secures Sharpe Ratio (or Efficiency) of -0.0405, which signifies that the etf had a -0.0405 % return per unit of risk over the last 3 months. Amplify Transformational Data exposes twenty-four different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm Amplify Transformational's Risk Adjusted Performance of (0.01), standard deviation of 2.44, and Mean Deviation of 1.88 to double-check the risk estimate we provide. The etf shows a Beta (market volatility) of 1.69, 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, Amplify Transformational will likely underperform.
Auto-correlation | -0.4 |
Poor reverse predictability
Amplify Transformational Data has poor reverse predictability. Overlapping area represents the amount of predictability between Amplify Transformational time series from 31st of October 2025 to 15th of December 2025 and 15th of December 2025 to 29th of January 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 Amplify Transformational price movement. The serial correlation of -0.4 indicates that just about 40.0% of current Amplify Transformational price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.4 | |
| Spearman Rank Test | -0.33 | |
| Residual Average | 0.0 | |
| Price Variance | 6.56 |
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Amplify Transformational 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.