The 3d Printing Etf Market Value
| PRNT Etf | USD 22.48 0.12 0.53% |
| Symbol | PRNT |
Understanding 3D Printing requires distinguishing between market price and book value, where the latter reflects PRNT's accounting equity. The concept of intrinsic value - what 3D Printing's is actually worth based on fundamentals - guides informed investors toward better entry and exit points. Analysts utilize numerous techniques to assess fundamental value, seeking to purchase shares when trading prices fall beneath estimated intrinsic worth. Market sentiment, economic cycles, and investor behavior can push 3D Printing's price substantially above or below its fundamental value.
It's important to distinguish between 3D Printing's intrinsic value and market price, which are calculated using different methodologies. Investment decisions regarding 3D Printing should consider multiple factors including financial performance, growth metrics, competitive position, and professional analysis. In contrast, 3D Printing's trading price reflects the actual exchange value where willing buyers and sellers reach mutual agreement.
3D Printing '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 3D Printing'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 3D Printing.
| 12/02/2025 |
| 03/02/2026 |
If you would invest 0.00 in 3D Printing on December 2, 2025 and sell it all today you would earn a total of 0.00 from holding The 3D Printing or generate 0.0% return on investment in 3D Printing over 90 days. 3D Printing is related to or competes with ProShares, Goldman Sachs, Innovator ETFs, Allianzim Large, IShares MSCI, AIM ETF, and Nicholas Global. The fund normally invests at least 80 percent of its total assets in securities that are included in the funds benchmark... More
3D Printing 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 3D Printing'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 The 3D Printing upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.25 | |||
| Information Ratio | 0.0051 | |||
| Maximum Drawdown | 7.89 | |||
| Value At Risk | (2.03) | |||
| Potential Upside | 2.05 |
3D Printing Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for 3D Printing's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as 3D Printing's standard deviation. In reality, there are many statistical measures that can use 3D Printing historical prices to predict the future 3D Printing's volatility.| Risk Adjusted Performance | 0.0615 | |||
| Jensen Alpha | (0.01) | |||
| Total Risk Alpha | (0.05) | |||
| Sortino Ratio | 0.0053 | |||
| Treynor Ratio | 0.0742 |
3D Printing March 2, 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 | 0.0615 | |||
| Market Risk Adjusted Performance | 0.0842 | |||
| Mean Deviation | 0.9088 | |||
| Semi Deviation | 1.08 | |||
| Downside Deviation | 1.25 | |||
| Coefficient Of Variation | 1333.31 | |||
| Standard Deviation | 1.29 | |||
| Variance | 1.65 | |||
| Information Ratio | 0.0051 | |||
| Jensen Alpha | (0.01) | |||
| Total Risk Alpha | (0.05) | |||
| Sortino Ratio | 0.0053 | |||
| Treynor Ratio | 0.0742 | |||
| Maximum Drawdown | 7.89 | |||
| Value At Risk | (2.03) | |||
| Potential Upside | 2.05 | |||
| Downside Variance | 1.55 | |||
| Semi Variance | 1.17 | |||
| Expected Short fall | (0.91) | |||
| Skewness | 0.7709 | |||
| Kurtosis | 3.12 |
3D Printing Backtested Returns
Currently, The 3D Printing is very steady. 3D Printing secures Sharpe Ratio (or Efficiency) of 0.0341, which signifies that the etf had a 0.0341 % return per unit of volatility over the last 3 months. We have found thirty technical indicators for The 3D Printing, which you can use to evaluate the volatility of the entity. Please confirm 3D Printing's risk adjusted performance of 0.0615, and Semi Deviation of 1.08 to double-check if the risk estimate we provide is consistent with the expected return of 0.0441%. The etf shows a Beta (market volatility) of 1.17, 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, 3D Printing will likely underperform.
Auto-correlation | -0.56 |
Good reverse predictability
The 3D Printing has good reverse predictability. Overlapping area represents the amount of predictability between 3D Printing time series from 2nd of December 2025 to 16th of January 2026 and 16th of January 2026 to 2nd of March 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 3D Printing price movement. The serial correlation of -0.56 indicates that roughly 56.0% of current 3D Printing price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.56 | |
| Spearman Rank Test | -0.43 | |
| Residual Average | 0.0 | |
| Price Variance | 0.25 |
Thematic Opportunities
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Check out 3D Printing Correlation, 3D Printing Volatility and 3D Printing Performance module to complement your research on 3D Printing. You can also try the Sign In To Macroaxis module to sign in to explore Macroaxis' wealth optimization platform and fintech modules.
3D Printing 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.