Proshares Big Data Etf Market Value
| DAT Etf | USD 41.51 0.33 0.79% |
| Symbol | ProShares |
The market value of ProShares Big Data is measured differently than its book value, which is the value of ProShares that is recorded on the company's balance sheet. Investors also form their own opinion of ProShares Big's value that differs from its market value or its book value, called intrinsic value, which is ProShares Big's true underlying value. Analysts utilize numerous techniques to assess fundamental value, seeking to purchase shares when trading prices fall beneath estimated intrinsic worth. Because ProShares Big's market value can be influenced by many factors that don't directly affect ProShares Big's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
It's important to distinguish between ProShares Big's intrinsic value and market price, which are calculated using different methodologies. Investment decisions regarding ProShares Big should consider multiple factors including financial performance, growth metrics, competitive position, and professional analysis. Meanwhile, ProShares Big's quoted price indicates the marketplace figure where supply meets demand through bilateral consent.
ProShares Big '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 ProShares Big'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 ProShares Big.
| 10/31/2025 |
| 01/29/2026 |
If you would invest 0.00 in ProShares Big on October 31, 2025 and sell it all today you would earn a total of 0.00 from holding ProShares Big Data or generate 0.0% return on investment in ProShares Big over 90 days. ProShares Big is related to or competes with ProShares Ultra, PGIM Nasdaq, ProShares, ProShares Ultra, JPMorgan Fundamental, IShares ESG, and JPMorgan Fundamental. The fund invests in financial instruments that ProShare Advisors believes, in combination, should track the performance ... More
ProShares Big 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 ProShares Big'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 ProShares Big Data upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.20) | |||
| Maximum Drawdown | 5.92 | |||
| Value At Risk | (2.87) | |||
| Potential Upside | 2.0 |
ProShares Big Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for ProShares Big's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as ProShares Big's standard deviation. In reality, there are many statistical measures that can use ProShares Big historical prices to predict the future ProShares Big's volatility.| Risk Adjusted Performance | (0.11) | |||
| Jensen Alpha | (0.29) | |||
| Total Risk Alpha | (0.35) | |||
| Treynor Ratio | (0.27) |
ProShares Big 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 | (0.11) | |||
| Market Risk Adjusted Performance | (0.26) | |||
| Mean Deviation | 1.17 | |||
| Coefficient Of Variation | (630.50) | |||
| Standard Deviation | 1.47 | |||
| Variance | 2.15 | |||
| Information Ratio | (0.20) | |||
| Jensen Alpha | (0.29) | |||
| Total Risk Alpha | (0.35) | |||
| Treynor Ratio | (0.27) | |||
| Maximum Drawdown | 5.92 | |||
| Value At Risk | (2.87) | |||
| Potential Upside | 2.0 | |||
| Skewness | 0.0804 | |||
| Kurtosis | (0.37) |
ProShares Big Data Backtested Returns
ProShares Big Data maintains Sharpe Ratio (i.e., Efficiency) of -0.16, which implies the entity had a -0.16 % return per unit of risk over the last 3 months. ProShares Big Data exposes twenty-four different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check ProShares Big's Coefficient Of Variation of (630.50), variance of 2.15, and Risk Adjusted Performance of (0.11) to confirm the risk estimate we provide. The etf holds a Beta of 0.9, which implies possible diversification benefits within a given portfolio. ProShares Big returns are very sensitive to returns on the market. As the market goes up or down, ProShares Big is expected to follow.
Auto-correlation | -0.02 |
Very weak reverse predictability
ProShares Big Data has very weak reverse predictability. Overlapping area represents the amount of predictability between ProShares Big 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 ProShares Big Data price movement. The serial correlation of -0.02 indicates that only 2.0% of current ProShares Big price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.02 | |
| Spearman Rank Test | 0.07 | |
| Residual Average | 0.0 | |
| Price Variance | 2.81 |
Thematic Opportunities
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Check out ProShares Big Correlation, ProShares Big Volatility and ProShares Big Performance module to complement your research on ProShares Big. You can also try the Crypto Correlations module to use cryptocurrency correlation module to diversify your cryptocurrency portfolio across multiple coins.
ProShares Big 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.