Bitwise Funds Trust Etf Market Value
| IETH Etf | 26.79 1.18 4.22% |
| Symbol | Bitwise |
The market value of Bitwise Funds Trust is measured differently than its book value, which is the value of Bitwise that is recorded on the company's balance sheet. Investors also form their own opinion of Bitwise Funds' value that differs from its market value or its book value, called intrinsic value, which is Bitwise Funds' true underlying value. Analysts utilize numerous techniques to assess fundamental value, seeking to purchase shares when trading prices fall beneath estimated intrinsic worth. Because Bitwise Funds' market value can be influenced by many factors that don't directly affect Bitwise Funds' underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Bitwise Funds' value and its price as these two are different measures arrived at by different means. Investors typically determine if Bitwise Funds is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. Meanwhile, Bitwise Funds' quoted price indicates the marketplace figure where supply meets demand through bilateral consent.
Bitwise Funds '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 Bitwise Funds' 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 Bitwise Funds.
| 11/04/2025 |
| 02/02/2026 |
If you would invest 0.00 in Bitwise Funds on November 4, 2025 and sell it all today you would earn a total of 0.00 from holding Bitwise Funds Trust or generate 0.0% return on investment in Bitwise Funds over 90 days. Bitwise Funds is related to or competes with CoinShares Altcoins, Grayscale Funds, VanEck Solana, ProShares Trust, Hashdex Nasdaq, and Grayscale Ethereum. Bitwise Funds is entity of United States More
Bitwise Funds 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 Bitwise Funds' 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 Bitwise Funds Trust upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.13) | |||
| Maximum Drawdown | 17.34 | |||
| Value At Risk | (7.48) | |||
| Potential Upside | 5.83 |
Bitwise Funds Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Bitwise Funds' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Bitwise Funds' standard deviation. In reality, there are many statistical measures that can use Bitwise Funds historical prices to predict the future Bitwise Funds' volatility.| Risk Adjusted Performance | (0.08) | |||
| Jensen Alpha | (0.56) | |||
| Total Risk Alpha | (0.70) | |||
| Treynor Ratio | (0.25) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Bitwise Funds' 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.
Bitwise Funds February 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 | (0.08) | |||
| Market Risk Adjusted Performance | (0.24) | |||
| Mean Deviation | 3.2 | |||
| Coefficient Of Variation | (849.24) | |||
| Standard Deviation | 4.13 | |||
| Variance | 17.02 | |||
| Information Ratio | (0.13) | |||
| Jensen Alpha | (0.56) | |||
| Total Risk Alpha | (0.70) | |||
| Treynor Ratio | (0.25) | |||
| Maximum Drawdown | 17.34 | |||
| Value At Risk | (7.48) | |||
| Potential Upside | 5.83 | |||
| Skewness | (0.14) | |||
| Kurtosis | (0.18) |
Bitwise Funds Trust Backtested Returns
Bitwise Funds Trust secures Sharpe Ratio (or Efficiency) of -0.0287, which signifies that the etf had a -0.0287 % return per unit of risk over the last 3 months. Bitwise Funds Trust exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm Bitwise Funds' Risk Adjusted Performance of (0.08), mean deviation of 3.2, and Standard Deviation of 4.13 to double-check the risk estimate we provide. The etf shows a Beta (market volatility) of 1.95, 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, Bitwise Funds will likely underperform.
Auto-correlation | -0.44 |
Modest reverse predictability
Bitwise Funds Trust has modest reverse predictability. Overlapping area represents the amount of predictability between Bitwise Funds time series from 4th of November 2025 to 19th of December 2025 and 19th of December 2025 to 2nd 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 Bitwise Funds Trust price movement. The serial correlation of -0.44 indicates that just about 44.0% of current Bitwise Funds price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.44 | |
| Spearman Rank Test | -0.2 | |
| Residual Average | 0.0 | |
| Price Variance | 2.16 |
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Bitwise Funds 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.