Yieldmax Snow Option Etf Market Value
| SNOY Etf | 12.36 0.17 1.36% |
| Symbol | YieldMax |
The market value of YieldMax SNOW Option is measured differently than its book value, which is the value of YieldMax that is recorded on the company's balance sheet. Investors also form their own opinion of YieldMax SNOW's value that differs from its market value or its book value, called intrinsic value, which is YieldMax SNOW's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because YieldMax SNOW's market value can be influenced by many factors that don't directly affect YieldMax SNOW's 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 YieldMax SNOW's value and its price as these two are different measures arrived at by different means. Investors typically determine if YieldMax SNOW is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, YieldMax SNOW'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.
YieldMax SNOW '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 YieldMax SNOW'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 YieldMax SNOW.
| 11/26/2025 |
| 12/26/2025 |
If you would invest 0.00 in YieldMax SNOW on November 26, 2025 and sell it all today you would earn a total of 0.00 from holding YieldMax SNOW Option or generate 0.0% return on investment in YieldMax SNOW over 30 days. YieldMax SNOW is related to or competes with YieldMax CVNA, YieldMax MARA, Pacer Swan, Hoya Capital, First Trust, Innovator ETFs, and Simplify Exchange. YieldMax SNOW is entity of United States More
YieldMax SNOW 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 YieldMax SNOW'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 YieldMax SNOW Option upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.04) | |||
| Maximum Drawdown | 13.87 | |||
| Value At Risk | (3.57) | |||
| Potential Upside | 2.76 |
YieldMax SNOW Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for YieldMax SNOW's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as YieldMax SNOW's standard deviation. In reality, there are many statistical measures that can use YieldMax SNOW historical prices to predict the future YieldMax SNOW's volatility.| Risk Adjusted Performance | 0.0016 | |||
| Jensen Alpha | (0.1) | |||
| Total Risk Alpha | (0.24) | |||
| Treynor Ratio | (0.03) |
YieldMax SNOW Option Backtested Returns
YieldMax SNOW Option shows Sharpe Ratio of -0.0155, which attests that the etf had a -0.0155 % return per unit of risk over the last 3 months. YieldMax SNOW Option exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check out YieldMax SNOW's Mean Deviation of 1.63, standard deviation of 2.18, and Market Risk Adjusted Performance of (0.02) to validate the risk estimate we provide. The entity maintains a market beta of 1.0, which attests to a somewhat significant risk relative to the market. YieldMax SNOW returns are very sensitive to returns on the market. As the market goes up or down, YieldMax SNOW is expected to follow.
Auto-correlation | -0.74 |
Almost perfect reverse predictability
YieldMax SNOW Option has almost perfect reverse predictability. Overlapping area represents the amount of predictability between YieldMax SNOW time series from 26th of November 2025 to 11th of December 2025 and 11th of December 2025 to 26th of December 2025. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of YieldMax SNOW Option price movement. The serial correlation of -0.74 indicates that around 74.0% of current YieldMax SNOW price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.74 | |
| Spearman Rank Test | -0.75 | |
| Residual Average | 0.0 | |
| Price Variance | 0.03 |
YieldMax SNOW Option lagged returns against current returns
Autocorrelation, which is YieldMax SNOW etf's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting YieldMax SNOW's etf expected returns. We can calculate the autocorrelation of YieldMax SNOW returns to help us make a trade decision. For example, suppose you find that YieldMax SNOW has exhibited high autocorrelation historically, and you observe that the etf is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
YieldMax SNOW regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If YieldMax SNOW etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if YieldMax SNOW etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in YieldMax SNOW etf over time.
Current vs Lagged Prices |
| Timeline |
YieldMax SNOW Lagged Returns
When evaluating YieldMax SNOW's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of YieldMax SNOW etf have on its future price. YieldMax SNOW autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, YieldMax SNOW autocorrelation shows the relationship between YieldMax SNOW etf current value and its past values and can show if there is a momentum factor associated with investing in YieldMax SNOW Option.
Regressed Prices |
| Timeline |
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.When determining whether YieldMax SNOW Option offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of YieldMax SNOW's financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Yieldmax Snow Option Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Yieldmax Snow Option Etf:Check out YieldMax SNOW Correlation, YieldMax SNOW Volatility and YieldMax SNOW Alpha and Beta module to complement your research on YieldMax SNOW. You can also try the Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
YieldMax SNOW 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.