Yieldmax Pypl Option Etf Market Value
| PYPY Etf | 41.91 0.32 0.77% |
| Symbol | Yieldmax |
The market value of Yieldmax PYPL 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 PYPL's value that differs from its market value or its book value, called intrinsic value, which is Yieldmax PYPL'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 PYPL's market value can be influenced by many factors that don't directly affect Yieldmax PYPL'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 PYPL's value and its price as these two are different measures arrived at by different means. Investors typically determine if Yieldmax PYPL is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Yieldmax PYPL'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 PYPL '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 PYPL'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 PYPL.
| 11/24/2025 |
| 12/24/2025 |
If you would invest 0.00 in Yieldmax PYPL on November 24, 2025 and sell it all today you would earn a total of 0.00 from holding Yieldmax PYPL Option or generate 0.0% return on investment in Yieldmax PYPL over 30 days. Yieldmax PYPL is related to or competes with Yieldmax XOM, YieldMax JPM, YieldMax ABNB, YieldMax DIS, MRP SynthEquity, Fidelity Income, and Neuberger Berman. Yieldmax PYPL is entity of United States More
Yieldmax PYPL 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 PYPL'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 PYPL Option upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.14) | |||
| Maximum Drawdown | 10.85 | |||
| Value At Risk | (2.79) | |||
| Potential Upside | 2.37 |
Yieldmax PYPL Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Yieldmax PYPL's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Yieldmax PYPL's standard deviation. In reality, there are many statistical measures that can use Yieldmax PYPL historical prices to predict the future Yieldmax PYPL's volatility.| Risk Adjusted Performance | (0.07) | |||
| Jensen Alpha | (0.29) | |||
| Total Risk Alpha | (0.36) | |||
| Treynor Ratio | (0.14) |
Yieldmax PYPL Option Backtested Returns
Yieldmax PYPL Option shows Sharpe Ratio of -0.0845, which attests that the etf had a -0.0845 % return per unit of risk over the last 3 months. Yieldmax PYPL Option exposes twenty-two different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check out Yieldmax PYPL's Mean Deviation of 1.46, standard deviation of 1.9, and Market Risk Adjusted Performance of (0.13) to validate the risk estimate we provide. The entity maintains a market beta of 1.49, which attests to 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, Yieldmax PYPL will likely underperform.
Auto-correlation | 0.56 |
Modest predictability
Yieldmax PYPL Option has modest predictability. Overlapping area represents the amount of predictability between Yieldmax PYPL time series from 24th of November 2025 to 9th of December 2025 and 9th of December 2025 to 24th 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 PYPL Option price movement. The serial correlation of 0.56 indicates that roughly 56.0% of current Yieldmax PYPL price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.56 | |
| Spearman Rank Test | -0.09 | |
| Residual Average | 0.0 | |
| Price Variance | 0.23 |
Yieldmax PYPL Option lagged returns against current returns
Autocorrelation, which is Yieldmax PYPL 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 PYPL's etf expected returns. We can calculate the autocorrelation of Yieldmax PYPL returns to help us make a trade decision. For example, suppose you find that Yieldmax PYPL 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 PYPL 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 PYPL etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Yieldmax PYPL etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Yieldmax PYPL etf over time.
Current vs Lagged Prices |
| Timeline |
Yieldmax PYPL Lagged Returns
When evaluating Yieldmax PYPL's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Yieldmax PYPL etf have on its future price. Yieldmax PYPL 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 PYPL autocorrelation shows the relationship between Yieldmax PYPL etf current value and its past values and can show if there is a momentum factor associated with investing in Yieldmax PYPL 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 PYPL 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 PYPL'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 Pypl Option Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Yieldmax Pypl Option Etf:Check out Yieldmax PYPL Correlation, Yieldmax PYPL Volatility and Yieldmax PYPL Alpha and Beta module to complement your research on Yieldmax PYPL. You can also try the Technical Analysis module to check basic technical indicators and analysis based on most latest market data.
Yieldmax PYPL 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.