Wbi Power Factor Etf Market Value
WBIY Etf | USD 32.35 0.56 1.76% |
Symbol | WBI |
The market value of WBI Power Factor is measured differently than its book value, which is the value of WBI that is recorded on the company's balance sheet. Investors also form their own opinion of WBI Power's value that differs from its market value or its book value, called intrinsic value, which is WBI Power'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 WBI Power's market value can be influenced by many factors that don't directly affect WBI Power'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 WBI Power's value and its price as these two are different measures arrived at by different means. Investors typically determine if WBI Power is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, WBI Power'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.
WBI Power '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 WBI Power'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 WBI Power.
04/02/2023 |
| 11/22/2024 |
If you would invest 0.00 in WBI Power on April 2, 2023 and sell it all today you would earn a total of 0.00 from holding WBI Power Factor or generate 0.0% return on investment in WBI Power over 600 days. WBI Power is related to or competes with Franklin Templeton, Altrius Global, Invesco Exchange, Franklin International, Madison ETFs, Amplify CWP, and Advisors Inner. Under normal circumstances the fund will invest at least 80 percent of its total assets in the securities of the underly... More
WBI Power 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 WBI Power'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 WBI Power Factor upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 0.7195 | |||
Information Ratio | (0.01) | |||
Maximum Drawdown | 4.33 | |||
Value At Risk | (0.96) | |||
Potential Upside | 1.39 |
WBI Power Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for WBI Power's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as WBI Power's standard deviation. In reality, there are many statistical measures that can use WBI Power historical prices to predict the future WBI Power's volatility.Risk Adjusted Performance | 0.0939 | |||
Jensen Alpha | 0.0124 | |||
Total Risk Alpha | (0.02) | |||
Sortino Ratio | (0.01) | |||
Treynor Ratio | 0.1148 |
WBI Power Factor Backtested Returns
At this stage we consider WBI Etf to be very steady. WBI Power Factor shows Sharpe Ratio of 0.12, which attests that the etf had a 0.12% return per unit of standard deviation over the last 3 months. We have found twenty-nine technical indicators for WBI Power Factor, which you can use to evaluate the volatility of the entity. Please check out WBI Power's Mean Deviation of 0.6493, risk adjusted performance of 0.0939, and Downside Deviation of 0.7195 to validate if the risk estimate we provide is consistent with the expected return of 0.0992%. The entity maintains a market beta of 0.81, which attests to possible diversification benefits within a given portfolio. As returns on the market increase, WBI Power's returns are expected to increase less than the market. However, during the bear market, the loss of holding WBI Power is expected to be smaller as well.
Auto-correlation | 0.53 |
Modest predictability
WBI Power Factor has modest predictability. Overlapping area represents the amount of predictability between WBI Power time series from 2nd of April 2023 to 27th of January 2024 and 27th of January 2024 to 22nd of November 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of WBI Power Factor price movement. The serial correlation of 0.53 indicates that about 53.0% of current WBI Power price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.53 | |
Spearman Rank Test | 0.46 | |
Residual Average | 0.0 | |
Price Variance | 1.51 |
WBI Power Factor lagged returns against current returns
Autocorrelation, which is WBI Power 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 WBI Power's etf expected returns. We can calculate the autocorrelation of WBI Power returns to help us make a trade decision. For example, suppose you find that WBI Power 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 |
WBI Power 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 WBI Power etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if WBI Power etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in WBI Power etf over time.
Current vs Lagged Prices |
Timeline |
WBI Power Lagged Returns
When evaluating WBI Power's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of WBI Power etf have on its future price. WBI Power 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, WBI Power autocorrelation shows the relationship between WBI Power etf current value and its past values and can show if there is a momentum factor associated with investing in WBI Power Factor.
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 WBI Power Factor offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of WBI Power'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 Wbi Power Factor Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Wbi Power Factor Etf:Check out WBI Power Correlation, WBI Power Volatility and WBI Power Alpha and Beta module to complement your research on WBI Power. You can also try the Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
WBI Power 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.