John Hancock Preferred Etf Market Value
| JHPI Etf | USD 22.95 0.06 0.26% |
| Symbol | John |
The market value of John Hancock Preferred is measured differently than its book value, which is the value of John that is recorded on the company's balance sheet. Investors also form their own opinion of John Hancock's value that differs from its market value or its book value, called intrinsic value, which is John Hancock'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 John Hancock's market value can be influenced by many factors that don't directly affect John Hancock'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 John Hancock's value and its price as these two are different measures arrived at by different means. Investors typically determine if John Hancock is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, John Hancock'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.
John Hancock '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 John Hancock'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 John Hancock.
| 11/16/2024 |
| 12/16/2024 |
If you would invest 0.00 in John Hancock on November 16, 2024 and sell it all today you would earn a total of 0.00 from holding John Hancock Preferred or generate 0.0% return on investment in John Hancock over 30 days. John Hancock is related to or competes with First Trust, First Trust, and SPDR ICE. Under normal market conditions, the fund invests at least 80 percent of its net assets in preferred stocks and other pre... More
John Hancock 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 John Hancock'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 John Hancock Preferred upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.2415 | |||
| Information Ratio | (0.32) | |||
| Maximum Drawdown | 1.22 | |||
| Value At Risk | (0.35) | |||
| Potential Upside | 0.5208 |
John Hancock Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for John Hancock's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as John Hancock's standard deviation. In reality, there are many statistical measures that can use John Hancock historical prices to predict the future John Hancock's volatility.| Risk Adjusted Performance | 0.0236 | |||
| Jensen Alpha | (0) | |||
| Total Risk Alpha | (0.03) | |||
| Sortino Ratio | (0.35) | |||
| Treynor Ratio | 0.06 |
John Hancock Preferred Backtested Returns
John Hancock is very steady at the moment. John Hancock Preferred holds Efficiency (Sharpe) Ratio of 0.0091, which attests that the entity had a 0.0091% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for John Hancock Preferred, which you can use to evaluate the volatility of the entity. Please check out John Hancock's Market Risk Adjusted Performance of 0.07, risk adjusted performance of 0.0236, and Downside Deviation of 0.2415 to validate if the risk estimate we provide is consistent with the expected return of 0.0024%. The etf retains a Market Volatility (i.e., Beta) of 0.0822, which attests to not very significant fluctuations relative to the market. As returns on the market increase, John Hancock's returns are expected to increase less than the market. However, during the bear market, the loss of holding John Hancock is expected to be smaller as well.
Auto-correlation | -0.74 |
Almost perfect reverse predictability
John Hancock Preferred has almost perfect reverse predictability. Overlapping area represents the amount of predictability between John Hancock time series from 16th of November 2024 to 1st of December 2024 and 1st of December 2024 to 16th of December 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 John Hancock Preferred price movement. The serial correlation of -0.74 indicates that around 74.0% of current John Hancock price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.74 | |
| Spearman Rank Test | 0.01 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
John Hancock Preferred lagged returns against current returns
Autocorrelation, which is John Hancock 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 John Hancock's etf expected returns. We can calculate the autocorrelation of John Hancock returns to help us make a trade decision. For example, suppose you find that John Hancock 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 |
John Hancock 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 John Hancock etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if John Hancock etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in John Hancock etf over time.
Current vs Lagged Prices |
| Timeline |
John Hancock Lagged Returns
When evaluating John Hancock's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of John Hancock etf have on its future price. John Hancock 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, John Hancock autocorrelation shows the relationship between John Hancock etf current value and its past values and can show if there is a momentum factor associated with investing in John Hancock Preferred.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
When determining whether John Hancock Preferred offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of John Hancock'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 John Hancock Preferred Etf. Outlined below are crucial reports that will aid in making a well-informed decision on John Hancock Preferred Etf:Check out John Hancock Correlation, John Hancock Volatility and John Hancock Alpha and Beta module to complement your research on John Hancock. You can also try the Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
John Hancock 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.