First Trust Equity Etf Market Value
| FPX Etf | USD 124.64 0.67 0.53% |
| Symbol | First |
The market value of First Trust Equity is measured differently than its book value, which is the value of First that is recorded on the company's balance sheet. Investors also form their own opinion of First Trust's value that differs from its market value or its book value, called intrinsic value, which is First Trust'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 First Trust's market value can be influenced by many factors that don't directly affect First Trust'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 First Trust's value and its price as these two are different measures arrived at by different means. Investors typically determine if First Trust is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, First Trust'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.
First Trust '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 First Trust'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 First Trust.
| 11/15/2024 |
| 12/15/2024 |
If you would invest 0.00 in First Trust on November 15, 2024 and sell it all today you would earn a total of 0.00 from holding First Trust Equity or generate 0.0% return on investment in First Trust over 30 days. First Trust is related to or competes with Vanguard Mid, SPDR SP, Vanguard. The fund will normally invest at least 90 percent of its net assets in the common stocks that comprise the index More
First Trust 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 First Trust'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 First Trust Equity upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.14 | |||
| Information Ratio | 0.1438 | |||
| Maximum Drawdown | 7.4 | |||
| Value At Risk | (1.56) | |||
| Potential Upside | 2.62 |
First Trust Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for First Trust's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as First Trust's standard deviation. In reality, there are many statistical measures that can use First Trust historical prices to predict the future First Trust's volatility.| Risk Adjusted Performance | 0.1651 | |||
| Jensen Alpha | 0.1699 | |||
| Total Risk Alpha | 0.1152 | |||
| Sortino Ratio | 0.1617 | |||
| Treynor Ratio | 0.2359 |
First Trust Equity Backtested Returns
First Trust appears to be very steady, given 3 months investment horizon. First Trust Equity secures Sharpe Ratio (or Efficiency) of 0.2, which denotes the etf had a 0.2% return per unit of risk over the last 3 months. We have found thirty technical indicators for First Trust Equity, which you can use to evaluate the volatility of the entity. Please utilize First Trust's Mean Deviation of 0.9524, downside deviation of 1.14, and Coefficient Of Variation of 451.03 to check if our risk estimates are consistent with your expectations. The etf shows a Beta (market volatility) of 1.17, which means 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, First Trust will likely underperform.
Auto-correlation | -0.54 |
Good reverse predictability
First Trust Equity has good reverse predictability. Overlapping area represents the amount of predictability between First Trust time series from 15th of November 2024 to 30th of November 2024 and 30th of November 2024 to 15th 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 First Trust Equity price movement. The serial correlation of -0.54 indicates that about 54.0% of current First Trust price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.54 | |
| Spearman Rank Test | -0.65 | |
| Residual Average | 0.0 | |
| Price Variance | 6.77 |
First Trust Equity lagged returns against current returns
Autocorrelation, which is First Trust 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 First Trust's etf expected returns. We can calculate the autocorrelation of First Trust returns to help us make a trade decision. For example, suppose you find that First Trust 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 |
First Trust 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 First Trust etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if First Trust etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in First Trust etf over time.
Current vs Lagged Prices |
| Timeline |
First Trust Lagged Returns
When evaluating First Trust's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of First Trust etf have on its future price. First Trust 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, First Trust autocorrelation shows the relationship between First Trust etf current value and its past values and can show if there is a momentum factor associated with investing in First Trust Equity.
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 First Trust Equity is a strong investment it is important to analyze First Trust's competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact First Trust's future performance. For an informed investment choice regarding First Etf, refer to the following important reports:Check out First Trust Correlation, First Trust Volatility and First Trust Alpha and Beta module to complement your research on First Trust. You can also try the Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
First Trust 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.