First Trust Low Etf Market Value
| LDSF Etf | USD 18.82 0.01 0.05% |
| Symbol | First |
The market value of First Trust Low 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.
| 12/06/2022 |
| 11/25/2024 |
If you would invest 0.00 in First Trust on December 6, 2022 and sell it all today you would earn a total of 0.00 from holding First Trust Low or generate 0.0% return on investment in First Trust over 720 days. First Trust is related to or competes with First Trust, First Trust, First Trust, First Trust, and First Trust. Under normal market conditions, the fund seeks to achieve its investment objectives by investing at least 80 percent of ... 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 Low upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.82) | |||
| Maximum Drawdown | 0.7954 | |||
| Value At Risk | (0.32) | |||
| Potential Upside | 0.2121 |
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 | (0.05) | |||
| Jensen Alpha | (0.01) | |||
| Total Risk Alpha | (0.04) | |||
| Treynor Ratio | (0.67) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of First Trust's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
First Trust Low Backtested Returns
First Trust Low secures Sharpe Ratio (or Efficiency) of -0.035, which denotes the etf had a -0.035% return per unit of risk over the last 3 months. First Trust Low exposes twenty-four different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm First Trust's Mean Deviation of 0.1197, standard deviation of 0.1624, and Variance of 0.0264 to check the risk estimate we provide. The etf shows a Beta (market volatility) of 0.0184, which means not very significant fluctuations relative to the market. As returns on the market increase, First Trust's returns are expected to increase less than the market. However, during the bear market, the loss of holding First Trust is expected to be smaller as well.
Auto-correlation | 0.61 |
Good predictability
First Trust Low has good predictability. Overlapping area represents the amount of predictability between First Trust time series from 6th of December 2022 to 1st of December 2023 and 1st of December 2023 to 25th 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 First Trust Low price movement. The serial correlation of 0.61 indicates that roughly 61.0% of current First Trust price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.61 | |
| Spearman Rank Test | 0.65 | |
| Residual Average | 0.0 | |
| Price Variance | 0.13 |
First Trust Low 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 Low.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
When determining whether First Trust Low 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 Efficient Frontier module to plot and analyze your portfolio and positions against risk-return landscape of the market..
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.