First Trust Nasdaq Etf Market Value
| FTXN Etf | USD 32.56 0.33 1.00% |
| Symbol | First |
The market value of First Trust Nasdaq 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.
| 04/27/2022 |
| 04/16/2024 |
If you would invest 0.00 in First Trust on April 27, 2022 and sell it all today you would earn a total of 0.00 from holding First Trust Nasdaq or generate 0.0% return on investment in First Trust over 720 days. First Trust is related to or competes with Invesco DWA, HUMANA, Morningstar Unconstrained, Thrivent High, High-yield Municipal, and Via Renewables. The fund will normally invest at least 90 percent of its net assets in the common stocks and depository receipts that co... 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 Nasdaq upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.9716 | |||
| Information Ratio | 0.195 | |||
| Maximum Drawdown | 3.84 | |||
| Value At Risk | (1.31) | |||
| Potential Upside | 1.83 |
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 | 0.1738 | |||
| Jensen Alpha | 0.2115 | |||
| Total Risk Alpha | 0.1516 | |||
| Sortino Ratio | 0.1971 | |||
| Treynor Ratio | 0.3673 |
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 Nasdaq Backtested Returns
First Trust appears to be very steady, given 3 months investment horizon. First Trust Nasdaq secures Sharpe Ratio (or Efficiency) of 0.34, which denotes the etf had a 0.34% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for First Trust Nasdaq, which you can use to evaluate the volatility of the entity. Please utilize First Trust's Downside Deviation of 0.9716, coefficient of variation of 364.05, and Mean Deviation of 0.7576 to check if our risk estimates are consistent with your expectations. The etf shows a Beta (market volatility) of 0.71, which means possible diversification benefits within a given portfolio. 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 | 0.16 |
Very weak predictability
First Trust Nasdaq has very weak predictability. Overlapping area represents the amount of predictability between First Trust time series from 27th of April 2022 to 22nd of April 2023 and 22nd of April 2023 to 16th of April 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 Nasdaq price movement. The serial correlation of 0.16 indicates that over 16.0% of current First Trust price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.16 | |
| Spearman Rank Test | 0.2 | |
| Residual Average | 0.0 | |
| Price Variance | 4.43 |
First Trust Nasdaq 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 Nasdaq.
Regressed Prices |
| Timeline |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards First Trust in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, First Trust's short interest history, or implied volatility extrapolated from First Trust options trading.
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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.