First Trust Lunt Etf Market Value
| FCTR Etf | USD 34.22 0.34 0.98% |
| Symbol | First |
The market value of First Trust Lunt 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.
| 07/20/2023 |
| 12/11/2024 |
If you would invest 0.00 in First Trust on July 20, 2023 and sell it all today you would earn a total of 0.00 from holding First Trust Lunt or generate 0.0% return on investment in First Trust over 510 days. First Trust is related to or competes with FT Vest, Northern Lights, Dimensional International, JPMorgan Fundamental, Matthews China, Davis Select, and Dimensional ETF. 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 Lunt upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.719 | |||
| Information Ratio | 0.1333 | |||
| Maximum Drawdown | 4.44 | |||
| Value At Risk | (1.06) | |||
| Potential Upside | 1.5 |
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 | 0.2109 | |||
| Jensen Alpha | 0.1275 | |||
| Total Risk Alpha | 0.0946 | |||
| Sortino Ratio | 0.1465 | |||
| Treynor Ratio | 0.2725 |
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 Lunt Backtested Returns
First Trust appears to be out of control, given 3 months investment horizon. First Trust Lunt secures Sharpe Ratio (or Efficiency) of 0.26, which denotes the etf had a 0.26% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for First Trust Lunt, which you can use to evaluate the volatility of the entity. Please utilize First Trust's Mean Deviation of 0.6051, coefficient of variation of 343.91, and Downside Deviation of 0.719 to check if our risk estimates are consistent with your expectations. The etf shows a Beta (market volatility) of 0.81, 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 | 0.58 |
Modest predictability
First Trust Lunt has modest predictability. Overlapping area represents the amount of predictability between First Trust time series from 20th of July 2023 to 31st of March 2024 and 31st of March 2024 to 11th 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 Lunt price movement. The serial correlation of 0.58 indicates that roughly 58.0% of current First Trust price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.58 | |
| Spearman Rank Test | 0.55 | |
| Residual Average | 0.0 | |
| Price Variance | 2.5 |
First Trust Lunt 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 Lunt.
Regressed Prices |
| Timeline |
Pair Trading with First Trust
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if First Trust position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in First Trust will appreciate offsetting losses from the drop in the long position's value.Moving together with First Etf
| 0.98 | VTI | Vanguard Total Stock | PairCorr |
| 0.96 | SPY | SPDR SP 500 | PairCorr |
| 0.96 | IVV | iShares Core SP | PairCorr |
| 0.9 | VIG | Vanguard Dividend | PairCorr |
| 0.97 | VV | Vanguard Large Cap | PairCorr |
Moving against First Etf
The ability to find closely correlated positions to First Trust could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace First Trust when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back First Trust - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling First Trust Lunt to buy it.
The correlation of First Trust is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as First Trust moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if First Trust Lunt moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for First Trust can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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.