First Trust Smid Etf Market Value
| FSGS Etf | 31.23 0.21 0.67% |
| Symbol | First |
Investors evaluate First Trust SMID using market value (trading price) and book value (balance sheet equity), each telling a different story. Calculating First Trust's intrinsic value—the estimated true worth—helps identify when the stock trades at a discount or premium to fair value. Analysts utilize numerous techniques to assess fundamental value, seeking to purchase shares when trading prices fall beneath estimated intrinsic worth. External factors like market trends, sector rotation, and investor psychology can cause First Trust's market price to deviate significantly 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. Conversely, First Trust's market price signifies the transaction level at which participants voluntarily complete trades.
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.
| 10/31/2025 |
| 01/29/2026 |
If you would invest 0.00 in First Trust on October 31, 2025 and sell it all today you would earn a total of 0.00 from holding First Trust SMID or generate 0.0% return on investment in First Trust over 90 days. First Trust is related to or competes with First Trust, WBI BullBear, ProShares Ultra, Strategy Shares, Nushares ETF, Global X, and JP Morgan. 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 SMID upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.8517 | |||
| Information Ratio | (0.01) | |||
| Maximum Drawdown | 3.7 | |||
| Value At Risk | (1.48) | |||
| Potential Upside | 1.56 |
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 | 0.0433 | |||
| Jensen Alpha | (0.01) | |||
| Total Risk Alpha | (0.02) | |||
| Sortino Ratio | (0.01) | |||
| Treynor Ratio | 0.0418 |
First Trust January 29, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0433 | |||
| Market Risk Adjusted Performance | 0.0518 | |||
| Mean Deviation | 0.6743 | |||
| Semi Deviation | 0.7908 | |||
| Downside Deviation | 0.8517 | |||
| Coefficient Of Variation | 1744.63 | |||
| Standard Deviation | 0.8737 | |||
| Variance | 0.7633 | |||
| Information Ratio | (0.01) | |||
| Jensen Alpha | (0.01) | |||
| Total Risk Alpha | (0.02) | |||
| Sortino Ratio | (0.01) | |||
| Treynor Ratio | 0.0418 | |||
| Maximum Drawdown | 3.7 | |||
| Value At Risk | (1.48) | |||
| Potential Upside | 1.56 | |||
| Downside Variance | 0.7254 | |||
| Semi Variance | 0.6253 | |||
| Expected Short fall | (0.71) | |||
| Skewness | 0.1267 | |||
| Kurtosis | 0.3864 |
First Trust SMID Backtested Returns
Currently, First Trust SMID is very steady. First Trust SMID secures Sharpe Ratio (or Efficiency) of 0.0573, which denotes the etf had a 0.0573 % return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for First Trust SMID, which you can use to evaluate the volatility of the entity. Please confirm First Trust's Downside Deviation of 0.8517, mean deviation of 0.6743, and Coefficient Of Variation of 1744.63 to check if the risk estimate we provide is consistent with the expected return of 0.0501%. The etf shows a Beta (market volatility) of 0.96, which means possible diversification benefits within a given portfolio. First Trust returns are very sensitive to returns on the market. As the market goes up or down, First Trust is expected to follow.
Auto-correlation | 0.46 |
Average predictability
First Trust SMID has average predictability. Overlapping area represents the amount of predictability between First Trust time series from 31st of October 2025 to 15th of December 2025 and 15th of December 2025 to 29th of January 2026. 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 SMID price movement. The serial correlation of 0.46 indicates that about 46.0% of current First Trust price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.46 | |
| Spearman Rank Test | 0.48 | |
| Residual Average | 0.0 | |
| Price Variance | 0.19 |
Thematic Opportunities
Explore Investment Opportunities
Check out First Trust Correlation, First Trust Volatility and First Trust Performance module to complement your research on First Trust. You can also try the Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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.