Ea Series Trust Etf Market Value
STXG Etf | 44.00 0.33 0.76% |
Symbol | STXG |
The market value of EA Series Trust is measured differently than its book value, which is the value of STXG that is recorded on the company's balance sheet. Investors also form their own opinion of EA Series' value that differs from its market value or its book value, called intrinsic value, which is EA Series' 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 EA Series' market value can be influenced by many factors that don't directly affect EA Series' 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 EA Series' value and its price as these two are different measures arrived at by different means. Investors typically determine if EA Series is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, EA Series' 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.
EA Series '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 EA Series' 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 EA Series.
10/31/2024 |
| 11/30/2024 |
If you would invest 0.00 in EA Series on October 31, 2024 and sell it all today you would earn a total of 0.00 from holding EA Series Trust or generate 0.0% return on investment in EA Series over 30 days. EA Series is related to or competes with EA Series, EA Series, EA Series, EA Series, and EA Series. EA Series is entity of United States. It is traded as Etf on NASDAQ exchange. More
EA Series 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 EA Series' 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 EA Series Trust upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 1.07 | |||
Information Ratio | 0.0026 | |||
Maximum Drawdown | 4.63 | |||
Value At Risk | (1.77) | |||
Potential Upside | 1.3 |
EA Series Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for EA Series' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as EA Series' standard deviation. In reality, there are many statistical measures that can use EA Series historical prices to predict the future EA Series' volatility.Risk Adjusted Performance | 0.1186 | |||
Jensen Alpha | 0.0209 | |||
Total Risk Alpha | (0.02) | |||
Sortino Ratio | 0.0022 | |||
Treynor Ratio | 0.152 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of EA Series' 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.
EA Series Trust Backtested Returns
At this point, EA Series is very steady. EA Series Trust retains Efficiency (Sharpe Ratio) of 0.21, which denotes the etf had a 0.21% return per unit of price deviation over the last 3 months. We have found twenty-nine technical indicators for EA Series, which you can use to evaluate the volatility of the entity. Please confirm EA Series' Standard Deviation of 0.915, downside deviation of 1.07, and Market Risk Adjusted Performance of 0.162 to check if the risk estimate we provide is consistent with the expected return of 0.18%. The entity owns a Beta (Systematic Risk) of 0.85, which means possible diversification benefits within a given portfolio. EA Series returns are very sensitive to returns on the market. As the market goes up or down, EA Series is expected to follow.
Auto-correlation | 0.88 |
Very good predictability
EA Series Trust has very good predictability. Overlapping area represents the amount of predictability between EA Series time series from 31st of October 2024 to 15th of November 2024 and 15th of November 2024 to 30th 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 EA Series Trust price movement. The serial correlation of 0.88 indicates that approximately 88.0% of current EA Series price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.88 | |
Spearman Rank Test | 0.89 | |
Residual Average | 0.0 | |
Price Variance | 0.16 |
EA Series Trust lagged returns against current returns
Autocorrelation, which is EA Series 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 EA Series' etf expected returns. We can calculate the autocorrelation of EA Series returns to help us make a trade decision. For example, suppose you find that EA Series 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 |
EA Series 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 EA Series etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if EA Series etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in EA Series etf over time.
Current vs Lagged Prices |
Timeline |
EA Series Lagged Returns
When evaluating EA Series' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of EA Series etf have on its future price. EA Series 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, EA Series autocorrelation shows the relationship between EA Series etf current value and its past values and can show if there is a momentum factor associated with investing in EA Series Trust.
Regressed Prices |
Timeline |
Currently Active Assets on Macroaxis
When determining whether EA Series Trust is a strong investment it is important to analyze EA Series' 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 EA Series' future performance. For an informed investment choice regarding STXG Etf, refer to the following important reports:Check out EA Series Correlation, EA Series Volatility and EA Series Alpha and Beta module to complement your research on EA Series. You can also try the Price Exposure Probability module to analyze equity upside and downside potential for a given time horizon across multiple markets.
EA Series 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.