Ea Series Trust Etf Market Value
| ARKZ Etf | 41.09 3.54 9.43% |
| Symbol | ARKZ |
The market value of EA Series Trust is measured differently than its book value, which is the value of ARKZ 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.
| 10/29/2024 |
| 11/28/2024 |
If you would invest 0.00 in EA Series on October 29, 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 Grayscale Bitcoin, ProShares Bitcoin, Amplify Transformational, Siren Nasdaq, Bitwise Crypto, Grayscale Bitcoin, and First Trust. 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 | 3.18 | |||
| Information Ratio | 0.0623 | |||
| Maximum Drawdown | 18.64 | |||
| Value At Risk | (4.96) | |||
| Potential Upside | 7.97 |
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 | 0.0792 | |||
| Jensen Alpha | 0.4287 | |||
| Total Risk Alpha | (0.25) | |||
| Sortino Ratio | 0.0809 | |||
| Treynor Ratio | (0.77) |
EA Series Trust Backtested Returns
EA Series appears to be not too volatile, given 3 months investment horizon. EA Series Trust retains Efficiency (Sharpe Ratio) of 0.15, which denotes the etf had a 0.15% return per unit of price deviation over the last 3 months. By examining EA Series' technical indicators, you can evaluate if the expected return of 0.66% is justified by implied risk. Please utilize EA Series' Market Risk Adjusted Performance of (0.76), downside deviation of 3.18, and Standard Deviation of 4.13 to check if our risk estimates are consistent with your expectations. The entity owns a Beta (Systematic Risk) of -0.48, which means possible diversification benefits within a given portfolio. As returns on the market increase, returns on owning EA Series are expected to decrease at a much lower rate. During the bear market, EA Series is likely to outperform the market.
Auto-correlation | 0.80 |
Very good predictability
EA Series Trust has very good predictability. Overlapping area represents the amount of predictability between EA Series time series from 29th of October 2024 to 13th of November 2024 and 13th of November 2024 to 28th 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 0.8 indicates that around 80.0% of current EA Series price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.8 | |
| Spearman Rank Test | 0.84 | |
| Residual Average | 0.0 | |
| Price Variance | 3.85 |
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 |
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.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 ARKZ 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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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.