Alpha Architect Quantitative Etf Market Value
| QMOM Etf | USD 56.70 0.84 1.50% |
| Symbol | Alpha |
The market value of Alpha Architect Quan is measured differently than its book value, which is the value of Alpha that is recorded on the company's balance sheet. Investors also form their own opinion of Alpha Architect's value that differs from its market value or its book value, called intrinsic value, which is Alpha Architect'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 Alpha Architect's market value can be influenced by many factors that don't directly affect Alpha Architect'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 Alpha Architect's value and its price as these two are different measures arrived at by different means. Investors typically determine if Alpha Architect is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Alpha Architect'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.
Alpha Architect '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 Alpha Architect'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 Alpha Architect.
| 05/14/2022 |
| 05/03/2024 |
If you would invest 0.00 in Alpha Architect on May 14, 2022 and sell it all today you would earn a total of 0.00 from holding Alpha Architect Quantitative or generate 0.0% return on investment in Alpha Architect over 720 days. Alpha Architect is related to or competes with Freedom Day, IShares MSCI, IShares Dividend, SmartETFs Dividend, Listed Funds, Martin Currie, and Global X. The Adviser employs a multi-step, quantitative, rules-based methodology to identify a portfolio of approximately 50 to 1... More
Alpha Architect 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 Alpha Architect'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 Alpha Architect Quantitative upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.35 | |||
| Information Ratio | 0.0487 | |||
| Maximum Drawdown | 5.4 | |||
| Value At Risk | (1.89) | |||
| Potential Upside | 2.12 |
Alpha Architect Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Alpha Architect's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Alpha Architect's standard deviation. In reality, there are many statistical measures that can use Alpha Architect historical prices to predict the future Alpha Architect's volatility.| Risk Adjusted Performance | 0.0629 | |||
| Jensen Alpha | 0.1023 | |||
| Total Risk Alpha | 0.0162 | |||
| Sortino Ratio | 0.0488 | |||
| Treynor Ratio | 0.5822 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Alpha Architect'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.
Alpha Architect Quan Backtested Returns
We consider Alpha Architect very steady. Alpha Architect Quan secures Sharpe Ratio (or Efficiency) of 0.0896, which signifies that the etf had a 0.0896% return per unit of risk over the last 3 months. We have found thirty technical indicators for Alpha Architect Quantitative, which you can use to evaluate the volatility of the entity. Please confirm Alpha Architect's Downside Deviation of 1.35, risk adjusted performance of 0.0629, and Mean Deviation of 1.09 to double-check if the risk estimate we provide is consistent with the expected return of 0.12%. The etf shows a Beta (market volatility) of 0.19, which signifies not very significant fluctuations relative to the market. As returns on the market increase, Alpha Architect's returns are expected to increase less than the market. However, during the bear market, the loss of holding Alpha Architect is expected to be smaller as well.
Auto-correlation | -0.38 |
Poor reverse predictability
Alpha Architect Quantitative has poor reverse predictability. Overlapping area represents the amount of predictability between Alpha Architect time series from 14th of May 2022 to 9th of May 2023 and 9th of May 2023 to 3rd of May 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 Alpha Architect Quan price movement. The serial correlation of -0.38 indicates that just about 38.0% of current Alpha Architect price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.38 | |
| Spearman Rank Test | -0.24 | |
| Residual Average | 0.0 | |
| Price Variance | 30.09 |
Alpha Architect Quan lagged returns against current returns
Autocorrelation, which is Alpha Architect 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 Alpha Architect's etf expected returns. We can calculate the autocorrelation of Alpha Architect returns to help us make a trade decision. For example, suppose you find that Alpha Architect 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 |
Alpha Architect 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 Alpha Architect etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Alpha Architect etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Alpha Architect etf over time.
Current vs Lagged Prices |
| Timeline |
Alpha Architect Lagged Returns
When evaluating Alpha Architect's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Alpha Architect etf have on its future price. Alpha Architect 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, Alpha Architect autocorrelation shows the relationship between Alpha Architect etf current value and its past values and can show if there is a momentum factor associated with investing in Alpha Architect Quantitative.
Regressed Prices |
| Timeline |
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Check out Alpha Architect Correlation, Alpha Architect Volatility and Alpha Architect Alpha and Beta module to complement your research on Alpha Architect. You can also try the Instant Ratings module to determine any equity ratings based on digital recommendations. Macroaxis instant equity ratings are based on combination of fundamental analysis and risk-adjusted market performance.
Alpha Architect 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.