Alps Etf Trust Etf Market Value
| OEFA Etf | 34.42 0.28 0.81% |
| Symbol | ALPS |
The market value of ALPS ETF Trust is measured differently than its book value, which is the value of ALPS that is recorded on the company's balance sheet. Investors also form their own opinion of ALPS ETF's value that differs from its market value or its book value, called intrinsic value, which is ALPS ETF'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 ALPS ETF's market value can be influenced by many factors that don't directly affect ALPS ETF'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 ALPS ETF's value and its price as these two are different measures arrived at by different means. Investors typically determine if ALPS ETF is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, ALPS ETF'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.
ALPS ETF '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 ALPS ETF'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 ALPS ETF.
| 10/17/2025 |
| 01/15/2026 |
If you would invest 0.00 in ALPS ETF on October 17, 2025 and sell it all today you would earn a total of 0.00 from holding ALPS ETF Trust or generate 0.0% return on investment in ALPS ETF over 90 days. ALPS ETF is related to or competes with John Hancock, Investment Managers, SPDR MSCI, Northern Lights, Pacer Swan, AllianzIM Large, and SmartETFs Dividend. More
ALPS ETF 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 ALPS ETF'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 ALPS ETF Trust upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.7786 | |||
| Information Ratio | (0.09) | |||
| Maximum Drawdown | 2.68 | |||
| Value At Risk | (1.42) | |||
| Potential Upside | 1.09 |
ALPS ETF Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for ALPS ETF's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as ALPS ETF's standard deviation. In reality, there are many statistical measures that can use ALPS ETF historical prices to predict the future ALPS ETF's volatility.| Risk Adjusted Performance | 0.0518 | |||
| Jensen Alpha | (0.04) | |||
| Total Risk Alpha | (0.07) | |||
| Sortino Ratio | (0.09) | |||
| Treynor Ratio | 0.0583 |
ALPS ETF Trust Backtested Returns
At this point, ALPS ETF is very steady. ALPS ETF Trust secures Sharpe Ratio (or Efficiency) of 0.0605, which signifies that the etf had a 0.0605 % return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for ALPS ETF Trust, which you can use to evaluate the volatility of the entity. Please confirm ALPS ETF's mean deviation of 0.588, and Risk Adjusted Performance of 0.0518 to double-check if the risk estimate we provide is consistent with the expected return of 0.0447%. The etf shows a Beta (market volatility) of 0.75, which signifies possible diversification benefits within a given portfolio. As returns on the market increase, ALPS ETF's returns are expected to increase less than the market. However, during the bear market, the loss of holding ALPS ETF is expected to be smaller as well.
Auto-correlation | -0.75 |
Almost perfect reverse predictability
ALPS ETF Trust has almost perfect reverse predictability. Overlapping area represents the amount of predictability between ALPS ETF time series from 17th of October 2025 to 1st of December 2025 and 1st of December 2025 to 15th 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 ALPS ETF Trust price movement. The serial correlation of -0.75 indicates that around 75.0% of current ALPS ETF price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.75 | |
| Spearman Rank Test | -0.82 | |
| Residual Average | 0.0 | |
| Price Variance | 0.38 |
ALPS ETF Trust lagged returns against current returns
Autocorrelation, which is ALPS ETF 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 ALPS ETF's etf expected returns. We can calculate the autocorrelation of ALPS ETF returns to help us make a trade decision. For example, suppose you find that ALPS ETF 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 |
ALPS ETF 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 ALPS ETF etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if ALPS ETF etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in ALPS ETF etf over time.
Current vs Lagged Prices |
| Timeline |
ALPS ETF Lagged Returns
When evaluating ALPS ETF's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of ALPS ETF etf have on its future price. ALPS ETF 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, ALPS ETF autocorrelation shows the relationship between ALPS ETF etf current value and its past values and can show if there is a momentum factor associated with investing in ALPS ETF 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 ALPS ETF Trust offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of ALPS ETF's financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Alps Etf Trust Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Alps Etf Trust Etf:Check out ALPS ETF Correlation, ALPS ETF Volatility and ALPS ETF Alpha and Beta module to complement your research on ALPS ETF. For information on how to trade ALPS Etf refer to our How to Trade ALPS Etf guide.You can also try the Portfolio Dashboard module to portfolio dashboard that provides centralized access to all your investments.
ALPS ETF 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.