Invesco Db Commodity Etf Market Value
| DBC Etf | USD 22.54 0.16 0.71% |
| Symbol | Invesco |
The market value of Invesco DB Commodity is measured differently than its book value, which is the value of Invesco that is recorded on the company's balance sheet. Investors also form their own opinion of Invesco DB's value that differs from its market value or its book value, called intrinsic value, which is Invesco DB'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 Invesco DB's market value can be influenced by many factors that don't directly affect Invesco DB'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 Invesco DB's value and its price as these two are different measures arrived at by different means. Investors typically determine if Invesco DB is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Invesco DB'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.
Invesco DB '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 Invesco DB'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 Invesco DB.
| 10/23/2024 |
| 11/22/2024 |
If you would invest 0.00 in Invesco DB on October 23, 2024 and sell it all today you would earn a total of 0.00 from holding Invesco DB Commodity or generate 0.0% return on investment in Invesco DB over 30 days. Invesco DB is related to or competes with Invesco DB, IShares SP, Invesco DB, IPath Bloomberg, and VanEck Agribusiness. The fund pursues its investment objective by investing in a portfolio of exchange-traded futures on Light Sweet Crude Oi... More
Invesco DB 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 Invesco DB'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 Invesco DB Commodity upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.17 | |||
| Information Ratio | (0.05) | |||
| Maximum Drawdown | 4.65 | |||
| Value At Risk | (1.92) | |||
| Potential Upside | 1.79 |
Invesco DB Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Invesco DB's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Invesco DB's standard deviation. In reality, there are many statistical measures that can use Invesco DB historical prices to predict the future Invesco DB's volatility.| Risk Adjusted Performance | 0.0371 | |||
| Jensen Alpha | 0.0413 | |||
| Total Risk Alpha | (0.11) | |||
| Sortino Ratio | (0.05) | |||
| Treynor Ratio | (9.51) |
Invesco DB Commodity Backtested Returns
At this point, Invesco DB is very steady. Invesco DB Commodity holds Efficiency (Sharpe) Ratio of 0.0087, which attests that the entity had a 0.0087% return per unit of risk over the last 3 months. We have found thirty technical indicators for Invesco DB Commodity, which you can use to evaluate the volatility of the entity. Please check out Invesco DB's Risk Adjusted Performance of 0.0371, downside deviation of 1.17, and Market Risk Adjusted Performance of (9.50) to validate if the risk estimate we provide is consistent with the expected return of 0.0099%. The etf retains a Market Volatility (i.e., Beta) of -0.0043, which attests to not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Invesco DB are expected to decrease at a much lower rate. During the bear market, Invesco DB is likely to outperform the market.
Auto-correlation | 0.52 |
Modest predictability
Invesco DB Commodity has modest predictability. Overlapping area represents the amount of predictability between Invesco DB time series from 23rd of October 2024 to 7th of November 2024 and 7th of November 2024 to 22nd 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 Invesco DB Commodity price movement. The serial correlation of 0.52 indicates that about 52.0% of current Invesco DB price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.52 | |
| Spearman Rank Test | -0.29 | |
| Residual Average | 0.0 | |
| Price Variance | 0.09 |
Invesco DB Commodity lagged returns against current returns
Autocorrelation, which is Invesco DB 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 Invesco DB's etf expected returns. We can calculate the autocorrelation of Invesco DB returns to help us make a trade decision. For example, suppose you find that Invesco DB 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 |
Invesco DB 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 Invesco DB etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Invesco DB etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Invesco DB etf over time.
Current vs Lagged Prices |
| Timeline |
Invesco DB Lagged Returns
When evaluating Invesco DB's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Invesco DB etf have on its future price. Invesco DB 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, Invesco DB autocorrelation shows the relationship between Invesco DB etf current value and its past values and can show if there is a momentum factor associated with investing in Invesco DB Commodity.
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 Invesco DB Commodity offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Invesco DB'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 Invesco Db Commodity Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Invesco Db Commodity Etf:Check out Invesco DB Correlation, Invesco DB Volatility and Invesco DB Alpha and Beta module to complement your research on Invesco DB. You can also try the My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
Invesco DB 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.