Db Gold Double Etf Market Value
| DZZ Etf | USD 2.06 0.06 3.00% |
| Symbol | DZZ |
The market value of DB Gold Double is measured differently than its book value, which is the value of DZZ that is recorded on the company's balance sheet. Investors also form their own opinion of DB Gold's value that differs from its market value or its book value, called intrinsic value, which is DB Gold'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 DB Gold's market value can be influenced by many factors that don't directly affect DB Gold'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 DB Gold's value and its price as these two are different measures arrived at by different means. Investors typically determine if DB Gold is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, DB Gold'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.
DB Gold '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 DB Gold'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 DB Gold.
| 12/20/2023 |
| 04/18/2024 |
If you would invest 0.00 in DB Gold on December 20, 2023 and sell it all today you would earn a total of 0.00 from holding DB Gold Double or generate 0.0% return on investment in DB Gold over 120 days. DB Gold is related to or competes with DB Gold, DB Gold, ProShares UltraShort, ProShares UltraShort, and ProShares UltraShort. The index is intended to reflect changes in the market value of certain gold futures contracts and is comprised of a sin... More
DB Gold 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 DB Gold'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 DB Gold Double upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.15) | |||
| Maximum Drawdown | 12.88 | |||
| Value At Risk | (4.08) | |||
| Potential Upside | 3.47 |
DB Gold Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for DB Gold's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as DB Gold's standard deviation. In reality, there are many statistical measures that can use DB Gold historical prices to predict the future DB Gold's volatility.| Risk Adjusted Performance | (0.07) | |||
| Jensen Alpha | (0.31) | |||
| Total Risk Alpha | (0.48) | |||
| Treynor Ratio | 9.37 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of DB Gold'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.
DB Gold Double Backtested Returns
DB Gold Double retains Efficiency (Sharpe Ratio) of -0.12, which denotes the etf had a -0.12% return per unit of price deviation over the last 3 months. DB Gold exposes twenty-four different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm DB Gold's Standard Deviation of 2.39, market risk adjusted performance of 9.38, and Information Ratio of (0.15) to check the risk estimate we provide. The entity owns a Beta (Systematic Risk) of -0.0328, which means not very significant fluctuations relative to the market. As returns on the market increase, returns on owning DB Gold are expected to decrease at a much lower rate. During the bear market, DB Gold is likely to outperform the market.
Auto-correlation | -0.66 |
Very good reverse predictability
DB Gold Double has very good reverse predictability. Overlapping area represents the amount of predictability between DB Gold time series from 20th of December 2023 to 18th of February 2024 and 18th of February 2024 to 18th of April 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 DB Gold Double price movement. The serial correlation of -0.66 indicates that around 66.0% of current DB Gold price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.66 | |
| Spearman Rank Test | -0.66 | |
| Residual Average | 0.0 | |
| Price Variance | 0.04 |
DB Gold Double lagged returns against current returns
Autocorrelation, which is DB Gold 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 DB Gold's etf expected returns. We can calculate the autocorrelation of DB Gold returns to help us make a trade decision. For example, suppose you find that DB Gold 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 |
DB Gold 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 DB Gold etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if DB Gold etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in DB Gold etf over time.
Current vs Lagged Prices |
| Timeline |
DB Gold Lagged Returns
When evaluating DB Gold's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of DB Gold etf have on its future price. DB Gold 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, DB Gold autocorrelation shows the relationship between DB Gold etf current value and its past values and can show if there is a momentum factor associated with investing in DB Gold Double.
Regressed Prices |
| Timeline |
Pair Trading with DB Gold
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if DB Gold position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in DB Gold will appreciate offsetting losses from the drop in the long position's value.Moving together with DZZ Etf
| 0.81 | SCO | ProShares UltraShort Buyout Trend | PairCorr |
| 0.96 | ZSL | ProShares UltraShort | PairCorr |
| 0.98 | GLL | ProShares UltraShort Gold | PairCorr |
| 0.9 | GDXD | MicroSectors Gold Miners | PairCorr |
| 0.9 | WTID | UBS ETRACS | PairCorr |
Moving against DZZ Etf
| 0.8 | TSJA | TSJA | PairCorr |
| 0.61 | DSJA | DSJA | PairCorr |
The ability to find closely correlated positions to DB Gold could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace DB Gold when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back DB Gold - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling DB Gold Double to buy it.
The correlation of DB Gold is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as DB Gold moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if DB Gold Double moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for DB Gold can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out DB Gold Correlation, DB Gold Volatility and DB Gold Alpha and Beta module to complement your research on DB Gold. Note that the DB Gold Double information on this page should be used as a complementary analysis to other DB Gold's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Efficient Frontier module to plot and analyze your portfolio and positions against risk-return landscape of the market..
DB Gold 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.