Commodities Strategy Fund Market Value
| RYMEX Fund | USD 31.22 0.07 0.22% |
| Symbol | Commodities |
Commodities Strategy '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 Commodities Strategy's mutual fund 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 Commodities Strategy.
| 01/26/2024 |
| 04/25/2024 |
If you would invest 0.00 in Commodities Strategy on January 26, 2024 and sell it all today you would earn a total of 0.00 from holding Commodities Strategy Fund or generate 0.0% return on investment in Commodities Strategy over 90 days. Commodities Strategy is related to or competes with Commodityrealreturn, and Pimco Commoditiesplus. The fund seeks exposure to the performance of the commodities markets More
Commodities Strategy 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 Commodities Strategy's mutual fund 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 Commodities Strategy Fund upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.8264 | |||
| Information Ratio | 0.0867 | |||
| Maximum Drawdown | 3.22 | |||
| Value At Risk | (1.43) | |||
| Potential Upside | 1.29 |
Commodities Strategy Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Commodities Strategy's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Commodities Strategy's standard deviation. In reality, there are many statistical measures that can use Commodities Strategy historical prices to predict the future Commodities Strategy's volatility.| Risk Adjusted Performance | 0.133 | |||
| Jensen Alpha | 0.147 | |||
| Total Risk Alpha | 0.0466 | |||
| Sortino Ratio | 0.081 | |||
| Treynor Ratio | 2.5 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Commodities Strategy'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.
Commodities Strategy Backtested Returns
We consider Commodities Strategy very steady. Commodities Strategy secures Sharpe Ratio (or Efficiency) of 0.13, which signifies that the fund had a 0.13% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Commodities Strategy Fund, which you can use to evaluate the volatility of the entity. Please confirm Commodities Strategy's Risk Adjusted Performance of 0.133, downside deviation of 0.8264, and Mean Deviation of 0.6313 to double-check if the risk estimate we provide is consistent with the expected return of 0.0982%. The fund shows a Beta (market volatility) of 0.0608, which signifies not very significant fluctuations relative to the market. As returns on the market increase, Commodities Strategy's returns are expected to increase less than the market. However, during the bear market, the loss of holding Commodities Strategy is expected to be smaller as well.
Auto-correlation | 0.23 |
Weak predictability
Commodities Strategy Fund has weak predictability. Overlapping area represents the amount of predictability between Commodities Strategy time series from 26th of January 2024 to 11th of March 2024 and 11th of March 2024 to 25th 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 Commodities Strategy price movement. The serial correlation of 0.23 indicates that over 23.0% of current Commodities Strategy price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.23 | |
| Spearman Rank Test | 0.28 | |
| Residual Average | 0.0 | |
| Price Variance | 0.37 |
Commodities Strategy lagged returns against current returns
Autocorrelation, which is Commodities Strategy mutual fund'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 Commodities Strategy's mutual fund expected returns. We can calculate the autocorrelation of Commodities Strategy returns to help us make a trade decision. For example, suppose you find that Commodities Strategy has exhibited high autocorrelation historically, and you observe that the mutual fund 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 |
Commodities Strategy 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 Commodities Strategy mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Commodities Strategy mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Commodities Strategy mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Commodities Strategy Lagged Returns
When evaluating Commodities Strategy's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Commodities Strategy mutual fund have on its future price. Commodities Strategy 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, Commodities Strategy autocorrelation shows the relationship between Commodities Strategy mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Commodities Strategy Fund.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
Check out Commodities Strategy Correlation, Commodities Strategy Volatility and Commodities Strategy Alpha and Beta module to complement your research on Commodities Strategy. Note that the Commodities Strategy information on this page should be used as a complementary analysis to other Commodities Strategy'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 Bond Analysis module to evaluate and analyze corporate bonds as a potential investment for your portfolios..
Commodities Strategy technical mutual fund 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, fund market cycles, or different charting patterns.