Commodities Strategy Fund Technical Analysis
| RYMBX Fund | USD 164.80 0.13 0.08% |
As of the 17th of February 2026, Commodities Strategy shows the Risk Adjusted Performance of 0.0636, downside deviation of 1.18, and Mean Deviation of 0.935. In respect to fundamental indicators, the technical analysis model gives you tools to check existing technical drivers of Commodities Strategy, as well as the relationship between them.
Commodities Strategy Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Commodities, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to CommoditiesCommodities |
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.
| 11/19/2025 |
| 02/17/2026 |
If you would invest 0.00 in Commodities Strategy on November 19, 2025 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 Retailing Fund, ProShares Ultra, Fidelity Income, Transportation Fund, Sp Smallcap, Sp 500, and Grayscale Funds. 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 | 1.18 | |||
| Information Ratio | 0.0148 | |||
| Maximum Drawdown | 6.05 | |||
| Value At Risk | (1.62) | |||
| Potential Upside | 1.82 |
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 | 0.0636 | |||
| Jensen Alpha | 0.0705 | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | 0.0145 | |||
| Treynor Ratio | 0.7017 |
Commodities Strategy February 17, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0636 | |||
| Market Risk Adjusted Performance | 0.7117 | |||
| Mean Deviation | 0.935 | |||
| Semi Deviation | 1.07 | |||
| Downside Deviation | 1.18 | |||
| Coefficient Of Variation | 1332.35 | |||
| Standard Deviation | 1.16 | |||
| Variance | 1.35 | |||
| Information Ratio | 0.0148 | |||
| Jensen Alpha | 0.0705 | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | 0.0145 | |||
| Treynor Ratio | 0.7017 | |||
| Maximum Drawdown | 6.05 | |||
| Value At Risk | (1.62) | |||
| Potential Upside | 1.82 | |||
| Downside Variance | 1.39 | |||
| Semi Variance | 1.15 | |||
| Expected Short fall | (1.05) | |||
| Skewness | (0.58) | |||
| Kurtosis | 1.13 |
Commodities Strategy Backtested Returns
At this stage we consider Commodities Mutual Fund to be very steady. Commodities Strategy secures Sharpe Ratio (or Efficiency) of 0.0937, which signifies that the fund had a 0.0937 % return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Commodities Strategy Fund, which you can use to evaluate the volatility of the entity. Please confirm Commodities Strategy's Mean Deviation of 0.935, downside deviation of 1.18, and Risk Adjusted Performance of 0.0636 to double-check if the risk estimate we provide is consistent with the expected return of 0.11%. The fund shows a Beta (market volatility) of 0.11, 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 | -0.15 |
Insignificant reverse predictability
Commodities Strategy Fund has insignificant reverse predictability. Overlapping area represents the amount of predictability between Commodities Strategy time series from 19th of November 2025 to 3rd of January 2026 and 3rd of January 2026 to 17th of February 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 Commodities Strategy price movement. The serial correlation of -0.15 indicates that less than 15.0% of current Commodities Strategy price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.15 | |
| Spearman Rank Test | 0.14 | |
| Residual Average | 0.0 | |
| Price Variance | 21.81 |
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.
Commodities Strategy Technical Analysis
The output start index for this execution was one with a total number of output elements of sixty. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Welles Wilder Directional Movement indicators. The ATR is a measure of Commodities Strategy volatility. High ATR values indicate high volatility, and low values indicate low volatility.
About Commodities Strategy Technical Analysis
The technical analysis module can be used to analyzes prices, returns, volume, basic money flow, and other market information and help investors to determine the real value of Commodities Strategy Fund on a daily or weekly bases. We use both bottom-up as well as top-down valuation methodologies to arrive at the intrinsic value of Commodities Strategy Fund based on its technical analysis. In general, a bottom-up approach, as applied to this mutual fund, focuses on Commodities Strategy price pattern first instead of the macroeconomic environment surrounding Commodities Strategy. By analyzing Commodities Strategy's financials, daily price indicators, and related drivers such as dividends, momentum ratios, and various types of growth rates, we attempt to find the most accurate representation of Commodities Strategy's intrinsic value. As compared to a bottom-up approach, our top-down model examines the macroeconomic factors that affect the industry/economy before zooming in to Commodities Strategy specific price patterns or momentum indicators. Please read more on our technical analysis page.
Commodities Strategy February 17, 2026 Technical Indicators
Most technical analysis of Commodities help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Commodities from various momentum indicators to cycle indicators. When you analyze Commodities charts, please remember that the event formation may indicate an entry point for a short seller, and look at different other indicators across different periods to confirm that a breakdown or reversion is likely to occur.
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0636 | |||
| Market Risk Adjusted Performance | 0.7117 | |||
| Mean Deviation | 0.935 | |||
| Semi Deviation | 1.07 | |||
| Downside Deviation | 1.18 | |||
| Coefficient Of Variation | 1332.35 | |||
| Standard Deviation | 1.16 | |||
| Variance | 1.35 | |||
| Information Ratio | 0.0148 | |||
| Jensen Alpha | 0.0705 | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | 0.0145 | |||
| Treynor Ratio | 0.7017 | |||
| Maximum Drawdown | 6.05 | |||
| Value At Risk | (1.62) | |||
| Potential Upside | 1.82 | |||
| Downside Variance | 1.39 | |||
| Semi Variance | 1.15 | |||
| Expected Short fall | (1.05) | |||
| Skewness | (0.58) | |||
| Kurtosis | 1.13 |
Commodities Strategy February 17, 2026 Daily Trend Indicators
Traders often use several different daily volumes and price technical indicators to supplement a more traditional technical analysis when analyzing securities such as Commodities stock. With literally thousands of different options, investors must choose the best indicators for them and familiarize themselves with how they work. We suggest combining traditional momentum indicators with more near-term forms of technical analysis such as Accumulation Distribution or Daily Balance Of Power. With their quantitative nature, daily value technical indicators can also be incorporated into your automated trading systems.
| Accumulation Distribution | 0.00 | ||
| Daily Balance Of Power | Huge | ||
| Rate Of Daily Change | 1.00 | ||
| Day Median Price | 164.80 | ||
| Day Typical Price | 164.80 | ||
| Price Action Indicator | 0.07 |
Other Information on Investing in Commodities Mutual Fund
Commodities Strategy financial ratios help investors to determine whether Commodities Mutual Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Commodities with respect to the benefits of owning Commodities Strategy security.
| Pair Correlation Compare performance and examine fundamental relationship between any two equity instruments | |
| Performance Analysis Check effects of mean-variance optimization against your current asset allocation | |
| Premium Stories Follow Macroaxis premium stories from verified contributors across different equity types, categories and coverage scope | |
| Aroon Oscillator Analyze current equity momentum using Aroon Oscillator and other momentum ratios |