Parametric Modity Strategy Fund Technical Analysis
| EAPCX Fund | USD 6.83 0.21 2.98% |
As of the 3rd of February, Parametric Commodity holds the Semi Deviation of 1.14, coefficient of variation of 757.2, and Risk Adjusted Performance of 0.1005. Parametric Commodity technical analysis gives you tools to exploit past prices in attempt to determine a pattern that determines the direction of the fund's future prices.
Parametric Commodity Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Parametric, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to ParametricParametric |
Parametric Commodity '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 Parametric Commodity'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 Parametric Commodity.
| 11/05/2025 |
| 02/03/2026 |
If you would invest 0.00 in Parametric Commodity on November 5, 2025 and sell it all today you would earn a total of 0.00 from holding Parametric Modity Strategy or generate 0.0% return on investment in Parametric Commodity over 90 days. Parametric Commodity is related to or competes with Nasdaq-100 Fund, Northern Mid, Harbor Small, Virtus Kar, Optimum Large, Columbia Acorn, and Fidelity Convertible. The fund invests primarily in commodity-linked derivative instruments backed by a portfolio of fixed-income securities More
Parametric Commodity 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 Parametric Commodity'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 Parametric Modity Strategy upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.28 | |||
| Information Ratio | 0.0852 | |||
| Maximum Drawdown | 6.22 | |||
| Value At Risk | (1.50) | |||
| Potential Upside | 1.83 |
Parametric Commodity Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Parametric Commodity's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Parametric Commodity's standard deviation. In reality, there are many statistical measures that can use Parametric Commodity historical prices to predict the future Parametric Commodity's volatility.| Risk Adjusted Performance | 0.1005 | |||
| Jensen Alpha | 0.1187 | |||
| Total Risk Alpha | 0.0731 | |||
| Sortino Ratio | 0.0755 | |||
| Treynor Ratio | 0.2908 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Parametric Commodity'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.
Parametric Commodity February 3, 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 | 0.1005 | |||
| Market Risk Adjusted Performance | 0.3008 | |||
| Mean Deviation | 0.8477 | |||
| Semi Deviation | 1.14 | |||
| Downside Deviation | 1.28 | |||
| Coefficient Of Variation | 757.2 | |||
| Standard Deviation | 1.13 | |||
| Variance | 1.28 | |||
| Information Ratio | 0.0852 | |||
| Jensen Alpha | 0.1187 | |||
| Total Risk Alpha | 0.0731 | |||
| Sortino Ratio | 0.0755 | |||
| Treynor Ratio | 0.2908 | |||
| Maximum Drawdown | 6.22 | |||
| Value At Risk | (1.50) | |||
| Potential Upside | 1.83 | |||
| Downside Variance | 1.63 | |||
| Semi Variance | 1.29 | |||
| Expected Short fall | (0.93) | |||
| Skewness | (1.03) | |||
| Kurtosis | 2.64 |
Parametric Commodity Backtested Returns
At this stage we consider Parametric Mutual Fund to be risky. Parametric Commodity maintains Sharpe Ratio (i.e., Efficiency) of 0.13, which implies the entity had a 0.13 % return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Parametric Commodity, which you can use to evaluate the volatility of the fund. Please check Parametric Commodity's Coefficient Of Variation of 757.2, risk adjusted performance of 0.1005, and Semi Deviation of 1.14 to confirm if the risk estimate we provide is consistent with the expected return of 0.15%. The fund holds a Beta of 0.48, which implies possible diversification benefits within a given portfolio. As returns on the market increase, Parametric Commodity's returns are expected to increase less than the market. However, during the bear market, the loss of holding Parametric Commodity is expected to be smaller as well.
Auto-correlation | 0.59 |
Modest predictability
Parametric Modity Strategy has modest predictability. Overlapping area represents the amount of predictability between Parametric Commodity time series from 5th of November 2025 to 20th of December 2025 and 20th of December 2025 to 3rd 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 Parametric Commodity price movement. The serial correlation of 0.59 indicates that roughly 59.0% of current Parametric Commodity price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.59 | |
| Spearman Rank Test | 0.44 | |
| Residual Average | 0.0 | |
| Price Variance | 0.05 |
Parametric Commodity 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.
Parametric Commodity Technical Analysis
The output start index for this execution was twenty-four with a total number of output elements of thirty-seven. 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 Parametric Commodity volatility. High ATR values indicate high volatility, and low values indicate low volatility.
About Parametric Commodity 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 Parametric Modity Strategy 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 Parametric Modity Strategy based on its technical analysis. In general, a bottom-up approach, as applied to this mutual fund, focuses on Parametric Commodity price pattern first instead of the macroeconomic environment surrounding Parametric Commodity. By analyzing Parametric Commodity'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 Parametric Commodity'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 Parametric Commodity specific price patterns or momentum indicators. Please read more on our technical analysis page.
Parametric Commodity February 3, 2026 Technical Indicators
Most technical analysis of Parametric 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 Parametric from various momentum indicators to cycle indicators. When you analyze Parametric 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 | 0.1005 | |||
| Market Risk Adjusted Performance | 0.3008 | |||
| Mean Deviation | 0.8477 | |||
| Semi Deviation | 1.14 | |||
| Downside Deviation | 1.28 | |||
| Coefficient Of Variation | 757.2 | |||
| Standard Deviation | 1.13 | |||
| Variance | 1.28 | |||
| Information Ratio | 0.0852 | |||
| Jensen Alpha | 0.1187 | |||
| Total Risk Alpha | 0.0731 | |||
| Sortino Ratio | 0.0755 | |||
| Treynor Ratio | 0.2908 | |||
| Maximum Drawdown | 6.22 | |||
| Value At Risk | (1.50) | |||
| Potential Upside | 1.83 | |||
| Downside Variance | 1.63 | |||
| Semi Variance | 1.29 | |||
| Expected Short fall | (0.93) | |||
| Skewness | (1.03) | |||
| Kurtosis | 2.64 |
Parametric Commodity February 3, 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 Parametric 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 | 0.97 | ||
| Day Median Price | 6.83 | ||
| Day Typical Price | 6.83 | ||
| Price Action Indicator | (0.10) |
Other Information on Investing in Parametric Mutual Fund
Parametric Commodity financial ratios help investors to determine whether Parametric 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 Parametric with respect to the benefits of owning Parametric Commodity security.
| Performance Analysis Check effects of mean-variance optimization against your current asset allocation | |
| Sign In To Macroaxis Sign in to explore Macroaxis' wealth optimization platform and fintech modules | |
| Top Crypto Exchanges Search and analyze digital assets across top global cryptocurrency exchanges |