Parametric Modity Strategy Fund Market Value
| EIPCX Fund | USD 6.50 0.03 0.46% |
| Symbol | Parametric |
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.
| 02/16/2023 |
| 02/05/2025 |
If you would invest 0.00 in Parametric Commodity on February 16, 2023 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 720 days. Parametric Commodity is related to or competes with Arrow Managed, and Small Pany. 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 | 0.7911 | |||
| Information Ratio | (0.05) | |||
| Maximum Drawdown | 3.67 | |||
| Value At Risk | (1.13) | |||
| Potential Upside | 0.974 |
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 | 0.0497 | |||
| Jensen Alpha | 0.0322 | |||
| Total Risk Alpha | (0.02) | |||
| Sortino Ratio | (0.05) | |||
| Treynor Ratio | 2.51 |
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 Backtested Returns
At this stage we consider Parametric Mutual Fund to be very steady. Parametric Commodity maintains Sharpe Ratio (i.e., Efficiency) of 0.12, which implies the entity had a 0.12 % 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 Semi Deviation of 0.6597, risk adjusted performance of 0.0497, and Coefficient Of Variation of 1624.37 to confirm if the risk estimate we provide is consistent with the expected return of 0.0767%. The fund holds a Beta of 0.0132, which implies not very significant fluctuations relative to the market. 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 | -0.41 |
Modest reverse predictability
Parametric Modity Strategy has modest reverse predictability. Overlapping area represents the amount of predictability between Parametric Commodity time series from 16th of February 2023 to 11th of February 2024 and 11th of February 2024 to 5th of February 2025. 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 -0.41 indicates that just about 41.0% of current Parametric Commodity price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.41 | |
| Spearman Rank Test | 0.08 | |
| Residual Average | 0.0 | |
| Price Variance | 0.04 |
Parametric Commodity lagged returns against current returns
Autocorrelation, which is Parametric Commodity 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 Parametric Commodity's mutual fund expected returns. We can calculate the autocorrelation of Parametric Commodity returns to help us make a trade decision. For example, suppose you find that Parametric Commodity 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 |
Parametric Commodity 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 Parametric Commodity mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Parametric Commodity mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Parametric Commodity mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Parametric Commodity Lagged Returns
When evaluating Parametric Commodity's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Parametric Commodity mutual fund have on its future price. Parametric Commodity 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, Parametric Commodity autocorrelation shows the relationship between Parametric Commodity mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Parametric Modity Strategy.
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.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.
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