Rough Rice Futures Commodity Market Value
| ZRUSD Commodity | 13.85 0.09 0.65% |
| Symbol | Rough |
Rough Rice '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 Rough Rice's commodity 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 Rough Rice.
| 01/02/2025 |
| 02/01/2025 |
If you would invest 0.00 in Rough Rice on January 2, 2025 and sell it all today you would earn a total of 0.00 from holding Rough Rice Futures or generate 0.0% return on investment in Rough Rice over 30 days.
Rough Rice 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 Rough Rice's commodity 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 Rough Rice Futures upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.19) | |||
| Maximum Drawdown | 5.21 | |||
| Value At Risk | (2.06) | |||
| Potential Upside | 1.78 |
Rough Rice Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Rough Rice's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Rough Rice's standard deviation. In reality, there are many statistical measures that can use Rough Rice historical prices to predict the future Rough Rice's volatility.| Risk Adjusted Performance | (0.08) | |||
| Jensen Alpha | (0.13) | |||
| Total Risk Alpha | (0.24) | |||
| Treynor Ratio | (1.79) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Rough Rice'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.
Rough Rice Futures Backtested Returns
Rough Rice Futures maintains Sharpe Ratio (i.e., Efficiency) of -0.0844, which implies the entity had a -0.0844 % return per unit of risk over the last 3 months. Rough Rice Futures exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check Rough Rice's Variance of 1.22, coefficient of variation of (993.22), and Risk Adjusted Performance of (0.08) to confirm the risk estimate we provide. The commodity holds a Beta of 0.0678, which implies not very significant fluctuations relative to the market. As returns on the market increase, Rough Rice's returns are expected to increase less than the market. However, during the bear market, the loss of holding Rough Rice is expected to be smaller as well.
Auto-correlation | -0.93 |
Near perfect reversele predictability
Rough Rice Futures has near perfect reversele predictability. Overlapping area represents the amount of predictability between Rough Rice time series from 2nd of January 2025 to 17th of January 2025 and 17th of January 2025 to 1st 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 Rough Rice Futures price movement. The serial correlation of -0.93 indicates that approximately 93.0% of current Rough Rice price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.93 | |
| Spearman Rank Test | -0.75 | |
| Residual Average | 0.0 | |
| Price Variance | 0.15 |
Rough Rice Futures lagged returns against current returns
Autocorrelation, which is Rough Rice commodity'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 Rough Rice's commodity expected returns. We can calculate the autocorrelation of Rough Rice returns to help us make a trade decision. For example, suppose you find that Rough Rice has exhibited high autocorrelation historically, and you observe that the commodity 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 |
Rough Rice 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 Rough Rice commodity is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Rough Rice commodity is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Rough Rice commodity over time.
Current vs Lagged Prices |
| Timeline |
Rough Rice Lagged Returns
When evaluating Rough Rice's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Rough Rice commodity have on its future price. Rough Rice 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, Rough Rice autocorrelation shows the relationship between Rough Rice commodity current value and its past values and can show if there is a momentum factor associated with investing in Rough Rice Futures.
Regressed Prices |
| Timeline |