Sugar Commodity Market Value
| SBUSX Commodity | 19.19 0.06 0.31% |
| Symbol | Sugar |
Sugar '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 Sugar'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 Sugar.
| 12/17/2024 |
| 03/17/2025 |
If you would invest 0.00 in Sugar on December 17, 2024 and sell it all today you would earn a total of 0.00 from holding Sugar or generate 0.0% return on investment in Sugar over 90 days.
Sugar 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 Sugar'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 Sugar upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.02) | |||
| Maximum Drawdown | 8.86 | |||
| Value At Risk | (3.82) | |||
| Potential Upside | 2.22 |
Sugar Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Sugar's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Sugar's standard deviation. In reality, there are many statistical measures that can use Sugar historical prices to predict the future Sugar's volatility.| Risk Adjusted Performance | (0.07) | |||
| Jensen Alpha | (0.17) | |||
| Total Risk Alpha | 0.0686 | |||
| Treynor Ratio | 0.932 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Sugar'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.
Sugar Backtested Returns
Sugar owns Efficiency Ratio (i.e., Sharpe Ratio) of -0.0225, which indicates the commodity had a -0.0225 % return per unit of risk over the last 3 months. Sugar exposes twenty-four different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please validate Sugar's Coefficient Of Variation of (1,243), variance of 3.08, and Risk Adjusted Performance of (0.07) to confirm the risk estimate we provide. The entity has a beta of -0.16, which indicates not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Sugar are expected to decrease at a much lower rate. During the bear market, Sugar is likely to outperform the market.
Auto-correlation | 0.42 |
Average predictability
Sugar has average predictability. Overlapping area represents the amount of predictability between Sugar time series from 17th of December 2024 to 31st of January 2025 and 31st of January 2025 to 17th of March 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 Sugar price movement. The serial correlation of 0.42 indicates that just about 42.0% of current Sugar price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.42 | |
| Spearman Rank Test | 0.09 | |
| Residual Average | 0.0 | |
| Price Variance | 0.92 |
Sugar lagged returns against current returns
Autocorrelation, which is Sugar 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 Sugar's commodity expected returns. We can calculate the autocorrelation of Sugar returns to help us make a trade decision. For example, suppose you find that Sugar 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 |
Sugar 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 Sugar commodity is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Sugar commodity is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Sugar commodity over time.
Current vs Lagged Prices |
| Timeline |
Sugar Lagged Returns
When evaluating Sugar's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Sugar commodity have on its future price. Sugar 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, Sugar autocorrelation shows the relationship between Sugar commodity current value and its past values and can show if there is a momentum factor associated with investing in Sugar.
Regressed Prices |
| Timeline |