Cotton Commodity Market Value
| CTUSX Commodity | 65.90 0.37 0.56% |
| Symbol | Cotton |
Cotton '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 Cotton'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 Cotton.
| 01/02/2025 |
| 02/01/2025 |
If you would invest 0.00 in Cotton on January 2, 2025 and sell it all today you would earn a total of 0.00 from holding Cotton or generate 0.0% return on investment in Cotton over 30 days.
Cotton 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 Cotton'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 Cotton upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.19) | |||
| Maximum Drawdown | 5.07 | |||
| Value At Risk | (1.82) | |||
| Potential Upside | 1.95 |
Cotton Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Cotton's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Cotton's standard deviation. In reality, there are many statistical measures that can use Cotton historical prices to predict the future Cotton's volatility.| Risk Adjusted Performance | (0.07) | |||
| Jensen Alpha | (0.1) | |||
| Total Risk Alpha | (0.21) | |||
| Treynor Ratio | 4.49 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Cotton'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.
Cotton Backtested Returns
Cotton secures Sharpe Ratio (or Efficiency) of -0.087, which signifies that the commodity had a -0.087 % return per unit of risk over the last 3 months. Cotton exposes twenty-two different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm Cotton's Standard Deviation of 1.01, risk adjusted performance of (0.07), and Mean Deviation of 0.7131 to double-check the risk estimate we provide. The commodity shows a Beta (market volatility) of -0.0223, which signifies not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Cotton are expected to decrease at a much lower rate. During the bear market, Cotton is likely to outperform the market.
Auto-correlation | 0.68 |
Good predictability
Cotton has good predictability. Overlapping area represents the amount of predictability between Cotton 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 Cotton price movement. The serial correlation of 0.68 indicates that around 68.0% of current Cotton price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.68 | |
| Spearman Rank Test | 0.65 | |
| Residual Average | 0.0 | |
| Price Variance | 0.33 |
Cotton lagged returns against current returns
Autocorrelation, which is Cotton 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 Cotton's commodity expected returns. We can calculate the autocorrelation of Cotton returns to help us make a trade decision. For example, suppose you find that Cotton 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 |
Cotton 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 Cotton commodity is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Cotton commodity is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Cotton commodity over time.
Current vs Lagged Prices |
| Timeline |
Cotton Lagged Returns
When evaluating Cotton's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Cotton commodity have on its future price. Cotton 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, Cotton autocorrelation shows the relationship between Cotton commodity current value and its past values and can show if there is a momentum factor associated with investing in Cotton.
Regressed Prices |
| Timeline |