Commodity Predictions Based on Machine Learning: Returns up to 19.96% in 7 Days

For this 7 Days forecast the algorithm had successfully predicted 7 out of 10 movements. The highest trade return came from ^JPLAT, at 19.96%. The suggested trades for PALL and CME_HG1 also had notable 7 Days yields of 8.35% and 7.17%, respectively. The package had an overall average return of 4.58% during the period.

Commodities Market Expectations Based on Genetic Algorithms: Returns up to 24.14% in 1 Month

This Commodities Package forecast had correctly predicted 9 out of 10 stock movements. The top performing prediction from this package was ^JPLAT with a return of 24.14%. ICE_B1, and MOO had notable returns of 5.45% and 3.17%. The package had an overall average return of 4.08% during the period.

Commodities Prices Based on Algo Trading: Returns up to 13.25% in 3 Days

Several predictions in this short-term 3 Days forecast saw significant returns. The algorithm had correctly predicted 9 out 10 stock movements. ^JPLAT was the top performing prediction with a return of 13.25%. Copper and CME_HG1 saw outstanding returns of 4.70% and 4.67%. The package had an overall average return of 3.12% during the period.

Commodities Predictions Based on a Self-learning Algorithm: Returns up to 19.22% in 3 Days

9 out of 10 stock prices in this forecast for the Commodities Package moved as predicted by the algorithm. ^JPLAT was our best stock pick this week a return of 19.22%. PALL and Uranium followed with returns of 6.62% and 4.98% for the 3 Days period. The package had an overall average return of 4.61% during the period.

Commodities Market Forecast Based on Genetic Algorithms: Returns up to 19.96% in 7 Days

The algorithm correctly predicted 7 out 10 of the suggested trades in the Commodities Package for this 7 Days forecast. ^JPLAT was the highest-earning trade with a return of 19.96% in 7 Days. Additional high returns came from CME_HG1 and PALL, at 7.95% and 7.65% respectively. The package had an overall average return of 4.69% during the period.

Commodities Prices Forecast Based on Algorithmic Trading: Returns up to 5.70% in 14 Days

7 out of 10 stock prices in this forecast for the Commodities Package moved as predicted by the algorithm. PALL was our best commodities prices forecast for this week a return of 5.70%. ^JPLAT and CME_LC1 followed with returns of 4.88% and 2.94% for the 14 Days period. The package had an overall average return of 1.11% during the period.

Commodity Market Predictions Based on AI: Returns up to 6.05% in 3 Days

Several predictions in this short-term 3 Days forecast saw significant returns. The algorithm had correctly predicted 7 out 10 stock movements. PALL was the top performing prediction with a return of 6.05%. GDX and ^APAPR.T saw outstanding returns of 4.28% and 3.65%. The package had an overall average return of 1.75% during the period.

Commodities Prices Prediction Based on a Self-learning Algorithm: Returns up to 4.50% in 7 Days

Several predictions in this short-term 7 Days forecast saw significant returns. The algorithm had correctly predicted 7 out 10 stock movements. CME_LC1 was the top performing prediction with a return of 4.50%. ICE_SB1 and SHFE_RU1 saw outstanding returns of 3.33% and 2.37%. The package had an overall average return of 0.77% during the period.

Commodity Market Forecast Based on Genetic Algorithms: Returns up to 7.25% in 7 Days

The algorithm correctly predicted 7 out 10 of the suggested trades in the Commodities Package for this 7 Days forecast. ICE_SB1 was the highest-earning trade with a return of 7.25% in 7 Days. Additional high returns came from SHFE_RU1 and CME_LC1, at 2.43% and 1.60% respectively. The package had an overall average return of 0.81% during the period.

Commodities Prices Forecast Based on Genetic Algorithms: Returns up to 3.70% in 3 Days

During the 3 Days forecasted period several picks in the Commodities Package saw significant returns. The algorithm had correctly predicted 5 out 10 returns. The prediction with the highest return was ICE_SB1, at 3.70%. Further notable returns came from CME_SM4 and CME_SM1 at 1.63% and 1.58%, respectively. The package had an overall average return of 0.75% during the period.

Commodities Market Predictions Based on Algo Trading: Returns up to 5.27% in 7 Days

The algorithm correctly predicted 8 out 10 of the suggested trades in the Commodities Package for this 7 Days forecast. ^JPLAT was the highest-earning trade with a return of 5.27% in 7 Days. Additional high returns came from PALL and CME_RB1, at 5.09% and 3.17% respectively. The package had an overall average return of 1.52% during the period.

Commodity Market Predictions Based on Genetic Algorithms: Returns up to 5.09% in 7 Days

This Commodities Package forecast had correctly predicted 7 out of 10 stock movements. The top performing prediction from this package was PALL with a return of 5.09%. ^JPLAT, and CME_RB1 had notable returns of 3.28% and 3.17%. The package had an overall average return of 1.36% during the period.

Commodity Market Forecast Based on a Self-learning Algorithm: Returns up to 3.55% in 3 Days

For this 3 Days forecast the algorithm had successfully predicted 7 out of 10 movements. The highest trade return came from PALL, at 3.55%. The suggested trades for CME_RB1 and ICE_B1 also had notable 3 Days yields of 3.16% and 2.57%, respectively. The package had an overall average return of 0.68% during the period.

Commodities Price Forecast Based on Machine Learning: Returns up to 8.60% in 1 Month

In this 1 Month forecast for the Commodities Package, there were many high performing trades and the algorithm correctly predicted 6 out 10 trades. The top-performing prediction in this forecast was SHFE_RB3, which registered a return of 8.60%. Other notable stocks were SHFE_RB2 and SHFE_RB5 with a return of 7.15% and 6.02%. The package had an overall average return of 0.86% during the period.

Commodities Price Forecast Based on Artificial Intelligence: Returns up to 2.95% in 3 Days

For this 3 Days forecast the algorithm had successfully predicted 7 out of 10 movements. The highest trade return came from PALL, at 2.95%. The suggested trades for ^JPLAT and USO also had notable 3 Days yields of 2.64% and 1.59%, respectively. The package had an overall average return of 0.71% during the period.

Commodities Market Prediction Based on a Self-learning Algorithm: Returns up to 3.10% in 3 Days

During the 3 Days forecasted period several picks in the Commodities Package saw significant returns. The algorithm had correctly predicted 9 out 10 returns. The prediction with the highest return was ^JPLAT, at 3.10%. Further notable returns came from USO and CME_CL1 at 1.61% and 1.53%, respectively. The package had an overall average return of 0.89% during the period.

Commodity Prediction Based on Machine Learning: Returns up to 4.65% in 3 Days

For this 3 Days forecast the algorithm had successfully predicted 6 out of 10 movements. The highest trade return came from Cocoa, at 4.65%. The suggested trades for ICE_CC1 and PALL also had notable 3 Days yields of 4.63% and 2.25%, respectively. The package had an overall average return of 0.73% during the period.

Commodity Forecast Based on Genetic Algorithms: Returns up to 5.41% in 7 Days

I Know First’s State of the Art Algorithm accurately forecasted 7 out of 10 trades in this Commodities Package for the 7 Days time period. The greatest return came from CME_O1 at 5.41%. SHFE_RB5 and SHFE_RB3 also performed well for this time horizon with returns of 3.83% and 3.71%, respectively. The package had an overall average return of 1.17% during the period.

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