Commodity Outlook Based on Genetic Algorithms: Returns up to 206.64% in 1 Year

In this 1 Year forecast for the Commodities Package, there were many high performing trades and the algorithm correctly predicted 7 out 10 trades. ^JPLAT was the top performing prediction with a return of 206.64%. PALL, and Nickel had notable returns of 68.77% and 24.33%. The package had an overall average return of 24.67% during the period.

Commodity ETFs Based on Pattern Recognition: Returns up to 63.2% in 1 Year

Several predictions in this 1 Year forecast saw significant returns. The algorithm had correctly predicted 9 out 10 stock movements. The top-performing prediction in this forecast was PALL, which registered a return of 63.2%. The suggested trades for GDX and Nickel also had notable 1 Year yields of 34.06% and 19.62%, respectively. The package had an overall average return of 17.33% during the period.

Commodity Outlook Based on Big Data Analytics: Returns up to 32.54% in 3 Months

Several predictions in this 3 Months forecast saw significant returns. The algorithm had correctly predicted 7 out 10 stock movements. The top-performing prediction in this forecast was ^JPLAT, which registered a return of 32.54%. PALL and Copper followed with returns of 27.05% and 9.28% for the 3 Months period. The package had an overall average return of 6.22% during the period.

Best Commodity ETFs Based on Machine Learning: Returns up to 60.07% in 1 Year

The algorithm correctly predicted 9 out 10 of the suggested trades in the Commodities Package for this 1 Year forecast. The prediction with the highest return was PALL, at 60.07%. GDX, and Nickel had notable returns of 31.74% and 21.58%. The package had an overall average return of 16.94% during the period.

Commodity Outlook Based on Artificial Intelligence: Returns up to 206.1% in 1 Year

7 out of 10 stock prices in this forecast for the Commodities Package moved as predicted by the algorithm. ^JPLAT was the highest-earning trade with a return of 206.1% in 1 Year. PALL, and Nickel had notable returns of 57.69% and 24.78%. The package had an overall average return of 27.5% during the period.

Commodity Outlook Based on Deep Learning: Returns up to 36.82% in 3 Months

For this 3 Months forecast the algorithm had successfully predicted 8 out of 10 movements. The greatest return came from ^JPLAT at 36.82%. Additional high returns came from PALL and WOOD, at 25.83% and 16.07% respectively. The package had an overall average return of 7.69% during the period.

Commodity Price Forecast Based on Deep-Learning: Returns up to 14.23% in 1 Month

During the 1 Month forecasted period several picks in the Commodities Package saw significant returns. The algorithm had correctly predicted 7 out 10 returns. The prediction with the highest return was ^JPLAT, at 14.23%. Other notable stocks were PALL and ICE_SB1 with a return of 12.29% and 4.02%. The package had an overall average return of 2.3% during the period.

Commodity Price Forecast Based on Big Data: Returns up to 41.25% in 3 Months

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 41.25%. PALL and WOOD also performed well for this time horizon with returns of 26.26% and 14.89%, respectively. The package had an overall average return of 9.21% during the period.

Commodity Outlook Based on Deep Learning: Returns up to 214.01% in 1 Year

8 out of 10 stock prices in this forecast for the Commodities Package moved as predicted by the algorithm. ^JPLAT was the highest-earning trade with a return of 214.01% in 1 Year. Further notable returns came from PALL and GDX at 56.76% and 34.74%, respectively. The package had an overall average return of 29.93% during the period.

Commodity Outlook Based on AI: Returns up to 16.77% in 1 Month

Several predictions in this 1 Month forecast saw significant returns. The algorithm had correctly predicted 7 out 10 stock movements. The highest trade return came from ^JPLAT, at 16.77%. PALL, and ICE_B1 had notable returns of 12.09% and 6.03%. The package had an overall average return of 4.13% during the period.

Commodity Price Forecast Based on Deep Learning: Returns up to 3.62% 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. ^XNG was the highest-earning trade with a return of 3.62% in 7 Days. ICE_B1 and CME_CL1 followed with returns of 3.36% and 2.58% for the 7 Days period. The package had an overall average return of 0.58% during the period.

Commodity Price Forecast Based on Predictive Analytics: Returns up to 201.61% in 1 Year

The algorithm correctly predicted 8 out 10 of the suggested trades in the Commodities Package for this 1 Year forecast. The prediction with the highest return was ^JPLAT, at 201.61%. Additional high returns came from PALL and GDX, at 54.3% and 38.5% respectively. The package had an overall average return of 33.34% during the period.

Commodity Outlook Based on Deep-Learning: Returns up to 10.73% in 1 Month

During the 1 Month forecasted period several picks in the Commodities Package saw significant returns. The algorithm had correctly predicted 7 out 10 returns. The top performing prediction from this package was ^JPLAT with a return of 10.73%. The suggested trades for PALL and ICE_B1 also had notable 1 Month yields of 9.97% and 8.71%, respectively. The package had an overall average return of 4.12% during the period.

Commodity Price Forecast Based on Machine Learning: Returns up to 204.07% in 1 Year

Several predictions in this 1 Year forecast saw significant returns. The algorithm had correctly predicted 9 out 10 stock movements. ^JPLAT was the top performing prediction with a return of 204.07%. Further notable returns came from PALL and GDX at 51.84% and 37.18%, respectively. The package had an overall average return of 33.19% during the period.

Commodity Price Forecast Based on Big Data: Returns up to 11.63% in 1 Month

This Commodities Package forecast had correctly predicted 8 out of 10 stock movements. The prediction with the highest return was ^JPLAT, at 11.63%. Additional high returns came from PALL and ICE_B1, at 8.22% and 8.22% respectively. The package had an overall average return of 3.77% during the period.

Commodity Outlook Based on Deep Learning: Returns up to 2.9% in 3 Days

For this 3 Days forecast the algorithm had successfully predicted 7 out of 10 movements. ICE_B1 was the highest-earning trade with a return of 2.9% in 3 Days. PPLT and CME_CL1 saw outstanding returns of 2.47% and 2.22%. The package had an overall average return of 0.91% during the period.

Commodity Price Forecast Based on Algorithmic Trading: Returns up to 19.67% in 1 Month

During the 1 Month forecasted period several picks in the Commodities Package saw significant returns. The algorithm had correctly predicted 9 out 10 returns. ^JPLAT was the top performing prediction with a return of 19.67%. PALL, and ICE_SB1 had notable returns of 7.29% and 4.39%. The package had an overall average return of 4.91% during the period.

Commodity ETFs Based on Pattern Recognition: Returns up to 53.94% in 1 Year

In this 1 Year forecast for the Commodities Package, there were many high performing trades and the algorithm correctly predicted 9 out 10 trades. The prediction with the highest return was PALL, at 53.94%. GDX and Nickel also performed well for this time horizon with returns of 38.83% and 31.36%, respectively. The package had an overall average return of 21.98% during the period.