Commodities Price Forecast Based on Stock Algorithm: Returns up to 47.34% in 3 Months

During the 3 Months 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 47.34%. Further notable returns came from ^CEX and Uranium at 8.27% and 8.16%, respectively. The package had an overall average return of 2.58% during the period.

Commodities Outlook Based on Deep-Learning : Returns up to 4.53% in 3 Days

Several predictions in this short-term 3 Days forecast saw significant returns. The algorithm had correctly predicted 6 out 10 stock movements. ICE_OJ1 was the top performing prediction with a return of 4.53%. CME_RB1 and CME_LC1 saw outstanding returns of 1.99% and 1.08%. The package had an overall average return of 0.53% during the period.

Commodity Price Forecast Based on Data Mining: Returns up to 59.34% in 3 Months

I Know First’s State of the Art Algorithm accurately forecasted 8 out of 10 trades in this Commodities Package for the 3 Months time period. The greatest return came from ^JPLAT at 59.34%. PPLT and GDX also performed well for this time horizon with returns of 10.24% and 7.84%, respectively. The package had an overall average return of 8.23% during the period.

Commodities Forecast Based on Stock Prediction Algorithm: Returns up to 56.74% 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 56.74%. PALL, and GDX had notable returns of 11.06% and 4.85%. The package had an overall average return of 7.50% during the period.

Commodities Forecast Based on Pattern Recognition: Returns up to 48.98% in 3 Months

8 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 48.98%. PALL and ICE_SB1 followed with returns of 14.46% and 5.32% for the 3 Months period. The package had an overall average return of 6.86% during the period.

Commodity Price Prediction Based on AI: Returns up to 12.99% in 14 Days

During the 14 Days forecasted period several picks in the Commodities Package saw significant returns. The algorithm had correctly predicted 8 out 10 returns. The prediction with the highest return was ^JPLAT, at 12.99%. Further notable returns came from Zinc and CME_RB1 at 7.29% and 6.89%, respectively. The package had an overall average return of 3.76% during the period.

Commodities Price Forecast Based on a Self-learning Algorithm: Returns up to 57.09% in 3 Months

8 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 57.09%. PALL and GDX followed with returns of 22.66% and 10.83% for the 3 Months period. The package had an overall average return of 6.63% during the period.

Commodities Price Forecast Based on Machine Learning: Returns up to 20.11% 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 20.11%. Further notable returns came from PALL and CME_CL1 at 7.84% and 6.35%, respectively. The package had an overall average return of 3.38% during the period.

Commodity Outlook Based on Algorithmic Trading: Returns up to 24.56% in 1 Month

For this 1 Month forecast the algorithm had successfully predicted 7 out of 10 movements. The highest trade return came from CME_RB1, at 24.56%. The suggested trades for CME_CL1 and ICE_B1 also had notable 1 Month yields of 6.35% and 5.86%, respectively. The package had an overall average return of 4.27% during the period.

Commodities Outlook Based on Algorithmic Trading: Returns up to 24.56% in 1 Month

The algorithm correctly predicted 7 out 10 of the suggested trades in the Commodities Package for this 1 Month forecast. CME_RB1 was the highest-earning trade with a return of 24.56% in 1 Month. Additional high returns came from CME_CL1 and ICE_B1, at 6.35% and 5.86% respectively. The package had an overall average return of 4.27% during the period.

Commodities Price Prediction Based on Artificial Intelligence: Returns up to 20.11% in 1 Month

7 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 20.11%. PALL and CME_CL1 followed with returns of 7.84% and 6.35% for the 1 Month period. The package had an overall average return of 3.68% during the period.

Commodity Outlook Based on Machine Learning: Returns up to 16.64% in 14 Days

In this 14 Days forecast for the Commodities Package, there were many high performing trades and the algorithm correctly predicted 10 out 10 trades. The top-performing prediction in this forecast was ^JPLAT, which registered a return of 16.64%. Other notable stocks were PALL and Nickel with a return of 8.94% and 5.12%. The package had an overall average return of 4.90% during the period.

Commodities Forecast Based on a Self-learning Algorithm: Returns up to 11.15% in 14 Days

Several predictions in this short-term 14 Days forecast saw significant returns. The algorithm had correctly predicted 7 out 10 stock movements. CME_RB1 was the top performing prediction with a return of 11.15%. SHFE_RU1 and CME_CL1 saw outstanding returns of 7.64% and 4.52%. The package had an overall average return of 2.98% during the period.

Commodities Forecast Based on Artificial Intelligence: Returns up to 17.20% in 1 Month

8 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 17.20%. Nickel and Uranium followed with returns of 16.14% and 9.23% for the 1 Month period. The package had an overall average return of 5.21% during the period.

Commodity Prediction Based on Deep-Learning : Returns up to 4.01% in 14 Days

For this 14 Days forecast the algorithm had successfully predicted 7 out of 10 movements. The highest trade return came from SHFE_RB2, at 4.01%. The suggested trades for SHFE_RB5 and SHFE_RU1 also had notable 14 Days yields of 3.38% and 1.67%, respectively. The package had an overall average return of 0.76% during the period.

Commodities Price Prediction Based on Artificial Intelligence: Returns up to 11.85% in 1 Month

In this 1 Month forecast for the Commodities Package, there were many high performing trades and the algorithm correctly predicted 10 out 10 trades. The top-performing prediction in this forecast was ^JPLAT, which registered a return of 11.85%. Other notable stocks were PALL and SLV with a return of 8.19% and 6.27%. The package had an overall average return of 4.46% during the period.

Commodities Price Forecast Based on Algo Trading: Returns up to 4.28% in 7 Days

For this 7 Days forecast the algorithm had successfully predicted 10 out of 10 movements. The highest trade return came from CME_CL1, at 4.28%. The suggested trades for CME_WS1 and CME_RB1 also had notable 7 Days yields of 4.28% and 3.72%, respectively. The package had an overall average return of 2.82% during the period.

Commodity Outlook Based on Pattern Recognition: Returns up to 5.24% in 1 Month

This Commodities Package forecast had correctly predicted 9 out of 10 stock movements. The top performing prediction from this package was CME_LC1 with a return of 5.24%. SHFE_RU1, and CME_S1 had notable returns of 3.73% and 3.62%. The package had an overall average return of 2.13% during the period.