Commodity Outlook Based on Artificial Intelligence: Returns up to 27.23% in 3 Months

6 out of 10 stock prices in this forecast for the Commodities Package moved as predicted by the algorithm. The top-performing prediction in this forecast was ^JPLAT, which registered a return of 27.23%. GDX and PALL also performed well for this time horizon with returns of 25.85% and 15.72%, respectively. The package had an overall average return of 6.54% during the period.

Commodity Outlook Based on Stock Prediction Algorithm: Returns up to 16.58% in 30 days

Commodity Outlook This Commodities Package is designed for investors who need commodity recommendations to find the best performing commodities in the industry. It includes 20 Commodity Outlook with bullish or bearish signals indicating which are best to buy: Top 10 commodities for the long position Top 10 commodities for the short position Package Name: Commodities […]

Commodity ETFs Based on Stock Prediction Algorithm: Returns up to 7.41% in 3 days

Commodity ETFs This Commodity ETFs Package is designed for investors who need commodity recommendations to find the best performing commodity ETFs in the industry. It includes 20 commodity ETFs with bullish or bearish signals indicating which are best to buy: Top 10 commodity ETFs for the long position Top 10 commodity ETFs for the short […]

Commodity Prediction Based on Pattern Recognition: Returns up to 16.02% in 30 days

During the 30 days forecasted period several picks in the Commodities Package saw significant returns. The algorithm had correctly predicted 8 out 10 returns. The highest trade return came from GDX, at 16.02%. The suggested trades for ICE_KC1 and ^JPLAT also had notable 30 days yields of 8.45% and 5.85%, respectively. The package had an overall average return of 4.01% during the period.

Commodity ETFs Forecast Based on Artificial Intelligence: Returns up to 6.88% in 14 Days

9 out of 10 stock prices in this forecast for the Commodities Package moved as predicted by the algorithm. GDX was our best stock pick this week a return of 6.88%. PALL and GLD followed with returns of 4.82% and 4.49% for the 14 Days period. The package had an overall average return of 2.65% during the period.

Commodity ETFs Outlook Based on Machine Learning: Returns up to 6.24% in 14 Days

I Know First’s State of the Art Algorithm accurately forecasted 9 out of 10 trades in this Commodities Package for the 14 Days time period. The greatest return came from GDX at 6.24%. GRU and IYM also performed well for this time horizon with returns of 2.68% and 2.61%, respectively. The package had an overall average return of 1.99% during the period.

Commodity ETFs Prediction Based on Machine Learning: Returns up to 6.78% in 7 Days

During the 7 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 PALL, at 6.78%. Further notable returns came from GDX and GRU at 5.39% and 4.10%, respectively. The package had an overall average return of 2.47% during the period.

Commodity Market Predictions Based on Artificial Intelligence: Returns up to 5.96% in 3 Days

During the 3 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 PALL, at 5.96%. Further notable returns came from ^JPLAT and GDX at 5.64% and 3.87%, respectively. Finally, positive returns resulted from positions on ICE_SB1 and XME gaining 2.82% and 1.43%, respectively, over the same forecast horizon.  The package had an overall average return of 1.98% during the period.

Commodities ETFs Predictions Based on Artificial Intelligence: Returns up to 5.01% in 7 Days

For this 7 Days forecast the algorithm had successfully predicted 10 out of 10 movements. The highest trade return came from GRU, at 5.01%. The suggested trades for WEAT and GDX also had notable 7 Days yields of 3.87% and 2.01%, respectively. Finally, positive returns resulted from positions on IYM and MOO gaining 1.95% and 1.80%, respectively, over the same forecast horizon. The package had an overall average return of 2.05% during the period.

Commodity Market Prediction Based on Artificial Intelligence: Returns up to 4.71% in 3 Days

10 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 4.71%. ICE_SB1 and ICE_KC1 followed with returns of 2.38% and 1.87% for the 3 Days period. Finally, positive returns came from long positions on CEX and MOO resulting in gains of 1.76% and 1.58% over the same investment time horizon. The package had an overall average return of 1.78% during the period.

Commodity ETFs Market Based on Stock Algorithm: Returns up to 9.58% in 14 Days

This Commodities Package forecast had correctly predicted 7 out of 10 movements. The top performing prediction from this package was FCG with a return of 9.58%. XME, and WOOD had notable returns of 7.91% and 7.51%. The package had an overall average return of 3.58% during the period.

Commodities Prediction Based on Big Data Analytics : Returns up to 2.03% in 7 Days

Several predictions in this short-term 7 Days forecast saw significant returns. The algorithm had correctly predicted 8 out 10 stock movements. CME_RB1 was the top performing prediction with a return of 2.03%. ^CEX and ICE_CC1 saw outstanding returns of 1.66% and 1.34%. The package had an overall average return of 0.68% during the period.

Commodity ETFs Outlook Based on Pattern Recognition: Returns up to 3.30% in 14 Days

This Commodities Package forecast had correctly predicted 7 out of 10 stock movements. The top performing prediction from this package was ^CEX with a return of 3.30%. IYM, and Cocoa had notable returns of 2.97% and 2.66%. The package had an overall average return of 1.17% during the period.

Commodities Price Prediction Based on Data Mining: Returns up to 9.85% in 1 Month

In this 1 Month forecast for the Commodities Package, there were many high performing trades and the algorithm correctly predicted 9 out 10 trades. The top-performing prediction in this forecast was CME_RB1, which registered a return of 9.85%. Other notable stocks were CME_CL1 and ICE_B1 with a return of 9.28% and 5.88%. The package had an overall average return of 3.38% during the period.

Commodity ETFs Outlook Based on Predictive Analytics: Returns up to 4.21% in 3 Days

Several predictions in this short-term 3 Days forecast saw significant returns. The algorithm had correctly predicted 8 out 10 stock movements. Cocoa was the top performing prediction with a return of 4.21%. WOOD and USO saw outstanding returns of 3.98% and 3.92%. The package had an overall average return of 2.03% during the period.

Commodity Price Prediction Based on Genetic Algorithms: Returns up to 5.47% in 3 Days

I Know First’s State of the Art Algorithm accurately forecasted 9 out of 10 trades in this Commodities Package for the 3 Days time period. The greatest return came from ^JPLAT at 5.47%. CME_CL1 and ^APAPR.T also performed well for this time horizon with returns of 3.05% and 2.01%, respectively. The package had an overall average return of 1.41% during the period.

Commodity Forecast Based on AI: Returns up to 13.83% in 7 Days

The algorithm correctly predicted 10 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 13.83% in 7 Days. Additional high returns came from PALL and XME, at 6.40% and 5.71% respectively. The package had an overall average return of 4.42% during the period.

Commodity Forecast Based on Stock Prediction Algorithm: Returns up to 9.82% in 3 Days

I Know First’s State of the Art Algorithm accurately forecasted 8 out of 10 trades in this Commodities Package for the 3 Days time period. The greatest return came from CME_NG1 at 9.82%. Uranium and IYM also performed well for this time horizon with returns of 3.64% and 1.52%, respectively. The package had an overall average return of 1.88% during the period.

Pages:123»