question_id int64 0 977 | question_type stringclasses 30
values | prompt stringlengths 231 943 | data_str stringlengths 401 2.09M | output_requirement stringclasses 10
values | executor_variables stringlengths 57 59 | ground_truth_data stringlengths 55 57 | context stringlengths 35 37 | constraint stringlengths 41 43 |
|---|---|---|---|---|---|---|---|---|
900 | energy_anomaly | I have 27 time series data for energy consumption of different buildings spanning 349 hours. There might be missing values in each time series. Please tell me whether there are anomalies (abnormal usage pattern) for each building and where are anomalies if present. Please return a 2D numpy array with 1 indicating an an... | I have 27 time series data for energy consumption of different buildings spanning 349 hours. There might be missing values in each time series.The energy consumption data of building id 163 is: [79.19, 172.8, 158.4, 161.97, 187.2, 190.8, 158.37, 190.8, 198.0, 198.03, 190.8, 208.78, 183.6, 194.4, 136.8, 126.0, 133.2, 12... | Answer:
prediction = np.array([...],dtype=np.float64)
prediction.shape = (seq length, num_ts) | external_data/executor_variables/executor_variables_900.pkl | external_data/ground_truth_data/ground_truth_data_900.pkl | external_data/context/context_900.pkl | external_data/constraint/constraint_900.pkl |
901 | energy_anomaly | I have 28 time series data for energy consumption of different buildings spanning 490 hours. There might be missing values in each time series. Please tell me whether there are anomalies (abnormal usage pattern) for each building and where are anomalies if present. Please return a 2D numpy array with 1 indicating an an... | I have 28 time series data for energy consumption of different buildings spanning 490 hours. There might be missing values in each time series.The energy consumption data of building id 53 is: [147.34, 149.37, 127.53, 114.22, 114.22, 121.33, 125.76, 122.26, 117.6, 118.08, 114.36, 112.92, 113.24, 113.35, 113.06, 113.1, ... | Answer:
prediction = np.array([...],dtype=np.float64)
prediction.shape = (seq length, num_ts) | external_data/executor_variables/executor_variables_901.pkl | external_data/ground_truth_data/ground_truth_data_901.pkl | external_data/context/context_901.pkl | external_data/constraint/constraint_901.pkl |
902 | energy_anomaly | I have 40 time series data for energy consumption of different buildings spanning 431 hours. There might be missing values in each time series. Please tell me whether there are anomalies (abnormal usage pattern) for each building and where are anomalies if present. Please return a 2D numpy array with 1 indicating an an... | I have 40 time series data for energy consumption of different buildings spanning 431 hours. There might be missing values in each time series.The energy consumption data of building id 165 is: [242.0, 252.0, 239.0, 255.0, 244.0, 237.0, 240.0, 237.0, 227.0, 257.0, 254.0, 247.0, 294.0, 292.0, 311.0, 300.0, 347.0, 326.0,... | Answer:
prediction = np.array([...],dtype=np.float64)
prediction.shape = (seq length, num_ts) | external_data/executor_variables/executor_variables_902.pkl | external_data/ground_truth_data/ground_truth_data_902.pkl | external_data/context/context_902.pkl | external_data/constraint/constraint_902.pkl |
903 | energy_anomaly | I have 26 time series data for energy consumption of different buildings spanning 364 hours. There might be missing values in each time series. Please tell me whether there are anomalies (abnormal usage pattern) for each building and where are anomalies if present. Please return a 2D numpy array with 1 indicating an an... | I have 26 time series data for energy consumption of different buildings spanning 364 hours. There might be missing values in each time series.The energy consumption data of building id 137 is: [133.0, 140.0, 153.0, 157.0, 160.0, 165.0, 171.0, 163.0, 167.0, 156.0, 147.0, 148.0, 140.0, 131.0, 130.0, 128.0, 127.0, 122.0,... | Answer:
prediction = np.array([...],dtype=np.float64)
prediction.shape = (seq length, num_ts) | external_data/executor_variables/executor_variables_903.pkl | external_data/ground_truth_data/ground_truth_data_903.pkl | external_data/context/context_903.pkl | external_data/constraint/constraint_903.pkl |
904 | energy_anomaly | I have 22 time series data for energy consumption of different buildings spanning 454 hours. There might be missing values in each time series. Please tell me whether there are anomalies (abnormal usage pattern) for each building and where are anomalies if present. Please return a 2D numpy array with 1 indicating an an... | I have 22 time series data for energy consumption of different buildings spanning 454 hours. There might be missing values in each time series.The energy consumption data of building id 199 is: [9.4, 10.35, 10.15, 10.97, 13.32, 5.65, 3.15, 3.08, 3.17, 3.17, 4.88, 10.18, 9.78, 9.35, 9.8, 9.18, 9.32, 9.18, 11.5, 9.22, 9.... | Answer:
prediction = np.array([...],dtype=np.float64)
prediction.shape = (seq length, num_ts) | external_data/executor_variables/executor_variables_904.pkl | external_data/ground_truth_data/ground_truth_data_904.pkl | external_data/context/context_904.pkl | external_data/constraint/constraint_904.pkl |
905 | energy_anomaly | I have 38 time series data for energy consumption of different buildings spanning 501 hours. There might be missing values in each time series. Please tell me whether there are anomalies (abnormal usage pattern) for each building and where are anomalies if present. Please return a 2D numpy array with 1 indicating an an... | I have 38 time series data for energy consumption of different buildings spanning 501 hours. There might be missing values in each time series.The energy consumption data of building id 97 is: [67.0, 67.0, 68.0, 67.0, 65.0, 66.0, 65.0, 66.0, 65.0, 65.0, 65.0, 66.0, 65.0, 65.0, 65.0, 66.0, 66.0, 64.0, 66.0, 66.0, 66.0, ... | Answer:
prediction = np.array([...],dtype=np.float64)
prediction.shape = (seq length, num_ts) | external_data/executor_variables/executor_variables_905.pkl | external_data/ground_truth_data/ground_truth_data_905.pkl | external_data/context/context_905.pkl | external_data/constraint/constraint_905.pkl |
906 | energy_anomaly | I have 34 time series data for energy consumption of different buildings spanning 472 hours. There might be missing values in each time series. Please tell me whether there are anomalies (abnormal usage pattern) for each building and where are anomalies if present. Please return a 2D numpy array with 1 indicating an an... | I have 34 time series data for energy consumption of different buildings spanning 472 hours. There might be missing values in each time series.The energy consumption data of building id 71 is: [4.5, 9.9, 12.5, 21.4, 21.5, 26.0, 25.8, 25.0, 20.8, 18.8, 17.5, 15.1, 8.7, 3.9, 4.6, 4.4, 4.6, 4.4, 4.3, 4.4, 4.1, 4.0, 4.8, 4... | Answer:
prediction = np.array([...],dtype=np.float64)
prediction.shape = (seq length, num_ts) | external_data/executor_variables/executor_variables_906.pkl | external_data/ground_truth_data/ground_truth_data_906.pkl | external_data/context/context_906.pkl | external_data/constraint/constraint_906.pkl |
907 | stock_investment | I have historical stock price data of ZIG for 31 days and I'm interested in investing in with a budget of 1576 dollars. Please give me an investment strategy for the next 53 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 53 ... | I have historical stock price data of ZIG for 31 days and I'm interested in investing in with a budget of 1576 dollars. The historical stock value data of ZIG for the past 31 days is: [24.08, 24.07, 23.87, 24.3, 24.38, 24.42, 23.69, 24.57, 24.5, 24.7, 24.53, 25.49, 26.18, 26.15, 26.88, 26.11, 25.58, 25.8, 26.0, 26.71, ... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_907.pkl | external_data/ground_truth_data/ground_truth_data_907.pkl | external_data/context/context_907.pkl | external_data/constraint/constraint_907.pkl |
908 | stock_investment | I have historical stock price data of LGI for 31 days and I'm interested in investing in with a budget of 9417 dollars. Please give me an investment strategy for the next 53 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 53 ... | I have historical stock price data of LGI for 31 days and I'm interested in investing in with a budget of 9417 dollars. The historical stock value data of LGI for the past 31 days is: [5.23, 5.32, 5.32, 5.27, 5.27, 5.27, 5.32, 5.23, 5.09, 5.09, 5.0, 4.92, 4.99, 5.01, 4.99, 4.94, 4.96, 4.88, 4.87, 4.92, 4.82, 4.82, 4.78... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_908.pkl | external_data/ground_truth_data/ground_truth_data_908.pkl | external_data/context/context_908.pkl | external_data/constraint/constraint_908.pkl |
909 | stock_investment | I have historical stock price data of ZHDG for 29 days and I'm interested in investing in with a budget of 1224 dollars. Please give me an investment strategy for the next 44 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 44... | I have historical stock price data of ZHDG for 29 days and I'm interested in investing in with a budget of 1224 dollars. The historical stock value data of ZHDG for the past 29 days is: [16.04, 16.05, 16.07, 16.07, 16.17, 16.22, 16.29, 15.99, 15.97, 16.07, 16.04, 16.17, 16.12, 16.26, 16.3, 16.16, 16.07, 16.11, 16.13, 1... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_909.pkl | external_data/ground_truth_data/ground_truth_data_909.pkl | external_data/context/context_909.pkl | external_data/constraint/constraint_909.pkl |
910 | stock_investment | I have historical stock price data of MLPR for 21 days and I'm interested in investing in with a budget of 2550 dollars. Please give me an investment strategy for the next 43 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 43... | I have historical stock price data of MLPR for 21 days and I'm interested in investing in with a budget of 2550 dollars. The historical stock value data of MLPR for the past 21 days is: [27.92, 26.68, 25.47, 26.67, 26.83, 27.62, 27.02, 26.51, 27.3, 25.28, 25.31, 26.77, 27.39, 26.78, 26.46, 26.61, 26.54, 27.21, 28.18, 2... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_910.pkl | external_data/ground_truth_data/ground_truth_data_910.pkl | external_data/context/context_910.pkl | external_data/constraint/constraint_910.pkl |
911 | stock_investment | I have historical stock price data of OBOR for 29 days and I'm interested in investing in with a budget of 7570 dollars. Please give me an investment strategy for the next 51 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 51... | I have historical stock price data of OBOR for 29 days and I'm interested in investing in with a budget of 7570 dollars. The historical stock value data of OBOR for the past 29 days is: [18.49, 18.39, 18.71, 18.69, 18.95, 19.17, 19.02, 19.11, 19.31, 19.0, 19.5, 19.65, 19.79, 19.68, 19.83, 19.67, 19.88, 19.88, 20.07, 20... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_911.pkl | external_data/ground_truth_data/ground_truth_data_911.pkl | external_data/context/context_911.pkl | external_data/constraint/constraint_911.pkl |
912 | stock_investment | I have historical stock price data of NVMI for 31 days and I'm interested in investing in with a budget of 8696 dollars. Please give me an investment strategy for the next 38 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 38... | I have historical stock price data of NVMI for 31 days and I'm interested in investing in with a budget of 8696 dollars. The historical stock value data of NVMI for the past 31 days is: [8.47, 8.58, 8.7, 8.7, 8.68, 8.57, 8.39, 8.35, 8.0, 8.12, 8.21, 8.24, 8.2, 8.29, 8.5, 8.44, 8.26, 8.68, 8.69, 8.43, 8.65, 8.51, 8.7, 8... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_912.pkl | external_data/ground_truth_data/ground_truth_data_912.pkl | external_data/context/context_912.pkl | external_data/constraint/constraint_912.pkl |
913 | stock_investment | I have historical stock price data of USEA for 39 days and I'm interested in investing in with a budget of 2047 dollars. Please give me an investment strategy for the next 51 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 51... | I have historical stock price data of USEA for 39 days and I'm interested in investing in with a budget of 2047 dollars. The historical stock value data of USEA for the past 39 days is: [2.4, 2.43, 2.44, 2.43, 2.36, 2.33, 2.37, 2.43, 2.43, 2.37, 2.43, 2.42, 2.34, 2.35, 2.32, 2.29, 2.36, 2.41, 2.49, 2.58, 2.65, 2.66, 2.... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_913.pkl | external_data/ground_truth_data/ground_truth_data_913.pkl | external_data/context/context_913.pkl | external_data/constraint/constraint_913.pkl |
914 | stock_investment | I have historical stock price data of PBTP for 23 days and I'm interested in investing in with a budget of 5242 dollars. Please give me an investment strategy for the next 41 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 41... | I have historical stock price data of PBTP for 23 days and I'm interested in investing in with a budget of 5242 dollars. The historical stock value data of PBTP for the past 23 days is: [23.83, 23.88, 23.89, 23.93, 23.95, 23.88, 23.87, 23.86, 23.95, 23.92, 23.89, 23.88, 23.92, 23.96, 23.94, 23.95, 23.94, 24.05, 24.08, ... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_914.pkl | external_data/ground_truth_data/ground_truth_data_914.pkl | external_data/context/context_914.pkl | external_data/constraint/constraint_914.pkl |
915 | stock_investment | I have historical stock price data of RETO for 37 days and I'm interested in investing in with a budget of 25752 dollars. Please give me an investment strategy for the next 41 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 4... | I have historical stock price data of RETO for 37 days and I'm interested in investing in with a budget of 25752 dollars. The historical stock value data of RETO for the past 37 days is: [561.0, 500.0, 558.0, 560.0, 500.0, 501.0, 500.0, 510.0, 500.0, 500.0, 500.0, 490.0, 510.0, 536.0, 549.0, 540.0, 508.0, 470.0, 540.0,... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_915.pkl | external_data/ground_truth_data/ground_truth_data_915.pkl | external_data/context/context_915.pkl | external_data/constraint/constraint_915.pkl |
916 | stock_investment | I have historical stock price data of XPP for 21 days and I'm interested in investing in with a budget of 5110 dollars. Please give me an investment strategy for the next 33 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 33 ... | I have historical stock price data of XPP for 21 days and I'm interested in investing in with a budget of 5110 dollars. The historical stock value data of XPP for the past 21 days is: [29.17, 28.74, 29.3, 30.88, 30.4, 32.3, 31.91, 31.21, 28.9, 28.92, 30.54, 28.62, 30.63, 30.67, 29.75, 30.57, 31.71, 33.42, 33.7, 32.45, ... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_916.pkl | external_data/ground_truth_data/ground_truth_data_916.pkl | external_data/context/context_916.pkl | external_data/constraint/constraint_916.pkl |
917 | stock_investment | I have historical stock price data of ZGN for 28 days and I'm interested in investing in with a budget of 7879 dollars. Please give me an investment strategy for the next 52 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 52 ... | I have historical stock price data of ZGN for 28 days and I'm interested in investing in with a budget of 7879 dollars. The historical stock value data of ZGN for the past 28 days is: [10.85, 10.63, 10.54, 10.21, 10.44, 11.24, 10.12, 9.9, 10.11, 9.99, 10.12, 10.0, 9.67, 9.86, 9.89, 10.2, 10.37, 9.97, 9.99, 9.72, 10.23,... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_917.pkl | external_data/ground_truth_data/ground_truth_data_917.pkl | external_data/context/context_917.pkl | external_data/constraint/constraint_917.pkl |
918 | stock_investment | I have historical stock price data of VOTE for 30 days and I'm interested in investing in with a budget of 7626 dollars. Please give me an investment strategy for the next 44 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 44... | I have historical stock price data of VOTE for 30 days and I'm interested in investing in with a budget of 7626 dollars. The historical stock value data of VOTE for the past 30 days is: [51.33, 52.26, 51.78, 52.83, 53.32, 53.28, 53.31, 53.44, 52.54, 52.56, 53.66, 52.55, 51.54, 52.27, 52.73, 53.3, 53.9, 54.51, 54.47, 54... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_918.pkl | external_data/ground_truth_data/ground_truth_data_918.pkl | external_data/context/context_918.pkl | external_data/constraint/constraint_918.pkl |
919 | stock_investment | I have historical stock price data of RILYK for 36 days and I'm interested in investing in with a budget of 6221 dollars. Please give me an investment strategy for the next 45 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 4... | I have historical stock price data of RILYK for 36 days and I'm interested in investing in with a budget of 6221 dollars. The historical stock value data of RILYK for the past 36 days is: [18.45, 18.22, 18.88, 19.16, 19.44, 19.58, 19.87, 19.73, 19.62, 19.13, 19.53, 19.34, 18.76, 18.84, 18.6, 18.87, 18.64, 18.48, 19.83,... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_919.pkl | external_data/ground_truth_data/ground_truth_data_919.pkl | external_data/context/context_919.pkl | external_data/constraint/constraint_919.pkl |
920 | stock_investment | I have historical stock price data of SIXL for 39 days and I'm interested in investing in with a budget of 5530 dollars. Please give me an investment strategy for the next 20 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 20... | I have historical stock price data of SIXL for 39 days and I'm interested in investing in with a budget of 5530 dollars. The historical stock value data of SIXL for the past 39 days is: [30.58, 30.88, 31.23, 31.46, 31.49, 31.48, 31.58, 31.42, 31.18, 31.11, 31.22, 30.75, 30.52, 30.95, 30.93, 30.44, 30.69, 30.58, 30.21, ... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_920.pkl | external_data/ground_truth_data/ground_truth_data_920.pkl | external_data/context/context_920.pkl | external_data/constraint/constraint_920.pkl |
921 | stock_investment | I have historical stock price data of SEE for 30 days and I'm interested in investing in with a budget of 9959 dollars. Please give me an investment strategy for the next 55 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 55 ... | I have historical stock price data of SEE for 30 days and I'm interested in investing in with a budget of 9959 dollars. The historical stock value data of SEE for the past 30 days is: [20.06, 20.04, 20.12, 20.19, 19.92, 20.1, 20.29, 20.21, 20.34, 20.58, 20.53, 20.81, 21.04, 20.77, 20.08, 20.17, 19.64, 20.95, 21.08, 21.... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_921.pkl | external_data/ground_truth_data/ground_truth_data_921.pkl | external_data/context/context_921.pkl | external_data/constraint/constraint_921.pkl |
922 | stock_investment | I have historical stock price data of TETE for 32 days and I'm interested in investing in with a budget of 4750 dollars. Please give me an investment strategy for the next 50 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 50... | I have historical stock price data of TETE for 32 days and I'm interested in investing in with a budget of 4750 dollars. The historical stock value data of TETE for the past 32 days is: [11.89, 11.92, 11.9, 11.88, 11.85, 11.9, 11.9, 11.92, 11.9, 11.9, 11.9, 11.9, 11.91, 11.91, 11.91, 11.91, 11.92, 11.9, 11.94, 11.94, 1... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_922.pkl | external_data/ground_truth_data/ground_truth_data_922.pkl | external_data/context/context_922.pkl | external_data/constraint/constraint_922.pkl |
923 | stock_investment | I have historical stock price data of PTF for 25 days and I'm interested in investing in with a budget of 5203 dollars. Please give me an investment strategy for the next 35 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 35 ... | I have historical stock price data of PTF for 25 days and I'm interested in investing in with a budget of 5203 dollars. The historical stock value data of PTF for the past 25 days is: [41.23, 39.78, 40.54, 39.13, 40.05, 40.66, 39.25, 40.32, 40.96, 41.84, 39.2, 38.6, 38.34, 37.58, 36.18, 37.57, 38.22, 38.95, 39.02, 37.6... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_923.pkl | external_data/ground_truth_data/ground_truth_data_923.pkl | external_data/context/context_923.pkl | external_data/constraint/constraint_923.pkl |
924 | stock_investment | I have historical stock price data of NCMI for 33 days and I'm interested in investing in with a budget of 7038 dollars. Please give me an investment strategy for the next 42 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 42... | I have historical stock price data of NCMI for 33 days and I'm interested in investing in with a budget of 7038 dollars. The historical stock value data of NCMI for the past 33 days is: [90.01, 93.08, 86.72, 88.62, 88.68, 89.78, 90.19, 88.97, 88.34, 87.82, 88.97, 87.82, 88.8, 87.69, 87.1, 87.98, 86.57, 85.93, 87.69, 88... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_924.pkl | external_data/ground_truth_data/ground_truth_data_924.pkl | external_data/context/context_924.pkl | external_data/constraint/constraint_924.pkl |
925 | stock_investment | I have historical stock price data of SOHOB for 27 days and I'm interested in investing in with a budget of 5063 dollars. Please give me an investment strategy for the next 50 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 5... | I have historical stock price data of SOHOB for 27 days and I'm interested in investing in with a budget of 5063 dollars. The historical stock value data of SOHOB for the past 27 days is: [19.93, 19.81, 19.74, 19.66, 19.98, 19.88, 19.86, 20.0, 20.11, 20.29, 20.03, 20.06, 20.17, 20.17, 20.17, 20.25, 20.32, 20.33, 20.38,... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_925.pkl | external_data/ground_truth_data/ground_truth_data_925.pkl | external_data/context/context_925.pkl | external_data/constraint/constraint_925.pkl |
926 | stock_investment | I have historical stock price data of TDW for 29 days and I'm interested in investing in with a budget of 22551 dollars. Please give me an investment strategy for the next 40 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 40... | I have historical stock price data of TDW for 29 days and I'm interested in investing in with a budget of 22551 dollars. The historical stock value data of TDW for the past 29 days is: [1986.55, 1972.22, 1963.11, 2029.54, 2068.62, 2084.25, 2008.96, 1976.65, 1980.04, 1868.53, 1826.85, 1872.44, 1782.56, 1741.65, 1735.92,... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_926.pkl | external_data/ground_truth_data/ground_truth_data_926.pkl | external_data/context/context_926.pkl | external_data/constraint/constraint_926.pkl |
927 | stock_investment | I have historical stock price data of QDEC for 33 days and I'm interested in investing in with a budget of 4672 dollars. Please give me an investment strategy for the next 38 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 38... | I have historical stock price data of QDEC for 33 days and I'm interested in investing in with a budget of 4672 dollars. The historical stock value data of QDEC for the past 33 days is: [22.25, 22.26, 22.1, 22.19, 22.0, 22.15, 22.27, 22.33, 22.3, 22.2, 22.19, 22.43, 22.51, 22.61, 22.67, 22.75, 22.62, 22.62, 22.71, 22.7... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_927.pkl | external_data/ground_truth_data/ground_truth_data_927.pkl | external_data/context/context_927.pkl | external_data/constraint/constraint_927.pkl |
928 | stock_investment | I have historical stock price data of REMX for 29 days and I'm interested in investing in with a budget of 2515 dollars. Please give me an investment strategy for the next 22 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 22... | I have historical stock price data of REMX for 29 days and I'm interested in investing in with a budget of 2515 dollars. The historical stock value data of REMX for the past 29 days is: [112.81, 119.18, 122.16, 121.48, 120.71, 119.44, 119.01, 115.87, 114.51, 110.6, 112.21, 110.94, 111.7, 111.11, 110.34, 110.0, 111.96, ... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_928.pkl | external_data/ground_truth_data/ground_truth_data_928.pkl | external_data/context/context_928.pkl | external_data/constraint/constraint_928.pkl |
929 | stock_investment | I have historical stock price data of MAT for 32 days and I'm interested in investing in with a budget of 8116 dollars. Please give me an investment strategy for the next 39 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 39 ... | I have historical stock price data of MAT for 32 days and I'm interested in investing in with a budget of 8116 dollars. The historical stock value data of MAT for the past 32 days is: [29.8, 30.74, 30.13, 30.41, 29.89, 30.34, 30.42, 29.74, 30.24, 30.66, 31.03, 31.35, 30.43, 30.06, 29.38, 29.95, 30.51, 30.18, 30.01, 29.... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_929.pkl | external_data/ground_truth_data/ground_truth_data_929.pkl | external_data/context/context_929.pkl | external_data/constraint/constraint_929.pkl |
930 | stock_investment | I have historical stock price data of VIRI for 20 days and I'm interested in investing in with a budget of 4310 dollars. Please give me an investment strategy for the next 56 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 56... | I have historical stock price data of VIRI for 20 days and I'm interested in investing in with a budget of 4310 dollars. The historical stock value data of VIRI for the past 20 days is: [5.28, 5.41, 5.32, 5.08, 5.05, 4.82, 4.84, 4.58, 4.67, 4.87, 4.88, 4.98, 5.08, 5.22, 5.01, 5.18, 5.35, 5.52, 5.62, 5.99]. Please give ... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_930.pkl | external_data/ground_truth_data/ground_truth_data_930.pkl | external_data/context/context_930.pkl | external_data/constraint/constraint_930.pkl |
931 | stock_investment | I have historical stock price data of TRV for 28 days and I'm interested in investing in with a budget of 2450 dollars. Please give me an investment strategy for the next 46 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 46 ... | I have historical stock price data of TRV for 28 days and I'm interested in investing in with a budget of 2450 dollars. The historical stock value data of TRV for the past 28 days is: [167.12, 167.1, 167.02, 164.76, 166.84, 170.32, 168.7, 169.44, 170.35, 170.07, 170.64, 170.35, 172.62, 169.36, 173.48, 171.81, 171.31, 1... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_931.pkl | external_data/ground_truth_data/ground_truth_data_931.pkl | external_data/context/context_931.pkl | external_data/constraint/constraint_931.pkl |
932 | stock_investment | I have historical stock price data of UTHR for 32 days and I'm interested in investing in with a budget of 3392 dollars. Please give me an investment strategy for the next 23 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 23... | I have historical stock price data of UTHR for 32 days and I'm interested in investing in with a budget of 3392 dollars. The historical stock value data of UTHR for the past 32 days is: [49.88, 49.99, 50.42, 50.0, 49.15, 48.85, 49.52, 50.64, 51.39, 51.25, 49.21, 49.5, 49.26, 49.58, 48.94, 47.65, 47.83, 46.6, 45.76, 44.... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_932.pkl | external_data/ground_truth_data/ground_truth_data_932.pkl | external_data/context/context_932.pkl | external_data/constraint/constraint_932.pkl |
933 | stock_investment | I have historical stock price data of LDUR for 24 days and I'm interested in investing in with a budget of 2735 dollars. Please give me an investment strategy for the next 33 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 33... | I have historical stock price data of LDUR for 24 days and I'm interested in investing in with a budget of 2735 dollars. The historical stock value data of LDUR for the past 24 days is: [92.16, 92.1, 92.12, 92.14, 92.11, 92.11, 92.14, 92.1, 92.14, 92.17, 92.21, 92.21, 92.21, 92.25, 92.27, 92.27, 92.19, 92.16, 92.22, 92... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_933.pkl | external_data/ground_truth_data/ground_truth_data_933.pkl | external_data/context/context_933.pkl | external_data/constraint/constraint_933.pkl |
934 | stock_investment | I have historical stock price data of RELX for 33 days and I'm interested in investing in with a budget of 1820 dollars. Please give me an investment strategy for the next 26 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 26... | I have historical stock price data of RELX for 33 days and I'm interested in investing in with a budget of 1820 dollars. The historical stock value data of RELX for the past 33 days is: [20.14, 20.21, 20.28, 20.37, 20.29, 20.41, 20.14, 20.09, 20.14, 19.95, 19.99, 20.01, 19.8, 19.8, 19.75, 20.0, 20.14, 19.91, 20.1, 19.9... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_934.pkl | external_data/ground_truth_data/ground_truth_data_934.pkl | external_data/context/context_934.pkl | external_data/constraint/constraint_934.pkl |
935 | stock_investment | I have historical stock price data of LAZR for 31 days and I'm interested in investing in with a budget of 2373 dollars. Please give me an investment strategy for the next 55 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 55... | I have historical stock price data of LAZR for 31 days and I'm interested in investing in with a budget of 2373 dollars. The historical stock value data of LAZR for the past 31 days is: [7.59, 7.21, 6.85, 6.96, 7.12, 6.8, 7.35, 7.62, 7.41, 7.77, 8.44, 8.23, 8.01, 7.75, 7.84, 7.5, 7.18, 7.14, 7.77, 8.35, 8.77, 8.63, 8.1... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_935.pkl | external_data/ground_truth_data/ground_truth_data_935.pkl | external_data/context/context_935.pkl | external_data/constraint/constraint_935.pkl |
936 | stock_investment | I have historical stock price data of UK for 28 days and I'm interested in investing in with a budget of 31119 dollars. Please give me an investment strategy for the next 38 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 38 ... | I have historical stock price data of UK for 28 days and I'm interested in investing in with a budget of 31119 dollars. The historical stock value data of UK for the past 28 days is: [2436.0, 2452.8, 2436.0, 2439.6, 2438.4, 2436.0, 2441.52, 2436.0, 2438.4, 2438.4, 2445.6, 2443.2, 2443.2, 2443.2, 2443.2, 2443.2, 2443.2,... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_936.pkl | external_data/ground_truth_data/ground_truth_data_936.pkl | external_data/context/context_936.pkl | external_data/constraint/constraint_936.pkl |
937 | stock_investment | I have historical stock price data of LSBK for 38 days and I'm interested in investing in with a budget of 8548 dollars. Please give me an investment strategy for the next 21 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 21... | I have historical stock price data of LSBK for 38 days and I'm interested in investing in with a budget of 8548 dollars. The historical stock value data of LSBK for the past 38 days is: [13.51, 13.51, 13.2, 13.51, 13.35, 13.35, 13.05, 13.05, 13.12, 13.02, 13.45, 13.48, 13.51, 13.09, 13.23, 13.08, 12.89, 12.89, 13.02, 1... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_937.pkl | external_data/ground_truth_data/ground_truth_data_937.pkl | external_data/context/context_937.pkl | external_data/constraint/constraint_937.pkl |
938 | stock_investment | I have historical stock price data of QSWN for 23 days and I'm interested in investing in with a budget of 1438 dollars. Please give me an investment strategy for the next 43 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 43... | I have historical stock price data of QSWN for 23 days and I'm interested in investing in with a budget of 1438 dollars. The historical stock value data of QSWN for the past 23 days is: [18.58, 18.9, 18.8, 18.96, 19.07, 19.1, 18.8, 18.69, 18.65, 18.72, 18.7, 18.53, 18.81, 18.8, 18.7, 18.45, 18.34, 18.43, 18.5, 18.46, 1... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_938.pkl | external_data/ground_truth_data/ground_truth_data_938.pkl | external_data/context/context_938.pkl | external_data/constraint/constraint_938.pkl |
939 | stock_investment | I have historical stock price data of TYLG for 22 days and I'm interested in investing in with a budget of 6243 dollars. Please give me an investment strategy for the next 23 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 23... | I have historical stock price data of TYLG for 22 days and I'm interested in investing in with a budget of 6243 dollars. The historical stock value data of TYLG for the past 22 days is: [22.22, 21.82, 21.95, 22.42, 22.18, 23.01, 22.99, 23.31, 23.07, 23.16, 23.38, 23.28, 23.33, 23.07, 23.35, 23.67, 23.89, 23.89, 23.79, ... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_939.pkl | external_data/ground_truth_data/ground_truth_data_939.pkl | external_data/context/context_939.pkl | external_data/constraint/constraint_939.pkl |
940 | stock_investment | I have historical stock price data of SRTS for 37 days and I'm interested in investing in with a budget of 9963 dollars. Please give me an investment strategy for the next 42 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 42... | I have historical stock price data of SRTS for 37 days and I'm interested in investing in with a budget of 9963 dollars. The historical stock value data of SRTS for the past 37 days is: [4.01, 3.81, 3.79, 3.81, 3.88, 3.88, 3.93, 4.2, 3.92, 4.09, 3.94, 3.98, 3.83, 3.8, 3.74, 3.71, 3.68, 3.7, 3.68, 3.7, 3.7, 3.7, 3.64, 3... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_940.pkl | external_data/ground_truth_data/ground_truth_data_940.pkl | external_data/context/context_940.pkl | external_data/constraint/constraint_940.pkl |
941 | stock_investment | I have historical stock price data of ZIMV for 31 days and I'm interested in investing in with a budget of 8754 dollars. Please give me an investment strategy for the next 56 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 56... | I have historical stock price data of ZIMV for 31 days and I'm interested in investing in with a budget of 8754 dollars. The historical stock value data of ZIMV for the past 31 days is: [11.63, 11.22, 11.42, 11.12, 11.53, 11.49, 11.79, 12.02, 11.85, 11.78, 11.58, 11.48, 10.99, 10.86, 10.92, 11.0, 10.93, 11.32, 10.96, 1... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_941.pkl | external_data/ground_truth_data/ground_truth_data_941.pkl | external_data/context/context_941.pkl | external_data/constraint/constraint_941.pkl |
942 | stock_investment | I have historical stock price data of PST for 37 days and I'm interested in investing in with a budget of 8834 dollars. Please give me an investment strategy for the next 22 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 22 ... | I have historical stock price data of PST for 37 days and I'm interested in investing in with a budget of 8834 dollars. The historical stock value data of PST for the past 37 days is: [37.73, 37.8, 37.16, 37.27, 37.23, 37.55, 37.12, 37.43, 36.86, 36.48, 36.98, 36.99, 37.28, 36.59, 36.85, 37.25, 37.98, 37.4, 37.33, 37.7... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_942.pkl | external_data/ground_truth_data/ground_truth_data_942.pkl | external_data/context/context_942.pkl | external_data/constraint/constraint_942.pkl |
943 | stock_investment | I have historical stock price data of SIHY for 37 days and I'm interested in investing in with a budget of 2576 dollars. Please give me an investment strategy for the next 33 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 33... | I have historical stock price data of SIHY for 37 days and I'm interested in investing in with a budget of 2576 dollars. The historical stock value data of SIHY for the past 37 days is: [43.31, 43.32, 43.24, 43.18, 43.39, 43.76, 43.8, 43.74, 43.75, 43.74, 43.63, 43.71, 43.75, 43.93, 44.0, 43.94, 43.98, 44.05, 44.08, 43... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_943.pkl | external_data/ground_truth_data/ground_truth_data_943.pkl | external_data/context/context_943.pkl | external_data/constraint/constraint_943.pkl |
944 | stock_investment | I have historical stock price data of STOT for 21 days and I'm interested in investing in with a budget of 1134 dollars. Please give me an investment strategy for the next 51 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 51... | I have historical stock price data of STOT for 21 days and I'm interested in investing in with a budget of 1134 dollars. The historical stock value data of STOT for the past 21 days is: [43.3, 43.37, 43.42, 43.46, 43.39, 43.39, 43.43, 43.42, 43.51, 43.54, 43.45, 43.46, 43.48, 43.48, 43.57, 43.53, 43.49, 43.46, 43.48, 4... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_944.pkl | external_data/ground_truth_data/ground_truth_data_944.pkl | external_data/context/context_944.pkl | external_data/constraint/constraint_944.pkl |
945 | stock_investment | I have historical stock price data of SBFG for 36 days and I'm interested in investing in with a budget of 5816 dollars. Please give me an investment strategy for the next 44 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 44... | I have historical stock price data of SBFG for 36 days and I'm interested in investing in with a budget of 5816 dollars. The historical stock value data of SBFG for the past 36 days is: [2.91, 2.87, 2.87, 2.91, 2.94, 2.97, 3.27, 3.21, 3.37, 3.34, 3.1, 3.09, 2.7, 2.65, 2.48, 2.49, 2.73, 2.53, 2.72, 2.81, 2.7, 2.75, 2.73... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_945.pkl | external_data/ground_truth_data/ground_truth_data_945.pkl | external_data/context/context_945.pkl | external_data/constraint/constraint_945.pkl |
946 | stock_investment | I have historical stock price data of WALD for 23 days and I'm interested in investing in with a budget of 6600 dollars. Please give me an investment strategy for the next 50 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 50... | I have historical stock price data of WALD for 23 days and I'm interested in investing in with a budget of 6600 dollars. The historical stock value data of WALD for the past 23 days is: [7.12, 6.6, 6.61, 7.46, 8.79, 10.77, 10.11, 9.75, 8.63, 8.81, 8.56, 8.26, 8.46, 9.23, 9.27, 9.81, 9.66, 9.41, 8.75, 9.03, 9.19, 9.1, 9... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_946.pkl | external_data/ground_truth_data/ground_truth_data_946.pkl | external_data/context/context_946.pkl | external_data/constraint/constraint_946.pkl |
947 | stock_investment | I have historical stock price data of NEGG for 35 days and I'm interested in investing in with a budget of 6989 dollars. Please give me an investment strategy for the next 26 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 26... | I have historical stock price data of NEGG for 35 days and I'm interested in investing in with a budget of 6989 dollars. The historical stock value data of NEGG for the past 35 days is: [1.0, 1.11, 1.05, 1.07, 1.02, 1.0, 0.94, 0.91, 0.88, 0.93, 0.9, 0.88, 0.92, 0.95, 0.91, 0.89, 0.91, 0.9, 0.88, 0.87, 0.86, 0.85, 0.85,... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_947.pkl | external_data/ground_truth_data/ground_truth_data_947.pkl | external_data/context/context_947.pkl | external_data/constraint/constraint_947.pkl |
948 | stock_investment | I have historical stock price data of XSD for 38 days and I'm interested in investing in with a budget of 5907 dollars. Please give me an investment strategy for the next 25 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 25 ... | I have historical stock price data of XSD for 38 days and I'm interested in investing in with a budget of 5907 dollars. The historical stock value data of XSD for the past 38 days is: [124.59, 124.87, 125.03, 124.24, 123.3, 125.7, 124.46, 124.42, 124.85, 123.32, 121.84, 120.85, 123.0, 123.46, 125.67, 125.5, 124.04, 126... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_948.pkl | external_data/ground_truth_data/ground_truth_data_948.pkl | external_data/context/context_948.pkl | external_data/constraint/constraint_948.pkl |
949 | stock_investment | I have historical stock price data of RM for 33 days and I'm interested in investing in with a budget of 534 dollars. Please give me an investment strategy for the next 39 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 39 tr... | I have historical stock price data of RM for 33 days and I'm interested in investing in with a budget of 534 dollars. The historical stock value data of RM for the past 33 days is: [25.49, 25.74, 26.05, 26.42, 26.5, 26.36, 26.57, 26.04, 25.51, 26.02, 25.92, 25.31, 25.41, 25.48, 26.26, 26.11, 26.82, 26.36, 25.78, 25.52,... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_949.pkl | external_data/ground_truth_data/ground_truth_data_949.pkl | external_data/context/context_949.pkl | external_data/constraint/constraint_949.pkl |
950 | stock_investment | I have historical stock price data of VLN for 24 days and I'm interested in investing in with a budget of 1628 dollars. Please give me an investment strategy for the next 29 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 29 ... | I have historical stock price data of VLN for 24 days and I'm interested in investing in with a budget of 1628 dollars. The historical stock value data of VLN for the past 24 days is: [2.46, 2.55, 2.49, 2.51, 2.7, 2.49, 2.47, 2.47, 2.44, 2.46, 2.46, 2.46, 2.46, 2.5, 2.59, 2.46, 2.46, 2.53, 2.57, 2.56, 2.59, 2.52, 2.5, ... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_950.pkl | external_data/ground_truth_data/ground_truth_data_950.pkl | external_data/context/context_950.pkl | external_data/constraint/constraint_950.pkl |
951 | stock_investment | I have historical stock price data of ONLN for 21 days and I'm interested in investing in with a budget of 3679 dollars. Please give me an investment strategy for the next 56 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 56... | I have historical stock price data of ONLN for 21 days and I'm interested in investing in with a budget of 3679 dollars. The historical stock value data of ONLN for the past 21 days is: [32.17, 32.84, 31.88, 32.25, 32.04, 29.81, 30.66, 30.69, 31.21, 31.6, 31.86, 33.15, 33.12, 35.1, 34.39, 32.19, 33.08, 31.97, 32.57, 32... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_951.pkl | external_data/ground_truth_data/ground_truth_data_951.pkl | external_data/context/context_951.pkl | external_data/constraint/constraint_951.pkl |
952 | stock_investment | I have historical stock price data of UVIX for 28 days and I'm interested in investing in with a budget of 4608 dollars. Please give me an investment strategy for the next 53 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 53... | I have historical stock price data of UVIX for 28 days and I'm interested in investing in with a budget of 4608 dollars. The historical stock value data of UVIX for the past 28 days is: [189.3, 188.1, 194.5, 184.4, 187.2, 212.5, 203.0, 189.3, 181.8, 182.3, 196.3, 208.1, 219.3, 197.0, 205.7, 195.7, 190.6, 184.5, 192.3, ... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_952.pkl | external_data/ground_truth_data/ground_truth_data_952.pkl | external_data/context/context_952.pkl | external_data/constraint/constraint_952.pkl |
953 | stock_investment | I have historical stock price data of TDC for 32 days and I'm interested in investing in with a budget of 5280 dollars. Please give me an investment strategy for the next 21 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 21 ... | I have historical stock price data of TDC for 32 days and I'm interested in investing in with a budget of 5280 dollars. The historical stock value data of TDC for the past 32 days is: [41.85, 42.3, 41.64, 42.16, 42.71, 42.62, 42.69, 43.17, 43.59, 44.46, 44.52, 44.2, 44.81, 44.68, 44.6, 44.73, 44.64, 45.32, 44.93, 44.99... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_953.pkl | external_data/ground_truth_data/ground_truth_data_953.pkl | external_data/context/context_953.pkl | external_data/constraint/constraint_953.pkl |
954 | stock_investment | I have historical stock price data of SWVL for 36 days and I'm interested in investing in with a budget of 7748 dollars. Please give me an investment strategy for the next 44 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 44... | I have historical stock price data of SWVL for 36 days and I'm interested in investing in with a budget of 7748 dollars. The historical stock value data of SWVL for the past 36 days is: [41.25, 41.5, 42.75, 41.0, 42.5, 42.5, 42.25, 44.25, 44.0, 39.75, 40.25, 40.0, 43.25, 45.0, 42.5, 42.5, 41.25, 40.75, 39.75, 42.25, 42... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_954.pkl | external_data/ground_truth_data/ground_truth_data_954.pkl | external_data/context/context_954.pkl | external_data/constraint/constraint_954.pkl |
955 | stock_investment | I have historical stock price data of NXGL for 31 days and I'm interested in investing in with a budget of 9851 dollars. Please give me an investment strategy for the next 49 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 49... | I have historical stock price data of NXGL for 31 days and I'm interested in investing in with a budget of 9851 dollars. The historical stock value data of NXGL for the past 31 days is: [1.82, 1.99, 1.85, 1.67, 1.74, 1.5, 1.63, 1.62, 1.55, 1.68, 1.71, 1.79, 2.0, 1.95, 2.0, 1.8, 1.87, 1.82, 1.72, 1.74, 1.89, 1.75, 1.8, ... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_955.pkl | external_data/ground_truth_data/ground_truth_data_955.pkl | external_data/context/context_955.pkl | external_data/constraint/constraint_955.pkl |
956 | stock_investment | I have historical stock price data of MLM for 23 days and I'm interested in investing in with a budget of 1883 dollars. Please give me an investment strategy for the next 34 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 34 ... | I have historical stock price data of MLM for 23 days and I'm interested in investing in with a budget of 1883 dollars. The historical stock value data of MLM for the past 23 days is: [74.64, 75.32, 74.88, 74.74, 72.95, 73.73, 73.95, 71.52, 70.04, 69.0, 68.63, 68.39, 67.7, 67.31, 68.6, 69.1, 67.63, 66.18, 66.33, 65.05,... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_956.pkl | external_data/ground_truth_data/ground_truth_data_956.pkl | external_data/context/context_956.pkl | external_data/constraint/constraint_956.pkl |
957 | stock_investment | I have historical stock price data of LFMD for 33 days and I'm interested in investing in with a budget of 7914 dollars. Please give me an investment strategy for the next 51 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 51... | I have historical stock price data of LFMD for 33 days and I'm interested in investing in with a budget of 7914 dollars. The historical stock value data of LFMD for the past 33 days is: [1.5, 1.5, 0.9, 1.6, 1.6, 0.9, 0.9, 0.9, 0.9, 1.6, 0.95, 1.4, 0.95, 1.35, 1.25, 1.25, 1.25, 1.0, 0.95, 0.95, 0.95, 0.95, 0.9, 0.95, 1.... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_957.pkl | external_data/ground_truth_data/ground_truth_data_957.pkl | external_data/context/context_957.pkl | external_data/constraint/constraint_957.pkl |
958 | stock_investment | I have historical stock price data of LEDS for 20 days and I'm interested in investing in with a budget of 9379 dollars. Please give me an investment strategy for the next 23 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 23... | I have historical stock price data of LEDS for 20 days and I'm interested in investing in with a budget of 9379 dollars. The historical stock value data of LEDS for the past 20 days is: [7.5, 8.0, 7.9, 8.5, 10.1, 10.1, 12.6, 12.4, 12.0, 10.1, 10.2, 10.0, 10.2, 10.0, 11.8, 12.7, 16.3, 14.1, 14.0, 13.4]. Please give me a... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_958.pkl | external_data/ground_truth_data/ground_truth_data_958.pkl | external_data/context/context_958.pkl | external_data/constraint/constraint_958.pkl |
959 | stock_investment | I have historical stock price data of RRR for 22 days and I'm interested in investing in with a budget of 228 dollars. Please give me an investment strategy for the next 45 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 45 t... | I have historical stock price data of RRR for 22 days and I'm interested in investing in with a budget of 228 dollars. The historical stock value data of RRR for the past 22 days is: [18.68, 18.77, 19.26, 19.67, 19.23, 19.31, 18.8, 18.83, 18.93, 18.53, 18.47, 18.66, 18.41, 18.16, 18.3, 18.57, 18.98, 18.98, 19.26, 18.96... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_959.pkl | external_data/ground_truth_data/ground_truth_data_959.pkl | external_data/context/context_959.pkl | external_data/constraint/constraint_959.pkl |
960 | stock_investment | I have historical stock price data of MQ for 38 days and I'm interested in investing in with a budget of 5737 dollars. Please give me an investment strategy for the next 44 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 44 t... | I have historical stock price data of MQ for 38 days and I'm interested in investing in with a budget of 5737 dollars. The historical stock value data of MQ for the past 38 days is: [5.82, 5.82, 6.07, 6.08, 6.0, 6.03, 5.91, 5.98, 5.92, 6.09, 6.35, 6.3, 5.96, 5.94, 5.87, 5.8, 5.95, 5.64, 6.0, 6.05, 5.87, 5.89, 6.02, 5.8... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_960.pkl | external_data/ground_truth_data/ground_truth_data_960.pkl | external_data/context/context_960.pkl | external_data/constraint/constraint_960.pkl |
961 | stock_investment | I have historical stock price data of WALD for 35 days and I'm interested in investing in with a budget of 1257 dollars. Please give me an investment strategy for the next 55 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 55... | I have historical stock price data of WALD for 35 days and I'm interested in investing in with a budget of 1257 dollars. The historical stock value data of WALD for the past 35 days is: [8.77, 8.88, 9.01, 8.9, 8.76, 9.2, 9.2, 9.18, 9.19, 9.2, 9.16, 9.0, 9.2, 9.02, 9.0, 8.84, 9.2, 9.09, 9.0, 9.16, 9.19, 9.85, 9.85, 9.69... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_961.pkl | external_data/ground_truth_data/ground_truth_data_961.pkl | external_data/context/context_961.pkl | external_data/constraint/constraint_961.pkl |
962 | stock_investment | I have historical stock price data of TBBK for 31 days and I'm interested in investing in with a budget of 7919 dollars. Please give me an investment strategy for the next 44 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 44... | I have historical stock price data of TBBK for 31 days and I'm interested in investing in with a budget of 7919 dollars. The historical stock value data of TBBK for the past 31 days is: [9.82, 9.93, 9.95, 10.02, 10.05, 10.18, 10.15, 10.23, 10.28, 10.44, 11.2, 10.95, 11.06, 10.95, 10.92, 11.1, 11.34, 11.48, 11.5, 11.25,... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_962.pkl | external_data/ground_truth_data/ground_truth_data_962.pkl | external_data/context/context_962.pkl | external_data/constraint/constraint_962.pkl |
963 | stock_investment | I have historical stock price data of SPVM for 23 days and I'm interested in investing in with a budget of 4128 dollars. Please give me an investment strategy for the next 35 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 35... | I have historical stock price data of SPVM for 23 days and I'm interested in investing in with a budget of 4128 dollars. The historical stock value data of SPVM for the past 23 days is: [33.59, 32.58, 32.68, 32.62, 32.97, 33.28, 33.08, 33.33, 33.5, 33.19, 32.75, 33.21, 33.49, 33.69, 33.45, 33.91, 33.82, 34.1, 34.23, 34... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_963.pkl | external_data/ground_truth_data/ground_truth_data_963.pkl | external_data/context/context_963.pkl | external_data/constraint/constraint_963.pkl |
964 | stock_investment | I have historical stock price data of OBDC for 24 days and I'm interested in investing in with a budget of 6843 dollars. Please give me an investment strategy for the next 45 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 45... | I have historical stock price data of OBDC for 24 days and I'm interested in investing in with a budget of 6843 dollars. The historical stock value data of OBDC for the past 24 days is: [9.9, 9.87, 9.85, 9.86, 9.73, 9.91, 9.88, 9.87, 9.62, 9.62, 9.85, 9.91, 9.78, 9.87, 9.93, 10.03, 10.05, 10.07, 9.95, 9.99, 10.02, 9.99... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_964.pkl | external_data/ground_truth_data/ground_truth_data_964.pkl | external_data/context/context_964.pkl | external_data/constraint/constraint_964.pkl |
965 | stock_investment | I have historical stock price data of LFVN for 29 days and I'm interested in investing in with a budget of 4624 dollars. Please give me an investment strategy for the next 46 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 46... | I have historical stock price data of LFVN for 29 days and I'm interested in investing in with a budget of 4624 dollars. The historical stock value data of LFVN for the past 29 days is: [8.42, 8.46, 8.25, 8.17, 8.33, 8.37, 8.39, 8.31, 8.19, 8.26, 8.25, 8.16, 8.2, 8.0, 7.95, 8.03, 8.13, 8.09, 8.34, 8.6, 9.11, 8.97, 8.81... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_965.pkl | external_data/ground_truth_data/ground_truth_data_965.pkl | external_data/context/context_965.pkl | external_data/constraint/constraint_965.pkl |
966 | stock_investment | I have historical stock price data of PWSC for 27 days and I'm interested in investing in with a budget of 6765 dollars. Please give me an investment strategy for the next 33 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 33... | I have historical stock price data of PWSC for 27 days and I'm interested in investing in with a budget of 6765 dollars. The historical stock value data of PWSC for the past 27 days is: [24.31, 23.48, 22.74, 23.53, 23.0, 23.69, 21.23, 21.01, 20.87, 20.72, 20.61, 20.57, 20.52, 20.65, 20.73, 20.65, 20.83, 20.46, 20.59, 2... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_966.pkl | external_data/ground_truth_data/ground_truth_data_966.pkl | external_data/context/context_966.pkl | external_data/constraint/constraint_966.pkl |
967 | stock_investment | I have historical stock price data of LBRT for 25 days and I'm interested in investing in with a budget of 2511 dollars. Please give me an investment strategy for the next 30 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 30... | I have historical stock price data of LBRT for 25 days and I'm interested in investing in with a budget of 2511 dollars. The historical stock value data of LBRT for the past 25 days is: [8.41, 8.36, 8.46, 8.57, 8.33, 8.24, 8.54, 8.38, 8.76, 9.25, 9.5, 9.69, 10.12, 10.28, 10.58, 10.57, 10.77, 10.68, 10.38, 10.71, 10.83,... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_967.pkl | external_data/ground_truth_data/ground_truth_data_967.pkl | external_data/context/context_967.pkl | external_data/constraint/constraint_967.pkl |
968 | stock_investment | I have historical stock price data of MTCH for 20 days and I'm interested in investing in with a budget of 6394 dollars. Please give me an investment strategy for the next 32 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 32... | I have historical stock price data of MTCH for 20 days and I'm interested in investing in with a budget of 6394 dollars. The historical stock value data of MTCH for the past 20 days is: [21.41, 22.43, 22.59, 21.43, 21.65, 22.04, 22.38, 21.79, 21.83, 22.54, 22.33, 22.52, 22.47, 22.6, 22.95, 22.17, 22.55, 22.62, 22.39, 2... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_968.pkl | external_data/ground_truth_data/ground_truth_data_968.pkl | external_data/context/context_968.pkl | external_data/constraint/constraint_968.pkl |
969 | stock_investment | I have historical stock price data of WOR for 33 days and I'm interested in investing in with a budget of 6772 dollars. Please give me an investment strategy for the next 55 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 55 ... | I have historical stock price data of WOR for 33 days and I'm interested in investing in with a budget of 6772 dollars. The historical stock value data of WOR for the past 33 days is: [6.73, 6.72, 6.6, 6.54, 6.8, 6.94, 6.86, 6.97, 6.88, 6.92, 6.98, 6.99, 6.9, 6.86, 6.69, 6.85, 6.64, 6.63, 6.88, 7.05, 6.9, 6.82, 6.79, 6... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_969.pkl | external_data/ground_truth_data/ground_truth_data_969.pkl | external_data/context/context_969.pkl | external_data/constraint/constraint_969.pkl |
970 | stock_investment | I have historical stock price data of NPAB for 38 days and I'm interested in investing in with a budget of 6495 dollars. Please give me an investment strategy for the next 58 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 58... | I have historical stock price data of NPAB for 38 days and I'm interested in investing in with a budget of 6495 dollars. The historical stock value data of NPAB for the past 38 days is: [10.62, 10.62, 10.62, 10.62, 10.65, 10.7, 10.7, 10.7, 10.7, 10.7, 10.7, 10.7, 10.7, 10.7, 10.7, 10.48, 10.49, 10.49, 10.49, 10.49, 10.... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_970.pkl | external_data/ground_truth_data/ground_truth_data_970.pkl | external_data/context/context_970.pkl | external_data/constraint/constraint_970.pkl |
971 | stock_investment | I have historical stock price data of MYRG for 37 days and I'm interested in investing in with a budget of 3227 dollars. Please give me an investment strategy for the next 23 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 23... | I have historical stock price data of MYRG for 37 days and I'm interested in investing in with a budget of 3227 dollars. The historical stock value data of MYRG for the past 37 days is: [35.85, 35.63, 35.83, 35.88, 35.93, 35.88, 35.9, 34.98, 35.29, 34.76, 34.69, 34.4, 33.97, 35.4, 35.98, 34.7, 35.05, 34.75, 35.06, 35.0... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_971.pkl | external_data/ground_truth_data/ground_truth_data_971.pkl | external_data/context/context_971.pkl | external_data/constraint/constraint_971.pkl |
972 | stock_investment | I have historical stock price data of SWZ for 25 days and I'm interested in investing in with a budget of 719 dollars. Please give me an investment strategy for the next 21 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 21 t... | I have historical stock price data of SWZ for 25 days and I'm interested in investing in with a budget of 719 dollars. The historical stock value data of SWZ for the past 25 days is: [6.7, 6.75, 6.77, 6.8, 6.8, 6.83, 6.77, 6.81, 6.82, 6.84, 6.88, 6.91, 7.05, 6.94, 6.87, 6.87, 6.84, 6.96, 7.02, 7.07, 7.15, 7.18, 7.18, 7... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_972.pkl | external_data/ground_truth_data/ground_truth_data_972.pkl | external_data/context/context_972.pkl | external_data/constraint/constraint_972.pkl |
973 | stock_investment | I have historical stock price data of TBIL for 28 days and I'm interested in investing in with a budget of 7569 dollars. Please give me an investment strategy for the next 31 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 31... | I have historical stock price data of TBIL for 28 days and I'm interested in investing in with a budget of 7569 dollars. The historical stock value data of TBIL for the past 28 days is: [45.79, 45.79, 45.83, 45.81, 45.82, 45.84, 45.82, 45.84, 45.84, 45.82, 45.88, 45.86, 45.88, 45.92, 45.91, 45.89, 45.89, 45.93, 45.93, ... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_973.pkl | external_data/ground_truth_data/ground_truth_data_973.pkl | external_data/context/context_973.pkl | external_data/constraint/constraint_973.pkl |
974 | stock_investment | I have historical stock price data of RGLD for 33 days and I'm interested in investing in with a budget of 2353 dollars. Please give me an investment strategy for the next 46 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 46... | I have historical stock price data of RGLD for 33 days and I'm interested in investing in with a budget of 2353 dollars. The historical stock value data of RGLD for the past 33 days is: [24.26, 23.21, 24.36, 23.22, 23.39, 23.01, 23.83, 23.9, 24.56, 24.03, 24.32, 24.97, 26.13, 26.51, 28.04, 26.7, 26.7, 26.84, 26.19, 27.... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_974.pkl | external_data/ground_truth_data/ground_truth_data_974.pkl | external_data/context/context_974.pkl | external_data/constraint/constraint_974.pkl |
975 | stock_investment | I have historical stock price data of SPXE for 34 days and I'm interested in investing in with a budget of 2253 dollars. Please give me an investment strategy for the next 30 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 30... | I have historical stock price data of SPXE for 34 days and I'm interested in investing in with a budget of 2253 dollars. The historical stock value data of SPXE for the past 34 days is: [28.44, 28.6, 28.52, 28.52, 28.66, 28.65, 28.68, 28.89, 28.91, 29.28, 29.15, 29.17, 29.02, 28.85, 28.96, 29.08, 29.64, 29.44, 29.67, 2... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_975.pkl | external_data/ground_truth_data/ground_truth_data_975.pkl | external_data/context/context_975.pkl | external_data/constraint/constraint_975.pkl |
976 | stock_investment | I have historical stock price data of WLYB for 38 days and I'm interested in investing in with a budget of 9235 dollars. Please give me an investment strategy for the next 41 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 41... | I have historical stock price data of WLYB for 38 days and I'm interested in investing in with a budget of 9235 dollars. The historical stock value data of WLYB for the past 38 days is: [46.36, 46.36, 46.14, 46.54, 45.96, 45.95, 45.71, 44.76, 44.76, 44.14, 45.12, 45.03, 46.2, 46.45, 46.2, 46.58, 46.33, 46.93, 46.28, 45... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_976.pkl | external_data/ground_truth_data/ground_truth_data_976.pkl | external_data/context/context_976.pkl | external_data/constraint/constraint_976.pkl |
977 | stock_investment | I have historical stock price data of YUMC for 30 days and I'm interested in investing in with a budget of 2215 dollars. Please give me an investment strategy for the next 39 trading days. For each trading day, generate a buy or sell signal based on the informaiton you have. Answer with a 1d numpy array for the next 39... | I have historical stock price data of YUMC for 30 days and I'm interested in investing in with a budget of 2215 dollars. The historical stock value data of YUMC for the past 30 days is: [33.05, 31.98, 31.13, 30.51, 30.38, 30.76, 31.55, 31.69, 31.38, 32.11, 31.57, 32.2, 32.56, 31.65, 32.57, 32.41, 32.54, 32.22, 32.8, 32... | Answer:
prediction = np.array([...],dtype=np.int64)
prediction.shape = (future length,) | external_data/executor_variables/executor_variables_977.pkl | external_data/ground_truth_data/ground_truth_data_977.pkl | external_data/context/context_977.pkl | external_data/constraint/constraint_977.pkl |
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