question_id
int64 0
903
| question_type
stringclasses 29
values | prompt
stringlengths 907
1.8k
| data_str
stringlengths 401
2.09M
| executor_variables
stringlengths 57
59
| ground_truth_data
stringlengths 55
57
| context
stringlengths 35
37
| constraint
stringlengths 41
43
|
|---|---|---|---|---|---|---|---|
900 | 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 trading days where 1 indicates buy and -1 indicates sell and 0 indicates hold. The historical stock price data is stored in variable VAL and the future stock price data is stored in variable future_VAL.
Closing price stored in column "Close".
The trading signal for calendar day t must be computed only from data available up to (and including) the close of day t-1. Do NOT use the close of day t or any later prices when deciding day t’s position.
If you use moving averages or any rolling statistics, shift them by one day (e.g., rolling(...).mean().shift(1)) or index them explicitly with [:i] so that today’s price is excluded from the calculation.
Treat future_VAL as arriving one value per trading day: append the newest price to your series only AFTER you have generated the signal for that day.
Requirements:
- Store your output in the variable called `predictions`, make sure to consider predictions to have the right shape according to the question's output requirements if it's supposed to be an array, there is no need to consider shapes if you only need to return a numerical value.
- Do not customly define/generate/overwrite the available variables, assume that the variables are already defined and available.
data note: VAL values are usually stored in either a dataframe or numpy values.
You should enclose your python code in <execute> </execute> tag and do not overwrite available variables that store the data. Do not use any other tags like ```python```. | 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, 27.1, 26.93, 27.72, 27.91, 27.75, 27.68, 29.03, 28.86, 28.99, 29.34, 29.53, 30.24, 30.25, 29.44]. 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 trading days where 1 indicates buy and -1 indicates sell and 0 indicates hold. The historical stock price data is stored in variable VAL and the future stock price data is stored in variable future_VAL. | 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 | 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 trading days where 1 indicates buy and -1 indicates sell and 0 indicates hold. The historical stock price data is stored in variable VAL and the future stock price data is stored in variable future_VAL.
Closing price stored in column "Close".
The trading signal for calendar day t must be computed only from data available up to (and including) the close of day t-1. Do NOT use the close of day t or any later prices when deciding day t’s position.
If you use moving averages or any rolling statistics, shift them by one day (e.g., rolling(...).mean().shift(1)) or index them explicitly with [:i] so that today’s price is excluded from the calculation.
Treat future_VAL as arriving one value per trading day: append the newest price to your series only AFTER you have generated the signal for that day.
Requirements:
- Store your output in the variable called `predictions`, make sure to consider predictions to have the right shape according to the question's output requirements if it's supposed to be an array, there is no need to consider shapes if you only need to return a numerical value.
- Do not customly define/generate/overwrite the available variables, assume that the variables are already defined and available.
data note: VAL values are usually stored in either a dataframe or numpy values.
You should enclose your python code in <execute> </execute> tag and do not overwrite available variables that store the data. Do not use any other tags like ```python```. | 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, 29.61, 29.49, 29.55, 29.63, 29.72, 29.86, 29.87, 29.83, 29.64, 29.58, 29.69, 29.61, 29.68, 29.77, 29.8]. 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 trading days where 1 indicates buy and -1 indicates sell and 0 indicates hold. The historical stock price data is stored in variable VAL and the future stock price data is stored in variable future_VAL. | 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 | 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 trading days where 1 indicates buy and -1 indicates sell and 0 indicates hold. The historical stock price data is stored in variable VAL and the future stock price data is stored in variable future_VAL.
Closing price stored in column "Close".
The trading signal for calendar day t must be computed only from data available up to (and including) the close of day t-1. Do NOT use the close of day t or any later prices when deciding day t’s position.
If you use moving averages or any rolling statistics, shift them by one day (e.g., rolling(...).mean().shift(1)) or index them explicitly with [:i] so that today’s price is excluded from the calculation.
Treat future_VAL as arriving one value per trading day: append the newest price to your series only AFTER you have generated the signal for that day.
Requirements:
- Store your output in the variable called `predictions`, make sure to consider predictions to have the right shape according to the question's output requirements if it's supposed to be an array, there is no need to consider shapes if you only need to return a numerical value.
- Do not customly define/generate/overwrite the available variables, assume that the variables are already defined and available.
data note: VAL values are usually stored in either a dataframe or numpy values.
You should enclose your python code in <execute> </execute> tag and do not overwrite available variables that store the data. Do not use any other tags like ```python```. | 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, 45.39, 45.37, 44.87, 45.32, 45.57, 45.11, 43.75, 44.59, 44.99, 44.8, 44.79, 44.53, 46.0, 46.0, 45.53, 43.3, 43.13, 42.06, 41.32]. 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 trading days where 1 indicates buy and -1 indicates sell and 0 indicates hold. The historical stock price data is stored in variable VAL and the future stock price data is stored in variable future_VAL. | 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 | 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 trading days where 1 indicates buy and -1 indicates sell and 0 indicates hold. The historical stock price data is stored in variable VAL and the future stock price data is stored in variable future_VAL.
Closing price stored in column "Close".
The trading signal for calendar day t must be computed only from data available up to (and including) the close of day t-1. Do NOT use the close of day t or any later prices when deciding day t’s position.
If you use moving averages or any rolling statistics, shift them by one day (e.g., rolling(...).mean().shift(1)) or index them explicitly with [:i] so that today’s price is excluded from the calculation.
Treat future_VAL as arriving one value per trading day: append the newest price to your series only AFTER you have generated the signal for that day.
Requirements:
- Store your output in the variable called `predictions`, make sure to consider predictions to have the right shape according to the question's output requirements if it's supposed to be an array, there is no need to consider shapes if you only need to return a numerical value.
- Do not customly define/generate/overwrite the available variables, assume that the variables are already defined and available.
data note: VAL values are usually stored in either a dataframe or numpy values.
You should enclose your python code in <execute> </execute> tag and do not overwrite available variables that store the data. Do not use any other tags like ```python```. | 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, 32.87, 33.76, 33.83, 33.05, 32.36, 33.53, 33.17, 33.72, 34.16, 34.06, 35.56]. 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 trading days where 1 indicates buy and -1 indicates sell and 0 indicates hold. The historical stock price data is stored in variable VAL and the future stock price data is stored in variable future_VAL. | 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 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.