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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
id: string
symbol: string
asof: timestamp[s]
horizon: int64
question: string
resolves_on: timestamp[s]
context: struct<close_asof: double, ret_21d: double, ret_252d: double>
child 0, close_asof: double
child 1, ret_21d: double
child 2, ret_252d: double
answer: bool
to
{'id': Value('string'), 'answer': Value('bool'), 'resolves_on': Value('timestamp[s]')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
id: string
symbol: string
asof: timestamp[s]
horizon: int64
question: string
resolves_on: timestamp[s]
context: struct<close_asof: double, ret_21d: double, ret_252d: double>
child 0, close_asof: double
child 1, ret_21d: double
child 2, ret_252d: double
answer: bool
to
{'id': Value('string'), 'answer': Value('bool'), 'resolves_on': Value('timestamp[s]')}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1879, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
id string | answer bool | resolves_on timestamp[s] |
|---|---|---|
AAPL-2025-04-11-21d | true | 2025-05-02T00:00:00 |
AAPL-2025-04-11-63d | false | 2025-06-13T00:00:00 |
AMZN-2025-04-11-21d | true | 2025-05-02T00:00:00 |
AMZN-2025-04-11-63d | true | 2025-06-13T00:00:00 |
BTC-USD-2025-04-11-21d | true | 2025-05-02T00:00:00 |
BTC-USD-2025-04-11-63d | true | 2025-06-13T00:00:00 |
EEM-2025-04-11-21d | true | 2025-05-02T00:00:00 |
EEM-2025-04-11-63d | true | 2025-06-13T00:00:00 |
EFA-2025-04-11-21d | true | 2025-05-02T00:00:00 |
EFA-2025-04-11-63d | true | 2025-06-13T00:00:00 |
ETH-USD-2025-04-11-21d | true | 2025-05-02T00:00:00 |
ETH-USD-2025-04-11-63d | true | 2025-06-13T00:00:00 |
GLD-2025-04-11-21d | true | 2025-05-02T00:00:00 |
GLD-2025-04-11-63d | true | 2025-06-13T00:00:00 |
GOOGL-2025-04-11-21d | true | 2025-05-02T00:00:00 |
GOOGL-2025-04-11-63d | true | 2025-06-13T00:00:00 |
HYG-2025-04-11-21d | true | 2025-05-02T00:00:00 |
HYG-2025-04-11-63d | true | 2025-06-13T00:00:00 |
IEF-2025-04-11-21d | true | 2025-05-02T00:00:00 |
IEF-2025-04-11-63d | true | 2025-06-13T00:00:00 |
IWM-2025-04-11-21d | true | 2025-05-02T00:00:00 |
IWM-2025-04-11-63d | true | 2025-06-13T00:00:00 |
JPM-2025-04-11-21d | true | 2025-05-02T00:00:00 |
JPM-2025-04-11-63d | true | 2025-06-13T00:00:00 |
META-2025-04-11-21d | true | 2025-05-02T00:00:00 |
META-2025-04-11-63d | true | 2025-06-13T00:00:00 |
MSFT-2025-04-11-21d | true | 2025-05-02T00:00:00 |
MSFT-2025-04-11-63d | true | 2025-06-13T00:00:00 |
NVDA-2025-04-11-21d | true | 2025-05-02T00:00:00 |
NVDA-2025-04-11-63d | true | 2025-06-13T00:00:00 |
QQQ-2025-04-11-21d | true | 2025-05-02T00:00:00 |
QQQ-2025-04-11-63d | true | 2025-06-13T00:00:00 |
SLV-2025-04-11-21d | false | 2025-05-02T00:00:00 |
SLV-2025-04-11-63d | true | 2025-06-13T00:00:00 |
SPY-2025-04-11-21d | true | 2025-05-02T00:00:00 |
SPY-2025-04-11-63d | true | 2025-06-13T00:00:00 |
TLT-2025-04-11-21d | true | 2025-05-02T00:00:00 |
TLT-2025-04-11-63d | false | 2025-06-13T00:00:00 |
TSLA-2025-04-11-21d | true | 2025-05-02T00:00:00 |
TSLA-2025-04-11-63d | true | 2025-06-13T00:00:00 |
USO-2025-04-11-21d | false | 2025-05-02T00:00:00 |
USO-2025-04-11-63d | true | 2025-06-13T00:00:00 |
UUP-2025-04-11-21d | true | 2025-05-02T00:00:00 |
UUP-2025-04-11-63d | false | 2025-06-13T00:00:00 |
VNQ-2025-04-11-21d | true | 2025-05-02T00:00:00 |
VNQ-2025-04-11-63d | true | 2025-06-13T00:00:00 |
XLB-2025-04-11-21d | true | 2025-05-02T00:00:00 |
XLB-2025-04-11-63d | true | 2025-06-13T00:00:00 |
XLE-2025-04-11-21d | true | 2025-05-02T00:00:00 |
XLE-2025-04-11-63d | true | 2025-06-13T00:00:00 |
XLF-2025-04-11-21d | true | 2025-05-02T00:00:00 |
XLF-2025-04-11-63d | true | 2025-06-13T00:00:00 |
XLI-2025-04-11-21d | true | 2025-05-02T00:00:00 |
XLI-2025-04-11-63d | true | 2025-06-13T00:00:00 |
XLK-2025-04-11-21d | true | 2025-05-02T00:00:00 |
XLK-2025-04-11-63d | true | 2025-06-13T00:00:00 |
XLP-2025-04-11-21d | true | 2025-05-02T00:00:00 |
XLP-2025-04-11-63d | true | 2025-06-13T00:00:00 |
XLU-2025-04-11-21d | true | 2025-05-02T00:00:00 |
XLU-2025-04-11-63d | true | 2025-06-13T00:00:00 |
XLV-2025-04-11-21d | true | 2025-05-02T00:00:00 |
XLV-2025-04-11-63d | false | 2025-06-13T00:00:00 |
XLY-2025-04-11-21d | true | 2025-05-02T00:00:00 |
XLY-2025-04-11-63d | true | 2025-06-13T00:00:00 |
XOM-2025-04-11-21d | true | 2025-05-02T00:00:00 |
XOM-2025-04-11-63d | true | 2025-06-13T00:00:00 |
AAPL-2025-05-01-21d | false | 2025-05-22T00:00:00 |
AAPL-2025-05-01-63d | true | 2025-07-03T00:00:00 |
AMZN-2025-05-01-21d | true | 2025-05-22T00:00:00 |
AMZN-2025-05-01-63d | true | 2025-07-03T00:00:00 |
BTC-USD-2025-05-01-21d | true | 2025-05-22T00:00:00 |
BTC-USD-2025-05-01-63d | true | 2025-07-03T00:00:00 |
EEM-2025-05-01-21d | true | 2025-05-22T00:00:00 |
EEM-2025-05-01-63d | true | 2025-07-03T00:00:00 |
EFA-2025-05-01-21d | true | 2025-05-22T00:00:00 |
EFA-2025-05-01-63d | true | 2025-07-03T00:00:00 |
ETH-USD-2025-05-01-21d | true | 2025-05-22T00:00:00 |
ETH-USD-2025-05-01-63d | true | 2025-07-03T00:00:00 |
GLD-2025-05-01-21d | true | 2025-05-22T00:00:00 |
GLD-2025-05-01-63d | true | 2025-07-03T00:00:00 |
GOOGL-2025-05-01-21d | true | 2025-05-22T00:00:00 |
GOOGL-2025-05-01-63d | true | 2025-07-03T00:00:00 |
HYG-2025-05-01-21d | true | 2025-05-22T00:00:00 |
HYG-2025-05-01-63d | true | 2025-07-03T00:00:00 |
IEF-2025-05-01-21d | false | 2025-05-22T00:00:00 |
IEF-2025-05-01-63d | false | 2025-07-03T00:00:00 |
IWM-2025-05-01-21d | true | 2025-05-22T00:00:00 |
IWM-2025-05-01-63d | true | 2025-07-03T00:00:00 |
JPM-2025-05-01-21d | true | 2025-05-22T00:00:00 |
JPM-2025-05-01-63d | true | 2025-07-03T00:00:00 |
META-2025-05-01-21d | true | 2025-05-22T00:00:00 |
META-2025-05-01-63d | true | 2025-07-03T00:00:00 |
MSFT-2025-05-01-21d | true | 2025-05-22T00:00:00 |
MSFT-2025-05-01-63d | true | 2025-07-03T00:00:00 |
NVDA-2025-05-01-21d | true | 2025-05-22T00:00:00 |
NVDA-2025-05-01-63d | true | 2025-07-03T00:00:00 |
QQQ-2025-05-01-21d | true | 2025-05-22T00:00:00 |
QQQ-2025-05-01-63d | true | 2025-07-03T00:00:00 |
SLV-2025-05-01-21d | true | 2025-05-22T00:00:00 |
SLV-2025-05-01-63d | true | 2025-07-03T00:00:00 |
End of preview.
FinzData Forecast Bench
Release 2026-10-13.
Each question is frozen as of its date and its context uses only data that was public then, so there is no look-ahead: a model cannot have seen the answer in training if it was trained before the resolution date. Answers are released after they resolve. Score with the Brier score and accuracy. Data from FinzData (https://finzdata.com).
820 questions over 33 US ETFs, stocks and crypto; 690 resolved. Files: data/questions.jsonl (no answers), data/answers.jsonl (resolved only). New questions are added on the first of each month and answers as they resolve. More data: https://finzdata.com
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