finstmt.forecast.models package¶

Submodules¶

finstmt.forecast.models.average module¶

class finstmt.forecast.models.average.AverageModel(config, item_config, base_config)[source]¶

Bases: ForecastModel

fit(series)[source]¶

mean: Optional[float] = None¶

predict()[source]¶

Return type:: Series

stderr: Optional[float] = None¶

finstmt.forecast.models.base module¶

class finstmt.forecast.models.base.ForecastModel(config, item_config, base_config)[source]¶

Bases: object

__init__(config, item_config, base_config)[source]¶

property desired_freq_t_multiplier: float¶

The multiplier of the forecast frequncy versus the historical frequency. E.g. if the forecast is annual and historical is quarterly then the multiplier is 4.

Returns:

fit(series)[source]¶

property historical_freq: str¶

last_historical_period: Optional[datetime] = None¶

orig_series: Optional[Series] = None¶

plot(ax=None, figsize=(12, 5), xlabel=None, ylabel=None, title=None)[source]¶

Return type:: Figure

predict()[source]¶

Return type:: Series

result: Optional[Series] = None¶

result_df: Optional[DataFrame] = None¶

finstmt.forecast.models.base.compare_freq_strs(freq1, freq2, ref_date='1/1/2000')[source]¶

Return type:: float

finstmt.forecast.models.cagr module¶

class finstmt.forecast.models.cagr.CAGRModel(config, item_config, base_config)[source]¶

Bases: ForecastModel

cagr: Optional[float] = None¶

fit(series)[source]¶

last_value: Optional[float] = None¶

predict()[source]¶

Return type:: Series

stderr: Optional[float] = None¶

finstmt.forecast.models.chooser module¶

finstmt.forecast.models.chooser.get_model(config, item_config, base_config)[source]¶

Return type:: ForecastModel

finstmt.forecast.models.manual module¶

class finstmt.forecast.models.manual.ManualForecastModel(config, item_config, base_config)[source]¶

Bases: ForecastModel

__init__(config, item_config, base_config)[source]¶

fit(series)[source]¶

predict()[source]¶

Return type:: Series

recent: Optional[float] = None¶

finstmt.forecast.models.prophet module¶

class finstmt.forecast.models.prophet.FBProphetModel(config, item_config, base_config)[source]¶

Bases: ForecastModel

__init__(config, item_config, base_config)[source]¶

fit(series)[source]¶

plot(ax=None, figsize=(12, 5), xlabel=None, ylabel=None, title=None)[source]¶

Return type:: Figure

predict()[source]¶

Return type:: Series

finstmt.forecast.models.recent module¶

class finstmt.forecast.models.recent.RecentValueModel(config, item_config, base_config)[source]¶

Bases: ForecastModel

fit(series)[source]¶

predict()[source]¶

Return type:: Series

recent: Optional[float] = None¶

finstmt.forecast.models.trend module¶

class finstmt.forecast.models.trend.LinearTrendModel(config, item_config, base_config)[source]¶

Bases: ForecastModel

fit(series)[source]¶

model: Optional[OLS] = None¶

model_result: Optional[RegressionResults] = None¶

predict()[source]¶

Return type:: Series