awt_quant.forecast.stochastic.pde_forecast¶

Module Contents¶

class awt_quant.forecast.stochastic.pde_forecast.SPDEMCSimulator(ticker, equation, start_date='2022-01-01', end_date='2022-03-01', dt=1, num_paths=1000, plot_vol=True)[source]¶

Stochastic Process & GARCH-based Forecasting Simulator.

ticker[source]¶

Stock ticker symbol.

Type:: str

equation[source]¶

Stochastic model (CIR, GBM, Heston, OU).

Type:: str

start_date[source]¶

Start date for fetching historical data.

Type:: str

end_date[source]¶

End date for fetching historical data.

Type:: str

dt[source]¶

Time increment (default: 1 for daily, 1/252 for annual).

Type:: float

num_paths[source]¶

Number of Monte Carlo simulation paths.

Type:: int

ticker[source]¶

start_date[source]¶

end_date[source]¶

dt = 1[source]¶

num_paths = 1000[source]¶

equation[source]¶

plot_vol = True[source]¶

forecasted_vol = None[source]¶

GARCH_fit = None[source]¶

device = 'cpu'[source]¶

download_data(train_test_split)[source]¶: Downloads historical stock data and splits into train-test sets.

simulate()[source]¶: Runs stochastic simulation based on the selected model.

backwards(strike_price, option)[source]¶: Calculates backward pricing probability for options.

plot_simulation()[source]¶: Plots the quantile paths for simulated stock price.

error_estimation(num_sim=100)[source]¶: Estimates the error of stock price forecasts.

backtest()[source]¶: Performs backtesting on the simulated data.

awt_quant.forecast.stochastic.pde_forecast.sim[source]¶