| def convert_to_returns(log_returns): | |
| """ | |
| This method exponentiates a sequence of log returns to get daily returns. | |
| :param log_returns: the log returns to exponentiated | |
| :return: the exponentiated returns | |
| """ | |
| return numpy.exp(log_returns) | |
| def convert_to_prices(param, log_returns): | |
| """ | |
| This method converts a sequence of log returns into normal returns (exponentiation) and then computes a price | |
| sequence given a starting price, param.all_s0. | |
| :param param: the model parameters object | |
| :param log_returns: the log returns to exponentiated | |
| :return: | |
| """ | |
| returns = convert_to_returns(log_returns) | |
| # A sequence of prices starting with param.all_s0 | |
| price_sequence = [param.all_s0] | |
| for i in range(1, len(returns)): | |
| # Add the price at t-1 * return at t | |
| price_sequence.append(price_sequence[i - 1] * returns[i - 1]) | |
| return numpy.array(price_sequence) |
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