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cantaro86
GitHub Repository: cantaro86/Financial-Models-Numerical-Methods
 Path: blob/master/src/FMNM/cost_utils.py
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#!/usr/bin/env python3

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# -*- coding: utf-8 -*-

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"""

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Created on Mon Jun 10 09:56:25 2019

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@author: cantaro86

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"""

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import numpy as np

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def no_opt(x, y, cost_b, cost_s):

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    cost = np.zeros((len(x), len(y)))

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    for i in range(len(y)):

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        if y[i] <= 0:

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            cost[:, i] = (1 + cost_b) * y[i] * np.exp(x)

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        else:

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            cost[:, i] = (1 - cost_s) * y[i] * np.exp(x)

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    return cost

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def writer(x, y, cost_b, cost_s, K):

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    cost = np.zeros((len(x), len(y)))

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    for i in range(len(x)):

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        for j in range(len(y)):

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            if y[j] < 0 and (1 + cost_b) * np.exp(x[i]) <= K:

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                cost[i][j] = (1 + cost_b) * y[j] * np.exp(x[i])

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            elif y[j] >= 0 and (1 + cost_b) * np.exp(x[i]) <= K:

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                cost[i][j] = (1 - cost_s) * y[j] * np.exp(x[i])

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            elif y[j] - 1 >= 0 and (1 + cost_b) * np.exp(x[i]) > K:

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                cost[i][j] = ((1 - cost_s) * (y[j] - 1) * np.exp(x[i])) + K

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            elif y[j] - 1 < 0 and (1 + cost_b) * np.exp(x[i]) > K:

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                cost[i][j] = ((1 + cost_b) * (y[j] - 1) * np.exp(x[i])) + K

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    return cost

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def buyer(x, y, cost_b, cost_s, K):

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    cost = np.zeros((len(x), len(y)))

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    for i in range(len(x)):

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        for j in range(len(y)):

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            if y[j] < 0 and (1 + cost_b) * np.exp(x[i]) <= K:

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                cost[i][j] = (1 + cost_b) * y[j] * np.exp(x[i])

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            elif y[j] >= 0 and (1 + cost_b) * np.exp(x[i]) <= K:

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                cost[i][j] = (1 - cost_s) * y[j] * np.exp(x[i])

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            elif y[j] + 1 >= 0 and (1 + cost_b) * np.exp(x[i]) > K:

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                cost[i][j] = ((1 - cost_s) * (y[j] + 1) * np.exp(x[i])) - K

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            elif y[j] + 1 < 0 and (1 + cost_b) * np.exp(x[i]) > K:

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                cost[i][j] = ((1 + cost_b) * (y[j] + 1) * np.exp(x[i])) - K

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    return cost

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