Overall Statistics |
Total Trades 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio 0 Probabilistic Sharpe Ratio 0% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio -1.517 Tracking Error 0.142 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 |
class EmptyAlgoToShareNotebooks(QCAlgorithm): def Initialize(self): self.SetStartDate(2020,12,1) # Set Start Date self.SetCash(1) # Set Strategy Cash def OnData(self, data): pass
import matplotlib.dates as mdates import matplotlib.pyplot as plt import pandas as pd import numpy as np import seaborn as sns def plot_df(df, color='blue', size=(16, 7), legend='Close Price', y_label='Price in USD', title=None, kind='line'): plt.style.use('dark_background') plt.rcParams["figure.figsize"] = size ax = df.plot(kind=kind) plt.title(title) plt.ylabel(y_label) x = 0.1 y = 0.05 plt.text(x, y, 'www.ostirion.net', fontsize=15, transform=ax.transAxes) plt.legend(ncol=int(len(df.columns) / 2)) date_form = mdates.DateFormatter("%m-%Y") plt.xticks(rotation=45); plt.show() def plot_corr_hm(df, title='Title', size=(16, 7), annot = True): corr = df.corr() plt.style.use('dark_background') plt.rcParams["figure.figsize"] = size mask = np.triu(np.ones_like(corr, dtype=bool)) cmap = sns.color_palette("RdBu") ax = sns.heatmap(corr, mask=mask, vmax=.3, center=0, cmap=cmap, annot=annot, square=True, linewidths=0, cbar_kws={"shrink": .5}, fmt='g') ax.set_title(title) plt.setp(ax.get_yticklabels(), rotation=0); plt.setp(ax.get_xticklabels(), rotation=90); plt.show() def plot_cm(df, title='Title', size=(16,7)): plt.style.use('dark_background') plt.rcParams["figure.figsize"] = size cmap = sns.color_palette("Blues") ax = sns.heatmap(df, cmap=cmap, annot=True, linewidths=0, cbar_kws={"shrink": .5}, fmt='g') ax.set_title(title) plt.xlabel('Predicted') plt.ylabel('True') plt.setp(ax.get_xticklabels(), rotation=0); def plot_hm(df, title='Title', size=(16, 7), annot = True, x_rot=90): plt.style.use('dark_background') plt.rcParams["figure.figsize"] = size cmap = sns.color_palette("RdBu") ax = sns.heatmap(df, vmax=.3, center=0, cmap=cmap, annot=annot, square=True, linewidths=0, cbar_kws={"shrink": .5}, fmt='g') ax.set_title(title) plt.setp(ax.get_yticklabels(), rotation=0); plt.setp(ax.get_xticklabels(), rotation=x_rot); plt.show()