import pandas as pd import yfinance as yf import plotly import plotly.graph_objs as go colors_list=['royalblue', 'darkorange', 'dimgrey', 'rgb(86, 53, 171)', 'rgb(44, 160, 44)', 'rgb(214, 39, 40)', '#ffd166', '#62959c', '#b5179e', 'rgb(148, 103, 189)', 'rgb(140, 86, 75)', 'rgb(227, 119, 194)', 'rgb(127, 127, 127)', 'rgb(188, 189, 34)', 'rgb(23, 190, 207)'] def merge_time_series(df_1, df_2, how='outer'): df = df_1.merge(df_2, how=how, left_index=True, right_index=True) return df def ichart(data, title='', colors=colors_list, yTitle='', xTitle='', style='normal', hovermode='x', yticksuffix='', ytickprefix='', ytickformat="", source_text='', y_position_source='-0.125', xticksuffix='', xtickprefix='', xtickformat="", dd_range=[-50, 0], y_axis_range_range=None): ''' style = normal, area, drawdowns_histogram colors = color_list or lightcolors hovermode = 'x', 'x unified', 'closest' y_position_source = -0.125 or bellow dd_range = [-50, 0] ytickformat = ".1%" ''' fig = go.Figure() fig.update_layout( paper_bgcolor='#F5F6F9', plot_bgcolor='#F5F6F9', hovermode=hovermode, title=title, title_x=0.5, yaxis = dict( ticksuffix=yticksuffix, tickprefix=ytickprefix, tickfont=dict(color='#4D5663'), gridcolor='#E1E5ED', range=y_axis_range_range, titlefont=dict(color='#4D5663'), zerolinecolor='#E1E5ED', title=yTitle, showgrid=True, tickformat=ytickformat, ), xaxis = dict( title=xTitle, tickfont=dict(color='#4D5663'), gridcolor='#E1E5ED', titlefont=dict(color='#4D5663'), zerolinecolor='#E1E5ED', showgrid=True, tickformat=xtickformat, ticksuffix=xticksuffix, tickprefix=xtickprefix, ), images= [dict( name= "watermark_1", source= "https://raw.githubusercontent.com/LuisSousaSilva/Articles_and_studies/master/FP-cor-positivo.png", xref= "paper", yref= "paper", x= -0.07500, y= 1.250, sizey= 0.15, sizex= 0.39, opacity= 1, layer= "below" )], annotations=[dict( xref="paper", yref="paper", x= 0.5, y= y_position_source, xanchor="center", yanchor="top", text=source_text, showarrow= False, font= dict( family="Arial", size=12, color="rgb(150,150,150)" ) ) ] ), # end if style=='normal': z = -1 for i in data: z = z + 1 fig.add_trace(go.Scatter( x=data.index, y=data[i], mode='lines', name=i, line=dict(width=1.3, color=colors[z]), )) if style=='area': z = -1 for i in data: z = z + 1 fig.add_trace(go.Scatter( x=data.index, y=data[i], hoverinfo='x+y', mode='lines', name=i, line=dict(width=0.7, color=colors[z]), stackgroup='one' # define stack group )) if style=='drawdowns_histogram': fig.add_trace(go.Histogram(x=data.iloc[:, 0], histnorm='probability', marker=dict(colorscale='RdBu', reversescale=False, cmin=-24, cmax=0, color=np.arange(start=dd_range[0], stop=dd_range[1]), line=dict(color='white', width=0.2)), opacity=0.75, cumulative=dict(enabled=True))) return fig def compute_growth_index(dataframe, initial_value=100, initial_cost=0, ending_cost=0): initial_cost = initial_cost / 100 ending_cost = ending_cost / 100 GR = ((1 + dataframe.pct_change()).cumprod()) * (initial_value * (1 - initial_cost)) GR.iloc[0] = initial_value * (1 - initial_cost) GR.iloc[-1] = GR.iloc[-1] * (1 * (1 - ending_cost)) return GR def download_quotes_yahoo(tickers, growth_index=False, start_date='1970-01-01', end_date='2030-06-12'): # Create empty DataFrame ETFs = pd.DataFrame() for ticker in tickers: # Download Quotes etf = yf.download(ticker,start = start_date, end = end_date, progress=False) # Get only Adj Close column as Dataframe etf = etf[['Adj Close']] # Change Column name etf.columns = [ticker] # Merge time series de etf com ETFs ETFs = merge_time_series(ETFs, etf) # Start when all ETFs are on the market ETFs = ETFs.dropna() if growth_index: ETFs = compute_growth_index(ETFs) return ETFs

# Função para data actual para cromos usarem from datetime import date today_date = date.today().strftime("%Y-%m-%d") today_date

# Download apple quotes aapl_df = yf.download('AAPL', start='1970-01-01', end='2030-06-12', progress=False, ) # Get only Adj Close column as Dataframe aapl_df = aapl_df[['Adj Close']] # Change Column name aapl_df.columns = ['AAPL'] print(aapl_df.head())

print(aapl_df.tail())

aapl_df.info()

aapl_df.plot();

tickers = ['SPY','QQQ'] # Create empty DataFrame ETFs = pd.DataFrame() for ticker in tickers: # Download Quotes etf = yf.download(ticker,start='1970-01-01', end='2030-06-12', progress=False) # Get only Adj Close column as Dataframe etf = etf[['Adj Close']] # Change Column name etf.columns = [ticker] # Merge time series de etf com ETFs ETFs = merge_time_series(ETFs, etf) # Start when all ETFs are on the market ETFs = ETFs.dropna() ETFs

ETFs_growth = compute_growth_index(ETFs['2020-01-01':]) ichart(round(ETFs_growth, 2))

etfs_yahoo_finance = download_quotes_yahoo(['SPY','QQQ'], growth_index=True, start_date='2020-01-01') ichart(etfs_yahoo_finance)