/goldhand

Primary LanguageJupyter Notebook

Goldhand

The ultimate python package to work with stock and crypto data

pip install goldhand

TradingView

from goldhand import *

# tradingView data
tw = Tw()

# data frame of the stocks 
tw.stock

# data frame of the top 300 crypto currency
tw.crypto

# data frame of the top 3000 etf
tw.etf
# Get a plot of the stock to see the location in the sector 
tw.get_sec_plot('AMD').show()

Sector plot

# Get a plot of the stock to see the location in the industry 
tw.get_sec_plot('AMD').show()

Sector plot

Goldhand class

The GoldHand class is a part of the goldhand Python package, which provides functionality for working with stock and crypto data. This class allows users to retrieve detailed information and charts for a specific stock.

# Get a detailed chart of a stock AMD
ticker = "AMD"
t = GoldHand(ticker)
t.df.tail().T

data structure

# Get a detailed chart of a stock AMD
ticker = "TSLA"
t = GoldHand(ticker)
t.plotly_last_year(tw.get_plotly_title(ticker)).show()

## Stock Chart

'Detailed stock chart'

# Get a detailed chart of a crypto
ticker = "BTC-USD"
t = GoldHand(ticker)
t.plotly_last_year(tw.get_plotly_title(ticker)).show()

'Detailed crypto chart'

GoldHand Line indicator

ticker = "TSLA"
t = GoldHand(ticker)
t.plot_goldhand_line(tw.get_plotly_title(ticker)).show()

'Detailed crypto chart'

Backtest

The Backtest class is a powerful tool for evaluating the performance of trading strategies using historical data. It allows you to simulate trades and calculate various performance metrics to assess the profitability and risk of your strategy.

It takes a data and a function and display the trades.

ticker= 'TSLA'
data = GoldHand(ticker).df
backtest = Backtest( data, rsi_strategy, plot_title=tw.get_plotly_title(ticker),  buy_threshold=30, sell_threshold=70)
backtest.summarize_strategy()

summarize_strategy will show the trades summary, a plot with trades and the trades in DataFrame.

'Summary of trades'

'Trades plot'

'Trades'

Strategys

RSI Strategy

    """
    RSI strategy for backtesting with Backtest class
    
    Parameters:
    - data: pandas DataFrame with columns: date, open, high, low, close, volume and rsi
    - buy_threshold: int, default 30,  buy when RSI is below this value
    - sell_threshold: int, default 70, sell when RSI is above this value
    """
    backtest = Backtest( data, rsi_strategy, plot_title=tw.get_plotly_title(ticker),  buy_threshold=30, sell_threshold=70)
ticker = 'TSLA'
p = show_indicator_rsi_strategy(ticker = ticker, buy_threshold=30, sell_threshold=70, plot_title=tw.get_plotly_title(ticker), add_strategy_summary=True)

'RSI strategy plot'

GoldHand Line indicator

    """
    This function implements the GoldHandLine strategy.
    
    Parameters:
    - data (pandas DataFrame) : The DataFrame containing the data.
    - buy_at (str): The color of the line to buy at. Default is 'gold'.
    - sell_at (str): The color of the line to sell at. Default is 'grey'.
    
    """
    backtest = Backtest( data, goldhand_line_strategy,)
ticker = 'BTC-USD'
show_indicator_goldhand_line_strategy(ticker = ticker, plot_title=tw.get_plotly_title(ticker), buy_at='gold', sell_at='blue',  add_strategy_summary=True)

'GoldHand Line strategy plot'