PyTCA: Python Library for Transaction Cost Analysis

PyTCA is a Python package for transaction cost analysis in financial markets, supporting both stock and forex data at the tick level.

Features

Load and process tick-level data for stocks and forex
Perform various analyses including slippage, market impact, and timing cost
Calculate key metrics such as VWAP and implementation shortfall
Generate visualizations and reports
RESTful API for integration with other systems
Support for Excel and KDB data sources

Installation

pip install pytca

Quick Start

import pytca

# Load tick data
tick_data = pytca.load_tick_data('path/to/tick_data.csv', data_type='stock')

# Analyze tick data
analysis_results = pytca.analyze_tick_data(tick_data)
print("Tick Data Analysis Results:", analysis_results)

# Visualize tick data
fig = pytca.plot_tick_data(tick_data, plot_type='summary')
fig.write_html('tick_data_summary.html')

More Examples

Loading Data from Different Sources

import pytca

# Load data from CSV
csv_data = pytca.load_tick_data('path/to/tick_data.csv', data_type='stock')

# Load data from Excel
excel_data = pytca.read_excel('path/to/tick_data.xlsx', sheet_name='Tick Data')

# Load data from KDB
kdb_handler = pytca.KDBHandler(host='localhost', port=5000)
kdb_data = kdb_handler.load_tick_data('tickdata', '2023.07.15T09:30:00.000', '2023.07.15T16:00:00.000')

Performing Analysis

import pytca

# Load data
stock_data = pytca.load_tick_data('path/to/stock_data.csv', data_type='stock')
forex_data = pytca.load_tick_data('path/to/forex_data.csv', data_type='forex')

# Analyze stock data
stock_analysis = pytca.analyze_stock_trade(stock_data, benchmark_data)
print("Stock Analysis Results:", stock_analysis)

# Analyze forex data
forex_analysis = pytca.analyze_forex_trade(forex_data, benchmark_data)
print("Forex Analysis Results:", forex_analysis)

# Calculate slippage
slippage = pytca.calculate_slippage(executed_price=100.05, benchmark_price=100.00)
print("Slippage:", slippage)

# Calculate VWAP
vwap = pytca.calculate_vwap(prices=[100.00, 100.05, 100.10], volumes=[1000, 2000, 1500])
print("VWAP:", vwap)

Generating Visualizations

import pytca

# Load data
tick_data = pytca.load_tick_data('path/to/tick_data.csv', data_type='stock')

# Create basic plot
basic_fig = pytca.plot_tick_data(tick_data, plot_type='basic')
basic_fig.savefig('basic_plot.png')

# Create candlestick chart
candlestick_fig = pytca.plot_tick_data(tick_data, plot_type='candlestick', interval='5min')
candlestick_fig.write_html('candlestick.html')

# Create order book depth chart
depth_fig = pytca.plot_tick_data(tick_data, plot_type='depth')
depth_fig.write_html('depth_chart.html')

# Create trade flow chart
trade_flow_fig = pytca.plot_tick_data(tick_data, plot_type='trade_flow', window='5min')
trade_flow_fig.write_html('trade_flow.html')

# Create summary dashboard
summary_fig = pytca.plot_tick_data(tick_data, plot_type='summary')
summary_fig.write_html('summary_dashboard.html')

Using the RESTful API

import pytca

# Start the API server
pytca.run_api(host='localhost', port=5000)

# Now you can make HTTP requests to the API endpoints, for example:
# POST http://localhost:5000/analyze_tick_data
# with JSON body: {"table_name": "tickdata", "start_time": "2023.07.15T09:30:00.000", "end_time": "2023.07.15T16:00:00.000", "symbols": ["AAPL", "GOOGL"]}

Documentation

For full documentation, please visit Read the Docs.

Contributing

We welcome contributions! Please see our Contributing Guide for more details.

License

This project is licensed under the BSD-2-Clause License - see the LICENSE file for details.

jialuechen / pytca