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Python for Finance

You're reading from   Python for Finance Apply powerful finance models and quantitative analysis with Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787125698
Length 586 pages
Edition 2nd Edition
Languages
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Author (1):
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Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Toc

Table of Contents (17) Chapters Close

Preface 1. Python Basics FREE CHAPTER 2. Introduction to Python Modules 3. Time Value of Money 4. Sources of Data 5. Bond and Stock Valuation 6. Capital Asset Pricing Model 7. Multifactor Models and Performance Measures 8. Time-Series Analysis 9. Portfolio Theory 10. Options and Futures 11. Value at Risk 12. Monte Carlo Simulation 13. Credit Risk Analysis 14. Exotic Options 15. Volatility, Implied Volatility, ARCH, and GARCH Index

Python SimPy module

SimPy is a process-based discrete-event simulation framework based on standard Python. Its event dispatcher is based on Python's generators and can also be used for asynchronous networking or to implement multi-agent systems (with both simulated and real communication). Processes in SimPy are simple Python generator functions and are used to model active components such as customers, vehicles, or agents. SimPy also provides various types of shared resources to model limited capacity congestion points (such as servers, checkout counters, and tunnels). From version 3.1, it will also provide monitoring capabilities to aid in gathering statistics about resources and processes:

import simpy
def clock(env, name, tick):
     while True:
         print(name, env.now)
         yield env.timeout(tick)
#
env = simpy.Environment()
env.process(clock(env, 'fast', 0.5))
env.process(clock(env, 'slow', 1))
env.run(until=2)
('fast', 0)
('slow&apos...
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