tpq.io

training.tpq.io

Python for Finance Trainings by The Python Quants GmbH

http://training.tpq.io/pythonforfinance.html

Earn Your University Certificate. With professional Python for Finance training classes by The Python Quants. Financial Data Science, Algorithmic Trading, Computational Finance and more. READ THE OVERVIEW PDF. This is our master class. In Python for Finance comprising all the other training classes and leading to a university certificate. Under certain conditions, the certificate represents the equivalent of 5 ECTS. The price for this program is. 3,495 EUR (net of VAT). The program can be started at.

training.tpq.io

Python for Finance Trainings by The Python Quants GmbH

http://training.tpq.io/algotrading.html

Become an algorithmic star trader. With professional Python for Finance training classes by The Python Quants. Financial Data Science, Algorithmic Trading, Computational Finance and more. READ THE OVERVIEW PDF. Python for Algorithmic Trading. The price for this training is. Book our special flagship deal. Receive a discount of 10% (15%) when booking two (three) major trainings. The next training starts on. Python, NumPy and pandas. Mdash; basics of Python programming and tools. FX, CFD and Stock Trading.

training.tpq.io

Python for Finance Trainings by The Python Quants GmbH

http://training.tpq.io/protopics.html

Become an Excel expert and pro developer. With professional Python for Finance trainings by The Python Quants. Financial Data Science, Algorithmic Trading, Computational Finance and more. READ THE OVERVIEW PDF. Learn about Python's read/write packages for Excel, how to use xlwings. How to write your own User Defined Functions with Python. The price for this training is. 349 EUR (net of VAT). Receive a discount of 10% (15%) when booking two (three) trainings. This training is available in the form of.

dx-analytics.com

Mean-Variance Portfolio Class — DX Analytics (Derivatives Analytics with Python)

http://dx-analytics.com/11_dx_mean_variance_portfolio.html

Without doubt, the Markowitz (1952) mean-variance portfolio theory. Is a cornerstone of modern financial theory. This section illustrates the use of the. Class to implement this approach. Market Environment and Portfolio Object. We start by instantiating a. Object which in particular contains a list of ticker symbols. In which we are interested in. Using pandas under the hood, the class retrieves historial stock price data. CPU times: user 236 ms, sys: 3 ms, total: 239 ms Wall time: 1.2 s. Portfolio am t...

dx-analytics.com

Framework Classes and Functions — DX Analytics (Derivatives Analytics with Python)

http://dx-analytics.com/01_dx_frame.html

Framework Classes and Functions. This section explains the usage of some basic framework classes and functions of DX Analytics. Mainly some helper functions, the discounting classes and the market environment class used to store market data and other parameters/data needed to model, value and risk manage derivative instruments. There are two helper functions used regulary:. Get year deltas: get a list of year deltas (decimal fractions) relative to first value in time list. Suppose we have a. Class repres...

dx-analytics.com

Multi-Risk Derivatives Portfolios — DX Analytics (Derivatives Analytics with Python)

http://dx-analytics.com/05_dx_portfolio_multi_risk.html

The step from multi-risk derivatives instruments to multi-risk derivatives instrument portfolios is not a too large one. This part of the tutorial shows how to model an economy with three risk factors. This sub-section models the single risk factors. We start with definition of the risk-neutral discounting object. Probability for jump p.a. Expected jump size [%]. Finally, the unifying valuation assumption for the valuation environment. These are added to the single. Objects of the risk factors. Time stat...

datapark.io

Data Science Know-how From The Experts (datapark.io)

http://www.datapark.io/datascience.html

On this page you find data science know-how in the form of talks and presentations, event announcements and reports, articles, language and library features, and more. In general, the know-how illustrated in the single pieces can be readily tested and applied on datapark.io. You can register for free under datapark.io. Python for Finance Certification. 4-day intensive training in New York. For further details and for registration. Quant Conference in London on 30. October 2015. For Python Quants in London.