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Optimization

Fast Implied Volatilities in the NAG Library nag.com

Published November 12, 2020 under Quant Finance

Fast Implied Volatilities in the NAG Library


Mark 27.1 of the NAG Library contains a new routine, s30acf, for computing the implied volatility of a European option contract for arrays of input data.

This routine gives the user a choice of two algorithms. The first is the method of Jäckel (2015), which uses a third order Householder method to achieve close to machine accuracy for all but the most extreme inputs. This method is fast for short vectors of input data.

The second algorithm is based on that of Glau et al. (2018), with additional performance enhancements developed in a collaboration between NAG and mathematicians at Queen Mary University of London. This method uses Chebyshev interpolation and is designed for long vectors of input data, where vector instructions can be exploited. For applications in which accuracy to machine precision is not required, the algorithm can also be instructed to aim for accuracy to roughly single precision (approximately seven decimal places), giving even further performance improvements.

NAG, Optimization

End To End Python Implementation Of Finding Optimised Efficient Investment Portfolios medium.com

Published January 18, 2020 under Quant Finance

End To End Python Implementation Of Finding Optimised Efficient Investment Portfolios

One of the milestones of the investment management application was to implement an end to end solution that starts by fetching company stock prices and builds a set of efficient and optimum portfolios using optimisation routines.

Efficient Frontier, Optimization, Python

How to make the most amount of money with the least amount of risk? towardsdatascience.com

Published June 3, 2019 under Quant Finance

In this article, we show one such amazing application of LP using Python programming in the area of economic planning — maximizing the expected profit from a stock market investment portfolio while minimizing the risk associated with it.

CVXPY, Economics, MPT, Optimization

PyPortfolioOpt: Financial portfolio optimisation in Python github.com

Published September 30, 2018 under Investing

Efficient Frontier, Optimization, Stocks

Crypto portfolio optimization with Python and Tensorflow medium.com

Published August 10, 2018 under Python

Cryptocurrency, Optimization, TensorFlow

How To Make Python Run As Fast As Julia ibm.com

Published January 2, 2016 under Python

Cython, Julia, Numba, Optimization, Python

Optimization with IPython robotwhale.wordpress.com

Published May 5, 2015 under Python

iPython, Optimization, Python

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