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casadi / casadi

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CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.

python c-plus-plus library modular optimization matlab mathematics nonlinear octave numerical-calculations scientific-computing derivatives code-generation parameter-estimation academic-project optimal-control symbolic-manipulation algorithmic-differentation nonlinear-programming
  • Updated Jan 10, 2021
  • C++
synthetix

Synthetixio / synthetix

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domokane / FinancePy

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FinDate Optimisation

domokane
domokane commented Dec 29, 2020

FinDate has been implemented with only some Python datetime dependency in a few functions.

However the issue of processing speed is becoming more important.

I would be interested to know which of the following approaches is superior in speed terms.

  1. Make FinDate (which now includes date and time) a thin layer over datetime i.e. all functions should call datetime functions rather than d
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s-brez / trading-server

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Multi-asset, multi-strategy, event-driven trade execution and management platform for automated buy-side trading of common markets, using MongoDB for storage and Telegram for user notifications/trade consent.

mongodb telegram trading trading-bot algo-trading forex cryptocurrency derivatives trading-platform technical-analysis futures algorithmic-trading backtest quantitative-trading bitmex backtesting binance portfolio-management trading-execution ftx
  • Updated Oct 23, 2020
  • Python

spacious-team / investbook

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notebooks

differential-machine-learning / notebooks

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Implement, demonstrate, reproduce and extend the results of the article 'Differential Machine Learning' (Huge & Savine, 2020), and cover implementation details left out of the working paper

machine-learning deep-learning tensorflow automatic-differentiation pricing derivatives quantitative-finance notebooks regression-models backpropagation risk-management computational-finance aad risk-magazine
  • Updated Jan 4, 2021
  • Jupyter Notebook

jkirkby3 / PROJ_Option_Pricing_Matlab

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Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Starting, Step, Fader

options monte-carlo derivatives option-pricing quantitative-finance american-options jump-diffusion stochastic-volatility-models black-scholes fourier-transform sabr european-options levy-processes heston-model asian-option bermudan-option swing-option lookback-option variance-swap barrier-option
  • Updated Jan 1, 2021
  • MATLAB

navjindervirdee / neural-networks

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Implemented Convolutional Neural Network, LSTM Neural Network, and Neural Network From Scratch in Python Language.

python deep-learning numpy jupyter-notebook cnn neural-networks convolutional-layers rnn derivatives scratch matplotlib convolutional-neural-networks handwritten-digit-recognition lstm-neural-networks iris-dataset lstm-cells lstm-networks backward-propagation forward-propagation backward-propagation-through-time
  • Updated Sep 19, 2018
  • Jupyter Notebook

VarunS2002 / Python-NSE-Option-Chain-Analyzer

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For doing technical analysis for option traders, the Option Chain is the most important tool for deciding entry and exit strategies. The National Stock Exchange (NSE) has a website which displays the option chain for traders in near real-time. This program scrapes this data from the NSE site and then generates useful analysis of the Option Chain for the specified Security or Index from the NSE website. It also continuously refreshes the Option Chain and visually displays the trend in various indicators and useful for Technical Analysis. Calculations are based on Mr. Sameer Dharaskar's Course.

python app options analysis script derivatives equity program nse nifty web-scrapping strike-price sameer option-chain dharaskar
  • Updated Jan 8, 2021
  • Python

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