A simple yet powerful way to visualize 4xdat trades.
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Updated
Jun 18, 2018 - MQL4
A simple yet powerful way to visualize 4xdat trades.
My first experiments in quantitative finance
Predicting the stock price using LSTM model.
Algoritmos en R para las volatilidades propuestas en el Capitulo 9 del libro Paul Wilmott Introduces Quantitative Finance.
Algunos de los temas que me interesan / Subjects I'm interested
TeX and other sources from my PhD thesis
My portfolio website
A series of methods contained in classes to implement volatility based approaches to underlying data. For example, volatility timing strategies.
Quantitative Finance With Python Materials From Basic
implementing CAMP, 3-4-5 factor models based on fama french
对GitHub上最靓的回测和实盘交易系统一个稍微详细的描述和分析. 持续更新中... more detailed description of the popular and awesome backtesting and livetrading system in github.
Simulate from and fit a discrete-time autoregressive log stochastic volatility model
FinStoch is a comprehensive Python library designed to model and analyze stochastic processes commonly used in financial applications. The library includes tools for simulating, visualizing, and applying stochastic models such as Geometric Brownian Motion, Merton's Jump-Diffusion, and Heston's model, etc. (In Progress)
Side-project to predict FX Markets that I was playing around on my free time. The end product was below expectations and I would not recommend using/investing.
An Excel addin for simple financial analytic UDFs written in F#. Not much here yet.
Demo of how to use R to solve financial problems: optimization and regression
Yield curve stripping using Eikon Python API.
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