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Wilson Freitas wilsonfreitas

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@wilsonfreitas
wilsonfreitas / README.md
Created January 14, 2024 08:43
Download de curvas da B3 utilizando os códigos de curvas

Download de curvas da B3

library(rb3)

fname <- download_marketdata("TaxasReferenciais",
                             refdate = as.Date("2024-01-12"),
                             curve_name = "TR")
df &lt;- read_marketdata(fname, "TaxasReferenciais", TRUE)
@wilsonfreitas
wilsonfreitas / B3FilesURLDownloader.py
Created October 2, 2022 09:22
class B3FilesURLDownloader(SingleDownloader):
calendar = bizdays.Calendar.load('ANBIMA.cal')
def download(self, refdate=None):
filename = self.attrs.get('filename')
refdate = refdate or self.get_refdate()
logging.info('refdate %s', refdate)
date = refdate.strftime('%Y-%m-%d')
url = f'https://arquivos.b3.com.br/api/download/requestname?fileName={filename}&date={date}&recaptchaToken='
res = requests.get(url)
msg = 'status_code = {} url = {}'.format(res.status_code, url)
@wilsonfreitas
wilsonfreitas / lru_cache.py
Created September 20, 2022 13:25 — forked from hughdbrown/lru_cache.py
Minimal lru_cache implementation for python 2.7
from functools import wraps
try:
from functools import lru_cache
except ImportError:
def lru_cache(user_function):
cache = {}
@wraps(user_function)
def wrapper(*args):
key = tuple(args)
@wilsonfreitas
wilsonfreitas / ft_gif.R
Created August 7, 2022 21:47 — forked from Athospd/ft_gif.R
Como gerar GIF com animação com R
f <- function(x) cos(x*20)
expi <- function(x) cos(x) + sin(x)*1i
par(mfrow = c(1,2))
L <- 40
medias_Re <- c()
fs <- c()
as <- seq(0.01, 1, l = 140)
animation::saveGIF({
for(a in as) {
@wilsonfreitas
wilsonfreitas / rb3-indexes-donuts.R
Created May 30, 2022 10:47
Indexes Composition in a Donuts Plot
library(rb3)
library(tidyverse)
top_weight <- function(.data, n = 10) {
top_10 <- .data |>
arrange(desc(weight)) |>
slice_head(n = n) |>
select(symbol, weight)
total_weight <- sum(top_10$weight)
others <- tibble(
@wilsonfreitas
wilsonfreitas / forwardrate-example.md
Created May 29, 2022 10:04
ForwardRate example - fixedincome package

forwardrate method, for a SpotRateCurve and with arguments t1 and t2, computes the forward rate between two future terms that exist in the term structure.

library(rb3)
library(fixedincome)

df_yc <- yc_get("2022-05-20")

crv &lt;- spotratecurve(
@wilsonfreitas
wilsonfreitas / working days per month not correctly reported by bizdays
Last active August 22, 2021 11:52
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Untitled0.ipynb",
"provenance": [],
"collapsed_sections": [],
"authorship_tag": "ABX9TyNsy4RaWWJJXRN8opuCmESy",
"include_colab_link": true
@wilsonfreitas
wilsonfreitas / README.md
Created April 21, 2021 12:59
Dúvida

Estou com dúvida em um tratamento aqui no R. Tenho um data frame que tem 3 colunas: data pregão, cód negociação ativo objeto e variação preço fechamento D0 x D-1. A partir dessas datas, o gostaria de incluir nesse data frame 5 datas úteis anteriores a cada uma dessas datas.

Vc tem alguma dica de como poderia fazer?

Tentei usar Index mas ele funciona bem para 1 data, agora quando temos várias datas...tentei um for tb mas não dei certo ainda....

@wilsonfreitas
wilsonfreitas / retorno_carteira.R
Created December 10, 2020 11:49
Cálculo de retorno de carteira de investimento com 10 ativos
library(xts)
library(tidyverse)
library(PerformanceAnalytics)
library(quantmod)
stocks_names <- c(
"ABEV3.SA",
"B3SA3.SA",
"CNTO3.SA",
@wilsonfreitas
wilsonfreitas / book_recs.md
Created June 10, 2020 11:26
Books I've used in class or found through other channels; spans Python, R, Java, C, C++, Finance, Data Science:

Machine Learning and AI for Finance

Advances in Financial Machine Learning, de Prado: http://www.quantresearch.org/
Machine Learning for Asset Managers, de Prado
Machine Learning for Factor Investing, Guida: http://www.mlfactor.com/
Big Data and Machine Learning in Quantitative Investment, Guida
Artificial Intelligence in Finance, Hilpisch: https://home.tpq.io/

Trading Analytics and Algorithms

Python for Finance 2d ed, Hilpisch
Derivatives Analytics with Python, Hilpisch