Stock-history-display - something like a easy yearly review for your stock performance

Overview

Stock History Display

Available on Heroku: https://stock-history-display.herokuapp.com/

The purpose

The purpose of this project is something an easy yearly review tool for your stock performance. This app will help you get a very quick and clear view of your past invesment, about whether you earn or loss, about how much you earn and loss, about when you buy-in and sell-out, about the volume in related buy/sell threade. We both know it's pretty annoying to review your Robinhood history long list and it's not clear at all.

By the help of this app, users will be able to have a better view from their past investment, and also get some feedback from it. This is super important in improving future stock market performance.

Sample result

System Structure

Steps

  • Step 1: Input stock abbreviation: By default, it is TSLA, which is the abbreviation of TESLA
  • Step 2: Copy and paste buy/sell histories from Robinhood history page, make sure you follow the format,
  • Step 3: (Optional) Choose a period: 1 year or 5 year. Also, you can choose a filter which could filter out small profit line to reduce distraction, default = 10.
  • Step 4: Click submit, then you should see buy/sell history picture attached to your stock line chart as below

Current Feature

  • Tech Stacks: Python, Flask, Html, JSON, Docker, Heroku
  • fetch Stock data from Yahoo Finance API
  • persist Stock data as file to reduce duplicated Yahoo Finance API request
  • parse history data: the personal operations history, like when you make a buy-in or sell-out transaction, this will add a datapoint into history. This app support parse data from history following Robinhood history page format. You may paste history from Robinhood history page.
  • bypass browser cache by random number naming
  • support parsing complicated transactions and generating simple buy or sell threads.
  • clear green and red view for earn and loss. 4K very high definition picture.

TODO

  • could not parse "split" in history
  • some bugs when parsing Nvidia data
  • try to improve definition to 4k
  • add this one to google sheet auto request
  • beautify the code
  • add title, introduction and github links into web app Metrics:
  • display total profit from the stock
  • display total transactions in this stock
  • max, avg, min hold days
  • max, avg, min profit statistics regarding the thread transactions

Future

  • Redis Cache
  • MySQL storage
  • support personal accounts, and support google login in
  • better de-deplicate mechanism, potentially using hash, SHA256
  • scale by different time length, year, month, day, etc
  • a better system design
  • beautify UI by Bootstrap

Reference

Owner
LiaoJJ
Actively seeking for a Software Engineer New Grad opportunities
LiaoJJ
[ICRA 2022] CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation

This is the official implementation of our paper: Bowen Wen, Wenzhao Lian, Kostas Bekris, and Stefan Schaal. "CaTGrasp: Learning Category-Level Task-R

Bowen Wen 199 Jan 04, 2023
U-Net Brain Tumor Segmentation

U-Net Brain Tumor Segmentation 🚀 :Feb 2019 the data processing implementation in this repo is not the fastest way (code need update, contribution is

Hao 448 Jan 02, 2023
Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning

structshot Code and data for paper "Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning", Yi Yang and Arz

ASAPP Research 47 Dec 27, 2022
This program can detect your face and add an Christams hat on the top of your head

Auto_Christmas This program can detect your face and add a Christmas hat to the top of your head. just run the Auto_Christmas.py, then you can see the

3 Dec 22, 2021
Seach Losses of our paper 'Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search', accepted by ICLR 2021.

CSE-Autoloss Designing proper loss functions for vision tasks has been a long-standing research direction to advance the capability of existing models

Peidong Liu(刘沛东) 54 Dec 17, 2022
Fine-grained Control of Image Caption Generation with Abstract Scene Graphs

Faster R-CNN pretrained on VisualGenome This repository modifies maskrcnn-benchmark for object detection and attribute prediction on VisualGenome data

Shizhe Chen 7 Apr 20, 2021
Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.

HAWQ: Hessian AWare Quantization HAWQ is an advanced quantization library written for PyTorch. HAWQ enables low-precision and mixed-precision uniform

Zhen Dong 293 Dec 30, 2022
Haze Removal can remove slight to extreme cases of haze affecting an image

Haze Removal can remove slight to extreme cases of haze affecting an image. Its most typical use is for landscape photography where the haze causes low contrast and low saturation, but it can also be

Grace Ugochi Nneji 3 Feb 15, 2022
Implementation of Feedback Transformer in Pytorch

Feedback Transformer - Pytorch Simple implementation of Feedback Transformer in Pytorch. They improve on Transformer-XL by having each token have acce

Phil Wang 93 Oct 04, 2022
Anchor-free Oriented Proposal Generator for Object Detection

Anchor-free Oriented Proposal Generator for Object Detection Gong Cheng, Jiabao Wang, Ke Li, Xingxing Xie, Chunbo Lang, Yanqing Yao, Junwei Han, Intro

jbwang1997 56 Nov 15, 2022
This PyTorch package implements MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation (NAACL 2022).

MoEBERT This PyTorch package implements MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation (NAACL 2022). Installation Create an

Simiao Zuo 34 Dec 24, 2022
Code release for our paper, "SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo"

SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo Thomas Kollar, Michael Laskey, Kevin Stone, Brijen Thananjeyan

68 Dec 14, 2022
The DL Streamer Pipeline Zoo is a catalog of optimized media and media analytics pipelines.

The DL Streamer Pipeline Zoo is a catalog of optimized media and media analytics pipelines. It includes tools for downloading pipelines and their dependencies and tools for measuring their performace

8 Dec 04, 2022
Python implementation of "Single Image Haze Removal Using Dark Channel Prior"

##Dependencies pillow(~2.6.0) Numpy(~1.9.0) If the scripts throw AttributeError: __float__, make sure your pillow has jpeg support e.g. try: $ sudo ap

Joyee Cheung 73 Dec 20, 2022
ReLoss - Official implementation for paper "Relational Surrogate Loss Learning" ICLR 2022

Relational Surrogate Loss Learning (ReLoss) Official implementation for paper "R

Tao Huang 31 Nov 22, 2022
Air Quality Prediction Using LSTM

AirQualityPredictionUsingLSTM In this Repo, i present to you the winning solution of smart gujarat hackathon 2019 where the task was to predict the qu

Deepak Nandwani 2 Dec 13, 2022
A symbolic-model-guided fuzzer for TLS

tlspuffin TLS Protocol Under FuzzINg A symbolic-model-guided fuzzer for TLS Master Thesis | Thesis Presentation | Documentation Disclaimer: The term "

69 Dec 20, 2022
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels

ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D

298 Dec 26, 2022
A deep learning network built with TensorFlow and Keras to classify gender and estimate age.

Convolutional Neural Network (CNN). This repository contains a source code of a deep learning network built with TensorFlow and Keras to classify gend

Pawel Dziemiach 1 Dec 18, 2021
Personalized Federated Learning using Pytorch (pFedMe)

Personalized Federated Learning with Moreau Envelopes (NeurIPS 2020) This repository implements all experiments in the paper Personalized Federated Le

Charlie Dinh 226 Dec 30, 2022