A stock generator that assess a list of stocks and returns the best stocks for investing and money allocations based on users choices of volatility, duration and number of stocks

Overview

Stock-Generator

Please visit "Stock Generator.ipynb" for a clearer view and "Stock Generator.py" for scripts.

The stock generator is designed to allow users to assess their list of tickers and select the valid tickers denominated in USD that best meet their needs using Python.

Users can choose volatility (whether they want to do safe, risky or wise investing), duration (short-term investment or long-term investment), number of stocks desired to choose and amount of money to invest. Users would need to have a csv file that contains a list of tickers they want to evaluate. Data sanitization would ensure invalid tickers are filtered out. The program extracts data from Yahoo Finance and assesses financial metrics like market capitalisation, beta, standard deviation, expected return and sharp ratio for each ticker provided.

Data analysis and integration were conducted to provide the stocks that best meet user's criteria and expectations from the given list based on financial calculations above. From the financial analaysis above, it would assign the companies with better performance with a greater weight. The program would eventually return a DataFrame of chosen companies, their weights, current closing price and money allocation calculated based on weights.

Owner
jmengnyay
jmengnyay
A Transformer-Based Siamese Network for Change Detection

ChangeFormer: A Transformer-Based Siamese Network for Change Detection (Under review at IGARSS-2022) Wele Gedara Chaminda Bandara, Vishal M. Patel Her

Wele Gedara Chaminda Bandara 214 Dec 29, 2022
PyTorch Implement for Path Attention Graph Network

SPAGAN in PyTorch This is a PyTorch implementation of the paper "SPAGAN: Shortest Path Graph Attention Network" Prerequisites We prefer to create a ne

Yang Yiding 38 Dec 28, 2022
LEAP: Learning Articulated Occupancy of People

LEAP: Learning Articulated Occupancy of People Paper | Video | Project Page This is the official implementation of the CVPR 2021 submission LEAP: Lear

Neural Bodies 60 Nov 18, 2022
ACV is a python library that provides explanations for any machine learning model or data.

ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any model or data and different Shapley Values for tree-based mod

Salim Amoukou 85 Dec 27, 2022
Large-scale language modeling tutorials with PyTorch

Large-scale language modeling tutorials with PyTorch 안녕하세요. 저는 TUNiB에서 머신러닝 엔지니어로 근무 중인 고현웅입니다. 이 자료는 대규모 언어모델 개발에 필요한 여러가지 기술들을 소개드리기 위해 마련하였으며 기본적으로

TUNiB 172 Dec 29, 2022
Neural Articulated Radiance Field

Neural Articulated Radiance Field NARF Neural Articulated Radiance Field Atsuhiro Noguchi, Xiao Sun, Stephen Lin, Tatsuya Harada ICCV 2021 [Paper] [Co

Atsuhiro Noguchi 144 Jan 03, 2023
Meta Self-learning for Multi-Source Domain Adaptation: A Benchmark

Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark Project | Arxiv | YouTube | | Abstract In recent years, deep learning-based methods

CVSM Group - email: <a href=[email protected]"> 188 Dec 12, 2022
Official Repository for our ECCV2020 paper: Imbalanced Continual Learning with Partitioning Reservoir Sampling

Imbalanced Continual Learning with Partioning Reservoir Sampling This repository contains the official PyTorch implementation and the dataset for our

Chris Dongjoo Kim 40 Sep 18, 2022
Very Deep Convolutional Networks for Large-Scale Image Recognition

pytorch-vgg Some scripts to convert the VGG-16 and VGG-19 models [1] from Caffe to PyTorch. The converted models can be used with the PyTorch model zo

Justin Johnson 217 Dec 05, 2022
A large-scale benchmark for co-optimizing the design and control of soft robots, as seen in NeurIPS 2021.

Evolution Gym A large-scale benchmark for co-optimizing the design and control of soft robots. As seen in Evolution Gym: A Large-Scale Benchmark for E

121 Dec 14, 2022
Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)

CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding (CVPR'22) Paper Link | Project Page Abstract : Manual an

Mohamed Afham 152 Dec 23, 2022
PyTorch implementation of Pay Attention to MLPs

gMLP PyTorch implementation of Pay Attention to MLPs. Quickstart Clone this repository. git clone https://github.com/jaketae/g-mlp.git Navigate to th

Jake Tae 34 Dec 13, 2022
In this project we use both Resnet and Self-attention layer for cat, dog and flower classification.

cdf_att_classification classes = {0: 'cat', 1: 'dog', 2: 'flower'} In this project we use both Resnet and Self-attention layer for cdf-Classification.

3 Nov 23, 2022
Pytorch implementation of the AAAI 2022 paper "Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification"

[AAAI22] Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification We point out the overlooked unbiasedness in long-tailed clas

PatatiPatata 28 Oct 18, 2022
LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image.

This project is based on ultralytics/yolov3. LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image. The related paper is avai

26 Dec 13, 2022
We simulate traveling back in time with a modern camera to rephotograph famous historical subjects.

[SIGGRAPH Asia 2021] Time-Travel Rephotography [Project Website] Many historical people were only ever captured by old, faded, black and white photos,

298 Jan 02, 2023
Kindle is an easy model build package for PyTorch.

Kindle is an easy model build package for PyTorch. Building a deep learning model became so simple that almost all model can be made by copy and paste from other existing model codes. So why code? wh

Jongkuk Lim 77 Nov 11, 2022
Robust and Accurate Object Detection via Self-Knowledge Distillation

Robust and Accurate Object Detection via Self-Knowledge Distillation paper:https://arxiv.org/abs/2111.07239 Environments Python 3.7 Cuda 10.1 Prepare

Weipeng Xu 6 Jul 01, 2022
Temporal Dynamic Convolutional Neural Network for Text-Independent Speaker Verification and Phonemetic Analysis

TDY-CNN for Text-Independent Speaker Verification Official implementation of Temporal Dynamic Convolutional Neural Network for Text-Independent Speake

Seong-Hu Kim 16 Oct 17, 2022
Permeability Prediction Via Multi Scale 3D CNN

Permeability-Prediction-Via-Multi-Scale-3D-CNN Data: The raw CT rock cores are obtained from the Imperial Colloge portal. The CT rock cores are sub-sa

Mohamed Elmorsy 2 Jul 06, 2022