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WebClinic's Projects

automated-sentiment-analysis icon automated-sentiment-analysis

This project looks to scrape news source sites and utilize such NLP transformers like Google’s BERT. The goal is to see if we can take an analyzed news article and correctly predict the direction a stock price will move.

automated-stock-prediction icon automated-stock-prediction

Model using Long Short Term Memory to predict stock prices. Input is OHLC data which the program will automatically procure from Yahoo! Finance using Python web scrapers. The input will be ticker, date range of OHLC data, and number of days for prediction.

automated-stock-trading-app icon automated-stock-trading-app

Automated Stock Trading application which utilizes the Alpaca API and Opening range breakout/breakdown strategy to manage a stock portfolio πŸ“ˆ

automated-trader icon automated-trader

3rd Year University Undergraduate dissertation project, supervised by https://www.nottingham.ac.uk/computerscience/people/thomas.gaertner focusing on using Natural Language Processing, AI Portfolio Optimisation and Machine Learning to produce an Automated Trading Agent. Received 89% overall.

automated-trader-for-nse icon automated-trader-for-nse

Automated Trader for NSE software is for trading the signals provided by The Portfolio Trader's NSE Trades. The software is provided FREE OF COST.

automated_options_trading_system icon automated_options_trading_system

Our project proposal highlights the effects of Market Regimes on the historical volatility and the trading performance of Options to which we present a technology stack and methodology aimed at developing an automated Options trading system and also present a Markov-switching Auto-regressive model as an effective model for predicting Regime shifts and lastly present a hedging strategy that minimizes the risk profile of an investment portfolio by utilizing our Market Regime predictive model to automatically re-balance the weights of assets in our investment portfolio to generate more consistent and favourable trading alphas.

automated_stock_prediction icon automated_stock_prediction

The goal of my final project work was to create a machine learning model, based on data from 130 stocks over the last 14 years, which is able to recognize patterns in price movements and make predictions.

automated_trading_agent icon automated_trading_agent

This study proposed an automated trading agent that could assist investors to maximized the value of portfolios. By leveraging the sentiment analysis, technical indicators and Deep Deterministic Policy Gradient, our agent is able to achieve +3% ROI in certain conditions.

automatedstocktrading-deepq-learning icon automatedstocktrading-deepq-learning

Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.

automatic-api icon automatic-api

A list of software that turns your database into a REST/GraphQL API

automatic-fundamental-investment-valuation icon automatic-fundamental-investment-valuation

Automatically performs the DCF calculation, sensitivity analysis and Piotroski f-score analysis for a given company. All financial data collected via the financialmodelingprep API.

automatic-stock-order-placement-prototype icon automatic-stock-order-placement-prototype

Used Alice blue API to fetch stock market data and then used python algorithms to apply conditions over it and placing hundreds of stock orders simultaneously and automatically notifying it.

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