Undergraduate thesis, Seoul National University Dept. of Economics — "Modeling Volatility and Risk Spillover Between the Financial Markets of US and China Using GARCH Value-at-Risk Forecasting and Granger Causality."

The increasing demand for energy is one of the biggest reasons behind the integration of solar energy into the electric grids or networks. To ensure the efficient use of energy PV systems it becomes important to forecast information reliably. The accurate prediction of solar power variation can enhance the quality of service. This integration of…

The NIFTY 50 is a benchmark Indian stock market index that represents the weighted average of 50 of the largest Indian companies listed on the National Stock Exchange. We use real-time dataset to calculate the stock predictions for future years.

Learned time series analysis from Quantstart

This project is to build Forecasting Models on Time Series data of monthly sales of Rose and Sparkling wines for a certain Wine Estate for the next 12 months.

Performing Temperature Prediction for 5 different cities in the USA using time series analysis on Python.

Python codes for time series forecasting

Time Series project inＲ

Streaming data management and time series analysis using R

Precious Metal Price ARIMA Prediction

StockOptionMetrics is an R project for calculating log returns, simple returns, and Sharpe ratios for specified stock options. It offers efficient data processing, customizable calculations, and comprehensive documentation. Analyze performance and risk with ease.

Udacity - Predictive Analysis for Business Projects

data analysis

This is a capstone research project for my Certificate in Applied Data Science (CADS) at my undergraduate institution, Wesleyan University, on the topic of "Understanding the Variances in COVID-19 Pandemic Outcome - Excess Mortality - with Social, Cultural, and Environmental Factors", sponsored by Prof. Maryam Gooyabadi.

Time Series analysis on INR vs USD using Holt WInter, explonential smoothing and ARIMA

Code Snippets - Data Science ,Machine Learning,Deep Learning,H2O,Time Series,Spark ,Big data,Azure Databricks

A detailed repository containing methods and analyses in R to enhance the efficiency of bike distribution for Madrid's bike rental system BiciMAD

A time series forecasting project about the brief application of lstm(deep learning), prophet, arima, holt, exponential smoothing algorithms

Predict stock returns using ARIMA and LightGBM to analyze historical data and uncover key drivers with feature importance in this financial forecasting project.

Analysed, plotted, and forecasted the time-series household energy data set based on Seasonal Auto Regressive Integrated Moving Average (SARIMA) model in R.