Deepshot is a machine learning model designed to predict NBA game outcomes using advanced team statistics and rolling averages. It combines historical performance trends with contextual game data to deliver highly accurate win predictions (71%)

Thesis project about Unsupervised anomaly detection on the streaming time-series data of porfolio risk measures and returns.

MSc Finance dissertation project at Newcastle University. This project focused on forecasting the volatility of exchange rates involving the Great British Pound using EWMA, GARCH-type and Implied Volatility models.

This repository consits of: projects and homeworks connected with research area such as Risk Management.

Time series decomposition into trend and cycle components. (Stochastic) trend estimation and forecasting

Simple python library thats implemented EWMA, IIR and Average filter.

Compute an exponentially weighted mean incrementally.

Discussed various methodologies that may help while implementing Time Series

Random Plotly Dash scripts, mostly TA related

An adaptive selector for short-term forecasting of multiple time series. For each time series, it finds the best method from a pool of candidates based on their past performance.

Volatility forecasting using ARCH, GARCH, and EWMA on JPM stock

An adaptive selector for short-term forecasting of multiple time series. For each time series, it finds the best method from a pool of candidates based on their past performance.

A tool to track and forecast system performance with advanced EWMA modelling

This repository represents additional control charts, various plans and variables that are used within the chart scope using Minitab software

Swift Struct implementing EWMA / Smooth Sequence of generic values

Adaptive Monitoring and Real-World Evaluation of Agentic AI Systems

ब्रह्मन् brahman

Codes for the design and the evaluation of the performance of control charts (Shewhart and EWMA) for a zero-inflated beta (BEZI) distribution

Code and experiments for detecting real-time shifts in correlation between time series. Includes simulation, calibration, and real-world case studies using CUSUM, Wilcoxon rank-sum sequential tests, MEWMA, and Adaptive EWMA.

EDA performed on timeseries data and different plots to get insights from data visualizations