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Nitish Mishra's Projects

deep_portfolio_theory icon deep_portfolio_theory

Deep Portfolio Theory is a portfolio selection method published by J. B. Heaton, N. G. Polson, J. H. Witte from GreyMaths Inc. Authors' codes are proprietary, We tried to implement this method on BSE Healthcare stocks. We constructed the deep portfolio method over the modern portfolio theory, Markowitz’s classic risk-return trade-off. Four-step routine of encode, calibrate, validate and verify to formulate an automated and general portfolio selection process. At the heart of our algorithm are deep hierarchical compositions of portfolios constructed in the encoding step. The calibration step then provides multivariate payouts in the form of deep hierarchical portfolios that are designed to target a variety of objective functions. The validate step trades-off the amount of regularization used in the encode and calibrate steps. The verification step uses a cross validation approach to trace out an ex post deep portfolio efficient frontier. We demonstrate all four steps of our portfolio theory numerically.

eth-todo-list icon eth-todo-list

Blockchain Todo App Tutorial Powered by Ethereum Smart Contracts

yolov4-cloud-tutorial icon yolov4-cloud-tutorial

This repository walks you through how to Build and Run YOLOv4 Object Detections with Darknet in the Cloud with Google Colab.

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