Grant Holtes

Currently working as a Quantitative Developer at JANA investment advisors.

Previously I held a number of different roles at Deloitte, ranging from data science and backend software engineering to project management and technical advisory.

My academic background includes two degrees from the University of Melbourne - a Bachelor of Commerce in Finance and a Graduate Diploma in Computer Science. My academic interests are broad, spanning finance, economics, econometrics, machine learning, distributed systems, and structural engineering.

Some things I've done: LinkedIn Resume

Technical Projects

Projects in quantitative finance, data science, econometrics and software engineering.

[2024] Explanatory Masks for Interpretable Financial Analysis

[2024] Critiquing Diversification Benefits through a Simplified Conditional Correlation Estimator, (Backup link)

[2024] Practical Guide to Factor Covariance Matrix Construction

[2024] Diverging from the Norm: An Examination of Non-Normality and its Measurement in Asset Class Returns, (Backup link)

[2024] Expressing Steady State Assumptions in Time Series Forecasting: AR and VAR models

[2024] Forecasting Returns from Hedging Foreign Assets

[2023] Return Volatility Estimates: A Review and Practical Analysis, (Backup link)

[2023] Impact of covariance matrix estimator choice on yield curve decomposition with PCA, (Backup link)

[2023] Subsampling leaf variables as an optimisation in Monte-Carlo simulations

[2023] Analysis of covariance matrix estimators for simple portfolio optimisation

[2022] Flow programming for computer vision applications

[2022] In browser TensorFlow object detection demo

[2021] Playlist optimisation for Spotify

[2021] Mapping Melbourne's cycling infrastructure with OpenLayers

[2021] Extracting Colour Palettes with Unsupervised Learning

[2021] Agent based modelling exploration

[2020] Statistical analysis of service deserts in Victoria: report, code

[2020] SortStream ML powered document sorting

[2020] DocDump text and document metadata extraction

[2020] Automated data exploration in R: code: Titanic example Economic example

[2019] Unsupervised ML image embedding to measure art style and visual similarity

[2019] Dimensionality reduction for art style embeddings

[2019] Navigation App for Urban Cyclists: Write up Code "The Submarine" feature

[2019] Exploration of ML Document Classification Techniques - Code

[2019] Interacting agent simulation and statistical physics to model fashion epidemics

[2019] Deep Dream implementation in Keras

[2018] A replication and extension of the paper "The Impact of Economic Conditions on Participation in Disability Programs: Evidence from the Coal Boom and Bust"

[2018] Economic and financial market evaluation with similarity methods

[2018] How Animal Investors Beat the Market

[2018] URL Sketchifier: Give your urls a look that Gmail will flag as suspicious

[2018] Logistic Regression — Understanding Explainable AI: write up code

[2018] Decision Trees — Understanding Explainable AI: write up code

[2018] Building Google's art and culture portrait matcher

[2018] Analysing bird flight by merging videos in MATLAB

[2017] Developing a compass web app with mobile sensor integration

[2017] Developing autoencoders for image correction

[2017] Mini-max algorithm for Connect 4

Creative Projects

Projects in generative art, image manipulation.

[2023] Sumimasen: A collection of images from Japan. Buy a physical copy on Amazon

[2022] Weighted attractor rendering

[2022] Rendering attractors at 60 FPS

[2022] Organic growth emulation in TouchDesigner

[2022] Esher's Cube Space Division in TouchDesigner

[2022] Creating sunset gradients in P5.js

[2022] Creating abstract images from lines

[2021] Abstract visualisation of what a state of the art object detection model is seeing


[2024] Git Guide