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Hugo Dolan

Applications of Time Series Analysis (ARMA-GARCH) To Improve Risk-Adjusted Return Screening Procedures.

You have been given the daily returns of several strategies / funds over the past year, how would you determine which one provides the best investment opportunity given only this information?

A naive approach might be to select the strategy with the best-annualized return, however, this ignores the level of potential risk that may materialize in future returns. For instance, suppose that the returns on Strategy A are better than that of Strategy B, but strategy A has a higher variance in daily returns (volatility). …


Applications of Monte Carlo Methods

Photo by Gary Saldana on Unsplash

The Rational Investor Allocation

Markowitz Portfolio Optimisation seeks to find a set of weights for N assets in a portfolio such that the risk adjusted return of the portfolio is maximised (aka the Sharpe Ratio).

This is the portfolio the so called “rational investor” would choose as clearly no one would want a portfolio that did not generate the best risk adjusted return right?

Let us introduce this with a little bit of mathematics to accompany this. Capital “Sigma” is the covariance matrix of asset returns, with entries measuring the strength with which one assets returns tend to move…


Applications of Change-point Detection, Cox Regression, and Bayesian Hierarchical Models

A company’s performance relative to its peers will be ultimately driven by management’s strategic decision making ability to drive growth and position the organisation for changing market conditions.

Whilst investors ultimately care about picking stocks with management teams that can generate returns for shareholders, it is also important to be able to correctly time these investments or trades. An extreme example would be to short a stock that where goes bankrupt, but in the near term skyrockets, forcing you to close at a loss.


Tips from a new ‘Kaggler’ building CNN’s for blindness detection

After recently competing in the 2019 APTOS Blindness Detection Kaggle Competition and finishing in top 32%, I thought I would share my process for training convolutional neural networks. My only prior deep learning experience was completing the Deeplearning.ai Specialisation, hence this is all you should need to read this article.

Sections to this article

  1. Competition context
  2. Keeping a logbook
  3. Get more data
  4. Leveraging existing kernels
  5. Preprocessing images
  6. Training is a very very slow process (but don’t worry)
  7. Transfer learning
  8. Model selection

Competition context

I spent the last 2–3 months working on and off on the APTOS 2019 Blindness Detection Competition on Kaggle, which required you to…


Unity is a great tool for prototyping everything from games, to interactive visualisations. In this article, we run through all you need to know to get started using Unity.

First, a little bit about me: I’m a hobbyist unity developer, 3d modeler and graphic designer who’s worked with Unity and Blender for over 5 years. I’m now a Financial Maths student at University College Dublin, and occasionally I do freelance graphic design, web prototyping, and game prototyping.

Concept art is one of the earliest phases in the game dev process, over the last 5 years i’ve got a lot of exposure to all areas of game design. Check out my Portfolio of Graphic, UX, Concept Art, Game Dev etc…

Introduction

This article is aimed at anyone who has never used Unity before, but has some previous experience programming or in web design /…


SVM’s are often considered ‘Black Boxes’. In this article we cover techniques to visualise learned SVM models and their performance on real world data.

Image Shot by Hugo Dolan

About the author

Hugo Dolan is an undergraduate Financial Mathematics student at University College Dublin. This is mostly based and motivated by recent data analytics and machine learning experiences in the NFL Punt Analytics Kaggle Competition and the being part of the team who won the Citadel Dublin Data Open, along with material from Stanford’s CS229 online course.

This article contains the following sections:

  1. Introduction to Linear Models, SVM’s and Kernels
  2. Interpreting high dimensional engineered feature spaces which are utilising SVM kernels…
  3. Techniques for evaluating the performance of high dimensional classification boundaries
  4. Practical options for working with large class imbalances


Hugo Dolan is a Dubai College graduate class of 2018 who studied Maths, Further Maths, Physics and DT. He has over 5 years of programming as a hobby and is currently studying Financial Mathematics at University College Dublin. He is part of an international team competing in Citadel Securities Data Open Championships @ The NYSE in April 2019

“photo of library with turned on lights” by Janko Ferlič on Unsplash

Hey guys, over the past few years I’ve written a number of data analytics and web design related articles and currently a writer for Towards Data Science. I’m going to continually update this resource as I publish more articles.

The primary purpose…


Photo by Clint McKoy on Unsplash

After recently using Pandas and Matplotlib to produce the graphs / analysis for this article on China’s property bubble , and creating a random forrest regression model to find undervalued used cars (more on this soon). I decided to put together this practical guide, which should hopefully be enough to get you up and running with your own data exploration using Pandas and MPL!

This article is broken up into the following Sections:

The Basic Requirements

  • Reading Data From CSV
  • Formatting, cleaning and filtering Data Frames
  • Group-by and Merge

Visualising Your Data

  • The Plot Function Basics
  • Seaborn violin and lm-plots


China’s megacities cities occupy the top 4 spots of the worlds most expensive cities to buy property, but is this upwards only market too good to be true?

The Chinese economy shares many of the same characteristics displayed in Canada’s present property bubble; rising property prices and extraordinary levels of Non Financial Debt (NFD 290% of GDP) . The actual value of Canada’s non financial debt however pales into insignificance in comparison to China’s (Figure 1) and is a serious cause for concern.

Whilst for both countries; key indicators (NFD, Property Price Index, GNI per capita) appear to move reasonably in tandem up to the end of 2015. …


Why you should consider it, the pain points and how to write your own lightweight reactive store

Keeping multiple simultaneous clients updated can be a nightmare

I’ve written this article at the end of my latest Angular4 project: Moveseats.com , which was architected to work in real time across many clients (See demo). Now its time share what I learnt while its still fresh!

Git repo link (For walkthrough below)

If there are issues or helpful improvements you wish to make, leave a comment or fork my repo, Thanks.

An Introduction

A reactive application can help to create:

  • Fluid user experience
  • Maintain consistent application state across many simultaneous clients
  • Save time in testing when every component and service is using the latest app state

A reactive applications can…

Hugo Dolan

UCD Statistics & ACM, Learning Data Science, Winning Team @ Citadel Dublin Data Open. www.hugodolan.com/linkedin | Mailing List: http://eepurl.com/gkV7ov

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