I am a quant researcher focused on execution at both the high (parent) and low (order routing) level. I also dabble in market-making and alpha signals when there is a spare 5 minutes at work.

Previously, I was a quant at BestX and spent the day researching financial markets with a focus on transaction cost analysis (TCA). Hopefully I shared some interesting insights about the world of FX, fixed income and equity trading and built some cool product features.

I have a PhD in Statistical Science from University College London (UCL) and my thesis was Bayesian Nonparametric Hawkes Processes with Applications. I also have an MRes in Computer Science and an MPhys in Theoretical Physics from the University of Manchester.

I run a dashboard for crypto liquidity and pre-trade analytics: https://cryptoliquiditymetrics.com/

I’m an open source contributor with multiple projects ongoing: dirichletprocess, HawkesProcesses.jl, AlphaVantage.jl, CoinbsePro.jl, AlpacaMarkets.jl.

I’ve written guest posts for QuestDB:

Want me to write for you or have something else interesting? Email me at dean[dot]markwick[at]talk21[dot]com

Talks

Articles

Some are behind a paywall.

Outside the Day Job

I also have a keen interest in sports modelling and how statistics can be used in professional sports and gambling, I enjoy a good film, watching a boxset too quickly and a bit of a foodie. Here I am enjoying some delicious Korean BBQ.

Delicious BBQ

My blog is also aggregated on https://www.r-bloggers.com/ and https://www.juliabloggers.com/.

Recent Post:

    Big Ticks and Small Ticks in Equity Microstructure

    I bought Trades, Quotes and Prices a few years ago and it came with access to some free data to help you understand the concepts. That data was from LOBSTER and it has the limit order book (LOB) of five tech stocks for a single day in 2012. I did a quick top of book size calculation in Python and the liquidity profiles looked completely different. Intel and Microsoft had hundreds of thousands of dollars at the best prices, while Google and Amazon had only a fraction of that size. So my first thought was that the orderbook data needs some explaining and basic analysis before going into anything more complicated. In this post, we’ll cover how to load and parse LOBSTER data in Python, calculate core microstructure statistics, and explore how a stock’s tick size changes how it trades (big-tick vs. small-tick stocks).