Market Fails & Computational Gibberish
Quick Post: “n people line up to sit in an n-seat theater” With a Nod to Schelling On Twitter, Josh Wolfe posted the above problem, which asks: 100 people line up to take their seats in a 100 seat theater. The 1st person in line lost her ticket and so sits in a seat at […]
Quick Post: Misrepresenting Evidence In Behavioral Finance/Genetics TL;DR: this post looks at a representative example of social scientists playing the telephone game with genetics papers. The intended takeaway is that researchers who wish to claim their hypotheses are founded on prior work in biology cannot freely change the compositions of groups or alter the findings […]
Accountability, Generalizability, and Rigor in Finance Research Machine Learning in Markets (Part II) Intro: Accountability and Code You’re looking to buy a car, and not just any car, you want a customized, durable, high performance machine that no one else has seen before. A young couple enthusiastically responds to your want ad saying that they’ve […]
Fitting to Noise or Nothing At All Machine Learning in Markets Derp Learning Academic finance literature naively applying machine learning (ML) and artificial neural network (ANN) techniques to market price prediction is a dumb farce. While this probably won’t surprise anyone who has done a paper replication in the past 6+ years, despite all of the advancements […]
NGDP Futures Targeting A Pretty Goofy Idea Expect The Expectations First: I don’t intend to argue over the merits of targeting NGDP in general. For a background in that, you can start with Hall and Mankiw’s great paper from 1994, or check out Scott Sumner’s argument in the last issue of Foreign Affairs, or read some skepticism from Stephen Williamson […]
Introduction to Agent-Based Models with respect to “The Future of Macroeconomics” Pre-Post: Thank You NYC BlogoTweetosphere I’m such a spoiled kid. A few months ago I was planning a long labor day weekend in NYC, so I sent out requests to a few of my heroes in the economics, finance, and math blogosphere to meet me for a […]
tyle=”text-align: center;”>Specificity and the Importance of Using Fake Data I reconstruct a model used in an academic paper on HFT “quote stuffing.” Then I apply several scenarios of mock data to show that the authors’ conclusion is invalid. There is still no evidence of quote stuffing.[1] Introduction A few weeks ago I wrote a post explaining how routine software […]
Still confused about high-frequency trading? Yes. This piece originally appeared as a guest post on Noahpinion. Professor ‘Pinion graciously offered me a platform to continue hoo-ha’ing. I obliged.[1] I’ve felt like a popular boy lately. In the five years I’ve been developer and researcher at a small trading firm, my family and friends mostly thought I […]
On High-Frequency Trading (Part II) Since my last post on HFT, Michael Lewis has released a new book heavily criticizing the field, even going as far as saying that the markets are “rigged”. Explosive debate soon followed. For an accurate and colorful analysis of Mr. Lewis’ book, see Scott Locklin. This post focuses on a […]
On High-Frequency Trading In which I identify errors in recent HFT academic papers and discuss some difficulties of knowledge Simplicity does not come of itself but must be created – Clifford Truesdell The Blogs Must Be Crazy When it comes to trading, especially of the high-frequency (HFT) variety, a few of my favorite finance and economics bloggers write […]
Your Our eyes deceive you Us, use The Force (Reader Note: this is a technical/wonk-ish post about statistical models) Update 3/23/2017 LOESS regressions have been on my mind lately and I wanted to update this post with the disclaimer: do not use them. Some day I’ll get around to talking to Kahan about why. Update […]
Foreword We live in an exciting period of accelerating technology, where computational power and algorithmic sophistication appear to be increasing exponentially with few ends in sight. Open source data analysis platforms like R and scikit-learn are making cutting edge techniques faster and more accessible. Big Data Hackathons bring all levels of interested individuals together to […]
So You Can Derp While You Dow Last Friday, one of my favorite math and data science bloggers, Cathy O’Neil[1], served up a lazy and confused bit of market commentary that I find highly uncharacteristic of her normal thoughtfulness. She begins with a 12 month chart of the DJIA The Dow is at an all-time […]
A Species of General Disapproval “It is true, as has been before observed that facts, too stubborn to be resisted, have produced a species of general assent to the abstract proposition that there exist material defects in our national system…” Alexander Hamilton[1], The Federalist Papers No. 15 Sure, I know that it’s always possible to […]