Events & Conferences – Recordings

AI in Digital Finance Online Seminars

Middlemen in limit-order markets
Speakers: Albert J. Menkveld & Boyan Jovanovic

About:

Exchanges operate limit-order markets where non-synchronous investors can trade. An early investor can leave a price quote for a late investor to consume. High-tech, informed middlemen entered these markets in the last two decades. Naturally, one expects better informed middlemen to hurt gains from trade (i.e., welfare), because they adversely select investor quotes. But, might they raise welfare as market makers who quickly refresh quotes on incoming information? And, as market makers, they offer investors the option to temporarily park their asset. We offer a model with all these features and calibrate it to study how middlemen affect welfare.

The slides are available here.

AI in Digital Finance Online Seminars

Predicting the Undead: Using Machine Learning to Forecast Cryptocurrency Zombies
Speaker: Piotr Wójcik

About:

Investors face the risk of cryptocurrencies disappearing from the market and becoming zombies. Our study aims to predict which cryptocurrencies will become untradable using predictors based on descriptive statistics of yield, volume and market capitalization. The sample includes crypto assets that have been listed on the markets for at least 210 days in the period from January 2015 to December 2022. We apply various machine learning algorithms and novel XAI tools, namely permutation-based feature importance and PDPs, to identify the main factors explaining the disappearance of cryptos and to understand the shape of the relationships. Our study shows that machine learning models allow us to predict that cryptocurrencies will become zombies within the next 28 days with 84% out-of-time accuracy. The tree-based models, especially random forests, outperformed traditional econometric approaches. The variables with the greatest explanatory power are related to volumes and returns calculated in previous periods.

The slides are available on Quantinar.