Latest¶

January 30, 2019
in Academy
10 min read

The Thin Crust of Liquidity

The role of market makers and importance of liquidity in the crypto industry

Eric Noll was getting frustrated. It was November 2011, and the senior Nasdaq executive was struggling to explain to a mostly disinterested House of Representatives panel why the changing stock exchange landscape was wreaking havoc for smaller public companies:

Today's US markets are increasingly fragmented and volatile. Liquidity in US stocks is dispersed across 13 exchanges and over 40 other execution venues. The declining cost of launching and operating electronic order crossing systems has led to a proliferation of decentralized pools of liquidity. However, the unintended consequences of that market fragmentation have been a lack of liquidity and price discovery in listed securities outside of the top 100 traded names. Such fragmentation of trading creates a thin crust of liquidity that is easily ruptured, as occurred on May 6^th (i.e. the 2010 Flash Crash)

Stifled yawns from Congressional onlookers aside, Noll was describing an unintuitive but important phenomenon that would make Milton Friedman roll over in his grave: more competition from exchanges leads to less liquidity for small issuers and greater systemic risk.

January 18, 2019
in Academy
3 min read

FAQ for New Crypto Algo Traders

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In this post, we've compiled helpful Q&A resources for developers interested in exploring crypto algo trading and traders with experience in trading but limited programming knowledge.

January 18, 2019
in Academy
8 min read

Getting Started with Algo Trading

Algorithmic trading is the process of using computers programmed to follow a pre-defined set of rules for automatically placing trades in order to generate profits at high speed and high frequency. These are called bots.

The pre-defined sets of rules, called an algorithm, can range from quantitative strategies to machine learning models that can reference any data or combination thereof, e.g. prices, volume, or tweets/news feeds for sentiment analysis.

Algo trading makes markets more liquid by introducing a large volume of trades and orders. Unlike human traders, computers don't need to rest or sleep, are much faster at calculating and sending instructions, and don't suffer from emotions (at least, not yet??).