Welcome back to the Hummingbot Academy!
The latest Hummingbot release (0.38) introduces an exciting strategy based on classical academic market-making models. This article will delve into the Avellaneda & Stoikov paper from 2008 and its implementation in Hummingbot.
For those who enjoy in-depth scientific papers, the original publication is readily accessible online or directly here.
Hummingbot is a modular framework for building highly reliable, and high performance trading bots. While the official Hummingbot package already allows you to run high frequency trading strategies on a number of cryptocurrency exchanges, the underlying framework is freely extensible for building custom strategies, custom market connectors, and more.
In this blog post, we will discuss some of the key architectural features in Hummingbot, and the rationales behind their designs.
While we wrote the original whitepaper and coined the term “liquidity mining”, the concept recently became popularized in DeFi with the emergence of Balancer, Curve.Fi, and, despite being late to the game, Uniswap, who recently introduced token distributions to the original Automated Market Maker (AMM) concept.
Our version of liquidity mining and that of DeFi share the same objective: finding an efficient way for token issuers and protocols to provide liquidity for digital assets. Token liquidity has long been a problem in the cryptocurrency market due to the large and growing number of token assets, exchanges, and exchange protocols, meanwhile there has only been a limited number of sophisticated (and expensive) hedge funds and market makers that could serve the markets.
Hummingbot Miners and AMM liquidity mining both take a decentralized, crowd-sourced approach to market making. They allow the general public, not just the professional market makers, to participate in providing liquidity for digital assets.
One important way in which they enable this is by creating frameworks for compensating a decentralized group of market makers.
Hello again Hummingbot community!
Today we will start to talk about what I consider the most important factor that is part of all types of trading operations: risk and risk management.
As one of the biggest investors of our time once said:
"Risk comes from not knowing what you're doing." ~ Warren Buffett
All kinds of financial operations have varying degrees of risk, and market making is no different.
While it seems more exciting to imagine and project future gains and fantasize about being the next Warren Buffet, the reality and less glamorous part of investing, and arguably the most important part, is trying to figure out what can go wrong and how to mitigate losses that can result.
There is a lot to cover about risk and risk management, but today we will focus on one major risk related to market making: inventory risk.
Here is what we’ll cover in today's article:
What is inventory value?
What is inventory risk?
How to mitigate inventory risk with Hummingbot
Welcome back to our Educational Center, where we aim to help you to learn more about market making, arbitrage, and everything related to algorithmic trading.
Today we will talk about one of the core strategies that can be used with hummingbot: cross-exchange market making.
The objective of this article is to help you understand:
Last week we published the first article of the Hummingbot Academy, covering an introduction to what is Market Making, and today we discuss Arbitrage in order to answer the following questions:
If you reached this page, there is a high probability that you have been asking one of these questions:
Then you are on the right place!
Here at Hummingbot, our goal is to help you learn more about market making and how to use our free open-source robot to implement your own strategy.
The need for liquidity is as constant a theme in the cryptocurrency market as are death and taxes. However, as we have previously written in other blogs (such as this one, the way in which token issuers and exchanges procure market making in the crypto market is broken. The reliance on high cost, price gouging crypto market makers is just not sustainable or scalable. This led us to propose the concept of liquidity mining and launch the Hummingbot Miners platform for decentralized and crowd-sourced market making.
We have been encouraged to see other projects experiment with community-based liquidity provision, most notably in DeFi with automated market makers (AMM). Whether it’s called “liquidity mining” or “yield farming”, there has been a surge in activity in DeFi as protocols such as Compound, Synthetix, Balancer, Ampleforth, and Loopring aim to propel wider market adoption by rewarding their communities for providing liquidity.
With this heightened interest in liquidity mining, we explain in this blog how our Hummingbot Miner platform fits into the landscape. We also compare and contrast liquidity mining in the order book model popularized by centralized exchanges versus the automatic market maker (AMM) model that is prevalent in DeFi.
We explain in more detail the methodology and mechanics of liquidity mining, a data-driven, objective methodology for quantifying market maker performance.
In our liquidity mining announcement, we introduced a data-driven, objective methodology for quantifying market maker performance. This serves as the basis for determining fair and open compensation for market makers. So how does it all work? In this post, we explain in more detail the methodology and mechanics of the platform.
Since Hummingbot is an open source bot platform that connects to many different exchanges, we have developed a deep understanding of the nuances between various exchange types.
In this post, we discuss the three main methodologies that digital asset exchanges use to facilitate asset transactions. We hope that this post helps crypto traders and developers choose the right exchange for their needs.
Exchanges perform the fundamental role in free markets of bringing together and coordinating buyers and sellers. Exchanges provide a venue for these parties to discover one another, negotiate and agree terms, and ultimately transact. Exchanges have adopted multiple methodologies to achieve this: