by Owen Hobbs
In numerous ways, markets can resemble the waves of the ocean. Both have peaks, bottoms, and ultimately return to a midpoint or sea level. The approach one takes to navigate the waves is largely dependent on the weather or market conditions affecting them. In this article, we are going to discuss a few of the ways someone using Hummingbot could navigate the various market conditions such as ranging, uptrend, and downtrend.
by Kyle Mizui
Trading is a rewarding and risky activity. If you’re new to hummingbot, welcome! You’re in the midst of a mature community that has found market making to be both exciting and profitable in the long term. That might be you, but before you go all-in and mortgage your house in crypto trading, here are top seven pitfalls and misconceptions that all Hummingbot beginners face. This article works best if you’ve at least spent some time taking Hummingbot on a test drive, but it’s by no means a requirement. Read it well, as they say, prevention is better than cure, and a dollar saved is a dollar earned.
In this guide, we will delve into various strategies and configurations you can employ using Hummingbot:
Discover the range of strategies available in Hummingbot by visiting the Hummingbot Foundation’s documentation site: Hummingbot Strategies
Learn about the global configurations applicable to most strategies: Global Configurations
Cross-exchange market making is a maker-taker strategy that involves conducting market-making trades between two markets: it involves placing limit orders in a market with lower liquidity and larger spreads, and placing market orders in a market with higher liquidity and smaller spreads whenever the limit orders are filled.
Arbitrage and cross-exchange market making are often considered "risk-free" because these strategies significantly reduce the main risk associated with market making: inventory risk. This characteristic makes these strategies more beginner-friendly. However, the primary risk that persists is execution risk.
This article will cover: 1. The fundamental principles of cross-exchange market making 2. The distinctions between cross-exchange market making, arbitrage, and pure market making strategies 3. The appropriate circumstances for employing this strategy
An order book is the list of orders that an exchange uses to record the interest of buyers and sellers for a particular financial market. A matching engine uses the book to determine which orders can be fully or partially executed.
Example of an order book on AscendEx where the prices in red indicate sell orders and the prices in blue indicate buy orders.
by Martin Kou
Update (February 2023): Hummingbot Gateway v2 is now available as a standalone Github repository: https://github.com/hummingbot/gateway. Most of the functionality listed in this post has now been implemented, and we welcome contributions from the community.
In Part 1 of this series, we have discussed the architectural changes we are making to Hummingbot Gateway v2 to improve its robustness and reliability, to bring it up to the service quality level expected of production trading systems.
by Martin Kou
Update (February 2023): Hummingbot Gateway v2 is now available as a standalone Github repository: https://github.com/hummingbot/gateway. Most of the functionality listed in this post has now been implemented, and we welcome contributions from the community.
Hummingbot Gateway is a software that allows Hummingbot to connect to decentralized exchanges like Uniswap.
The Hummingbot Gateway is a separate piece of software apart from Hummingbot, because software libraries needed for accessing decentralized exchanges, e.g. the Uniswap Smart Order Router, are usually not written in Python. The gateway provides Hummingbot access to these decentralized exchanges with their differing software stacks, by exposing a secure and unified API interface to Hummingbot. This API interface can also be used by other potential gateway clients, such as proprietary trading software.
In the last article - Hummingbot Architecture - Part 1 - of this series, we've discussed the design motivations behind Hummingbot, the clock and the market connectors. Today, we'll be discussing the architecture behind trading strategies - the very component that decides Hummingbot trades with your money. We will also discuss how you can diagnose problems and debug Hummingbot in live trading.
In our previous blog post, we introduced the new avellaneda_market_making strategy. This time, we delve deeper into the mathematical aspects of this strategy. We aim to explain how we adapted the original Avellaneda-Stoikov model for the cryptocurrency market and simplified the calculation of key parameters, known as greeks.
This article mathematically substantiates the assumptions and calculations that made the authors' model more suitable for Hummingbot traders.
Let's start by revisiting the core equations from the Avellaneda-Stoikov paper:
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.