Summary:

  • Order book is the most common technique used to match buy and sell orders on exchanges 
  • Due to the information provided such as pricing, availability, trading volume on order books, they aid in increased market transparency
  • An order book is divided into three sections: purchase orders, sell orders, and order history

A crypto order book: What is it?

While buyers and sellers in the cryptocurrency spot market are apparent, it might be more challenging to picture the order book without physically going to a crypto exchange. 

An order book essentially allows traders to place the most recent buy and sell orders. The book allows for the placement of both buy and sell orders. The sell orders are presented in red, while the purchase orders are displayed in green. Users can accept an order already in the order book or enter a new order at a different price. An order book is a kind of digital ledger that lists the buy and sell orders for a certain exchange.

Furthermore, it’s crucial to remember that centralised cryptocurrency exchanges, which are typically chosen by both crypto newbies and institutional investors, employ this type of ledger. An order book is a crucial element of a centralized crypto exchange. It guarantees a higher degree of transparency, but to use this to your advantage – whatever strategy you’re using – you should be able to read the data provided.  Liquidity pools are their DeFi counterparts.

An order book is dynamic since it is updated daily in real-time. The continuous book is how it is referred to on exchanges like Nasdaq. Orders that call for execution right at the opening or closing of the market are kept separate. The terms opening (order) book and closing (order) book refer to them, respectively.

For instance, the Nasdaq market opens with the opening and continuous books combined to provide a single opening price. When the market closes, the closing book and continuous book are combined to produce a single closing price. 

Reading an Order Book

An order book typically consists of three components: buy orders, sell orders, and order history.

  • Buy orders include information on the buyer, such as all the bids and the quantity they want to buy.
  • In contrast to buy orders, sell orders contain all of the offers (or asking prices) or locations where users are eager to sell.
  • Market order histories list each transaction that has ever been made.

The highest bid and lowest ask prices are at the book’s top. These indicate the primary market and the price required to fill an order. A candlestick chart that offers helpful information about the market’s past and present situation is frequently included in the book.

The order book aids traders in making better trading choices. They can assess whether institutional or individual investors are driving market activity by determining which brokerages are buying and selling assets. The order book also reveals order imbalances that might explain an asset’s short-term trajectory.

For instance, a significant disparity between buy and sell orders may signal a rise in the stock price due to purchasing pressure. Traders may also use the order book to identify probable support and resistance levels for a stock. An excess of sell orders at or around one price may indicate a region of resistance. In contrast, a concentration of numerous purchase orders at a specific price may indicate a level of support.

FLUID’s Global Order Book – A Primary Model vs. Traditional Statistical Quant Models

FLUID’s aggregated order book technology addresses latency and market inefficiencies using proprietary AI-based predictive models. FLUID AI’s core platform aggregates liquidity from the spot, futures, and options markets within both CEXs and DEXs. The ability to predict order books with 99%+ accuracy into the future gives FLUID the ability to offer Best Execution to all liquidity seekers.

Research studies have indicated that statistical quant models are restricted in predictive precision due to their linear nature and inability to comprehend various variables of mass data, and this is where FLUID employs AI. Using Machine Learning and Deep Learning techniques, FLUID can comprehend macro and micro economic variables needed to predict the price of an aggregated order book more precisely. 

FLUID’s AI employs a proprietary hybrid cryptocurrency prediction model in which machine learning and deep learning are used to predict real-time order book prices with a high level of confidence. As cryptocurrency prices are dynamic and highly volatile with large volumes of data, preprocessing and feature selection affect the running of the model when harvesting real-time data.

FLUID is comprised of the following:

  • AI-based low-latency trading infrastructure
  • Liquidity aggregation across CEXs and DEXs
  • Crossing Engine
  • Margin trading
  • Delta-neutral strategies
  • Public and private tokenized market