Glossary
Below are terms often used in the finance industry. Here we explain precisely how we understand those terms.
Backtesting
Section titled BacktestingBacktesting is the process of running a trading strategy (or algorithm) on past historical data to assess past performance on various datasets. If acceptable performance is observed, the strategy must be worth worked on and eventually traded live on exchanges.
Dataset
Section titled DatasetDatasets are types, or shape, of data that is relevant to different analysis tasks. Analysts select the right dataset depending on the study.
Derivative
Section titled DerivativeQuoting from Investopedia, Derivatives are financial contracts, set between two or more parties, that derive their value from an underlying asset, group of assets, or benchmark. A derivative can trade on an exchange or over-the-counter. Prices for derivatives derive from fluctuations in the underlying asset.
In crypto, derivatives can trade on an exchange or on-chain. Here are the different types that we identify:
- Futures
- Perps (aka Perpetual futures, Perpetual swaps)
- Vanilla options (aka Options, Warrants)
- Futures spreads (aka Calendar spreads) are a combination of futures contract that are listed as one product (Deribit).
- Option strategies are specific combination of options that are listed as one product (Deribit).
- Other derivatives collectively referred as swaps, such as leveraged tokens.
Financial instrument
Section titled Financial instrumentAn instrument is a tradable asset. Instrument widely traded in crypto finance are spot and derivatives.
Quote
Section titled QuoteQuote is quite an overloaded term in finance and can mean many things. However in the context of crypto data, it usually refers to top-of-book levels (i.e. best bid best offer, BBBO), usually with associated quantities available, recorded every time the best bid/ask price changes (or quantities available for them).
- It is equivalent to orderbook snapshots, limited to one level, updated at every top-of-book change.
- It is commonly refered as L1 orderbook data.
- It represent the marginal price at which you can trade an instrument at an exchange.
- It is handy to provide an estimation of the price of an instrument at every time, as opposed to trade data that is usually much less frequent and that typically needs to be interpolated in order to produce an homogenous time serie.
Symbol
Section titled SymbolA symbol is the code of an instrument traded on an exchange. For spot, the name is usually a concatenation of the base currency and the quote currency, e.g. (BTC/USD or BTCUSD). For derivatives, the symbol often contains information about the underlying instrument traded (e.g. BTC-PERP).
Some exchanges sometimes have symbols not referring instruments but time series such as index prices, etc.
The spot market is where financial instruments, such as commodities, currencies, and securities, are traded for immediate delivery. (Investopedia), i.e. the immediate exchange of a cryptocurrency against another crypto, a stable coin, or a fiat currency.
Timestamp
Section titled TimestampDigital record of the time of occurrence of a particular event.
When sourcing data from a stream (usually a websocket connection), we record at least two timestamps:
- remote timestamp is the creation time of the message at the source (i.e. the time at which the matching enginer recorded a trade).
- local timestamp is the time at which we read the message from the stream.
Some exchanges provide additional timestamps, i.e. the time at which they sent the message in the connection (vs the time of the event’s creation).