Flash Crash Systemic Event

Description

This lecture delves into the systemic event known as the flash crash, exploring how it propagated from futures to stocks, options, and other commodities, causing market chaos. The instructor discusses the regulatory response, the importance of understanding latency in trading systems, and the impact of latency on market volatility. The lecture also touches on the role of high-frequency trading strategies, the measurement of latency, and the implications of introducing additional functionality into trading platforms.

Official source

https://mediaspace.epfl.ch/media/0_9y68i5v5

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related concepts (26)

Algorithmic trading

Algorithmic trading is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. This type of trading attempts to leverage the speed and computational resources of computers relative to human traders. In the twenty-first century, algorithmic trading has been gaining traction with both retail and institutional traders. A study in 2019 showed that around 92% of trading in the Forex market was performed by trading algorithms rather than humans.

High-frequency trading

High-frequency trading (HFT) is a type of algorithmic trading in finance characterized by high speeds, high turnover rates, and high order-to-trade ratios that leverages high-frequency financial data and electronic trading tools. While there is no single definition of HFT, among its key attributes are highly sophisticated algorithms, co-location, and very short-term investment horizons in trading securities. HFT uses proprietary trading strategies carried out by computers to move in and out of positions in seconds or fractions of a second.

Automated trading system

An automated trading system (ATS), a subset of algorithmic trading, uses a computer program to create buy and sell orders and automatically submits the orders to a market center or exchange. The computer program will automatically generate orders based on predefined set of rules using a trading strategy which is based on technical analysis, advanced statistical and mathematical computations or input from other electronic sources. These automated trading systems are mostly employed by investment banks or hedge funds, but are also available to private investors using simple online tools.

Day trading

Day trading is a form of speculation in securities in which a trader buys and sells a financial instrument within the same trading day, so that all positions are closed before the market closes for the trading day to avoid unmanageable risks and negative price gaps between one day's close and the next day's price at the open. Traders who trade in this capacity are generally classified as speculators. Day trading contrasts with the long-term trades underlying buy-and-hold and value investing strategies.

Program trading

Program trading is a type of trading in securities, usually consisting of baskets of fifteen stocks or more that are executed by a computer program simultaneously based on predetermined conditions. Program trading is often used by hedge funds and other institutional investors pursuing index arbitrage or other arbitrage strategies.