they could put in place to insulate themselves from potential intraday losses. bis central bankers ’ speeches and to the integrity of the market. even if such acts are not intentionally misleading, they can still result in a false sense of market liquidity. finally, firms employing high volume automated trading strategies could harm market liquidity if they do not manage those strategies carefully, particularly given the significant share of market activity they represent. as i will explain later, the treasury market practices group has updated its best practices to emphasize the importance of supporting market liquidity as well as avoiding automated trading strategies that create a false impression of market price, depth, or liquidity. in conjunction with those best practices, the tmpg also released a white paper on automated trading that reviews several categories of associated risk, including operational risk, potential systemic counterparty risk, market manipulation risk, and transmission risk. october 15 let me now turn to the unusual events of october 15. on that day, treasury yields exhibited extreme volatility, with the benchmark ten - year yield trading in a range of about 35 basis points between the market open and close. this included a sharp decline in yields following the u. s. retail sales report at 8 : 30 et that morning, and a highly unusual round - trip in yields just after 9 : 33 a. m. at that time, the ten - year yield fell about 15 basis points in a five - minute period, before nearly fully retracing that move in roughly the same increment of time. that very short “ event window ” was a remarkable occurrence in one of the world ’ s most liquid markets, and likely reflected a unique dynamic on what was already an unusual day. indeed, the net change on the session as a whole was less than 10 basis points – a small fraction of the extraordinary intraday range that we are still discussing today ( see the chart ). bis central bankers ’ speeches historical examples of sharp intraday changes in u. s interest rates have tended to be associated with important economic events, such as major monetary policy announcements. there does not yet appear to be consensus by market participants around a single cause of the volatility on october 15. to be sure, a number of factors likely contributed, including concerns about the global macroeconomic outlook and the unwinding of positions by leveraged investors. indeed, such concerns probably help explain why a modest surprise in u. s. retail sales could trigger such a strong reaction around 8 : 30

requires a significant investment in technology and communications systems designed to reduce the amount of time necessary to transmit and process information. although high - frequency trading has garnered much attention in the media, it is worth pointing out that distinguishing between “ automated trading ” and “ high - frequency trading ” is not clear cut. in fact, many features ascribed to high - frequency trading, such as minimizing the time between trading decisions and execution, also apply to automated trading more broadly. automated trading is conducted by a range of different firms, including broker - dealers and specialized proprietary trading firms that trade without client money. firms specializing in automated trading generally participate in trading venues with “ protocols ” that allow for highspeed activity, most notably those operating with a central limit order book ( or “ clob ” ). clobs have long been a fixture of the futures, fx, and equity markets, and allow participating firms to place anonymous orders to buy or sell securities into a standing queue, and to rapidly execute such orders at any given moment in time. 7 in the treasury market, automated trading has become most pronounced in the treasury futures market and the interdealer market for on - the - run securities, both of which operate with a clob protocol. in fact, proprietary automated trading firms are believed to account for over half of the volume transacted over the major interdealer trading platforms. it is helpful to think of two basic types of automated trading strategies : those whose primary purpose is to earn a return by making markets, and those whose primary purpose is to generate excess returns – what market participants sometimes call “ alpha - seeking ” strategies. a market - making algorithm might be designed to supply liquidity to a clob under a set of rules that depend on, for example, historical analysis of market and order book dynamics. an alpha - seeking strategy, on the other hand, might better describe a set of trading practices that is more likely to consume liquidity to produce excess returns. examples of alpha - seeking strategies might be momentum detection, statistical arbitrage, and spread trading. 8 one important difference between most automated trading firms and traditional brokerdealers is their balance sheet properties. traditional broker - dealers generally carry net long or short positions in treasury securities from one day to another, an activity that requires capital. dealers hold treasuries for a variety of reasons, including to support the liquidity needs of their customers, to hedge exposure in other fixed - income products, and to