Modern US Equity Market Structure Rise of Off-Exchange Trading Very fragmented and highly automated A product of regulatory changes and rapid advances in technology

Modern US Equity Market Structure Rise of Off-Exchange Trading 11 Exchanges Nearly 50 “Dark Pools” Variety of Fee Structures and Business Models 1998: Regulation ATS opened the door to the creation of ECNs, ATSs, and off exchange trading venues (“Dark Pools”) 2000: Decimalization increased competition to quote spawning the creation of Electronic Market Makers and other types of HFT 85% of KO traded on NYSE before… 2007: Regulation NMS required exchanges to route marketable orders to venue with best quote, ensuring price priority across venues and opening the door to increase competition …but only 25% after Reg ATS, Decimalization, and Reg NMS Source: Bernstein

Modern US Equity Market Structure The Rise of HFT HFT grew aggressively, became less profitable, and is now cashing out Getco bought Knight Capital (KCG) Virtu IPO Flow Traders IPO Regulatory changes and technological advancements allowed HFT to flourish Source: TABB Group Though the space has become less profitable More in dark, tighter spreads, smaller trade sizes Source: TABB Group Source: Fidessa

Modern US Equity Market Structure Market Response - IEX & Flash Boys Michael Lewis’ “Flash Boys” released on March 31, preceded by 60 Minutes feature on Sunday prior IEX expected to launch exchange in Q1 2016 IEX steadily gaining market share

Modern US Equity Market Structure Diverse Locations for Trading Centers Source: datacenterknowledge.com

Modern US Equity Market Structure Latency Arbitrage Source: qz.com

Modern US Equity Market Structure Securities Information Processor (SIP) Arbitrage Source: qz.com

Modern US Equity Market Structure High Frequency Trading In Action – 500 milliseconds Source: Nanex

AUTOMATED DECISION MAKING – BROKER ALGORITHMS Automated Decision Making plays a vital role in today’s equity markets and is the core underpinning of broker algorithms. Broker algorithms provide mutual funds, hedge funds and other types of funds the ability to execute their large orders intelligently in a complex environment. These algorithms could be described as a “search engine” – find the best and most relevant results based on limited information and a broad spectrum of choices. The decisions made by these algorithms are based on a multiple of factors: How many shares are you trying to execute? What is the objective of the algorithm in terms of trading style? What trading venues are available to chose from and where are they located? What is the current supply and demand? What estimations can be applied? How do we deal with gaming factors (High Frequency Trading)?

AUTOMATED DECISION MAKING – BROKER ALGORITHMS Brief Overview of Automated Trading Process Source: maroonanalytics.com

AUTOMATED DECISION MAKING – BROKER ALGORITHMS Supply and Demand – A View of Buyers and Sellers at Various Prices Source: Bloomberg