This document discusses the centralization of markets through the Securities Information Processor (SIP) and National Best Bid and Offer (NBBO), which consolidate market data like bid/ask quotes and trades from various trading venues. It also describes high-frequency and algorithmic trading strategies, like latency arbitrage and index arbitrage, and how they provide liquidity but can also harm other investors. Dark pools are mentioned as markets that hide liquidity. The document analyzes market data from an event on August 24, 2015 and questions whether high-frequency traders exacerbated volatility.

1. Algorithmic & High-Frequency Trading
COMPLEXITY ARISING FROM CENTRALIZATION

2. Electronic Trading
• Open Outcry to Computer-based Execution
• Reduced Costs
• Greater Liquidity
• Tighter Spreads
• Increased Competition
• More Transparency
• Transition gained velocity in the early 2000s

3. SEC Regulation NMS (National Market System)
• Order Protection Rule – receive best price when executing an order.
• Access Rule – improve access to quotes from exchanges in the NMS by required linkages
and reduced access fees.
• Sub-Penny Rule – quotation increment for all stocks over $1.00/share to at least $0.01
• Market Data Rule – revenue allocated to organizations that promote and improve
market data access.
• Aimed at improving fairness in price execution, displayed quote data, and
access to market data.
• Prices are posted on all (most) exchanges simultaneously improving chances
for investors to ascertain the best price.

4. Centralizing the Markets
• SIP – “Securities Information Processor”
• Links US markets by consolidating all protected bid/ask quotes and
trades from every trading venue into a single data feed.
• NBBO – “National Best Bid and Offer”
• The best price (lowest available ask price / highest available bid
price)
• The “typical” bid/ask the average person sees.
• LULD – “limit up limit down” price bands
• Regulatory Halts & Short Sale Restrictions
• UTP – “Unlisted Trading Priveleges”
• Regulation the gives exchanges the right to trade securities
without meeting the minimum requirements (security not listed
or registered on the exchange)

5. Dark Pools
• No Swimming Allowed
• Markets/exchanges where liquidity is deliberately hidden
• Report trades to the SIP and trades recorded to the national consolidated
tape but with as much delay as possible (to reduce market impact) and
recorded as OTC transactions (detailed volume and transaction type data is
not reported)
• Market Impact
• Allow large blocks of shares to be traded while reducing the effect of such
size orders would have on the market price
• Liquidity seen by a trader in the book may not be an accurate reflection of
the true liquidity available.

6. Arbitrage Strategies
• Index and ETF Arbitrage
• Taking advantage of mispricing between indices and associated ETFs
• Statistical Arbitrage
• Does contribute to increased liquidity.
• Latency Arbitrage
• Increases liquidity at the expense of other investors/traders.
• Large order enters the market, HFT traders are able to buy shares from other exchanges (often a penny
or so cheaper) before the order hits the other exchanges.
• Market participants both receive a slightly less than best possible price had the middle man not been
present.
• Rebate Arbitrage
• Exchanges offer rebates or fees for making and taking liquidity
• Fees differ from between exchanges
• Would a broker route an order to an exchange that offers a rebate rather than charges a fee
resulting in an execution that may not give the best possible price to the client?

7. HFT Visualized

8. One Half of One Second of Trades in One Stock Around the World

9. Slowed Down to the Millisecond

10. Footprints of the Middle Man

11. No Shortage of Examples

12. The Bigger Picture Trumps All

13. August 24th, 2015
• LULD bands prevented a much more catastrophic event.
• Stocks such as AAPL traded in <2% ranges in under 60 seconds.
• AAPL itself opened -10%, fell to -12%, but closed +3%. Kudos to all of you
who bought under $93.
• The overall market rally into the end of the day became the
headline. Most don’t want to acknowledge that something was
seriously wrong, many have no idea, and the rest aren’t going to
risk their profits by saying anything.
• One headline did note that an HFT firm posted a record-breaking
profit that day.

15. Liquidity in eMini Contracts – 2008 to 2015

16. Futures Tick Data – 8/24/2015

17. Tick Data for 220 ETFs – 8/24/2015

19. AAPL – 8/24/2015 – 9:30am to 9:32am

21. Black Swan Events
• The Black Swan Theory was developed by Nassim Nicholas Taleb.
• The disproportionate role of high-profile, hard-to-predict, and rare
events that are beyond the realm of normal expectations in history,
science, finance, and technology.
• The non-computability of the probability of the consequential rare
events using scientific methods (owing to the very nature of small
probabilities).
• This is to say events that have a probability in the tail of a normal
distribution far (greater than 2 or even 3 Std Devs) from the center.
• Taleb advises a hedge fund that made in excess of 1 billion dollars
on August 24th representing a 20% increase in the firms valuation.

22. Some Final Thoughts
• Over 50% of all trades in the US equity markets are from algorithmic
execution of block orders but are represent an important tool controlled
execution of share blocks.
• HFT traders provide volume but not necessarily liquidity.
• Regulation on HFT and electronic market-making is being “reviewed and
implemented”. Just keep in mind the old saying: “Ye who has the gold
makes the rules”
• Look up the name Navinder Sarao, an individual trader who caused (was blamed
for causing) the 2010 flash crash.
• Algorithmic trading and HFT are here to stay.
• I want to the thank Nanex, LLC for the incredible images provided as well as their ongoing work in
analyzing the vasts amounts of market data and bringing to light many of the issues that would
otherwise never be known by the average investor. You can follow the founder of Nanex, Eric Scott
Hunsader, on Twitter @nanexllc.