Detailed summary (part 4/4) of Trading and exchanges (D0C14A) (18/20 first chance)

Part 4: Competition between trading venues; H4.1
Introduction to fragmentation in trading
-> applications precious chapters
1. Introducti on: some numbers

-> Trading in stock markets nowadays is very fragmented
-> The next slides provide some numbers for stocks in the BEL20 and the FTSE100
-> The source for all numbers is Fidessa Fragulator
-> MIFID1,2 regulate the competition between venues
-> Bel 20




-> FTSE100




=> Very fragmented
2. Pros and cons of fragmentati on


-> Competition effect
-> reduce costs and fees
-> improve performance
-> foster innovation
-> Different types of markets can cater to different needs and types of traders (large traders,
non- HFTs, liquidity traders… )




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Part 4

,-> Exchanges have natural monopoly under certain assumptions
-> Arbitrage (ask in one market is below bid in another)
-> Informed traders may be more difficult to detect
-> Potential for risk sharing is lower
-> Between traders
-> Search costs to detect the best price
-> can be automated via SORT, but still costly
-> Liquidity externalities
-> When all the people are the same venue, it is easier to find a match
-> It gives an incentive for a lot of traders to go for a large part to 1 venue




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, H4.2 Competition been Lit Venues
2. Two limit order market

-> Foucault and Menkveld (2008) study competition between 2 limit order books
-> A first part of the paper develops a theoretical model
-> assume there is an incumbent trading venue (exchange) and an entrant (alternative trading
system)
-> they allow for differences in order submission fees
-> 2 types of brokers exist
-> smart routers, who route orders across markets to obtain the best execution price
-> non smart routers, who ignore quotes in the entrant market and always trade in the
incumbent market
-> the latter traders generate so-called trade-throughs: the reasoning in the model is that
some traders only consider one market, and not the entrant market (which potentially
may offer a better price)
-> The model generates 2 main empirical predictions




-> This results is driven by the absence of time priority across markets
-> The reasoning is that it allows traders to jump ahead of the queue of limit orders in one market
by submitting a limit order in the competing market
-> Because there is no time priority across markets, only holds in one market
-> That’s gonna give an incentive to traders to submit more LO, witch gonna create more
depth




-> The intuition is that more smart routers increase the execution probability of limit orders
submitted to the entrant market
-> Their empirical analysis confirms these predictions
-> They analyze the entry of a new market (i.e. EuroSETS from the London Stock Exchange), next to
an incumbent market (Euronext) in the Netherlands
-> They find an increase in consolidated depth after the entry of EuroSETS
-> Secondly, also depth on the incumbent market Euronext increases after the entry
-> the reasoning is that Euronext reduced its fees around the entry of EuroSETS
-> The resulting increase in depth more than compensates the loss of order flow to
the entrant market
-> Finally, EuroSETS has lower spreads and a larger share in consolidated depth for
stocks with a larger proportion of smart routers



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Part 4