High Frequency Trading:
To be Nurtured or Banned?
By
Hans Degryse
KU Leuven and CEPR
Brussels Exchange Forum, April 25, 2014
Hot topic
• Michael Lewis book “Flash Boys”
• Investigation by FBI
…
Let me aim to summarize academic evidence…
Outline
1.High Frequency Trading (HFT):
– Definition
– Identification
– HFT in the US and Europe: some stylized facts
2.Impact of HFT: what does theory suggest?
3.HFT and market quality
4.HFT and market stability
5.HFT, social welfare and regulatory responses
1. High-Frequency Trading: Definition
Difficult animal to define. SEC (2014) defines them as:
1. Use of extraordinarily high speed and sophisticated programs for
generating, routing, and executing orders.
2. Use of co-location services and individual data feeds offered by
exchanges and others to minimize network and other latencies.
3. Very short time-frames for establishing and liquidating positions.
4. Submission of numerous orders that are cancelled shortly after
submission.
5. Ending the trading day in as close to a flat position as possible (that
is, not carrying significant, unhedged positions overnight).
1. HFT: Identification
Different methods
1. Direct classification based upon trader IDs, i.e. HFT Flag
– E.g. NASDAQ dataset (used by e.g. Brogaard, Hendershott and Riordan (2013),
Hirshey (2013), Zhang (2013)); ESMA dataset (Degryse, De Winne, Gresse and
Payne (in progress))
– Pure HFT firms
– Typically all HFT flags have co-location
2. Quantitative method employing “order-to trade ratios”, “intraday
inventory management”, or “order modification and cancellation
speed”
–
Apply to all IDs, apply to specific trades
–
E.g. E-mini datasets (e.g. Kirilenko et al. (2011)); Canadian dataset (e.g.
Malinova, Park and Riordan (2013), Euronext (e.g. Verschelden (2014)).
1. HFT: stylized facts (US)
1. HFT: stylized facts (Europe)
1. HFT: stylized facts (Europe (2))
•
HFT more important on Multilateral Trading Facilities than Regulated Markets
1. HFT: stylized facts (Europe (3))
•
Order-to-trade ratios of HFT much larger than other participants
1. HFT: stylized facts (Europe (4))
•
HFT more active in stocks that are more fragmented across trading venues ->
HFT “klit” together different trading venues (see Menkveld (2014))
1. HFT: stylized facts – general
• HFT is not a monolithic phenomenon but encompasses a
diverse range of trading strategies
• Not all HFT trading is passive
• NASDAQ dataset (Brogaard, Hendershott and Riordan (2013)):
more than half of trading is attributable to liquidity taking (market)
orders, even more so in small cap stocks
• UK dataset (Benos and Sagade (2012)): less than half of trading is
liquidity taking
• HFT much less active in small stocks in the US; seems less the case in
Euronext (Verschelden (2014))
• Quite some variation across countries within Europe (ESMA (2014))
2. HFT – Theory
• Theory essentially models two forces : speed and information
• Implications for HFT, other traders, social welfare
1) Speed
• Hoffmann (JFE forth)
• fast traders reduce exposure to picking off risk -> beneficial for HFT and
social welfare
• Presence of fast traders changes strategies of slow traders that submit limit
orders with a lower execution probability such that trading rate declines
• Speed endogenized: speed is market power and allows to extract rents
from slower traders => arm’s race leading to overinvestment from a social
welfare perspective
• Calls for randomized “speed bumps” as now inplemented in some FX
markets
• Menkveld and Jovanovic (2012):
• HFT may lead to more competition reducing spreads
2. HFT – Theory (2)
2) Information – advantage of machines over humans is ability to process vast amounts of
information at superhuman speed
•
Jovanovic and Menkveld (2012):
• HFT process hard information faster which lowers adverse selection for them
• But they throw an adverse selection problem on others
• Calibration exercise shows that social welfare improves
•
Biais, Foucault and Moinas (2013):
• HFT have a higher likelihood of finding trading opportunities which induces a higher trading rate which is
good for welfare
• but HFT expose in this way adverse selection on others reducing trading rates and thus welfare.
3) Combination of these two:
•
Bernales and Daoud (2013)
• HFT benefit in two ways: (1) picking off “stale” orders (2) react faster on information => slow traders
modify their strategies and trade more through market orders
• Benefit or cost to slow traders depends on their relative presence: if many slow traders, picking off risk
dominates and they are worse off; if few slow traders, HFT are beneficial.
• HFT with informational advantage is good for welfare; HFT with only speed advantage is bad for welfare;
having both is better for welfare => suggests 70% of HFT is optimal
•
Bongaerts and Van Achter (2013):
• endogenize number of HFT and slow traders => HFT drive some slow traders out of market.
• With substantial asymmetric information, HFT shun the market inducing slow traders also to leave =>
endogenous market freezes and small crashes.
3. HFT and Market Quality
• Fragmentation in “lit markets” (proxy for HFT) improved market quality but
dark trading decreased it (see e.g. Degryse, de Jong and van Kervel (2013))
• HFT effect on market quality:
• Passive HFT strategies have beneficial effects: lower spreads and intraday volat
• Jovanovic and Menkveld (2012) find that the entry of a large, primarily passive HFT
reduces spreads by 15% in Dutch markets
• Malinova, Park and Riordan (2013) exploit chock in exchange fees that affect HFT
traders and find that bid-ask spreads increase in Canadian markets
• Liquidity consuming activities of HFT less beneficial:
• More price impact (Zhang and Riordan (2011) for large stocks, Zhang (2013),
Brogaard, Riordan and Hendershott (2013))
• Competition between HFT harmful?
• Breckenfelder (2013) finds that when HFT compete there are more liquidity consuming
trades by HFT
• HFT may lead to “ghost liquidity” for slow traders
• van Kervel (2013) shows that trades executed in one venue lead to substantial
cancellations on other venues
4. HFT and Market Stability
•
•
Do HFT increase financial instability and systemic risk in financial markets?
Example: the flash crash, May 6, 2010
•
Role of HFT in Flash Crash (see e.g. Kirilenko (2011)): not triggering the
shock but maybe deepening the volatility
Hagstromer and Norden (2013): more passive HFT activity reduces intraday
volatility.
Systemic risk concern:
• HFT have little capital
• HFT trade a lot with each other -> contagion?
•
•
5. HFT, Social Welfare and Regulatory Responses
• Evidence suggests that market quality has improved and markets may
have become more informational efficient
• Should be beneficial to firms and real economy
• However,
• Slow traders may need to change trading strategy and may ultimately be
worse off => switch from limit orders to market orders
• Is gain in informational efficiency socially productive? Information
would have been incorporated at slightly lower speed anyhow
• HFT may improve slow traders outcomes when they act as market
makers, but reduce slow trader welfare when picking-off risk
increases
• Should HFT be allowed to buy preferential treatment? Probably not!
• Earlier access to information releases is disturbing fair level playing field
• Co-location for every one -> should look into business model of RM and MTF
to see how this is allocated
5. HFT, Social Welfare and Regulatory Responses (2)
• Regulatory responses:
• Fair level playing field in terms of access to information
• If HFT by quote stuffing or excessive order flow delay other
participants -> introduce order withdrawal fees; but difficult to separate
“good” from “bad” order flow
• MiFID II: HFT strategies subject to regulatory authorization
• Change market structure: batch auctions every “xxx” milliseconds
• Some concluding thoughts
• HFTs have allowed new trading platforms to arrive and have induced
competition in trading and post-trading fees. Both are important as
“cum-fee liquidity” has improved substantially (see e.g. Colliard and Foucault
(RFS2012) and Degryse, Van Achter and Wuyts (2013))
• In sum, HFTs have been beneficial but regulators need to take care of
potential externalities
• Too much dark trading might be a more important concern (MiFID II)