high frequency equities trading & microstructural cost...
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Agenda
• HFT – Benefits and Challenges
• Studying the Challenges
– Analyzing an Institutional Order: Separating Impact & Timing Costs
– VWAP Versus Implementation Shortfall Algorithms
– Dark Aggregating Algorithms
• Conclusion
What is High-Frequency Trading?
• Generally fall into two broad categories:
– (1) Electronic Market Making
• Try to profit from the spread between bid and ask prices
• Rarely hold positions over night
• Benefit from „liquidity rebates‟ paid by exchanges and
market centers
– (2) Statistical Arbitrage
• Identify and capitalize on inefficient pricing of
financial instruments
• Market efficiency
• Information/Interest arbitrage
– Inter-venue latency arbitrage
– „Trading ahead‟ of significant order flow
Speed is Everything
• Need ultrafast, high capacity systems to thrive
– Freshest market data on every tradable security
• Nasdaq ITCH or BATS‟ FASTPITCH vs SIP feed (Securities
Information Processor)
• Co-location
– Absolute most minimum time delay, or latency
• EMM‟s send and cancel thousands of orders simultaneously
to effectively manage risk
Impact of HFTs
• Benefits
– Liquidity provision
– Decreased bid/ask spreads & lower fees
• Challenges
– Shift of exchange rebates to EMM shops
– Information/Interest Arbitrage
– „Interpositioning Effect‟
• In James Brigagliano‟s testimony before the Senate
Banking Subcommittee on Securities, Insurance &
Investment, October 28 of last year:
– “This quicker access could, for example, enable
high-frequency traders to successfully implement
„momentum‟ strategies designed to prompt sharp price
movements and then profit from the resulting short-
term volatility”
– “In combination with a „liquidity detection‟
strategy that seeks solely to ascertain whether
there is a large buyer or seller in the market (such
as an institutional investor), a high-frequency
trader may be able to profit from trading ahead of
the large order”
Challenges
Inter-venue Latency ArbitrageInterpositioning Effect: Case 1
$30.22
Bid
$30.24
Offer
$30.23
Bid
$30.24
Offer
Broker enters $30.23
Bid on Nasdaq,
decreasing spread
to $0.01
An HFT sees this on his Nasdaq ITCH feed
before others relying on the
consolidated feed and INSTANTANEOUSLY
bids $30.23 on another venue such as
BATS, NYSE Arca or Direct Edge
NasdaqBATS
$30.21
Bid
$30.25
Offer
$30.23
Bid
$30.25
Offer
$30.24
Bid
Price-Time Priority DOES NOT apply across
venues
Trading Ahead with Speed AdvantageInterpositioning Effect: Case 2
$30.23
Bid
$30.26
Offer
$30.25
Offer
Nasdaq
$30.24
Bid
Broker
representing
Institution A may
want to sell 300
shares at $30.25
Broker
representing
Institution B may
want to Buy 300
shares at the
market
An HFT might step
in and bid $30.24
for 300 shares
Then instantaneously turn
around and sell at $30.25
to Institution B, beating
Institution A‟s broker to
the best offer
QSG Methodology
• Helping institutional investors deal with the challenges
• Analyze broker placements with a tick-based cost
methodology
– Separate the cumulative price impact from timing costs within
the Implementation Shortfall framework.
• Liquidity Charge (a)
– Cumulative price concessions
for liquidity
• Timing Consequence (b)
– Price impact of the market
during the execution horizon
• Execution Differential (Implementation Shortfall), = (a +
b)
– The Total Shortfall of the trade from Arrival Price
QSG Methodology
What is a „price concession‟? Your executed price compared
to the previous execution in the name: Individual
Liquidity Charge.
$30.21 Bid
$30.23
Offer
$30.22 (last
sale)
$30.23 (you)
$30.22 Bid
$30.24
Offer
$30.24 (you)
$30.24 Bid
$30.26
Offer
$30.26 (you)
100
Shares
100
Shares
100
Shares
$0.01 Individual
LC
$0.01 Cumulative
$0.01 Individual
LC
$0.02 Cumulative
LC
$0.02 Individual
LC
$0.04 Cumulative
LC
Avg Price = $ 30.24333
„Arrival Price‟ = $30.22
IS = 2.33 cents
LC = 2.33 cents
TC = 0
QSG Methodology
What is a „price concession‟? Your executed price compared
to the previous execution in the name: Individual
Liquidity Charge.
$30.21 Bid
$30.23
Offer
$30.22 (last
sale)
$30.23 (you)
$30.22 Bid
$30.24
Offer
$30.24 (NOT
you)
$30.24 Bid
$30.26
Offer
$30.26 (you)
100
Shares
100
Shares
100
Shares
$0.01 Individual
LC
$0.01 Cumulative
$0.02 Individual
LC
$0.03 Cumulative
LC
Avg Price = $ 30.245
„Arrival Price‟ = $30.22
IS = 2.45 cents
LC = 2.00 cents =
((100*0.01)+(100*0.03))/200
TC = 0.45 cents
QSG Methodology
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-100
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Basis Points Cost/Savings
Example of Shortfall Decomposition with Negative Timing
Consequence
Cumulative Liquidity Charge Timing Consequence Execution Differential
QSG Methodology
-80
-60
-40
-20
0
20
40
60
80
100
Basis Points Cost/Savings
Example of Shortfall Decomposition With Positive Timing
Consequence
Cumulative Liquidity Charge Timing Consequence Execution Differential
QSG Methodology
-120
-100
-80
-60
-40
-20
0
20
40
60
80
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Basis Points Cost/Savings
Example of Shortfall Decomposition with Varying
Timing Consequence & Liquidity Premium (Europe)
Liquidity Premium Cumulative Liquidity Charge Timing Consequence Execution Differential
QSG Methodology
• Classifying orders with a popular price-momentum stock
selection signal
• Industry Relative Reversion
-60.00
-50.00
-40.00
-30.00
-20.00
-10.00
0.00
10.00
20.00
D1 D2 D3 D4 D5 D6 D7 D8 D9 D10
Basis Points
Shortfall Decomposition of Buy/Cover Trades In
Stocks Deciled By Industry Relative Reversion:
Russell 1000; 2008 - 2010YTD
-60.00
-50.00
-40.00
-30.00
-20.00
-10.00
0.00
10.00
20.00
D1 D2 D3 D4 D5 D6 D7 D8 D9 D10
Basis Points
Shortfall Decomposition of Sell/Short Trades
In Stocks Deciled
By Industry Relative Reversion: Russell 1000;
2008 - 2010YTD
Liquidity Charge Vs. „Market Drift‟
• Timing Consequence (a.k.a. „Market Drift‟) nets to ZERO
over many orders and investment strategies
• Cumulative Liquidity Charge is the persistent cost to the
investor over time
-120.00
-100.00
-80.00
-60.00
-40.00
-20.00
0.00
20.00
Jan-08
Mar-08
May-08
Jul-08
Sep-08
Nov-08
Jan-09
Mar-09
May-09
Jul-09
Sep-09
Nov-09
Jan-10
Mar-10
May-10
Jul-10
Basis Points
Average Monthly Timing Consequence for Orders
in Stocks in the Tail and the Middle of a
Distribution of Relative Rank Against Industry
Relative Reversion (Russell 1000, 0-5% ADV)
Timing Consequence (Tail)
Timing Consequence (Middle)
-25.00
-20.00
-15.00
-10.00
-5.00
0.00
Basis Points
Average Monthly Liquidity Charge for Orders
in Stocks in the Tail and the Middle of a
Distribution of Relative Rank Against
Industry Relative Reversion (Russell 1000,
0-5% ADV)
Liquidity Charge (Tail)
Liquidity Charge (Middle)
Impact of HFT on the VWAP Strategy – An
Example
• Do VWAP algorithms‟ impact-driven execution strategy
cost more to execute?
• Is this cost attributed to liquidity concession or
timing consequence?
VWAP Study - Sample Set
• QSG client data with algorithm flags
• 1/1/2009 through 8/05/2010
– Over 55 thousand orders
– More than $18B executed value
• VWAP and Arrival Price algorithms
• control group
– All orders ~1% ADV
• experimental group
– All orders ~1% ADV, < $10 stock price and $0.01
bid/offer spread
Results – Overall
OverallAlgorit
hm
Market Trade
Velocity
(strikes/min)
Avg
% of
DV
Avg
Fills
Per
Order
Avg %
Adverse
Tick
(Client)
Avg % Adv
Tick
(Market)
No Spread/Price
Constraint
Arrival 82 1% 100 19% 16%
VWAP 65 1% 63 28% 17%
$0.01 Spread &
<$10 Price
Constraint
Arrival 126 1% 111 12% 9%
VWAP 116 1% 145 26% 10%
-60.00
-50.00
-40.00
-30.00
-20.00
-10.00
0.00
Arrival VWAP Arrival VWAP
No Spread/Price Constraint $0.01 Spread & <$10 Price Constraint
Basis Points
Effect of Stock Price and Spread Size on Shortfall Decomposition for VWAP and
Arrival Price Algorithmic Orders of Size 1% ADV
Liquidity Charge
Results - IRR Factor Quartile Screen
OverallAlgorit
hm
Market Trade
Velocity
(strikes/min)
Avg
% of
DV
Avg
Fills
Per
Order
Avg %
Adverse
Tick
(Client)
Avg % Adv
Tick
(Market)
No Spread/Price
Constraint
Arrival 92 1% 95 19% 16%
VWAP 72 1% 73 27% 17%
$0.01 Spread &
<$10 Price
Arrival 147 1% 118 13% 9%
-60.00
-50.00
-40.00
-30.00
-20.00
-10.00
0.00
Arrival VWAP Arrival VWAP
No Spread/Price Constraint $0.01 Spread & <$10 Price Constraint
Basis Points
Effect of Stock Price and Spread Size on Shortfall Decomposition for VWAP and Arrival Price Algorithmic Orders of Size 1% ADV,
Ranked in the Top/Bottom Quartile of IRR over R1K on the Trade Date
Liquidity Charge
Results with IRR Factor Quartile Screen (Normalized)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
Arrival VWAP Arrival VWAP
No Spread/Price Constraint $0.01 Spread & <$10 Price Constraint
Bid/Offer Spread Units
Effect of Stock Price and Spread Size on Spread-Adjusted Liquidity Charge for VWAP and Arrival Price Algorithmic Orders
of Size 1% ADV, Ranked in the Top/Bottom Quartile of IRR over R1K on the Trade Date
Spread-Adjusted Liquidity Charge
How Prevalent is HFT in the Dark?
• Top 4 pools allow HFT flow, Bottom 4 do not
Source: Rosenblatt Securities
Daily Volume
(Millions)
Dark Toxicity Example
• Venue Analysis view on QSG‟s SYNC transaction cost
management platform for an institutional order in ECPG
(Encore Capital Group, 478 M Market Cap):
• NFSC (Dark Aggregator) showing poor execution quality
with respect to:
• Avg Trade Size
• Liquidity Charge
• % Adverse Tick Client
Dark Toxicity Example
• ECPG on June 9th, 2010, 2:20:0 PM – 2:30:00 PM EST
• Midpoint Spread Dark Seller residing in all pools (via
an Aggregator) with a low limit price of $18.45
1
2
3
4
(1)The bid side of
the book is taken
out by visible
executions at
$18.46(2) Milliseconds
later, the
offering side of
the book is walked
down $0.11(3) The Dark Sell
order is
executed at a
B/D‟s internal
dark book at
$18.455(4) Within 5
seconds the
offering side
moves up $0.06
and within 10
seconds it is up
$0.18 from the
execution
9 ½
min
30
sec
Dark Aggregator Analysis
• Same methodology can be applied across dark execution
channels to measure signaling risk, toxicity and
quality of execution
– Comparison of 3 B/D Dark Aggregators
• $1B – $10B cap stocks
• 5% - 25% ADV
– Execution quality measures used:
• Implementation Shortfall
• Liquidity Charge
• 15-Min Post Trade Price (Adverse Selection)
• 20% Participation-Weighted VWAP
Dark Aggregator Analysis
-35
-30
-25
-20
-15
-10
-5
0
5
Dark Aggregator 2 Dark Aggregator 1 Dark Aggregator 3
Basis Points
Execution Quality Measures By Dark Aggregator
Arrival Price Shortfall (bps) Liquidity Charge (bps)
Dark Aggregator Analysis
-12
-10
-8
-6
-4
-2
0
2
4
Last Print
5Min 10Min 15Min 30Min 60min
Basis Points
Average Post-Trade Reversal By Dark
Aggregator
Dark Aggregator 2 Dark Aggregator 1
Dark Aggregator 3
Algorithm
% Value
Executed
Off-
Exchange
%
Liquidity
Charge
From Off-
Exchange
Dark
Aggregator 167% 65%
Dark
Aggregator 246% 46%
Dark
Aggregator 351% 74%
Conclusions
• VWAP algorithms show increased parceling
activity and increased adverse tick execution in
stocks below $10 in Price having $0.01 Bid/Offer
Spreads when compared to Arrival Price
algorithms
• Costs attributed to Liquidity Charge and
Execution Differential also increased, but
Liquidity Charge is more pronounced, especially
when screening trades by the Industry Relative
Reversal ranking
• Increased adverse ticks and Liquidity Charges
suggest disadvantages at the micro structural
level
• Methodology can be applied to next-generation
These materials are confidential. Distribution is Prohibited.
© 2010 Quantitative Services Group LLC. All Rights Reserved.
The examples in this presentation are for information purposes only and do not constitute investment advice or any recommendation to
transact. Investors should consider the appropriate professional advice before making an any investment decision.
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