Katya Malinova PRO
I am an Associate Professor, Mackenzie Investments Chair in Evidence-Based Investment Management at the DeGroote School of Business, McMaster University, Canada.
Systematic volume spikes and intraday liquidity patterns:
Fingerprints of HFT activity?
Discussion by Katya Malinova
Will J. Armstrong, Laura Cardella, and Nasim Sabah
Main Results
"Non-macro-news days" still have "teeth"
Volume "clusters" at discrete time nodes
Only partially explained by news anouncements
- Conjecture:
- "volume spikes" driven by HFT rebalancing activity
- \(\Rightarrow\) Propose a new HFT proxy:
- use the "spikes" as a proxy for HFT liquidity provision
Main Results
Key Insight: Trades Cluster!
No such thing as "steady trade/order flow
\(\Rightarrow\) Caution is needed when interpreting traditional (esp. time-weighted) measures
- Malinova and Park (2019 WP):
- 67% of dollar volume in "within-10ms-clusters"
- Admati&Pfleiderer (1988)
- Easley, Lopez De Prado, O'Hara (RFS 2012):
- "The most important aspect of high frequency modeling is that trades are not equally spaced in terms of time."
- Mandelbrot and Taylor (1967): true even in 1960s
Key New Insight
Trades Cluster at Discrete Nodes
Volume is (predictably?) higher at 10:00, 10:30, 11:00, 11:30,...
- Broussard and Nikiforov (2014; "Intraday periodicity in algorithmic trading"; Journal of International Financial Markets, Institutions and Money) document similar patterns
- 30-second buckets
Broussard and Nikiforov (2014): Volume
Broussard and Nikiforov: % Changes in Volume
Question: What causes the spikes?
The authors:
- "almost surely machine based" \(\Rightarrow\) HFT
- + improvements in liquidity
- \(\Rightarrow\) Conjecture:
- HFT aggressively rebalancing their inventories
- Coordinate on discrete points to "pool liquidity"
Alternate explanations?
Question: What causes the spikes?
Broussard and Nikiforov (2014):
- a result of optimizing behavior by algorithms that seek to concentrate their trading.
- a side effect of humans’ (programmers) tendency to prefer round numbers.
- Third alternative = the combination of the two:
- only some algorithms have rigid round time marks
- influence the behavior of “smarter” algorithms that do not have such constraints.
- They claim to support #2 but not #1.
Source: Doug Clark (ITG Canada); TSX Data on November 30 2011
Orders submission periodicity (sub-second)
- Buy-side algos split orders across time
- These algos may revisit the mkt every few ms/sec/min
- \(\Rightarrow\) trading at predictable times and (?) predictable quantity
Likely "machine based" -- but need not be HFT
- \(\Rightarrow\) may well be HFT trading during spikes
- but not necessarily because of rebalancing inventory
Question: What causes the spikes?
Question: What causes the spikes?
Suppose buy-side algos trade at discrete nodes:
- If aggressive \(\Rightarrow\) HFT may post aggressively in anticipation
- Or: if buy-side uses aggressive limit orders, HFTs may trade against these passive orders
Can we identify/disentangle cause and consequence?
\(\Rightarrow\) improvements in the spreads possible in either of these
Other features may also match the authors' findings, e.g. more prominent/easier to detect in small stocks
Measure of HFT Liquidity Provision?
What about the costs?
If HFTs respond to predictable buy-side trading:
- can still be viewed as "providing liquidity"
- Irrespective of whether HFT is passive or active
- \(\Rightarrow\) Volume at the "nodes" may correlate with HFT liquidity provision
- But: volume spikes may also be present with little HFT participation ...
Dig deeper into "spikes" & liquidity?
If HFTs "front-run" predictable, say, buy orders
- cancel/take out the asks, "run the price up"
- sell "high" and then buy as the price reverts to "normal"
Spreads can be higher but what about price changes?
- Do you observe price changes around the "nodes"?
- Before or after the "nodes"?
- If "front-running" \(\Rightarrow\) the price impact of trades at the nodes may be low or even negative -- yet a cost!
- Caution when dealing with events:
- Can event-related spikes driven by a single event (i.e. major unexpected news on one particular day)?
Other Comments
- More explanations, precise regression equations, robustness?
- Timeframe? 1 second is not that short ....
- Intraday Amihud: correlation with other intraday measures?
- Economic magnitude (% spread \(\times 10^6\) in bps?)
Filtering the announcements:
- Does Ravenpack do it or did you do this manually?
- What is news is delayed?
@katyamalinova
malinovk@mcmaster.ca
slides.com/kmalinova
https://sites.google.com/site/katyamalinova/
Discussion WiMM 2019
By Katya Malinova
Discussion WiMM 2019
This is a discussion that I gave at the Women in Microstructure Meeting June 2019. The slides are arranged in a "2x2 table" and meant to be viewed " column-by-column".
