This is an extensive summary. In this summary you can find a sentence or two about each graph and figure based on the authors conclusion. Mainly, it contains some important aspects from the paper. I took out of the article the main important parts.
Exchange-Traded Funds, Market Structure, and the Flash
Crash
Title, authors, journals
Title: Exchange-Traded Funds, Market Structure, and the Flash Crash
Author: Ananth Madhavan
Journal: Financial Analysts Journal
Research Question + underlying intuition
Research Question: Is market structure important in understanding the propagation of a liquidity
shock?
I hypothesize that order book liquidity for securities that experience market fragmentation is more
susceptible to the effects of transitory order imbalances.
Were securities with greater fragmentation prior to 6 May 2010 disproportionately affected during
the flash crash?
Underlying intuition: The author analyses the relationship between market structure and the flash
crash. The proliferation of trading venues has resulted in a market that is more fragmented than
ever. The author constructs measures to capture fragmentation and shows that they are important in
explaining extreme price movements. New market structure reforms should help mitigate such
market disruptions in the future but have not eliminated the possibility of another flash crash, albeit
with a different catalyst.
- This article instead focuses on the relationship between market structure and the flash crash
without taking a view on its catalyst.
- My hypothesis is that equity market structure is a key determinant of the risk of extreme
price changes.
Main methodology
From the slides
Technological Advancement from the side of the trader
– Algorithmic Trading
– High Frequency Trading
, HFT’s: – Firms using investor capital to trade for their own account using algorithms / high-frequency
strategies
What types of strategies?
– Liquidity Making strategies
• Market making (remember Flow Traders clip)
– Liquidity Taking strategies
• Fake quotes to manipulate prices
– Spoofing, Layering, Quote stuffing
• Arbitrage
– Between trading venues – Events – Statistical – Index
• Ticker tape trading
• News based trading
A review of the Flash Crash
- He explained how it happened
- Some possible reason for the crash
o Fat finger
o Error in algorithm
- The official reason was related to a broker who traded mini-futures
Data Sources and Procedures
- Sample selection
- Measures of Fragmentation
Empirical Analysis
- Descriptive Statistics
- Time-Series in Fragmentation
- Determinants of Market Fragmentation
- Analysis of Drawdown
, - Table 1 shows the venue shares of the U.S. equity market for December 2011 based on all
reported trades and quotes.
- The first column represents the share of dollar volume.
- The second and third columns capture the market shares in quotation frequency and total
dollar quoted depth (i.e., liquidity available at the inside quote), respectively.
- In terms of the statistics reported above, markets are less fragmented from a quotation
perspective.
- In particular, the shares of NASDAQ and NYSE Arca as a fraction of all quotes at the best bid
or offer are larger—34.7% and 21.9%, respectively, versus 23.8% and 16.5% of total dollar
volume.
- Note that in terms of venues’ shares of total inside liquidity (i.e., total liquidity at the best bid
or offer), the market is a little less concentrated compared with looking at just the frequency
of quotes.
- At the single stock level, of course, these differences are not significant
Discussion of findings.
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