IS 356 IT for Financial Services http://www..evergreen.loyola.edu/~pptallon/is356.htm IS 356 IT for Financial Services The Search for Large Block Liquidity: From Liquidnet to OptiMark Please use this space for making ANNOTATIONS or for adding comments to individual slides.

Characteristics of an Ideal Market Certified confidentiality Price discovery at all sizes Liquidity available A frequent call or continuous market Cancellations at electronic speeds © Paul Tallon

The Block Trade Problem source: http://www.iinews.com/site/pdfs/TP_Spring_02_Merrin.pdf © Paul Tallon

Transaction Costs According to the Plexus Group, institutions on average incur hidden transaction costs of $.39 per share for every trade they make. This amounts to $100 billion in transactions costs each year. change in stock price Announcement Costs © Paul Tallon

Block Trading Video: Seth Merrin Click above to launch video. © Paul Tallon

Regulation coming soon… Almost 40% of US stock traded through dark pools but nobody knows who does what… we only know aggregate data monthly Click logo above for video. Might LiquidNet be able to dodge potential SEC regulations involving dark pool trading? © Paul Tallon

When and how would a dealer use Optimark rather than another market source? Options When How Nasdaq Desire to place order with a single price and quantity Loose network of broker-dealers serving as market makers. Use own K to buy/sell stocks and profit from spread between bid/offer prices quoted “real time” NYSE Desire for order driven trades of listed stock in auction market model Labor intensive Physical floor Via a specialist (1 market maker) ECN Desire to display order anonymously but disclosed to traders Seek lower cost structure Screen order book displays bids/offers of investors and continuously matches orders electronically Optimark Desire to place multiple orders with multiple price and quantities without disclosure to traders Indicate “willingness” to buy via graphical interface designating preferences Algorithm continuously matches orders electronically © Paul Tallon

OptiMark: Buy-side and Sell-side Large institutional investors such as mutual fund or pension managers on the “buy-side” Brokerage firms on the “sell-side” to help out their institutional clients Small retail investors who benefit from matching the aggregated interest of other small traders to a large investor © Paul Tallon

Innovative Idea New means of representing trading strategies based on simple color visualization of preferences Lighter colors reflect greater satisfaction For larger orders, I would be willing to pay more just to get the order executed but I cap the amount I am willing to pay when it reaches the black cells. Buy order Signal willingness to pay a little extra to have the order completed © Paul Tallon

Graphical rendering © Paul Tallon

Fees: OptiMark vs. Others NASDAQ – Revenues from commissions which can be 5 –10 cents a share, bid-ask spread and market impact, timing cost and opportunity costs ECN – Charge their users-per share access fees and charge commission to dealers OptiMark – Transaction fee of one cent per share from each side of a trade for member's own customer accounts. For trades in customer accounts, fee is paid out of brokerage commission © Paul Tallon

Value Proposition for Institutions Traditional Costs Trading cost for an Institution Commission 0.13 % Bid-Ask-Spread 0.27 % Timing Cost 0.43 % Opportunity 0.53 % Total 1.36 % OptiMark’s Cost Sell 1¢ / Share Buy 1¢ / Share Total 2¢ / Share 100,000 shares of Microsoft bought & sold at $50 Sell .0136% x 100,000 x $50 = $68,000 Buy .0136% x 100,000 x $50 =$68,000 TOTAL = $136,000 Sell 100,000 x 1 ¢ = $1000 Buy 100,000 x 1 ¢= $1000 TOTAL = $2,000 © Paul Tallon

NASDAQ – OptiMark Connectivity source: http://www.nasdaqnews.com/news/optichart.html © Paul Tallon

OptiMark Troubles $236m in funding from Merrill Lynch, Goldman Sachs, CSFB, PaineWebber and Softbank ($100m alone) Revenues $3m in 1999 – 75% came from 4 users!!! Typical daily volume was 1m shares, a few 3m+ days, so revenues were low (1,000,000 x $0.01 = $10,000); this eventually declined to 100k shares per day Not a specialist, so they could not provide capital or a source of liquidity to ensure a fair and balanced market Officially, they could trade 250 NASDAQ stocks, but their system was so complex, they could only manage 10 Most of their matches were found on the NYSE: TTR © Paul Tallon

For Next Class… Read Read the Oriental Fortune case study (emerging markets) We will review the case in class and discuss some other international initiatives to design efficient equity markets Second blog is due on Oct. 9 There will be an exam on Oct. 16 covering everything we’ve done so far © Paul Tallon