Comments (1)

By Tai, August 14, 2010 11:29 am

NYSE: order-driven. NASDAQ: quote-driven. LSE: quote-driven. ASX: order-driven.

NYSE faster for market orders. NASDAQ is faster overall (25 seconds). NYSE slower (50 seconds) because of manual execution & auction.

Liquidity

Liquidity has U-shape pattern: high at open and close. Trade while liquidity is high. Prices are more informative in liquid parcels.

NYSE orders are consolidated. NASDAQ orders are fragmented because NASDAQ has different trading locations.

Switch from NASDAQ to NYSE: liquidity & price efficiency improved, volatility reduced. Consolidation is more valuable for less liquid stocks.

Spreads

NASDAQ: spreads are stable through out the day but narrow near close.

NASDAQ spreads remain constant during first hour. NYSE spreads decline.

NASDAQ spreads narrow near close, NYSE spreads widen near close.

CBOE options: spread high at open, narrows after open, lowest at close.

NYSE: reversed-J spread shape.

Inverse relationship between spreads and activity. Relationship between risk and spreads. Relationship between spreads and information coming to market. Inverse relationship between spreads and competition.

Switch from NASDAQ to NYSE: quoted spreads & effective spreads decrease.

Institutional Trading

70% trading volume on NYSE is by member firms & institutional investors.

Large block institutional sale: perceived as liquidity motivation. Block purchase: perceived as containing favorable information, especially for small stocks.

Seller-initiated: down then slightly up, price effect is temporary. Buy-initiated: up then slightly down, price effect is permanent.

Seller-initiated: price reaches equilibrium after 3 trades, most adjustments in the first trade. Buy-initiated: equilibrium after 1 trade.

Downticks: price effect is largely permanent. Upticks: permanent price effect dominates.

Brokers do short to accommodate block purchase.

Anonymity

Spreads decline. Aggressiveness decline. Orderbook depth increases.

Limit order traders are more willing to expose under anonymity.

Anonymity attracts order flow from non-anonymous markets, but only for large stocks.

Anonymity has few benefits to inactive stocks, and higher benefits in presence of information asymmetry.

Increase in spreads foreshadows increase in volatility.

Positive relationship between spreads in one parcel and magnitude of price change in the subsequent.

Exchanges in fragmented markets should consider anonymous trading to improve price competition and liquidity.

Bibliography

Bennett & Wei, 2006, Market structure, fragmentation, and market quality

Admati & Pfleiderer, 1998, A theory of intraday patterns: volume and price variability

Chan, Christie & Schultz, 1995, Market structure and the intraday pattern of bid-ask spread for NASDAQ securities

Chan, Chung & Johnson, 1995, The intraday behavior of bid-ask spreads for NYSE stocks and CBOE options

Chan & Lakonishok, 1992, Institutional trades and intraday stock price behavior

Comerton-Forde & Tang, 2009, Anonymity, liquidity and fragmentation

Foucault, Moinas & Theissen, 2005, Does anonymity matter in electronic limit order markets?

Holthausen & Leftwich, 1987, The effect of large block transactions on security prices

Holthausen, Leftwich & Mayers, 1990, Large-block transactions, the speed of response, and temporary and permanent stock-price effect

McInish & Wood, 1992, An analysis of intraday patterns in bid/ask spreads for NYSE stocks

Comments (0)

By Tai, August 8, 2010 4:55 am

Stefan Binder, Duk Jang, Tai Tran

The Australian Stock Exchange has two Call sessions At The Open and At The Close. Within these two sessions, price is determined so as to ensure the number of executable orders is maximized.

Below is the spreadsheet that calculates matching price given order volumes.

Click here to view.

Comments (2)

By Tai, July 15, 2010 12:10 am

Foster’s Group Limited Analysis and Valuation

Investment Decision Making Support

June 2010

Phuong Ho, Thanh Luong, Hanh Pham, Khoi Tran, Tai Tran, Huy Truong

Abstract

Valuation is the key activity for investment decisions. This document analyses Strategy, Accounting, and Financial conditions of Foster’s Group Limited within the context of the Australian Alcoholic Beverage Industry. The information is ultimately synthesized for Forecast and Valuation of the company. Time-series analysis is done for the 2007-2009 period with reference to the 2005-2006 period. Cross-sectional analysis puts Foster in contrast to its major competitor Lion Nathan. All information is from publicly available academic and reputable business sources.

On industry level, Foster is the largest player in a concentrated market. Foster can take advantage of the acquisition of Lion Nathan to move ahead in the competition. In terms of strategy, Foster is implementing various initiatives so as to maintain its position in Australasia and expand to the US and Asia. Accounting of the company is at high quality; however a concern of write-down is raised. On financial performance, Foster’s business is more fluctuating resulting from turbulence of its operations in the US market, compared to its opponent Lion Nathan. The volatility of earnings and growth may account for uncertainty of market perception toward the company and thus result in an undervaluation. Forecast of company sales growth ranges between 2.7% to 3.1% which is higher than industry value weighted average, and forecast of net operating profit margin is 18%. Valuation using three difference methods yields a fair price of AUD 5.85. We find the stock currently undervalued while the company has great prospects in long-term horizon, thus recommend Buy and Hold strategy. This recommendation receives analysts’ consensus.

To receive the document, please comment on this post with your real email (won’t be publicized).

Comments (0)

By Tai, January 27, 2010 11:08 am

US

ρ (DJIA, VNI) _2006-2009 = 0.7741

ρ (S&P 500, VNI) _2006-2009 = 0.7528

EU

ρ (FTSE, VNI) _2006-2009 = 0.7374

ρ (DAX, VNI) _2006-2009 = 0.8406

Asia & Oceania

ρ (NIKKEI 225, VNI) _2006-2009 = 0.7114

ρ (HSI, VNI) _2006-2009 = 0.6509

ρ (STI, VNI) _2006-2009 = 0.8519

ρ (CN SSE, VNI) _2006-2009 = 0.6936

ρ (ASX, VNI) _2006-2009 = 0.8507

Below is the regression lines between one high, one ‘medium’ and one ‘low’ correlations

Comments (0)

By Tai,

The UK has the floating rate LIBOR as the reference rate at which banks borrow in the money market. This floating rate is also used for engineering other derivatives.

Respectively, Australia has BBSW: bank-bill reference rate.

In Vietnam, the inter-bank rate between Vietcombank, Agribank, Vietinbank and BIDV has recently been used e.g. for bonds. The full term is long, so I came up with an acronym for it: VAVB. This term is sheerly for the ease of remembering and discussion; the order of the letters serves no other purpose.