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Relevance to the finance industry
The Price Formation of Substitute Markets
Michael T Chng, Accounting & Finance Monash University
Aihua Xia Mathematics&Statistics, University of Melbourne.
Relevance to the Finance Industry & Opportunity for Industry Involvement
Price discovery, the adjustment process where information inherent in trading is
incorporated into prices timely and efficiently, generates economic interest. This
includes investment decisions to allocate scarce resources, corporate decisions to
make acquisitions, and regulatory decisions to promote trading platform integrity.
Price discovery is measured by price formation models that examine how intraday
prices evolve from investor trading. These models differ in the observable trading
parameter(s) that each highlights to depict the trading process. The existing literature
offers a comprehensive coverage of parameters, including lagged returns, lagged
volatility, trade and/or order size, time between sequential trades, no-trade duration,
trader identity and trade direction i.e. whether the trade is buyer or seller initiated.
Nonetheless, many of these are single-market models. The literature pays
considerably less attention to developing cross market price formation models.
The objective of this project is twofold. First, to develop a cross-market price
formation model for gauging the price discovery between pair-wise substitute markets
X & Y. We can perceive a pair of substitute markets under one of three categories:
Shares listed on different boards of the same stock exchange
Our model’s focus variable is trade direction. A justification for trade direction
rather than a more popular variable (say) trade size is the practise of stealth trading. If
institutional traders break up their orders to smaller parcels in an attempt to hide their
trading intention and/or to minimize the price impact from off-loading a huge
position, then this will induce auto-correlation in trade directions i.e. a series of
consecutive buy or sell trades. Our model is able to measure such autocorrelation
effects. In addition, it is able to compute the long-run transition probability of Market
X (Y) continuing in the same direction and Market Y (X) reversing direction to
follow Market X (Y) at time t, conditional on the fact that X & Y actually went in
opposite directions at time t-1. Second, we plan to demonstrate the flexibility and
breadth of our model application by fitting it across all three categories of pair-wise
It is a common scene to see derivative contracts written on an increasing array
of tradable assets and resources (including electricity and the weather), to see firms
listed across multiple stock exchanges, and to see multiple futures exchanges
competing in similar derivative products. Gauging price discovery between substitute
markets allows practitioners a better understand of the origin of information
processing, thereby facilitating better investment, corporate and regulatory decision-
making. This requires a price formation model that jointly considers the trading
process of both markets, especially if trading hours overlap. We offer such a model.
We are also currently working to generalize our model to address three other
aspects of trading, namely: i) an absence of trading, ii) the asymmetry price impact of
buyer versus seller-initiated trades and iii) trade size. Hence our model offers a new
approach to differentiate the price impact between good and bad news motivated
Our model has a less policy-orientated potential application in terms of a trading
strategy that involves pair-wise trading. This is drawn from the co-movement
literature. Not dissimilar to hedge-funds, the strategy, in brief, takes opposite
positions a pair of similar stocks e.g. NAB & CBA, CML & WOW, or BHP & RIO,
when the pricing gap between two similar (substitute) firms rises above a certain
threshold level. Our model, which revolves on the price formation of a pair of
substitute markets taking into account observable trading parameters, has a natural
Indeed, our incentive to adapt our model to the preceding application stems
from the level of interest and potential financial support that the investment
community is willing to vest in the current stage of our model development.
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