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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