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Moore and Payne Size, specialism and the nature of informational advantage in inter-dealer foreign exchange trading. Discussion by Ian Marsh Cass Business School. Selling points of paper. This paper tries to address the key issue in foreign exchange rate modelling
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Cass Business School
Why is there such a huge correlation between exchange rate changes and order flow?
Argue that if it is all about information then there should be differences in the way prices react to deals by traders likely to have asymmetric information
Show by means of regression of price impact on indicator dummies that price impacts differ in plausible ways
That’s fine but so what?
It isn’t clear to me we learn a vast amount from this
Most importantly, we do not learn what the title suggests we will:
“Size, specialism and the nature of informational advantage in inter-dealer foreign exchange trading”
What we learn is that when a big or specialist trader supplies liquidity he suffers smaller costs than a smaller generalist trader
Similarly, when a big or specialist trader takes liquidity he creates a larger price impact than does a smaller generalist trader
How does the market learn from trading?
Deals are anonymous on this platform
Only the taker and maker know identities
Everyone else just sees an arrow on screen
There is no information revelation
So how does the rest of the market differentiate between a OMST deal (0.59 price impact) and a SMOT (0.14)?
Maybe price impacts reflect information differences and the market can perform miracles
But differential PIs might just reflect trader skill even if all traders are uninformed
A $:€ trader for a big bank won’t keep his job long if he gets caned every time he supplies liquidity and doesn’t make a gain when he initiates a trade
The paper is pretty silent on where these large specialist traders get their info from
It is mostly thought that they get the info from their customers
Customer might be a smart hedge fund that knows the true value of FX
Or might be a dumb corporate who reveals that UK is doing well by selling £ to repatriate earnings
Or something vague like liquidity preference shifts
This paper tells us nothing about the nature of the information that leads big specialist traders to trade well
To get that, the authors would need to look at customer order flows, not the interdealer flows they use here
The analysis is at such a high frequency that I worry the customer-dealer info link is weakened
The depvar is price change from -5 to +10 trades in main results, 1 minute in $/€
Is this really the appropriate horizon over which to measure information effects?
Finally, having taught financial statistics for a term, a cheap shot
We criticise macro FX modellers for not being able to explain much using macro fundamentals
But the R2s in this paper are around 1%
And price impact coefficients are fractions of a basis point