A recent case in the NSW Supreme Court is a challenge for industry players that intend to respond to investigations and enforcement actions with the usual industry rules of thumb. In Schlaepfer v ASIC, Justice Fagan rejected the use of unsupported rules in favour of a robust statistical method, and demonstrated the impact of the scientific method on the courts’ approach to allegations of misconduct in securities markets. This is a judicial approach that is gaining traction and we would call this progress.
Although a defamation case, the judgement explains Justice Fagan’s approach to the question of determining whether trading constitutes market manipulation and, therefore, in breach of sections s 1041A and B of the Corporations Act, which respectively deal with trading that does not reflect the forces of genuine supply and demand, and trading that creates a false and misleading appearance of active trading. Justice Fagan criticised the ‘industry ratios’ relied upon by Dr Carr, despite the expert’s claim that these ratios are used by the American SEC in its investigation and enforcement efforts. Justice Fagan went to great lengths to explain the statistical methodology deployed by Professor Putnins and the reasons he found it robust and persuasive in the absence of legitimate commercial reasons for the trading.
The findings in Schlaepfer v ASIC are the most recent example of an increasing body of decisions that show the courts applying the scientific method in their judgements about allegations of misconduct in securities markets, including Whitebox Trading in Australia, the Warminger case in New Zealand and the DaVinci case in the UK. This challenges market participants to move beyond traditional rules of thumb and further develop their skills and resources in an environment beset with rapidly evolving technology, a fire-hose of data and regulators empowered and emboldened in their investigation and enforcement efforts. This is all the more challenging in an environment where only ASIC, as the market surveillance authority, has a consolidated view of trading across all platforms, as opposed to the limited view that each market participant is privy to and which constrains their surveillance diagnosis. Justice Fagan does touch upon this difficulty in the current judgement, noting at par. 258 the limits of a surveillance strategy predicated on simply accepting ‘absurd “explanations” from traders’.
Justice Fagan found six measures “to be compelling … and ample to support the inference that non-bona fide, manipulative trading was undertaken on the relevant stock/days. I found one characteristic not significant. The remaining three, while having merit, need not be considered in detail because of the strength of the defendant’s position without them.”
The ten measures are the following:
- a marked imbalance in Select Vantage’s ordering as between the buy and sell sides;
- a high level of ordering or quoting activity;
- an abnormally high rate of cancellation of orders;
- a low probability of execution;
- buying volume during a trading day being approximately equal to selling volume;
- trades commonly being executed on the opposite side of the order book to the side on which there is an imbalance of resting orders;
- cancelling orders on one side of the market after executing an order on the opposite side;
- a measure of the use of the unlit market;
- a measure concerned Select Vantage placing or maintaining resting bids at times when it is clear that the traders’ intentions must have been to sell stock in order to revert their balance to zero;
- a second measure with respect to Select Vantage placing or maintaining resting bids at times when it is clear that the traders’ intentions must have been to sell stock in order to revert their balance to zero.
Noting the robustness of Professor Putnins’ analysis, Justice Fagan accepted “… that a number of the characteristics are inconsistent with legitimate speculative trading and that they strongly indicate an absence of bona fide intention to execute the large volume of bid-side orders that were placed”.
Professor Putnins’ opinion adds to our work synthetising best practice in this area into a coherent, evidence-based, testable and replicable approach, which our experts are publishing in May in the form of a ten step methodology to detect potential market manipulation, which we described in this post: https://www.linkedin.com/pulse/we-contribute-chapter-corruption-fraud-financial-markets-ann-leduc/?trackingId=fpdawssJKgkrKtl6%2BuqSOQ%3D%3D.