A Primer on Broker Selling Profiles

Transcription

1 ASX TRADING ISSUES Contact: Web: asxinsights.com Research Paper 1 A Primer on Broker Selling Profiles Re: Insights into non-genuine selling anomalies on the ASX Published June 2015 Copyright 2015 DISCLAIMER: All information presented as research has been sourced from broker trading records, registry records and public media. While the author considers the data to be accurate and free from transcription errors, no guarantees can be given regarding conclusions and/or commentary provided. Interested readers are encouraged to do their own Due Diligence and to make up their own minds in regard to the causes of any trends present in trading data.

2 2 INTRODUCTION The paper introduces the concept of broker selling profiles, and by the use of broker profiles demonstrates how non-genuine selling represents a significant feature of daily ASX selling. It is an important issue as non-genuine trading is associated with the creation of artificial prices, and such activity is deemed to be illegal under the Corporations Act. BROKER SELLING PROFILES Broker daily selling profiles simply compare two attributes of trading for each broker. 1. the number of Downtick trades achieved by a broker, to all Downtick trades put through the market (expressed as a percentage), and 2. the selling volume supplied by a broker, compared to all selling that occurred in the market (also expressed as a percentage). Broker selling profiles are also explained in the two YouTube clips below. Part 1 Part 2

3 3 SAMPLE BROKER SELLING PROFILES SELLING PROFILES Broker selling profiles represent a convenient method to compare brokers and to assess the genuineness of trading as explained in YouTube Video Broken Markets 1 <Link>. As a basis for assessing the genuineness of trading, if a broker is responsible for say 10% of all selling, then Downticks of around 10% would appear reasonable. It would be unreasonable however if say, 1.5% of all selling resulted in 28% of all Downtick trades. On that basis the profile of Broker 1 is reasonable and Broker 3 appears somewhat efficient in avoiding price falls with their selling. However, the profile of Broker 2 would raise price rigging concerns as the trading does not reflect that of a genuine seller. Genuine sellers want higher prices so don t act to cause lower prices through executing large numbers of trades that cause price falls. Non-genuine selling results in artificial adjustments to prices which represents illegal activity. Broker performances as suggested by selling profiles vary markedly, however a small subset of brokers, all with co-location privileges, tend to dominate in causing price reductions, and they tend to do so from minimal volumes of selling. It is a counterintuitive outcome and it arises from the tuning of algorithms. But it portends a market controlled by mathematical formulas, not a market responding to the genuine forces of supply and demand. The result is that prices can be artificially set with relative ease and that shows up in gross undervaluations in many companies REGARDING targeted ALGORITHMIC by algorithmic TRADING. trading and short selling. In clarifications provided by ASIC to a concerned investor about trades taking place for just a few shares, it was explained that entities can use algorithms to minimize the impact on the market when selling a large parcel of shares by dividing the parcel up order up into small parcels, and then executing the small trades over time. The explanation appears reasonable but makes no allowance for the manipulative trades that take place where algorithms are tuned to force price reductions (i.e. Downticks) in favour of trading agendas, rather than to genuinely dispose of shares.

4 4 THE OFFICIAL POSITION REGARDING NON-GENUINE SELLING AND ARTIFICIAL PRICES A decision by the Australian High Court in June 2013 is particularly helpful in being able to assess what might constitute non-genuine selling. The Australian High Court simply stated that a genuine buyer seeks to pay the minimum for shares not pay up or for higher prices, and by inference, it is clear that a genuine seller seeks to maximize the proceeds of sales, not push prices lower. A broker with a comparatively minor market share by selling volume, who also happens to be a leading supplier of Downtick transactions, therefore attracts a great deal of suspicion. Selling characteristics of that type identify with non-genuine intent where the focus is to deliberately impact prices rather than to genuinely exchange shares. It is very clear in trading data that algorithms offer the discretion to either impact prices or to trade without causing price falls, and it comes about through the choice of algorithms and through the settings supplied to them by brokers. The High Court also clarified that non-genuine trading results in artificial prices which constitutes illegal activity under the Corporations Act. It means that being able to identify non-genuine trading is vitally important if price rigging is to be prevented. To summarise: Dubious Broker Selling Profiles Small volumes of selling resulting in large numbers of price falls identifies with market rigging as it results in artificial adjustments to prices. Such selling is particularly dubious when Downticks are the result of broker crossings. Small cross trades that impact prices, while appearing frivolous, are nevertheless executed for highly strategic purposes. In modern markets, tiny profits repeated over and over amount to substantial gains which means that all non-genuine adjustments to prices require the closest of scrutiny. In modern markets, tiny profits repeated over and over amount to substantial gains which means that all non-genuine adjustments to prices require the closest of scrutiny.

5 SELLING PROFILES FOR PANAUST LTD (PNA) ON MAY 12, 2015 The following chart summarizes the features that regularly appear in broker selling profiles. 5 Trading in PanAust Ltd (PNA) on May 12, 2015 Non-genuine selling profiles Dubiously efficient profiles The chart reflects selling patterns that are completely at odds with how genuine sellers operate. Around 89% of broker RBS Morgan s Downtick trades had an average parcel size of just 38 shares, worth around $70 each. All were crossings. In contrast the selling by UBS and JPM was ultra-efficient in having minimal impact on prices. The trading patterns are far removed from those expected in a fair market driven by the genuine forces of supply and demand. The charts that follow show snapshots of trading across a range of companies during ober 2013, and represent the trading that occurred on ober 1, ober 15 and ober 31. The extent of non-genuine trading is clearly evident. The charts need to be viewed from the perspective that non-genuine trading is associated with artificial adjustments to prices i.e., activity deemed to be illegal. The data trends are clearly not isolated events but purposefully come about through the tuning of algorithms. The companies summarized include: CSR CSR Limted RSG Resolute Mining KAR Karoon Gas EGP Echo Entertainment LEI - Leigton Holdings SBM St Barbara PBG Pacific Brands FMG Fortescue

6 6. Examples of Selling Anomalies in Daily Trading ober 2013 CSR ober 1 LEI ober 1 Non-genuine selling profiles are circled CSR ober 15 LEI ober 15 CSR ober 31 LEI ober 31

7 7 Examples of Selling Anomalies in Daily Trading ober 2013 RSG ober 1 SBM ober 1 Non-genuine selling profiles are circled RSG ober 15 SBM ober 15 RSG ober 31 SBMober 31

8 8 Examples of Selling Anomalies in Daily Trading ober 2013 KAR ober 1 PBG ober 1 Non-genuine selling profiles are circled KAR ober 15 PBG ober 15 KAR ober 31 PBG ober 31

9 9 Examples of Selling Anomalies in Daily Trading ober 2013 EGP ober 1 FMG ober 1 Non-genuine selling profiles are circled EGP ober 15 FMG ober 15 EGP ober 31 FMG ober 31

10 BHP BILLITON DAILY SELLING PROFILES: ober 2013 Trading 10 Anomalous trends in broker selling profiles for trading in BHP Billiton during ober 2013 are again clearly evident. Even with a highly liquid stock such as BHP, the profiles of brokers who are the leading sellers of Downtick trades usually reflect non-genuine patterns of trading. BHP ober 1 On ober 1, the profiles of Merrill Lynch and Instinet both reflect non-genuine selling profiles. UBS Securities also shows a bias towards causing Downticks in prices. Citigroup and Deutesche Bank appear extremely efficient with their selling. Non-genuine selling profiles are circled On ober 15,,the profile of Instinet again shows the characteristics of non-genuine selling. BHP ober 15 It is extraordinary that in a highly liquid stock such as BHP, a broker with just 1% of all selling can be responsible for 17% of all trades associated with reductions in price. Citigroup along with Credit Suisse were seemingly efficient sellers with relatively minimal impact to prices from substantial levels of selling. BHP ober 31 Non-genuine selling wasn t as obvious on ober 31, apart from Instinet who again focussed on causing price reductions with the small volumes of selling they put through the market.

11 11 Brokers who show up in daily charts as being leading sellers of Downtick trades tend to rotate roles from one day to the next. The fluctuations could be random and unrelated, or they could be by design with proprietary trading strategically wound back or increased, or entities could be switching brokers from day to day. It is why audits are required to get to the bottom of trading anomalies. BHP BILLITON: EXTENDED SELLING PROFILES Brokers who emerge with anomalous profiles over extended periods of time show a concentration of non-genuine selling. Merrill Lynch and Instinet (below) are cases in point in trading for BHP over all of ober The selling in the chart represents all broker selling over the entire month, and the Downticks refer to all Downticks recorded over the entire month. The chart represents a very large amount of data. It makes trading anomalies particularlry significant as it reflects entrenched behaviours dictated by the tuning of algorithms, not the genuine forces of supply and demand. 14% Broker Selling Profiles for BHP Trading ober % 10% Strong levels of nongenuine selling? 8% 6% 4% 2% 0% In assessing the data, only trades below 20,000 shares in size were considered. It meant that broker market shares regarding selling volumes weren t influenced by the very large cross trades that take place in a stock such as BHP.

12 12 Merrill Lynch (MERL) Daily Profiles ober 2013 The prominence by Merill Lynch (MERL) regarding the forcing of Downticks with their trading regarding BHP during ober 2013, is emphasized further by assessing their daily trading profiles over the course of the month 30% Daily Selling Profiles for MERL in Relation to BHP trading ober % 20% Non-genuine selling? 15% 10% 5% 0% Instinet (INST) Daily Profiles ober 2013 Instinet s prominence was more spasmodic than Merrill Lynch but on particular days their non-genuine selling was particularly pronounced. Non-genuine selling generally is contrasted with selling on days such as ober 9, 10 and 14 where algorithms were tuned much differently to other days. The flexibility for algorithms to be tuned to impact prices means that artificial adjustments to prices can be imposed at will. The reality of artificial prices is borne out by under-valuations in stocks such as PanAust Ltd which become vulnerable to takeover. 25% 20% 15% Daily Selling Profiles for INST in Relation to BHP trading ober 2013 Instinet has a history of non-genuine selling as revealed by fines paid for wrong-doing in Australia and elsewhere. 10% 5% 0%

13 13 OTHER EXTENDED BROKER PROFILES Further monthly anomalies are highlighted below to demonstrate that the problems such as those evident in BHP are systemic, not random events. The extent of anomalies are further highlighted in the series of YouTube presentations listed in Broken Markets 2. ACRUX LIMITED (ACR): Monthly Profile For December % 18% 16% 14% 12% 10% 8% 6% 4% 2% 0% ST BARBARA (SBM): Monthly Profile for ober % 16% 14% 12% 10% 8% 6% Strong levels of nongenuine selling? Strong levels of nongenuine selling? for Dec 2013 for Dec 2013 Summary Disturbing trends in empirical data are a reality of ASX trading. The trends are cemented into trading data and they come about through the tuning of algorithms that incorporate short selling trades. Particular brokers routinely have anomalous selling profiles that identify with non-genuine selling, yet their profiles can suggest genuine trading at other times. There are no plausible explanations that can smooth away concerns and at the same tim satisfy fair trading and legal guidelines. The trends identify with nongenuine trading, and therefore artificial prices. The trends show that trading that identifies with being illegal is being sanctioned. 4% 2% 0% for 2013 for 2013

14 14 Further Anomalies Non-Genuine Buying Non-genuine broker profiles are not confined to selling. Research has shown that non-genuine buying is also widespread. It involves brokers with relatively small buying volumes in the market generating large numbers of transactions that result in price increases. i.e., non-genuine selling is matched by non-genuine buying. Wide ranging anomalies that illustrate non-genuine trading reflect on a substantially compromised system of trading where the market is prevented from acting as a true market. It is because algorithmic transactions that produce artificial adjustments to prices interfere with fair price discovery. Moreover, the impact on price discovery stems from activities that identify with being illegal as they involve artificial adjustments to prices. Collusive Interactions For every non genuine sale there is a buyer taking the other side of the trade, and similarly, there is a seller taking the other side of every non-genuine purchase. Research has demonstrated that those on the other side of non-genuine transactions are also associated with anomalous trends. The trends are evident with particular brokers being successful in regard to: buying large numbers of Downtick trades but from minimal volumes of buying. receiving Upticks for selling trades, but from minimal volumes of selling. These further anomalies are not the result of good luck or exceptional trading skills. Rather, they suggest collusive interactions between designated sellers and preferred buyers; not the sort of activity expected in a genuine market place. Alternative Trading Venues Further anomalies in trading data show how prices can be artificially controlled through trades being directed to the Chi X exchange. The lightly traded Chi X venue is used to magnify adjustments to prices, where for example trading for Acrux (ACR) during December 2013 showed that with only 9.6% of trading volumes directed through Chi X, the reduced selling volumes nevertheless resulted in 33.7% of all Downtick transactions that occurred for the month. It is an extremely revealing statistic. Alternative venues, whether it be Chi X, or non-transparent dark pools run by investment bank brokers, clearly provide increased flexibility to engage in non-genuine trading. Trading Agendas Implemented through Algorithms Trading that involves an algorithmic template being applied to all stocks irrespective of fundamentals, the sector, or other factors, have also been identified in trading data. It suggests the relentless implementation of trading agendas and it involves substantial levels of non-genuine selling. (Refer here and here)

15 15 The crucial aspect to trading anomalies is that the trends coincide with the requirements needed for short selling to be successfully implemented. It is not a coincidence. A successful short selling cycle requires: 1. Sales to be entered into the market without impacting price; 2. Prices to fall; 3. Short sold positions to be covered through re-purchases from the market, again without impacting price; and 4. Prices to rise. The cycle can then repeat. Short Selling Issues As it happens, trading anomalies identified by research happen to coincide with all requirements for successful short selling. 1. Efficient selling (i.e., sales with minimal impact to prices) 2. Non-genuine selling causing reductions in price 3. Efficient buying (i.e., purchases with minimal impact to prices) 4. Non-genuine buying causing increases in price All anomalies are fully explained in the Broken Market series of tutorials available <here>. Check the website as while some are already available, others will be posted as soon as they become available. Readers are invited to register to receive an alert by sending a request to asxinsights@gmail.com Recommended Link Broken Markets 2 A summary of research findings as presented in a series of YouTube videos, and all fully supported by trends in empirical data. The findings have enormous implications for our so called fair and orderly market system. Trends in ASX data reveal a system that is far different than officially promoted and it is because artificial adjustments to prices can result in rigged markets in whatever stocks attracts the interest of predatory traders. <Close the current web browser to return to asxinsights.com>

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