Lecture 5 The Market Abuse Framework PDF

Lecture 5 The market abuse framework Diego Valiante, Ph.D. Opinions expressed are strictly personal and cannot be LEIF Master Programme attributed in any way to the Europe...

Lecture 5 The market abuse framework Diego Valiante, Ph.D. Opinions expressed are strictly personal and cannot be LEIF Master Programme attributed in any way to the European Commission.  Agenda Financial market functioning and the role of analysts Mandatory disclosure – Disclosure at issuance – Ongoing disclosure – The role of gatekeepers Market abuse framework – Market manipulation 2011 Coscia’s market manipulation (case study) – Insider trading – Transaction Reporting – Benchmark regulation – Short selling regulation © Valiante Diego - 2  Let's recap on the primary role of regulation The minimum amount of regulation that would enable a market to function shall aim to increase the accuracy of analysts in capturing price/value deviations by: 1. Reducing costs of pricing information or 2. Reducing risks of not capturing the deviation (e.g. misleading information) 1. Mandated disclosure rules – Reduces the probability of misevaluation by reducing the costs of pricing information 2. Prohibition of fraud and manipulation – Reduces probability of encountering misleading information (so risk of not capturing the price deviation) 3. Prohibition of insider trading – Reduces the risk of crowding out analysts, so deteriorating market quality under adverse selection All of them needs effective enforcement mechanisms to work. © Valiante Diego- 3  (2) Prohibition of market manipulation and (3) insider trading © Valiante Diego - 4  Prohibition of mkt manipulation and insider trading The basic laws of financial markets include the prohibition of ‘market abuse’, which is composed of: 1. A prohibition of market manipulation, which reduces probability of encountering misleading information (so risk of not capturing the price deviation) Artificial movement of prices to make a profit or avoid a loss through, for instance, the use of false information or rumours. This prohibition should help to reduce verification costs. 2. A prohibition of insider trading, which reduces the risk of crowding out analysts, so deteriorating market quality under adverse selection. Insider trading is also seen as a violation of the company’s relationship of trust and confidence with their ‘insiders’ (e.g. managers). In the US, for instance, this is a specific fiduciary duty, i.e. to refrain from self dealing in confidential information owned by another party (the company). Prohibition and prevention of market abuse thus promotes – Market efficiency; and – Market integrity (investor protection). © Valiante Diego - 5  Market abuse framework in the EU Market Abuse Regulation EU n. 596/2014 and Directive n. 2014/57/EU are key pieces for the EU framework on market abuse, which define ‘market abuse’ as: 1. Market manipulation (art. 12 MAR), which can be: a. trade-based (through a transaction or simply an order to trade); or b. information based (through false or misleading information, including submissions to benchmark indexes) 2. Insider dealing (art. 8 MAR), which include: a. Trading on inside information; or b. Dissemination of inside information. Market abuse has typically low probability of detection, so they are often accompanied by harsh monetary and criminal sanctions. © Valiante Diego - 6  Market manipulation © Valiante Diego - 7  Market manipulation The market manipulation framework embeds an effects-based approach to complement the general definition, so that it identifies a list of actions: – Sending misleading signal or spreading false information – Creating an artificial price level through trading activity (e.g. HFT- based strategies) – Providing false input to benchmarks – Cornering in commodity derivative markets (art.12.2(a), MAR) Position limits are often used to prevent such manipulation. © Valiante Diego - 8  Market manipulation – Accepted Market Practices (AMPs) There are also actions that resemble market manipulation, but they are considered Accepted Market Practices (AMP) if they follow a list of criteria (art. 13 MAR), including: – Positive impact on liquidity and efficiency – No or negligible impact on market integrity (i.e. impact on price formation process and on the perception of liquidity; ESMA) An example of AMP are: – Liquidity contracts for market-making activities (to be entered in a written form etc) – Buyback of bonds issued at predetermined conditions They shall be notified to ESMA ex ante. ESMA issues a non-binding opinion, but NCA has to explain why it deviates from that opinion (in case it does). See ESMA report on AMPs for more info. © Valiante Diego - 9  The 2011 Coscia’s manipulation (Case Study) © Valiante Diego - 10  Some background information Michael Coscia was a commodity trader. The FCA concluded that Mr Coscia deliberately engaged in a form of manipulative trading known as “layering” and “spoofing” between 6 September 2011 and 18 October 2011 on ICE, which generated a profit of $1.4 million. Mr Coscia placed and rapidly cancelled large orders which he did not intend to trade, with the intention of creating a false impression as to the weight of buyer or seller interest thereby “layering” the order book and manipulating the market. In November 2015, Mr Coscia became the first person to be convicted of “spoofing” while trading futures contracts on exchanges in the United States and United Kingdom in 2011. On 13 July 2016, Mr. Coscia was sentenced in Chicago to three years’ imprisonment on six charges of spoofing as well as six charges of commodities fraud. He paid overall fines for $2.8 million in the US and roughly £600k in the UK. © Valiante Diego - 11  2011 Coscia’s manipulation – Source: FCA (Case Study) An example of Mr Coscia's trading (00:00:00.000 to 00:00:00.609) Lots buy/sell Price 400 115.9 The chart explained: horizontal axis shows the timing of the trades in milliseconds 115.89 300 right hand vertical axis shows the price of the Brent contracts left hand vertical axis shows the lot size of orders to buy or 115.88 sell 200 time and price Mr Coscia’s buy orders 115.87 cumulative size of Mr Coscia’s buy orders 100 Buy order for 17 lots @115.86 115.86 cumulative size of all buy orders in the market within five ticks of the best bid Cumulative buy order positions shown by the blue line 115.85 0 time and price of Mr Coscia’s sell orders -20 80 Time (milliseconds) 180 280 380 480 580 cumulative size of Mr Coscia’s sell orders 115.84 0 -100 cumulative size of all sell orders in the market within five ticks of the best offer 115.83 changes in the mid price (average of the best bid/offer price) -200 115.82 -300 115.81 Cumulative Buy Orders Cumulative Sell Orders Mid Price Trade Price Mr Coscia Sell Order Price Mr Coscia Buy Order Price © Valiante 2 Diego - 12  The Coscia’s manipulation – Source: FCA (Case Study) An example of Mr Coscia's trading (00:00:00.000 to 00:00:00.609) Lots buy/sell Price 400 115.9 3 large sell orders: 115.89 300 122 lots @ 115.89 115.88 85 lots @ 115.88 200 54 lots @ 115.87 115.87 Cumulative sell order position is shown by 100 downward movement in the red line 115.86 115.85 0 -20 80 Time (milliseconds) 180 280 380 480 580 115.84 0 -100 115.83 -200 115.82 -300 115.81 Cumulative Buy Orders Cumulative Sell Orders Mid Price Trade Price Mr Coscia Sell Order Price Mr Coscia Buy Order Price © Valiante 3 Diego - 13  The Coscia’s manipulation – Source: FCA (Case Study) An example of Mr Coscia's trading (00:00:00.000 to 00:00:00.609) Lots buy/sell Price 400 115.9 115.89 300 115.88 Buy order for 17 lots traded @ 115.86 in 200 two shapes (3 and 14 lots) 115.87 Shown by the downward movement in the blue line 100 115.86 115.85 0 -20 80 Time (milliseconds) 180 280 380 480 580 0 Buy trade triggers cancellation of all 3 115.84 -100 large sell orders Shown by the upward movement of the 115.83 red line -200 115.82 -300 115.81 Cumulative Buy Orders Cumulative Sell Orders Mid Price Trade Price Mr Coscia Sell Order Price Mr Coscia Buy Order Price © Valiante 4 Diego - 14  The Coscia’s manipulation – Source: FCA (Case Study) An example of Mr Coscia's trading (00:00:00.000 to 00:00:00.609) Lots buy/sell Price 400 115.9 115.89 300 115.88 200 115.87 Sell order for 17 lots @ 115.88 (2 “ticks” higher than the purchase price) 100 115.86 Shown by the downward movement in the red line 115.85 0 -20 80 Time (milliseconds) 180 280 380 480 580 115.84 0 -100 115.83 -200 115.82 -300 115.81 Cumulative Buy Orders Cumulative Sell Orders Mid Price Trade Price Mr Coscia Sell Order Price Mr Coscia Buy Order Price 5 © Valiante Diego - 15  The Coscia’s manipulation – Source: FCA (Case Study) An example of Mr Coscia's trading (00:00:00.000 to 00:00:00.609) Lots buy/sell Price 400 115.9 3 large buy orders: 99 lots @ 115.82 115.89 88 lots @ 115.83 300 122 lots @ 115.86 Shown by the upward 115.88 movement in the blue line 200 115.87 100 115.86 115.85 0 -20 80 Time (milliseconds) 180 280 380 480 580 115.84 0 -100 115.83 -200 115.82 -300 115.81 Cumulative Buy Orders Cumulative Sell Orders Mid Price Trade Price Mr Coscia Sell Order Price Mr Coscia Buy Order Price 6 Diego - 16 © Valiante  The Coscia’s manipulation – Source: FCA (Case Study) An example of Mr Coscia's trading (00:00:00.000 to 00:00:00.609) Lots buy/sell Price 400 115.9 115.89 Sell order for 17 lots traded @ 115.88. 300 Shown by the upward movement in the red line 115.88 200 115.87 100 115.86 115.85 0 -20 80 Time (milliseconds) 180 280 380 480 580 115.84 0 -100 115.83 Sell order trade triggers cancellation of all 3 -200 large buy orders 115.82 Shown by the downward movement in the blue line -300 115.81 Cumulative Buy Orders Cumulative Sell Orders Mid Price Trade Price Mr Coscia Sell Order Price Mr Coscia Buy Order Price © Valiante 7 Diego - 17  The Coscia’s manipulation – Source: FCA (Case Study) An example of Mr Coscia's trading (00:00:00.000 to 00:00:00.609) Lots buy/sell Price 400 115.900 The bid/ offer spread and the mid price moves up after the large orders are placed 115.890 300 Shown by the upward movement in the green line Mr Coscia’s small sell order then traded at a 115.880 higher price resulting in a profit of USD 340 200 115.870 100 115.860 115.850 0 -20 80 Time (milliseconds) 180 280 380 480 580 115.840 0 The bid/offer spread narrows and the price -100 moves down after the sell orders are placed Shown by the downward movement in the green 115.830 line -200 Mr Coscia’s small buy order then traded at a lower price 115.820 -300 115.810 Cumulative Buy Orders Cumulative Sell Orders Mid Price Trade Price Mr Coscia Sell Order Price Mr Coscia Buy Order Price © Valiante8Diego - 18  The Coscia’s manipulation – Source: FCA (Case Study) An example of Mr Coscia's trading (00:00:00.000 to 00:00:00.609) Lots buy/sell Price 400 115.900 Mr Coscia’s large orders have a significant impact on the market as Mr Coscia’s large buy orders respectively make they make up a significant proportion up 64,77, and 87% of all buy orders in the 115.890 of the market depth. This is assessed market within 5 ticks of the best bid price 300 by comparison to all other orders in the market to buy or sell within 5 ticks of the best bid or offer price. 115.880 200 115.870 100 115.860 115.850 0 -20 80 Time (milliseconds) 180 280 380 480 580 115.840 0 -100 115.830 -200 115.820 Mr Coscia’s sell orders respectively make up 84, 89 and 87% of all sell orders in the market within 5 ticks of the best offer price -300 115.810 Cumulative Buy Orders Cumulative Sell Orders Sell Order market depth Buy Order market depth Mid Price Trade Price Mr Coscia Sell Order Price Mr Coscia Buy Order Price © Valiante 9 Diego - 19  High-Frequency Trading, artificial intelligence and other ‘new’ challenges © Valiante Diego - 20  HFT-based manipulation strategies HFT-based manipulation strategies include (non-exhaustive list from ESMA 2012, Moloney et al. 2015): – Layering and Spoofing (Coscia’s case)- submitting multiple orders often away from the touch on one side of the order book (layering) or at the top of the book only (spoofing) with the intention of executing a trade on the other side of the order book. Once that trade has taken place, the manipulative orders will be removed. – Ping orders – entering small orders in order to ascertain the level of hidden orders and particularly used to assess what is resting on a dark platform. – Quote stuffing - entering large numbers of orders and/or cancellations/updates to orders so as to create uncertainty for other participants, slowing down their process and to camouflage their own strategy. – Momentum ignition - entry of orders or a series of orders intended to start or exacerbate a trend, and to encourage other participants to accelerate or extend the trend in order to create an opportunity to unwind/open a position at a favourable price. – ‘Marking/banging the close’ – where trading activity takes place either before or during the close of trading with the aim of impacting on settlement prices. © Valiante Diego - 21  Algo trading and Artificial Intelligence 1. Increasing use of autonomous trading mechanisms (AI) – Can it lead to autonomous misconduct of AI systems? – AI traders can act independently on markets, learn by experience from the outcomes of the own decisions, while pursuing a pre- defined objective (e.g. profit maximisation/risk). – Can they learn to cheat? YES! Market manipulation – AI can lead to optimized algorithmic manipulative strategies regardless of human intent (Ringe et al. 2021; Mizuta 2020; Martínez Miranda et al. 2016; López de Prado 2018) (Tacit) collusion (e.g. Calvano et al. 2020; Klein 2019 for examples) – Facilitating factors to collusion: (i) market transparency, (ii) frequency of interactions, (iii) product homogeneity, (iv) market concentrations, (v) entry barriers and innovation. © Valiante Diego - 22  Algo trading and Artificial Intelligence (2) 2. The Application of established legal concepts (intent, causation and negligence) becomes more problematic – Legal systems require proof of a manipulator’s ‘intent’ In hybrid human-AI systems like ATS, the relevant state of mind has to be found along the opaque AI supply-chain. – Autonomous AI agents can break the chain in ‘causation’ (or making it difficult to detect) between the wrongdoing and the alleged harm. – Difficult to identify ‘negligence’ too. Not only enforcement authorities but also the human experts who are involved in creating, developing, using, and maintaining AI might not be able to foresee a priori all the ways in which ‘black box’ AI trading behaves © Valiante Diego - 23  Algo trading and Artificial Intelligence (3) 3. Market surveillance and enforcement of rules under AI – Technical and legal issues arising from lack of “explainability” of AI financial decision-making (compliance) – Authorities need assessing liability among a long list of possible individuals, which requires knowing their exact contributions to the AI misconduct (enforcement) As a result, it may become increasingly hard to identify whether an AI misconduct is an unintended (or intended) consequence of a human intent or an autonomous AI decision. Inability for algo trading companies to show good faith may create barriers to entry. Any remedies? 1. Improving explainability of algorithmic trading systems (transparency) 2. Testing/validation (with or without pre-approval) and ex ante surveillance of algorithms 3. Ex post surveillance at trading venue level (e.g. circuit breaker) 4. Ensure traceability to a human © Valiante Diego - 24  What about crypto assets? MAR/D are only applicable to financial instruments traded on regulated venues (RM, MTF and OTF) or financial instruments having an impact on instruments traded on those venues. – Prohibition of market manipulation also applies to Some spot commodity contracts (and related financial instruments), Benchmarks (see next slides) Any transaction, order or behaviour related to those instruments, even if they do not take place on a trading venue. Rules apply to any action and omission on those instruments within or outside the Union. New rules on crypto assets (Markets in Crypto Assets Regulation, MiCAR) mirror MAR rules into this new regime, plus they introduce new elements, such as market manipulation by ‘securing a dominant position over the supply of or demand for a crypto asset’ with impact on prices and trading conditions. – It potentially applies to all crypto assets transactions and not just to specific cornering actions in the cash forward or Emission Trading Scheme markets (as per Market Abuse Regulation (EU) 596/2014, Art. 12(2)). © Valiante Diego - 25  Insider trading © Valiante Diego - 26  Insider trading Insider trading/dealing involves acting upon inside information to acquire or dispose of, directly or indirectly, a financial instrument, emission allowances or other auctioned products to make a profit or avoid a loss (art. 8 MAR) – ‘inside information’ is non-public information of a ‘precise nature’ that, directly or indirectly, would be likely to have ‘a significant effect on prices’ of related financial instruments (price-sensitive) ‘precise nature’ means circumstances that exist or an event that occurred known to a level of detail that allows to draw conclusions on ‘possible’ effects ‘non-public’ does not even mean ‘selective disclosure’ to a limited number of investors or potential investors ‘price-sensitive’ means information which a ‘reasonable investor’(retail) would be likely to use for his/her investment decision © Valiante Diego - 27  Insider trading Inside information disclosure can only happen in the normal exercise of an employment, a profession or duties (art. 10.1, MAR) Insider lists (to be kept updated) – Also advisors could become insiders if, during their activities, come across inside information, as well as those receiving market soundings. – SMEs on Growth Markets are exempted under specific conditions, but able to provide upon request (art. 18.6 MAR) Market soundings are legal – Def: A communication of information prior to the announcement of a transaction in order to gauge the interest of potential investors in the context of a market transaction to potential investors (merger) or a takeover bid. – “A disclosing market participant shall, prior to conducting a market sounding, specifically consider whether the market sounding will involve the disclosure of inside information. The disclosing market participant shall make a written record of its conclusion and the reasons therefor. It shall provide such written records to the competent authority upon request.” (art. 11.3, MAR) Detailed procedure (e.g. identify what is the info and the persons who can receive it and get his/her agreement) © Valiante Diego - 28  Market soundings (examples) Recital (32) of MAR highlights that “the ability to conduct market soundings is important for the proper functioning of financial markets and market soundings should not in themselves be regarded as market abuse”. Recital (33) of MAR provides three examples of market sounding: 1. a sell-side firm has been in discussions with an issuer on a potential transaction, and it has decided to gauge potential investor interest to determine the terms that will make up a transaction; 2. where an issuer intends to announce a debt issuance or additional equity offering and key investors are contacted by a sell-side firm and given the full terms of the deal to obtain a financial commitment to participate in the transaction; and 3. where the sell-side firm is seeking to sell a large amount of securities on behalf of an investor and seeks to gauge potential interest in those securities from other potential investors. © Valiante Diego - 29  Enforcement Enforcement is key since market abuse is typically a low probability (of detection) and high reward event, so sanctions have to be somehow strong enough to produce deterrence. In the US, there has been historically a strong link with criminal sanctions, while EU has only adopted criminal sanctions in the 2014 MAD for natural persons and companies. – A maximum term of imprisonment of at least 4 years – Disqualification from practising commercial activities © Valiante Diego - 30  Transaction reporting (Title IV, MiFIR) The market abuse regime and enforcement is supported by the extensive transaction reporting regime imposed by MiFID II (Title IV, MiFIR) All orders and all transactions in financial instruments carried out by investment firms, whether on own account or on behalf of clients. Investment firms which execute transactions in financial instruments shall report complete and accurate details of such transactions to the competent authority as quickly as possible, and no later than the close of the following working day. – To be shared with the NCA of the most relevant market. All orders advertised through their systems by a trading venue shall be kept at disposal of NCAs for 5 years. The operator of a trading venue shall report details of transactions in financial instruments traded on its platform which are executed through its systems by a firm which is not subject to this Regulation. – Reporting bodies are investment firms themselves, trading venues or other Approved Reporting Mechanisms (ARMs). The latter are supervised either by NCAs (if small) or ESMA) Harmonisation of formats among NCAs is taking place (especially due to the sharing of transaction reporting information) © Valiante Diego - 31  Manipulation risks and benchmarks © Valiante Diego - 32  Setting the scene ‘Benchmark’ means any index by reference to which the amount payable under a financial instrument or a financial contract, or the value of a financial instrument, is determined, or an index that is used to measure the performance of an investment fund with the purpose of tracking the return of such index or of defining the asset allocation of a portfolio or of computing the performance fees (art. 3.1(2) EU Benchmark Regulation 2016/1011) There are hundreds of trillions of euros of financial transactions whose value/price depends on a reference index (e.g. mortgages) This is particularly the case for benchmark of interbank funding cost, which are typically used as a floor for lending costs of companies and individuals (e.g. EURIBOR + premium for mortgages). © Valiante Diego - 33  The London InterBank Offered Rate (LIBOR) scandal © Valiante Diego - 34  The LIBOR scandal ‘The use and manufacturing of such benchmarks went largely unregulated until a scandal (again) hit the financial system: The London InterBank Offered Rate (LIBOR) scandal. The LIBOR (managed by the British Bankers’ Association since 1986) used to be reference for more than $300tn derivatives deals (notional value) and more than $10tn in loans. The EURIBOR is the European counterpart. Submission-based index (averaging rates paid by banks in their deals in the interbank market) formed by a representative panel of global banks. LIBOR was offered for multiple currency pairs. © Valiante Diego - 35  The LIBOR scandal ‘Evidence showed that multiple banks manipulated submissions to make the benchmark look lower than actual funding cost during the financial crisis of 2008 and, in other occasions before, to make profits in derivative trades pegged to the funding rate. – After Lehman Brothers’ went bust, LIBOR shot up and remained elevated for months, putting pressures on submitters to reduce upward pressures. – But it remained at a lower level of volatility compared to peer rates, like federal funds in the US, the EURIBOR and treasuries. – This gave the first signal that something wasn’t right. The FED informed the BoE of credibility risks in 2008, but nothing really happened until 2012. – The CFTC and UK authorities investigation started in 2009 and, by 2012, they started to offload charges and reach settlements with big financial institutions (e.g. $1.5bn only for UBS). – Barclays took the fall, but later many more were exposed (incl. UBS, Rabobank, etc) and the cartel was also fined by the EU (Barclays applied for leniency). © Valiante Diego - 36  The ‘multi-layered’ policy response 1. First thing was the opening up of governance and administration of the Benchmark (NYSE took over in 2014 after an open competition). 2. False or misleading submission is now included in the definition of market manipulation (in the MAR). 3. Attempting to expand the panel of banks submitting in different currencies to increase credibility and risk of manipulation. Harder to achieve when now banks risk liability. 4. EU Regulation 2016/1011 includes: 1. A classification between critical, significant and non-significant benchmarks. 2. Governance and organisational rules for both administrators and contributors. 3. Transparency and consumer protection rules. 5. Requirements to deal with the cessation of LIBOR © Valiante Diego - 37  BMR Classification – Critical benchmarks (art. 20 BMR) Key criterion. Use for financial contracts, instruments of for measuring performance of investment funds for a total value of at least €500bn. ‘Criticality assessment’ to be reviewed at least every 2 years. Mandatory administration of the benchmark (cessation of activity to be notified and approved, under specific conditions, incl. a plan with actions to be taken) Fair, reasonable, transparent and non-discriminatory distribution of information related to the benchmark. Mandatory contributions for contributors for up to 4 weeks or earlier if the assessment by the administrator is released. This period can be extended to 24 months if required and duly justified by the Competent Authority. The requirements above come on top of rules in Title II BMR, which include rules on governance and control of the administrator (e.g. conflict of interest rules), input data and methodology requirements and transparency, reporting of infringements, code of conduct and requirements for contributors (e.g. recordkeeping and how input data must be provided). © Valiante Diego - 38  BMR Classification -Significant and benchmark statement 2. Significant benchmarks (art. 24 BMR) – Key criterion. Use for financial contracts, instruments of for measuring performance of investment funds for a total value of at least €50bn over 12 months. With no or very few appropriate market-led substitutes. – Lighter rules than what imposed in Title II, such as (not exhaustive list): No operational separation from other administrator’s businesses Input may not be verifiable No code of conduct for each family of benchmarks – Unless Competent Authorities justifies a partial or total application of the Title II regime. © Valiante Diego - 39 For info  BMR Classification -Significant and benchmark statement 3. Non-significant benchmarks (residual category) – Disapplies even more Title II requirements (incl. no requirements for oversight function within an administrator, no special procedure for transparency of methodology) – The administrator may choose to disapply the other parts of Title II too, but it needs to be properly justified (‘comply or explain’ regime) Additional transparency and consumer protection rules (for all) 1. Benchmark statement Transparency document highlighting key feature of the new benchmark or family of benchmarks (e.g. elements of calculation of the benchmark on which discretion may be applied; market or economic reality being measured). 2. Procedure for changes or cessation of a benchmark. © Valiante Diego - 40 For info  BMR Classification – Special regimes Special regime for interest rate benchmarks (in Annex I, BMR)… – In addition or as a substitute of Title II requirements …and commodity benchmarks (Annex II, BMR) – Annex II instead of Title II and no ‘significant benchmark’ regime. No Title II requirements for regulated data benchmarks. ‘Supervised entities’ can only use benchmarks under EU rules (or non-EU if there is equivalence decision). © Valiante Diego - 41 For info  Short selling © Valiante Diego - 42  What is a short sale? The selling of a security that the seller does not own, i.e. any sale that is completed via the delivery of a security borrowed by the seller (typically from a stock broker). The short sale agreement also requires the short seller to rebuy the same amount of securities lent from the third party (stock broker, pension fund etc) at the market price. – If price lower, short seller will pocket the difference between what he/she sold at and what he/she paid to rebuy same security. – If price higher, short seller will pay more than what he/she sold the security at. The short seller, being bound to rebuy the same amount of security at some point (whether of own will or forced by the broker that lent the securities in given circumstances), is exposed to unlimited loss (theoretically!!!) Finally, excessive short selling activities can cause short squeezes when prices revert (go up), as the rush to cover up positions may reduce availability of securities in the market leading to an artificial high price (i.e. a price squeeze). © Valiante Diego - 43  Regulating short selling in shares and sovereign debt Distinction between covered and uncovered (or naked) short selling (SS) in shares – Uncovered SS are sale of shares that the seller does not own yet (in the process to acquire them) It can lead to ‘Failure to deliver’ – Only uncovered short selling that have credible arrangements to avoid settlement failures are allowed (for sovereign bonds-correlated instruments, and for hedging, no such limits will apply; art. 12-13 Short Selling Regulation). – Not applicable to market-making activities (art. 17 SSR) © Valiante Diego - 44  Regulating short selling in shares and sovereign debt Disclosure requirements (artt. 5-6 SSR) – if net positions above 0.2% to National Competent Authorities – if above 0.5% to the public too and – then every 0.1% increment NCAs’ powers include: – Power to collect more information in specific circumstances; and – Power to ban temporarily short selling, in the case of a significant fall in prices of 10% or more for liquid shares or indefinitely in exceptional circumstances (e.g. COVID 19 ban for several banks). © Valiante Diego - 45  Recommended readings Armour J., D. Awrey, P. Davies, L. Enriques, J. N. Gordon, C. Mayer and J. Payne, Principles of Financial Regulation, OUP, 2016 (Chapter 9) Harry McVea, ‘Supporting Market Integrity’, in The Oxford Handbook of Financial Regulation, Edited by Niamh Moloney, Eilís Ferran, and Jennifer Payne (2015) Additional readings – Azzutti, Ringe and Siegfried, Machine Learning, Market Manipulation and Collusion on Capital Markets: Why the 'Black Box' matters (February 19, 2021)available at https://ssrn.com/abstract=3788872 – NY FED report on LIBOR scandal https://www.newyorkfed.org/medialibrary/media/research/staff_report s/sr667.pdf – Andrew Verstein, Benchmark Manipulation, 56 B.C.L. REV. 215 (2015) Benchmark Manipulation (bc.edu) – Avgouleas, E., The Mechanics and Regulation of Market Abuse: A Legal and Economic Analysis. : Oxford University Press. © Valiante Diego - 46  Diego Valiante LEIF Master Programme [email protected] www.unibo.it