Futures and Options Report 12/2024

The Introduction of Derivative Market Manipulation

Part I

Pei-Fang Hsieh
pfhsieh@mx.nthu.edu.tw
College of Technology Management,
National Tsing Hua University

Abstract. In this article, I first introduce the definition and types of market
manipulation. The market manipulation tactics in derivative contract market would be
illustrated in the first part. I express two common themes of derivative market
manipulation 1) close price manipulation, and 2) order-based manipulation – spoofing
tactics.

1. Introduction
This article discusses the definition and several methods of market manipulation. I
will concentrate on potential manipulation in derivative contract markets. This essay
will first describe numerous potential manipulation tactics, and then outline legal
detections. Finally, I will provide evidence for potential manipulation of the derivative
markets discovered in crucial Asian derivative markets.
In the opening of Alexander and Cumming's (2020) book, Tālis J. Putniņš claims
that "Market manipulation is as old as markets." Numerous examples of market
manipulation exist in history and can be found in markets all around the world, in
almost all asset, and in a wide variety of forms. The impact of manipulation on asset
prices can be enormous, and the majority of these effects are considered illegal.
There is no generally accepted definition of market manipulation. The phrase
"market manipulation" is often used imprecisely in finance and economics literature
due to the lack of defined legal definitions. This issue has sparked a long-running
argument regarding the meaning of market manipulation. The US courts have devised
a four-part test for market manipulation, which includes capacity, intent to deceive,
causality, and artificiality (Johnson, 1981). In most jurisdictions, proving intent and
artificiality are the most challenging aspects of market manipulation case law. For legal
detections or empirical works, we should prove the investors’ intent to distinguish
manipulative from non-manipulative trading. Manipulation differs from legal trading
in that it involves an illegal intent (Goldwasser, 1999), although both can have similar
market impacts. Market manipulation involves trading with the intention of deceiving

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others or influencing prices or volumes. The second element, artificiality, is refer to the
artificial price is created when 1) a market player engages in or submits trades or orders
with an illegal aim and 2) these orders and trades affect market prices. These actions
create artificial supply or demand that brings the false information to cause the price to
be influenced by the false information.
"Market manipulation" refers to multiple types of strategies. Figure 1 presents a
taxonomy of the most typical types of market manipulation, illustrating their
relationships. The taxonomy expands on Putniņš's (2012) approach to include recent
kinds of market manipulation. Manipulation is broadly classified into four types: runs,
contract-based or benchmark manipulations, spoofing, and market power tactics.
Manipulation can be classified based on the technique used, such as trade-based,
information-based, action-based, submission-based, or order-based. Within these
systems, there are a variety of individual manipulation strategies. These categories and
methods are not mutually exclusive, and hybrid manipulation schemes incorporate
several of the individual techniques or their components.
In the first type of market manipulation, "runs," the manipulator takes a long or
short position in a stock, inflates or deflates the stock's price to entice other traders, and
then reverses his position at the inflated or deflated price. Runs are not limited to the
stock market and can occur in any financial security. "Pump-and-dump" manipulation
refers to taking a long position and then inflating a stock's price, while "bear raid"
manipulation involves taking a short position and then manipulating the price
downward.
The second type of market manipulation is "contract-based manipulation," also
known as "benchmark manipulation" or "reference price manipulation." This differs
from a run in that the manipulator profits from a contract or market outside the
manipulated market. This kind of manipulation is common in derivative contract
market.
The third category of manipulation involves "spoofing" and other order-based
techniques. Spoofing is the process of sending orders to a market and canceling them
before they are executed. This category focuses on manipulating orders, which may
include transactions as part of the strategy. Spoofing and order-based market
manipulation techniques have gained popularity as algorithmic and high-frequency
trading become more prevalent.
In the fourth category of manipulation strategies, the manipulator uses market
power to manipulate the supply of a security. Market power tactics, like contract-based
manipulation, rely on mechanical processes rather than runs. Manipulation, like runs,
involves profiting from market participants.
Within the board categories of market manipulation, the manipulation techniques

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that are often to observed in derivative market is contract-based manipulation. This

form of market manipulation is common in cash-settled derivative contracts. Spoofing
and order-based market manipulation techniques are also used in derivative market
especially the exchange offer the high frequency trading mechanisms. In addition, the
manipulators also use their market power to affect the reference price and get profits
from derivative contracts. For concentrating on the market manipulation knowledge in
derivative market, I will introduce the specific derivative contract manipulating tactics
in the following section and present some empirical evidence in the second part of this
article.
2. Market Manipulation in Derivative Market
Derivative market manipulation frequently occurs on cash-settled derivative
contracts. An agent who holds a cash-settled derivative contract, at contract expiration,
receives a payment linked to a price benchmark (hereafter said reference price, close
price or settlement price), which is determined based on trade prices of certain
underlying assets. If the agent holds large number of derivative positions may have
incentives to manipulate price benchmarks and influence payoffs on their larger
contract positions by trading relatively small amounts of underlying assets. Contract
market manipulation is illegal in the US and other jurisdictions, but it is challenging to
identify and prosecute. US authorities presently regulate manipulation through a
behavioral approach. Trading with the purpose to manipulate prices and contract
payoffs is a crime. Regulators often prosecute traders based on evidence from email or
phone communications.
Zhang (2022) presents a theoretical model for contract market manipulation. The
model clearly defines manipulation as a distinct sort of strategic trading activity.
Manipulation can affect both hedgers and spot market participants, while official
initiatives like contract position limitations can improve the situation. Manipulation-
induced market distortions vary based on aggregate storage capacity, competition level,
and contract size of spot traders. Contract market regulators frequently use data to
determine the magnitude of manipulation-induced distortions. I will display the
potential empirical evidence of close price manipulation in the last section.
The integrity of closing pricing is important. Closing prices are used to calculate
mutual fund net asset value (NAV), option and futures settlement values, variation
margin, mark-to-market, and daily settlement for derivative contracts. Detecting
closing price manipulation is tough, and only a small percentage of cases are convicted.
Comerton-Forde and Putniņš (2011) examine the effects of closing price manipulation
and find that manipulation is associated with large increases in day-end returns, return
reversals, trading activity and bid ask spreads. There are two research themes related to
the potential manipulation of closing prices in derivative market. First, I analyze how

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financial intermediaries responded to a well-documented suspected manipulation

involving a portfolio manager using 'bang-the-close' trades to impact commodity
futures contract settlement prices. Second, I express the potential manipulation of
closing stock prices around equity option expiration dates.
Atanasov, Davies, and Merrick (2015) investigated how NYMEX floor traders
reacted to an alleged manipulation involving a hedge fund portfolio manager (PM)
submitting massive 'bang-the-close' buy orders for platinum and palladium futures
contracts over a 7-month period from November 2007 to May 2008. Court transcripts
show that the PM aimed to acquire contracts at high prices, resulting in 'buy signals'
and new highs in futures daily settlement prices. The PM had a financial incentive to
raise platinum and palladium prices, as his fund had significant net long positions worth
nearly a billion dollars at the peak. This manipulation tactics is very hard to detect.
Atanasov, Davies, and Merrick (2015) provide a decompose method to detect the short-
term reaction of other market participants to the bang-the-close orders, however it is
more challenging to determine the long-term effects from the manipulation.
In option markets, 'pinning' occurs when a stock price closes at or near an option
strike price on its expiration date. Pinning occurs when both call and put options at a
specific strike price expire worthless, leading some market participants to suspect stock
price manipulation. Ni, Pearson, and Poteshman (2005) demonstrate that closing stock
prices tend to cluster around option strike prices on option expiration days. However, it
remains unclear if the pinning is deliberate manipulation or a result of market maker
delta hedging. Stock pinning has become more prevalent as exchange-traded option
trading volumes have skyrocketed. Stivers and Sun (2013) analyze stock return patterns
during option expiration weeks for S&P 100 stocks. Market makers' rebalancing
through delta-hedging creates predictable weekly returns patterns, according to their
argument. Market makers typically hold a net long position in call options, resulting in
short equity positions. Short positions are unwound around expiration, resulting in
larger weekly returns. Traders sometimes believe that equities are manipulated to close
at the 'max pain' price during option expiration dates. The term "max pain" refers to the
stock price that causes the majority of outstanding options to expire 'out-of-the-money'
(i.e., worthless). Although commonly debated in the trading community, there has been
little scholarly research on max pain and other forms of option expiry manipulation.
Order spoofing is kind of order book manipulations, using limit orders, which is
designed to provide the manipulator with an unfair advantage. Order spoofing is a form
of order book manipulation in which limit orders are placed to deceive other market
participants, including traditional traders and algorithmic trading bots, into believing
there is greater demand or supply. These spoof orders are typically high in quantity to
provide the impression of a significant order imbalance. When a spoof order is made

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and succeeds, the market swings based on its conviction that the imbalance exists.
Spoof orders can be used to influence prices and execute trades on opposing sides of
the book. Brogaard, Li, and Yang (2024) present a concrete description of spoofing and
evidence that it has emerged in high frequency trading techniques. Because the majority
of derivative markets use high frequency trading systems, spoofing in derivative
markets is a potential topic for investigation.
In the second section of this article, I discuss probable empirical evidence of close
price manipulation and spoofing in the derivatives market. I will describe two working
articles on these two topics, which focus on critical Asian derivative markets.

Figure 1 Taxonomy of manipulation techniques.

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Reference
Alexander, C., Cumming, D., 2020. Corruption and Fraud in financial markets:
Malpractice, Misconduct and Manipulation. John Wiley & Sons.
Atanasov, V., Davies, R.J. and Merrick, J.J., 2015. Financial intermediaries in the midst
of market manipulation: Did they protect the fool or help the knave? Journal
of Corporate Finance 34, 210-234.
Brogaard, J., Li, D. and Yang, J., 2024. Does High Frequency Market Manipulation
Harm Market Quality? Working paper, University of Utah. SSRN:
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4280120
Comerton-Forde, C. and Putniņš, T.J., 2011. Measuring closing price manipulation.
Journal of Financial Intermediation 20, 135-158.
Goldwasser, V., 1999. Stock market manipulation and short selling. Sydney: CCH
Australia/The Centre for Corporate Law and Securities Regulation.
Johnson, P.M., 1981. Commodity Market Manipulation. Washington and Lee Law
Review 38, 725-732.
Ni, S.X., Pearson, N.D. and Poteshman, A.M., 2005. Stock price clustering on option
expiration dates. Journal of Financial Economics 78, 49-87.
Putniņš T. J.¸ 2012. Market Manipulation: A Survey. Journal of Economic Surveys 26,
52-967.
Stivers, C.T. and Sun, L., 2013. Returns and option activity over the option-expiration
week for S&P 100 stocks. Journal of Banking and Finance 37, 4226-4240.
Zhang, A. L., 2022. Competition and manipulation in derivative contract markets.
Journal of Financial Economics, 144, 396–413.

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