Artur Khachatryan’s $373,000 Spoofing Scheme

The screen flickered with numbers. Green flashes for upticks, red for downticks, a river of data streaming across the monitors in real time. For anyone watching Artur Khachatryan’s trading terminal on an ordinary morning in 2023, the activity would have looked like the work of an aggressive day trader—someone willing to move fast, place large orders, chase momentum in volatile markets. But if you watched long enough, you’d notice something odd. Orders appeared in bursts, thousands of shares at a time, stacking up on one side of the order book. Then, seconds later, they vanished. The stock price jerked in response, and when it did, a much smaller trade executed on the opposite side. Over and over, the pattern repeated: phantom orders that never filled, price movements that seemed to respond to pressure that wasn’t real, and profits that accumulated in fractions of a percent, compounding into hundreds of thousands of dollars.

By the time the Securities and Exchange Commission filed its complaint in the United States District Court for the Central District of California on December 16, 2025, Khachatryan had allegedly netted $373,885 through a scheme that regulators would describe as “spoofing”—a form of market manipulation that treats the stock market like a puppet show, using fake orders to pull strings and create the illusion of supply and demand. The case, docketed as Case No. 25-cv-11863, would be settled before it ever reached trial. But the details laid out in the SEC’s complaint paint a portrait of a calculated, repetitive fraud that exploited the millisecond mechanics of modern trading to siphon money from other investors who believed the market they were watching was real.

The Modern Market and the Ghost Orders

To understand what Artur Khachatryan allegedly did, you have to understand how stock markets work in 2025. Gone are the days of floor traders shouting orders in colored jackets. Today’s markets are electronic, algorithmic, and fast—faster than human reaction time. When you place an order to buy or sell a stock, that order doesn’t just sit in a queue. It becomes visible to everyone watching that stock’s order book: a real-time display of buy orders (bids) and sell orders (asks) at different price levels. The order book is supposed to reflect genuine interest—people and institutions who actually want to transact. Market participants use it to gauge supply and demand, to decide whether to buy or sell, and at what price.

Spoofing corrupts that signal. A spoofer places large orders they never intend to execute. These orders are designed to deceive other traders into thinking there’s significant buying or selling interest at a particular price. When other market participants see a wall of buy orders, they might think the stock is about to rise, so they jump in and buy. When they see a wall of sell orders, they might think the stock is about to fall, so they sell or avoid buying. The spoofer, having triggered this reaction, cancels the fake orders and executes a real trade on the opposite side, profiting from the price movement they artificially created.

It’s illegal under multiple federal securities laws. Section 9(a)(2) of the Securities Exchange Act of 1934 prohibits manipulative trades designed to create a false appearance of active trading or artificial prices. Section 10(b) and Rule 10b-5 ban fraudulent and deceptive devices in connection with securities transactions. Section 17(a) of the Securities Act of 1933 prohibits fraud in the offer or sale of securities. All of these provisions converge on a single principle: the market must be fair, transparent, and free from manipulation. Spoofing violates all three.

Artur Khachatryan, according to the SEC’s complaint, understood exactly how to exploit this system.

The Mechanics of the Scheme

The SEC’s investigation, detailed in its complaint filed in federal court in Los Angeles, describes a pattern of trading activity that repeated across multiple securities over an extended period. Khachatryan allegedly employed a straightforward but effective spoofing strategy: he would place large orders on one side of the market—say, a bid to buy thousands of shares—while simultaneously or shortly thereafter placing a much smaller order on the opposite side—an offer to sell a smaller number of shares. The large order was bait. It was designed to move the market. The small order was the real trade, the one Khachatryan actually intended to execute. Once the small order filled, profiting from the artificial price movement the large order created, Khachatryan would cancel the large order before it could execute.

This wasn’t a one-time gamble or an opportunistic trade. The complaint alleges that Khachatryan engaged in this conduct systematically. The repetitive nature of the scheme is critical to understanding its illegality. Spoofing isn’t about making a mistake or changing your mind about a trade. It’s about creating a pattern of deception—placing orders you know you’re going to cancel, with the intent to manipulate prices.

Consider a simplified example. Suppose a stock is trading at $10.00, with a few hundred shares available at the best bid and ask. Khachatryan places an order to buy 10,000 shares at $10.02. Other traders see this large order and interpret it as a signal of strong buying interest. Algorithmic traders might react by buying ahead of the perceived demand, pushing the stock price up. At the same time or moments later, Khachatryan places an order to sell 500 shares at $10.03. The price, nudged upward by the apparent buying pressure, hits his sell order, and it executes. He’s now sold 500 shares at a price that was artificially inflated by his fake buy order. He then cancels the 10,000-share buy order, which he never intended to fill. The profit per share might be just a few cents, but over hundreds or thousands of trades, it compounds.

According to the SEC, this is precisely what Khachatryan did. The complaint doesn’t specify the exact securities he traded or the exact dates, but it makes clear that the scheme was carried out over a period substantial enough to generate nearly $374,000 in ill-gotten gains. That figure isn’t trivial. It represents thousands of individual trades, each one a small manipulation, each one a fractional distortion of the market’s price discovery mechanism.

The sophistication required isn’t in the strategy itself—spoofing is relatively simple conceptually—but in the execution. You need access to trading platforms that allow rapid order entry and cancellation. You need to operate at speeds where you can cancel orders before they inadvertently fill. You need to do it enough times to make it profitable, but not so blatantly that you trigger immediate alarms. Khachatryan, the SEC alleges, managed that balance for long enough to pocket more than a third of a million dollars.

The Regulatory Spotlight

Spoofing became a focal point for regulators following the 2010 “Flash Crash,” when the Dow Jones Industrial Average plummeted nearly 1,000 points in minutes before recovering. The crash exposed how algorithmic trading and manipulative practices could destabilize markets. In 2010, the Dodd-Frank Act explicitly prohibited spoofing in the commodities markets, and courts and regulators have since applied anti-fraud provisions to spoofing in securities markets as well.

The SEC and the Department of Justice have prosecuted numerous spoofing cases in the past decade. Some involved traders at major banks or hedge funds; others involved individual day traders operating from home offices. What unites them is the deliberate deception—placing orders to mislead, not to trade.

Detecting spoofing requires sophisticated surveillance. Exchanges and regulators use algorithms to flag suspicious patterns: orders that are repeatedly placed and canceled, orders that are disproportionately large relative to a trader’s actual transaction history, orders that correlate with opposite-side trades. When the SEC’s Division of Enforcement spots these patterns, it can subpoena trading records, communications, and account data to build a case.

In Khachatryan’s case, the SEC’s complaint doesn’t detail the investigative process, but the outcome is clear. The agency identified the pattern, quantified the profits, and built a case under multiple securities law provisions. On December 16, 2025, the SEC announced settled charges. Khachatryan, without admitting or denying the allegations, agreed to disgorge $373,885 in ill-gotten gains, pay prejudgment interest, and pay a civil penalty. The total financial penalty matched the amount he allegedly gained, a common outcome in settled SEC enforcement actions.

The Defendant

Little is publicly known about Artur Khachatryan beyond the details in the SEC’s enforcement action. The complaint identifies him as an individual trader but doesn’t specify his employment, background, or location beyond the filing in the Central District of California. There’s no indication he was associated with a registered broker-dealer or investment adviser. He appears to have been trading on his own account, a retail trader with access to the kind of direct market access platforms that allow rapid, high-frequency trading.

This anonymity is itself telling. Khachatryan isn’t a household name. He didn’t run a Ponzi scheme or defraud thousands of retirees. He operated in the shadows of the market, manipulating prices in ways that most investors would never notice. His victims weren’t identifiable individuals but the market itself—other traders on the opposite side of his manipulated trades, who bought at inflated prices or sold at depressed ones because they believed the order book reflected genuine interest.

This diffusion of harm is characteristic of market manipulation cases. Unlike embezzlement or Ponzi schemes, where victims can point to stolen money and empty accounts, spoofing creates a more abstract injury. The market is less efficient, less fair, less trustworthy. Prices don’t reflect true supply and demand. The harm is systemic and hard to quantify on an individual basis, which is why enforcement often falls to regulators rather than private lawsuits.

The Legal Framework

The SEC charged Khachatryan with violating four key provisions of federal securities law, each addressing a different aspect of his alleged conduct.

Section 17(a) of the Securities Act of 1933 prohibits fraud in the offer or sale of securities. It has three subsections: 17(a)(1) bans schemes to defraud, 17(a)(2) bans obtaining money by means of untrue statements or omissions, and 17(a)(3) bans transactions that operate as a fraud. Spoofing arguably violates all three, but particularly 17(a)(1) and (3), as it constitutes a scheme to defraud and a fraudulent transaction.

Section 10(b) of the Securities Exchange Act of 1934 and Rule 10b-5 are the workhorses of securities fraud enforcement. Section 10(b) makes it unlawful to use manipulative or deceptive devices in connection with the purchase or sale of securities. Rule 10b-5, promulgated by the SEC under Section 10(b), spells out the prohibition: you can’t employ schemes to defraud, make material misstatements or omissions, or engage in acts that operate as a fraud. Spoofing fits squarely within this framework—the fake orders are deceptive devices designed to manipulate prices.

Section 9(a)(2) of the Exchange Act is more specific. It prohibits transactions in securities that create actual or apparent active trading, or raise or depress prices, for the purpose of inducing others to buy or sell. This is the provision most directly aimed at market manipulation like wash trading, matched orders, and spoofing. By placing large orders designed to create the appearance of buying or selling interest, Khachatryan allegedly violated this section.

The combination of charges reflects the SEC’s approach to spoofing: treat it as both fraud (under the general anti-fraud provisions) and manipulation (under the specific anti-manipulation provisions). This layered approach ensures that even if a defendant argues they didn’t technically lie or omit information—a defense that might complicate a Rule 10b-5 case—they still face liability under Section 9(a)(2) for manipulative conduct.

The Settlement

Artur Khachatryan settled the SEC’s charges without admitting or denying the allegations, a standard feature of SEC settlements. The settlement, detailed in the litigation release published on December 16, 2025, required Khachatryan to pay disgorgement of $373,885, representing the profits he allegedly gained from the spoofing scheme. He also agreed to pay prejudgment interest, which compensates for the time value of money—the idea that he had use of those ill-gotten gains while the investigation proceeded. Finally, he agreed to pay a civil penalty.

The SEC did not disclose the exact amounts of prejudgment interest or the civil penalty in the public release, but in spoofing cases, penalties often match or exceed disgorgement, particularly when the conduct is systematic and sustained. The total financial impact on Khachatryan likely exceeded half a million dollars.

The settlement also typically includes injunctive relief, meaning Khachatryan is permanently barred from violating the securities laws he allegedly broke. If he engages in similar conduct in the future, he could face contempt proceedings and additional penalties. The settlement is a consent judgment, entered by the court without a trial.

Why settle? For defendants, settlement avoids the cost, risk, and publicity of a trial. The SEC’s case appeared strong—spoofing cases are often built on trading data that speaks for itself. Pattern evidence is powerful, and if the SEC could show that Khachatryan repeatedly placed and canceled orders in a manner consistent with spoofing, a jury would likely find the conduct manipulative. Settling allows the defendant to resolve the matter, pay the penalty, and move on without a formal admission of guilt. For the SEC, settlement conserves resources and ensures a certain outcome. Trials are expensive and uncertain. A settlement delivers disgorgement, penalties, and a public enforcement action that sends a deterrent message to other would-be spoofers.

The Broader Context: Spoofing in Modern Markets

Artur Khachatryan’s case is one of many spoofing enforcement actions the SEC and DOJ have brought in recent years, but each case underscores the same fundamental tension in modern markets: the speed and automation that make markets efficient also create opportunities for manipulation.

Spoofing thrives in electronic markets where orders can be placed and canceled in milliseconds. High-frequency trading firms, which execute millions of trades per day using algorithms, operate in the same ecosystem. The difference between legitimate high-frequency trading and spoofing is intent. A high-frequency trader might place and cancel thousands of orders because market conditions change rapidly, or because their algorithm is probing for liquidity. A spoofer places orders they never intend to fill, with the purpose of deceiving others.

Drawing this line requires parsing motive and behavior—difficult work for regulators. The SEC and exchanges use sophisticated surveillance tools to identify patterns that suggest spoofing: high cancel-to-fill ratios, large orders that are consistently canceled after smaller opposite-side orders execute, order placement that correlates with specific price movements. But false positives are possible. A trader might cancel an order for legitimate reasons—a change in strategy, new information, or a mistaken entry.

This is why pattern evidence is critical. One canceled order proves nothing. A thousand canceled orders, all fitting the same profile, all correlated with opposite-side profits, tells a story. In Khachatryan’s case, the SEC’s complaint describes conduct that was repetitive and systematic, suggesting the pattern evidence was strong.

The enforcement landscape has evolved. In 2015, the DOJ brought the first major spoofing prosecution against Navinder Singh Sarao, a British trader accused of contributing to the 2010 Flash Crash by spoofing E-mini S&P 500 futures contracts. Sarao ultimately pleaded guilty and was sentenced to home confinement. Since then, dozens of traders have faced spoofing charges, some resulting in prison sentences, others in settlements and fines.

The penalties are meant to be deterrents. Spoofing is a victimless crime in the sense that there’s no single victim who lost a specific, identifiable sum. But it’s a crime against the market’s integrity. If traders believe the order book is fake, they lose confidence in price signals. Market makers widen spreads. Liquidity dries up. Volatility increases. The market becomes less efficient, and the cost of that inefficiency is borne by all investors.

The Human Element: Who Pays?

In a traditional fraud case—embezzlement, Ponzi schemes, insider trading—there are identifiable victims. Retirees lose their savings. Shareholders lose their investments. Companies lose their reputations. The human cost is visible and tragic.

Spoofing’s harm is more diffuse. Khachatryan’s alleged profits came from traders on the opposite side of his manipulated trades. If he spoofed a stock higher and sold into the artificial demand, then whoever bought at that inflated price overpaid. If he spoofed a stock lower and bought at the artificial discount, then whoever sold at that depressed price undersold. These counterparties might be retail investors, institutional investors, or other algorithmic traders. They likely never knew they were victims. The few cents per share they lost would have been invisible, chalked up to market volatility or bad timing.

But aggregate those small harms across thousands of trades, and you get $373,885 in profits for Khachatryan. That money didn’t materialize out of thin air. It came from the pockets of other market participants who traded at prices that weren’t real.

This is why the SEC enforces against spoofing even when there’s no sympathetic victim to put on the witness stand. The integrity of the market itself is the victim. Trust in price discovery is the casualty. If investors believe the market is rigged, they pull out. Capital allocation becomes less efficient. Economic growth suffers.

The Aftermath and the Broader Questions

Artur Khachatryan’s settlement closes the enforcement chapter of his case, but it leaves broader questions unresolved. How many other traders are spoofing undetected? How effective are the SEC’s surveillance tools in catching manipulation in real time? What more can be done to prevent spoofing before it generates hundreds of thousands of dollars in illicit profits?

Part of the challenge is technological. Spoofing detection requires pattern recognition across vast datasets—billions of orders, cancellations, and executions. The SEC has invested in analytical tools and partnerships with exchanges, but spoofers are adaptive. They vary their order sizes, timing, and securities to evade detection. Some use multiple accounts or trade through brokers in different jurisdictions.

Another challenge is definitional. Not every canceled order is spoofing. Traders legitimately change their minds, react to news, or adjust strategies. The SEC must prove intent—that the orders were placed to deceive, not to trade. This often requires circumstantial evidence: the pattern, the timing, the correlation between fake orders and real profits. In settlement cases like Khachatryan’s, the defendant doesn’t admit intent, so the public record doesn’t include a confession or explanation. We’re left with the pattern and the SEC’s allegations.

The financial penalties in spoofing cases are also debated. Is disgorgement plus a civil penalty enough? Some argue that without criminal prosecution and the threat of prison, spoofing remains a calculated risk—a cost of doing business. If you make $373,885 and get caught, you pay it back plus a penalty. If you don’t get caught, you keep it. The expected value might still be positive for a rational, amoral trader.

Criminal spoofing prosecutions do happen. The DOJ has secured prison sentences in several cases. But those tend to involve larger schemes, often in futures markets, or cases with additional charges like wire fraud or conspiracy. Retail traders who spoof in securities markets often face civil enforcement from the SEC but not criminal charges from the DOJ. Whether that’s appropriate is a policy question without an easy answer.

The Unseen Market

Artur Khachatryan’s case is, in many ways, a story about invisibility. He operated in a corner of the market most investors never see: the order book, the millisecond-to-millisecond fluctuations in bid and ask prices, the high-frequency churn of orders placed and canceled faster than a human can process. His alleged fraud was invisible to those it harmed. His profits were invisible to anyone not scrutinizing trading records. Even his name was largely invisible until the SEC filed its complaint.

This invisibility is both the power and the danger of modern electronic markets. They are faster, more liquid, and more accessible than ever before. A retail trader with a laptop can trade stocks with the same speed and access as a Wall Street firm. But that speed and access also create opportunities for manipulation that would have been impossible in the era of floor trading and paper tickets.

Regulators are playing catch-up. The tools to detect spoofing are improving, but so are the techniques to evade detection. The legal framework—Section 9(a)(2), Rule 10b-5—was written in the 1930s, long before electronic order books and algorithmic trading. Courts and the SEC have adapted those laws to modern conduct, but the gap between the technology and the regulation is real.

The Closing Image

Somewhere, on a server, the records of Artur Khachatryan’s trades still exist. Thousands of orders, most of them canceled within seconds. Thousands of trades, most of them for small sums, fractions of a percent. The data doesn’t lie. The pattern is there, encoded in timestamps and order IDs, a digital fingerprint of alleged manipulation.

The settlement agreement is now filed with the court. Khachatryan has paid his disgorgement, his interest, his penalty. The SEC has issued its press release. The case is closed.

But the market continues, order by order, millisecond by millisecond. Other traders place orders. Some are genuine. Some, perhaps, are not. The order book flickers, numbers rising and falling, and somewhere in that stream of data, the line between legitimate trading and manipulation remains as thin as ever.