Home > Articles > Business & Management > Finance & Investing

Crapshoot Investing: How Tech-Savvy Traders and Clueless Regulators Turned the Stock Market into a Casino

Equity markets are now high-speed casinos rigged against individual investors. Now, Jim McTague reveals the twin causes: high-frequency traders and blundering regulators.
This chapter is from the book

Strange Encounters

Beginning in 2007, two long-time equities traders named Sal Arnuk and Joseph Saluzzi noticed some weirdly disturbing price movements in the stock markets as they observed client trades on their multiple screens in a small trading room in quiet Chatham, New Jersey. When they went to hit a bid on certain exchanges, the price suddenly disappeared and a lower bid instantly appeared in its place. It was as though some invisible, malign force was attempting to trick the traders into chasing the stock up or down the price ladder. Never before had they seen anything like it. The ghostly presence was so incredibly fast that there was absolutely no chance of the traders ever winning the game. The deck was stacked against them. If they took the bait, they would always end up paying more or getting less than the market's consolidated tape of prices had initially advertized.

The price jumps were aggravating. Arnuk's and Saluzzi's job was to obtain the best execution price on large orders of shares for their institutional clients, which included large mutual fund managers such as INVESCO. Somebody was threatening their livelihood. Their firm, Themis Trading LLC, was named for a Greek goddess who personified fairness and trust.1 Someone subtly was trying to subtract these two attributes from the market, and this got their blood boiling. It also got them wondering how the bastard was doing it.

The blocks of stock handled by Arnuk and Saluzzi were not small potatoes. They frequently ranged in size from 300,000 shares to 2 million shares. The transactions had to be conducted gingerly to avoid "information leakage" that could cause imbalances in the market, raising the cost of transacting the business. The stock market always had provided a habitat for predators who exploited weaknesses and inefficiencies in its structure, and if you did not avoid these cold-hearted traders, you had about as much chance as an anchovy in a shark tank. The game of hide and seek was relentless. The predators always were probing for new weaknesses. If, for instance, the predators discovered through the grapevine that a seller had a huge inventory of stock to unload, they would short the stock, sending its price lower and costing the institution precious nickels, dimes, and pennies. If they discovered that a mutual fund or a pension fund was attempting to accumulate a large position in a stock, they would front-run the order, buying up the shares ahead of the bigger buyer and then selling it to them for a cent or two more than it would have paid if its intentions had remained secret.

To avoid predation, cagey traders like Arnuk and Saluzzi employed numerous strategies to camouflage both their identities and their order size. If a big mutual fund wanted to sell several hundred thousand shares of a stock to rebalance its portfolio, it might use a trusted broker as an intermediary to locate another, equally large institution to buy its position at a negotiated price. It was hush-hush. Blabbermouths were excluded from such arrangements.

If a large counterparty could not be found, the fund's traders might take a portion of the order to a so-called dark pool, an off-exchange venue where block traders anonymously submit buy and sell orders, hoping to get at least a portion of the order executed. Some dark pools were exclusive. Participants were expected to be fair and honest, and any violation of the rules could result in immediate suspension or even permanent expulsion. Because the bid and offers in a dark pool were not posted in the public or "lit" markets, they did not affect the prices on the consolidated quote. The public or lit market had no idea that a seller was looking for buyers and vice versa until stock was actually sold. Then the execution price was listed on the consolidated tape—the data feed one sees crawling across the bottom of CNBC.

To sell the remaining shares, the fund often resorted to automated trading software to break up the block into smaller orders, which then were sent to the various lit exchanges. The size and frequency of the orders was determined by algorithms looking at price and volume and the time parameters of the transaction. Finally, the funds and institutions enlisted the aid of human traders such as Arnuk and Saluzzi to use their wiles to avoid the predators.

Each of the methods had an Achilles' heel. For instance, there were limits on order sizes at the dark pools. And the algorithms that were employed to slice and dice big orders could be reverse-engineered in a matter of milliseconds by a predator's faster, more sophisticated algorithm, allowing it to automatically front-run the order. In the course of a year, a millisecond advantage for a high-frequency trader over the institutional traders can be worth $100 million.2

The funny business detected by Arnuk and Saluzzi was on a much higher level than the usual pitfalls that traders faced. The flickering prices were so radical that it was like a squadron of F-16 fighter jets suddenly appearing among the Sopwith Camels of World War I. Ironically, the phenomenon had appeared just about the time the U.S. Securities and Exchange Commission (SEC) had implemented its Regulation NMS (National Market System)—a sweeping reform aimed at increasing competition among the exchanges to both decrease customer costs and make the stock market friendlier to long-term investors. The rule, demanded by Congress in 1975, finally had been produced by the SEC 30 years later in 2005 and activated 2 years after that. Clearly, there was a link. Intrigued, the two traders decided to dig into the matter.

Arnuk and Saluzzi had not been spoiling for a fight or longing for the limelight. They had no idea what they were getting into and no premonition that their discovery would rattle the investment world. Since 2002, both had been living the good life in the upscale suburban community of Chatham, a rustic borough tucked off a highway near the uber-chic Short Hills Mall. Take the exit off of Route 24 by Neiman Marcus and, behold, you were on Main Street in Leave It to Beaver land, with handsome, 1940s-era wood houses, tree-lined streets, and neatly trimmed lawns. Chatham was just 25 miles from Wall Street, but it might as well have been 10,000 miles away. None of Lower Manhattan's furious rush was evidenced here. There were no throngs of sharp-elbowed, driven people barreling down sidewalks, no blaring taxis clogging the streets. During the week, it seemed as quiet as Sunday.

Both men were veterans of Wall Street. After a decade working for big firms, they had traded a 2-hour round-trip commute between Manhattan and Brooklyn for a 10-minute, round-trip commute that saved them enough time to coach their kids' Little League games.3 This was a utopia. They could balance their priorities of breadwinning and parenting with no maddening traffic jams and crowded subways in between.

They leased an office in a quaint, wooden retail village in the heart of town, opposite a dance studio, a tea restaurant, a tennis shop, and a beauty salon. It was not the locale usually associated with a trading floor. Their space was open and airy and had big windows on three walls to let the sun shine in. If they hadn't taken the space, it probably would have been occupied by a real estate office or a small accounting firm.

Inside, it had the air of a man cave, with golf clubs leaning against the wall. Arnuk and Saluzzi and three other traders dressed their Saturday's best: dungarees or shorts, and tee shirts. And there were lots of computers. Their "trading floor" was a long desk topped with four or five multiscreened computer screens where they watched the world, the markets, and their clients buy and sell orders and talked about the frustrating New York Mets between trades.

Both men love baseball, although neither played beyond the youth-league level. As adults, they both coached their sons' teams with passion. Arnuk, who had attended the prestigious Poly Prep high school in Brooklyn, a private high school whose alumni include former SEC Chairman Arthur Levitt, had bonded with his father and siblings as he grew up watching baseball on a black-and-white television. He also bonded with his own kids through baseball. Arnuk was a sturdy, soft-spoken man who wore black-rimmed glasses and looked like a professor. His calm exterior belied his highly competitive side. Saluzzi, who had attended Bishop Ford High School in Brooklyn, carried himself like a ball player. He was trim and walked with a relaxed, sure-footed gait.

The Brooklyn natives went a long way back and appeared to be as close as brothers. They had met in the late 1980s at Morgan Stanley, their first employer after college. Arnuk, who grew up in Brooklyn's Bay Ridge section, had a BA in finance from SUNY Binghamton University; and Saluzzi, who hailed from the Sheepshead Bay neighborhood, had a BA in finance from NYU. After a few years at the prestigious firm, they both concluded independently that to advance in the world of finance, they'd have to obtain graduate degrees. So they both left Morgan Stanley to enroll in MBA programs. Arnuk started attending the Stern School of Business at NYU part time; and Saluzzi resigned a few months later to attend the Kenan-Flagler Business School of the University of North Carolina.

Arnuk graduated in 1991, and Saluzzi in 1993. Arnuk began working for Instinet, a global brokerage firm that specialized in computerized trading. He recruited Saluzzi for a job there. They were neighbors at this point. Both men had married and secured homes in Bay Ridge.

In 2002, Saluzzi and Arnuk got tired of the rat race and decided to move to New Jersey and start their own company. Arnuk was the first to go, and he convinced Saluzzi to join him in a trading venture.

They were not making the kind of big money that drives a congressman to denounce Wall Street from the floor of the House or the Senate, but they were not doing badly either. The business wasn't exclusively about money anyway. They were self-sufficient. They were their own bosses. But in 2007, someone was threatening their business by playing unfairly. It was like a ball player shooting up on steroids so he could muscle the ball farther than anyone else. Someone in the market was using the equivalent of steroids to trade in and out of the market faster than everybody else.

As the men began to track down the hombre, they learned just how radically Regulation NMS had changed the market, and it surprised them. The change had engendered an explosion in the number of high-frequency traders plying the markets with super-charged computers and advanced pattern-recognition and statistical software designed to beat the market. These guys always had been around, but now there seemed to be a lot more of them, and their robotic trading machines were much faster than anything ever deployed in the markets. They programmed these overclocked computers to make money buying and selling stocks without direct human oversight. For every dozen firms, there were hundreds of these robotic trading wunderkinds, and their numbers were growing every day because venture capitalists and hedge funds were bankrolling start-ups left and right. Clearly, a lot of people thought high-frequency trading (HFT) was a path to quick and easy profits.

The general investment public had no idea that this market version of the Invasion of the Body Snatchers was under way. Some of the biggest players in the high-frequency trading sector were not household names: They were proprietary trading firms such as Getco and Tradebot and hedge funds such as Millennium, DE Shaw, WorldQuant, and Renaissance Technologies. Others were household names, but investors hadn't paid much attention to their forays into mechanized trading because it was a relatively small portion of their earnings and they did not break out the numbers in their annual reports. Goldman Sachs, which had become notorious in the public's eyes, owing to its role in the collapse of the mortgage market, had a sizable high-frequency trading desk. Registered brokers like Bank of America and Lime Brokerage and Credit Suisse offered suites of exotic trading algorithms and other services to customers who wanted to engage in the practice. But they all were secretive about the success of these operations. Why tempt copycats?

Joining the gold rush were commodities traders and teams of computer scientists and mathematicians with formulas designed to outsmart any human trader. The human brain was not smart enough or quick enough to compete with the over-clocked, nitrogen-cooled computing engines designed by whiz kids and trading hundreds of millions of stock shares every day. The trader-scientists began writing algorithms so that their computers could outsmart competing trading computers, triggering the equivalent of an arms race. Teams of mathematicians and computer scientists worked round-the-clock to improve their machines.

Arnuk and Saluzzi discovered that these new competitors had another significant technological advantage: Most of them possessed servers that were "collocated" at or near the exchanges. This meant that for a steep, monthly rental, a high-frequency trading firm was allowed to link its servers directly to the servers of the stock exchanges and get price and trading data milliseconds faster than anyone who could not or would not spring for such a hookup, like retail investors. In the view of the HFT crowd, this "low-latency" networking was completely within the bounds of acceptable behavior. Alistair Brown, founder of Lime Brokerage, which caters to high-frequency traders, said in a magazine interview in 2007, "Any fair market is going to select the best price from the buyer or seller who gets their order in their first. Speed definitely becomes an issue. If everyone has access to the same information, when the market moves, you want to be the first. The people who are too slow are going to be left behind."4

Depending on which strategies they employed, the HFT firms programmed their computers to hold the stocks anywhere from 2 minutes to 2 days. Their object was to make a little money on each trade, not swing for the fence. It was a fairly predictable business because the shorter the period of time under study, the easier it is to forecast the future based on historic pricing, volume, and other data. Systems become increasingly unstable over time, which is why long-range weather forecasts are unreliable and which is why hedge funds making multiyear credit bets lost their shirts in 2007. The lesson of 2007 had made a deep impression on so-called quants, which was short for "quantitative investors." They embraced HFT with religious fervor. Less risk equaled more money. The founder of Tradebot, an HFT located in Kansas City, Missouri, told students in 2008 that his firm typically held stocks for 11 seconds and had not suffered a losing day in four years.5

There was no public source of information of HFT industry profits, just anecdotes and rumors, so no one knew for certain how much money they were pulling down in a given year. The best conservative estimate was $20 billion just for firms that tried to earn small spreads and fees from the exchanges by playing the role of market maker. They represented less than 10% of the HFT universe.

A market maker takes the opposite side of an incoming order to earn a small profit on the spread on fees. Often this is less than 2 cents per share. But if the HFT firm trades millions of shares each day, it can rack up a handsome annual return. Some earn returns of close to 300%.

By December 2008, Saluzzi and Arnuk had a strong suspicion as to what was going on in the markets. Like all good investigators, they had cultivated inside sources from a number of HFT firms. What they found was disturbing: Based on their reading of the facts, high-frequency shops were using their superior computing power in new, devious, and possibly unethical ways to covertly attack institutional customers and consequently raise their trading costs. Some of the strategies looked like bare-faced attempts to manipulate the market. Arnuk and Saluzzi detected signs of momentum ignition, in which an algorithm initiates a series of trades in an attempt to trick other machines into believing that a particular stock is headed higher or lower; and spoofing, a practice in which the machines feign interest in buying or selling a stock to manipulate its price. The victims of these questionable techniques included mutual funds and pensions, so in the final analysis, it was the small investor who was getting nicked by this new iteration of Wall Street avarice. No one had noticed—least of all the SEC and examiners at the Financial Industry Regulatory Authority (FINRA), an industry-financed outfit charged with policing brokers and the stock exchanges. The SEC staff members had so little day-to-day personal contact with Wall Street professionals that they knew almost nothing about what was really happening there beyond the direction of the stock averages. They relied on FINRA, which had a reputation of being less than diligent.

Arnuk and Saluzzi were not politically connected. Theirs was a small-fry firm. But they felt compelled to sound an alarm and bring their suspicions to the attention of the broader investing public. Something was askew in the marketplace. So the men elected to disseminate their findings in a white paper to their 30 institutional clients and then post the paper on their blog. Those clients typically ran just 2% to 5% of their order flow through Themis Trading. Arnuk and Saluzzi figured the clients were losing lots of money to high-frequency traders on the remainder of the order flow transacted elsewhere because they were unaware of what was going on.

They titled their paper "Toxic Equity Trading Order Flow on Wall Street: The Real Force Behind the Explosion in Volume and Volatility." The white paper read more like an op-ed piece than the academic treatise suggested by its title. Arnuk and Saluzzi offered no empirical evidence, just their hunches. Hard evidence was tough to come by; no one, not even HFT consultant Tabb Group, could say with absolute certainty how many HFT firms existed. The HFT corner of the market was unregulated. It was also guarded. Traders worked behind closed doors with upmost secrecy to protect their "secret sauces," the algorithms that they used to outsmart other traders. The duo did have 40 years of combined trading experience, however. They understood the mechanics of the market, and they had seen hundreds of schemes designed to take advantage of unwary investors. And they had their snitches. They were convinced that such scheming was occurring now on a grand scale.

The white paper asserted that the explosion in market volatility that most people ascribed to the global financial crisis that had begun in August 2007 was largely the product of high-frequency traders who had invaded the market en masse to exploit changes wrought by SEC's new rules.

"The number of quote changes has exploded," they wrote. "The reason is high-frequency traders searching for hidden liquidity. Some estimates are that these traders enter anywhere from several hundred to one million orders for every 100 trades they actually execute." HFT machines would enter an order and cancel it almost immediately, just to see if there was buying interest at a particular price level. Arnuk and Saluzzi referred to this practice as pinging, conjuring the image of a destroyer conducting a sonar sweep for a hidden submarine. High-frequency trading computers would issue an order ultra-fast away from the listed price of a stock, and if nothing happened, they would cancel it immediately and send out another. The machines were looking for hidden information to use to their advantage, such as whether there were big institutional customers afoot trying to fill large orders.

The strategy was cunning. Say there was an institutional trader who had instructed a computer to purchase shares of a stock for between $20.00 and $20.03, but no higher. Theoretically, no one else in the marketplace would know this. The high-frequency trader's algorithm, however, might recognize that a pattern of purchases for the particular stock's shares at $20 was typical of algorithms employed by institutions accumulating a large position. So the HFT algorithm would ping the institution's algorithm, offering perhaps to sell 100 shares of the stock to the institution at $20.05. If nothing were to happen, the HFT algorithm immediately would cancel the trade and offer 100 shares at $20.04. If nothing again happened, it would cancel and offer $20.03. If the institution's algorithm were to buy the stock, the HFT algorithm would know that it had found a buyer willing to pay up to $20.03 for a stock listed at $20. The HFT algorithm then quickly plunged back into the market offering to buy the same stock at a penny above the institution's original $20.00 bid. Then it would turn around and continuously sell those shares to the institution's algorithm at $20.03. That extra penny, Arnuk and Saluzzi asserted, amounted to a "stealth tax" on retail and institutional investors.

Most investors—retail lambs and the large, bovine institutional traders—didn't realize that they were being bled because it was a death by a thousand cuts as opposed to a pneumatically propelled bolt to the forehead. They had no way of knowing that an uninvited middleman had come between them and the stock market.

This sort of shenanigan had begun in 2007 because Regulation NMS took away the duopoly status of NASDAQ and the New York Stock Exchange (NYSE) by allowing any exchange to trade listed securities. Previously, the majority of trades on NYSE-listed stocks were done on the NYSE and NASDAQ-listed stocks in the NASDAQ market. New computerized exchanges proliferated, anxious to get a slice of NASDAQ's and the NYSE's lucrative business. To survive in the face of the new competition, NASDAQ and the NYSE were compelled to go public. Suddenly, they were accountable to stockholders who vocally demanded a decent return on their investment; so the once-dominant exchanges had to fight tooth and claw against the new competitors for the trade volume they had lost. They soon discovered deep-pocketed customers in the form of the high-frequency traders, who were arbitraging price inefficiencies among the dozen or so equity exchanges and between the equities markets and the commodities markets. The NYSE and the NASDAQ solicited the HFT business, as did all the other exchanges. They offered these prime customers special trading advantages as an inducement.

"Before 2007 and Regulation NMS, you really didn't have this high-frequency stuff," said Saluzzi. "The NYSE was still a slow market, and 80% of the trades were on the floor of the exchange. But once those trades migrated to newer, electronic exchanges, trading became fast. Overall market volume went from 3 billion shares to 10 billion shares because regulation NMS opened a whole new playground for high-frequency traders, and they went crazy."

Some of the exchanges offered the HFT firms rebates of sub-pennies-per-share for serving as market makers and buying stocks from other customers. Buy and sell tens of millions of shares a day, and that fraction of a cent adds up to substantial profit. Arnuk and Saluzzi said in their white paper that the rebate scheme inadvertently led to what they termed hot-potato trading that inflated market volume statistics and made the market seem much more liquid than it was.

"If two guys trade 1,000 shares back and forth a million times, that's a billion shares. Did a billion shares actually trade, or did the thousand shares change hands a million times between two guys playing hot potato? We argue that the real volume is 1,000 shares."

The volume, real or not, generated data for the consolidated tape, which in turn was a marketable product. The more data that an exchange generated for the tape at year end, the bigger its share of the revenues from sales of that data to information vendors and brokerages. So they were not about to crack down on this practice.

Saluzzi and Arnuk charged that the high-frequency traders were playing other games as well, all because they were able to move faster than everyone else. In part, it was because the NYSE and the NASDAQ had invited them to collocate their servers close to the exchange's servers. This arrangement reduced the time required to get an order executed. The cost ranged from $1,500 to $50,000 per month for each server cabinet. There also was an installation charge that ran anywhere from $5,000 to $50,000. The NYSE was so grateful for the new business that it took steps in October 2007 to make it easier for program traders to move the markets higher and lower. The NYSE publicly removed curbs that shut down the program trading if the market moved more than two percent in any direction, the white paper stated. NYSE asserted that the approach to limiting market volatility envisioned by the use of the "trading collars" was not as meaningful today as it had been in the late 1980s when the rules were adopted. The rules had been put in place in 1987 following Black Monday, the largest one-day crash since the Great Depression. The white paper said, "On a more commercial level, the NYSE had been at a competitive disadvantage because other market centers that didn't have curbs were getting the program trading business."

One nefarious-sounding strategy, cited by the white paper, was designed to quickly move the price of a share higher by 10 to 15 cents by employing a handful of 100- to- 500- share trades executed in rapid succession. Then the high-frequency trader would suddenly short the stock, knowing full well he had artificially pumped up the price and that it shortly would begin to fall.

In a fictional example by the authors, an institutional buyer is trying to accumulate stock between $20 and $20.10 per share. Using the same techniques as the rebate trader, a high-frequency trader spots the $20 bid as an institutional order. When the institution next bids $20.01, the high-frequency trader buys stock at $20.02, driving up the price. The institution follows and buys more shares at $20.02. The high-frequency trader in this matter runs the stock up to $20.10 per share, with the institution chasing the stock. At this point, the high-frequency traders also stock short at $20.10 knowing it is highly likely that the price of the stock will fall back to the low $20 range.

Finally, the two traders accused their high-frequency competition of a sin known in the parlance of the industry as momentum ignition. The high-frequency traders engage this strategy to juice a market already moving up or down, creating either a major decline or a big upward spike in prices. A trader could rapidly submit and cancel many orders, and execute some actual trades to "spoof" the algorithms of other traders into action and cause them to buy or sell more aggressively. Or the trader might try to trigger some standing stop loss orders that would cause a price decline. By establishing a position early on, the trader could profit by liquidating the position if he is successful in igniting a price movement. This strategy might be most effective in less actively traded stocks, which receive little help and public attention and are vulnerable to price movements sparked by a relatively small amount of volume.6

After sending the paper to clients, Arnuk and Saluzzi posted a copy of the white paper on their blog site, where they expected its contents to be discovered by the larger investing world and then widely disseminated and discussed. That, after all, was the way things regularly happened on the World Wide Web, wasn't it?

"We were not trying to make a name for ourselves," Arnuk said later. "All that we wanted to do was fix what was wrong. We were sharing it with our customers so they could improve what they were doing when they traded away from us."

The charges by Arnuk and Saluzzi were sensational and potentially explosive. The markets were being manipulated. No one else had noticed what they had noticed. Regulators had been asleep. They hadn't blown any time-out whistles or thrown any penalty flags for spoofing or momentum ignition or pinging. This was outrageous, because the SEC and FINRA were supposed to be cleaning up their act after missing abuses like Bernie Madoff's outrageous Ponzi scheme.

But after the two traders disseminated the white paper, nothing happened—nothing at all. Investors in December 2008 had other things on their minds. They were consumed by bailouts, failures, bankruptcies, and the incoming Democratic administration of Barack Obama. The white paper was little more than background noise.

"Outside of our clients, no one made a stink or even mentioned our findings," recalled Arnuk.7

The two men may have been disappointed, but they were not quitters. For them, this was personal. The HFT firms were a threat to their way of life. They continued to plug away, albeit in relative obscurity. In a prescient, follow-up white paper published in early July, Arnuk and Saluzzi warned of the possibility of a lightning-fast market collapse induced by high-frequency traders with unfiltered connections to the stock exchanges through so-called "sponsored access agreements" with a registered broker. The brokers essentially vouched for the integrity of their customers without doing real due diligence. The firms might be thinly capitalized or controlled by criminals, for all the regulators knew.

"Many of these arrangements do not have any pre-trade risk controls since these clients demand the fastest speed. Due to the fully electronic nature of the equity markets today, one keypunch error could wreak havoc. Nothing would be able to stop a market destroying order once the button was pressed," they wrote.

Once again, few people paid attention. It sounded shrill and far-fetched, like the Y2K scare that had predicted a meltdown of computers worldwide on January 1, 2000 because twentieth-century computer programs would not recognize dates after 1999. This apathy about their white paper would begin to evaporate days later as a result of a quasi-comic confluence of events involving the FBI, short-tempered Wall Street bankers, a Bulgarian-born blogger, and a preening U.S. senator.

InformIT Promotional Mailings & Special Offers

I would like to receive exclusive offers and hear about products from InformIT and its family of brands. I can unsubscribe at any time.

Overview


Pearson Education, Inc., 221 River Street, Hoboken, New Jersey 07030, (Pearson) presents this site to provide information about products and services that can be purchased through this site.

This privacy notice provides an overview of our commitment to privacy and describes how we collect, protect, use and share personal information collected through this site. Please note that other Pearson websites and online products and services have their own separate privacy policies.

Collection and Use of Information


To conduct business and deliver products and services, Pearson collects and uses personal information in several ways in connection with this site, including:

Questions and Inquiries

For inquiries and questions, we collect the inquiry or question, together with name, contact details (email address, phone number and mailing address) and any other additional information voluntarily submitted to us through a Contact Us form or an email. We use this information to address the inquiry and respond to the question.

Online Store

For orders and purchases placed through our online store on this site, we collect order details, name, institution name and address (if applicable), email address, phone number, shipping and billing addresses, credit/debit card information, shipping options and any instructions. We use this information to complete transactions, fulfill orders, communicate with individuals placing orders or visiting the online store, and for related purposes.

Surveys

Pearson may offer opportunities to provide feedback or participate in surveys, including surveys evaluating Pearson products, services or sites. Participation is voluntary. Pearson collects information requested in the survey questions and uses the information to evaluate, support, maintain and improve products, services or sites, develop new products and services, conduct educational research and for other purposes specified in the survey.

Contests and Drawings

Occasionally, we may sponsor a contest or drawing. Participation is optional. Pearson collects name, contact information and other information specified on the entry form for the contest or drawing to conduct the contest or drawing. Pearson may collect additional personal information from the winners of a contest or drawing in order to award the prize and for tax reporting purposes, as required by law.

Newsletters

If you have elected to receive email newsletters or promotional mailings and special offers but want to unsubscribe, simply email information@informit.com.

Service Announcements

On rare occasions it is necessary to send out a strictly service related announcement. For instance, if our service is temporarily suspended for maintenance we might send users an email. Generally, users may not opt-out of these communications, though they can deactivate their account information. However, these communications are not promotional in nature.

Customer Service

We communicate with users on a regular basis to provide requested services and in regard to issues relating to their account we reply via email or phone in accordance with the users' wishes when a user submits their information through our Contact Us form.

Other Collection and Use of Information


Application and System Logs

Pearson automatically collects log data to help ensure the delivery, availability and security of this site. Log data may include technical information about how a user or visitor connected to this site, such as browser type, type of computer/device, operating system, internet service provider and IP address. We use this information for support purposes and to monitor the health of the site, identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents and appropriately scale computing resources.

Web Analytics

Pearson may use third party web trend analytical services, including Google Analytics, to collect visitor information, such as IP addresses, browser types, referring pages, pages visited and time spent on a particular site. While these analytical services collect and report information on an anonymous basis, they may use cookies to gather web trend information. The information gathered may enable Pearson (but not the third party web trend services) to link information with application and system log data. Pearson uses this information for system administration and to identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents, appropriately scale computing resources and otherwise support and deliver this site and its services.

Cookies and Related Technologies

This site uses cookies and similar technologies to personalize content, measure traffic patterns, control security, track use and access of information on this site, and provide interest-based messages and advertising. Users can manage and block the use of cookies through their browser. Disabling or blocking certain cookies may limit the functionality of this site.

Do Not Track

This site currently does not respond to Do Not Track signals.

Security


Pearson uses appropriate physical, administrative and technical security measures to protect personal information from unauthorized access, use and disclosure.

Children


This site is not directed to children under the age of 13.

Marketing


Pearson may send or direct marketing communications to users, provided that

  • Pearson will not use personal information collected or processed as a K-12 school service provider for the purpose of directed or targeted advertising.
  • Such marketing is consistent with applicable law and Pearson's legal obligations.
  • Pearson will not knowingly direct or send marketing communications to an individual who has expressed a preference not to receive marketing.
  • Where required by applicable law, express or implied consent to marketing exists and has not been withdrawn.

Pearson may provide personal information to a third party service provider on a restricted basis to provide marketing solely on behalf of Pearson or an affiliate or customer for whom Pearson is a service provider. Marketing preferences may be changed at any time.

Correcting/Updating Personal Information


If a user's personally identifiable information changes (such as your postal address or email address), we provide a way to correct or update that user's personal data provided to us. This can be done on the Account page. If a user no longer desires our service and desires to delete his or her account, please contact us at customer-service@informit.com and we will process the deletion of a user's account.

Choice/Opt-out


Users can always make an informed choice as to whether they should proceed with certain services offered by InformIT. If you choose to remove yourself from our mailing list(s) simply visit the following page and uncheck any communication you no longer want to receive: www.informit.com/u.aspx.

Sale of Personal Information


Pearson does not rent or sell personal information in exchange for any payment of money.

While Pearson does not sell personal information, as defined in Nevada law, Nevada residents may email a request for no sale of their personal information to NevadaDesignatedRequest@pearson.com.

Supplemental Privacy Statement for California Residents


California residents should read our Supplemental privacy statement for California residents in conjunction with this Privacy Notice. The Supplemental privacy statement for California residents explains Pearson's commitment to comply with California law and applies to personal information of California residents collected in connection with this site and the Services.

Sharing and Disclosure


Pearson may disclose personal information, as follows:

  • As required by law.
  • With the consent of the individual (or their parent, if the individual is a minor)
  • In response to a subpoena, court order or legal process, to the extent permitted or required by law
  • To protect the security and safety of individuals, data, assets and systems, consistent with applicable law
  • In connection the sale, joint venture or other transfer of some or all of its company or assets, subject to the provisions of this Privacy Notice
  • To investigate or address actual or suspected fraud or other illegal activities
  • To exercise its legal rights, including enforcement of the Terms of Use for this site or another contract
  • To affiliated Pearson companies and other companies and organizations who perform work for Pearson and are obligated to protect the privacy of personal information consistent with this Privacy Notice
  • To a school, organization, company or government agency, where Pearson collects or processes the personal information in a school setting or on behalf of such organization, company or government agency.

Links


This web site contains links to other sites. Please be aware that we are not responsible for the privacy practices of such other sites. We encourage our users to be aware when they leave our site and to read the privacy statements of each and every web site that collects Personal Information. This privacy statement applies solely to information collected by this web site.

Requests and Contact


Please contact us about this Privacy Notice or if you have any requests or questions relating to the privacy of your personal information.

Changes to this Privacy Notice


We may revise this Privacy Notice through an updated posting. We will identify the effective date of the revision in the posting. Often, updates are made to provide greater clarity or to comply with changes in regulatory requirements. If the updates involve material changes to the collection, protection, use or disclosure of Personal Information, Pearson will provide notice of the change through a conspicuous notice on this site or other appropriate way. Continued use of the site after the effective date of a posted revision evidences acceptance. Please contact us if you have questions or concerns about the Privacy Notice or any objection to any revisions.

Last Update: November 17, 2020