High Frequency Traders are Stealing from You

Readers,

I would like to provide a brief update on my life and post an article I wrote for clients of West Coast Asset Management. I am back in school but have luckily been able to continue my relationship with WCAM. I am working a few days a week from LA doing research and creating content for quarterly letters and blogs.

However, what takes up most of my time is this field study I am performing with a number of my colleagues on the Student Investment Fund at Anderson. We are attempting to come up with a proposal to improve the investment management (IM) program at Anderson. We are contemplating a number of suggestions, including a yearly speaker series, an IM conference (like the one Columbia hosts each year), a stock pitching challenge, a curriculum refresh that includes more practical investing classes and maybe even a separate track for IM like those offered by Columbia and Kellogg. Additionally, we are looking for support from UCLA alumni and any asset managers in the LA area. So, if you or anyone you know would like to be involved, please email me.

Without further ado, the following is an article I wrote about high frequency trading (HFT). The subject was getting a lot of press until ForeclosureGate started dominating the newswires. But, despite the lack of headlines, mini flash crashes continue to happen in certain securities on a weekly basis. This is a warning sign that the system itself is very unstable and that we may be at risk of another crash like the one we saw in May of this year. For those who are still unclear on what HFT is and what risks it may pose, I tried to put together a simple primer on the subject. I am not an expert on this subject but I hope this adds to people's understanding of what I believe is an undesirable trend towards more computer control of the stock market.

High Frequency Traders are Stealing from You

The history and backdrop

Most people are well acquainted with the stock market crash that occurred on October 19^th, 1987 in which the Dow Jones dropped by 508 points or 22.61%. After the fact, the largest one day percentage decline in the market’s history was mainly blamed on portfolio insurance. This was a risk management tool that employed stop losses through automatic, computer-based selling. Unfortunately, the prevalent use of this strategy caused a cascade of selling once the market started to drop. Hindsight being 20/20, commentators who opined on the events of the day of course claimed that the outcome was obvious and predictable. Clearly it should not have been a surprise that indiscriminate selling by computers could cause the market to plunge. How could anyone have believed that thoughtless machines controlling the most important stock market in the world was a good idea?

Now, here we are almost 23 years later and apparently we have learned nothing from our past mistakes. In fact, computer trading programs, or algorithms if you will, now dominate the day-to-day trading on the major exchanges. While it is difficult to quantify precisely, most estimates suggest that what is known as high frequency trading (HFT) makes up between 50% and 75% of all trades¹. Let us say that again: Robots trading shares in between one another now accounts for anywhere between half and three-quarters of market activity on a daily basis. So much for fundamental, bottom’s up investing.

What is HFT? (Moved to the top from the bottom)

We understand that we are attempting to tackle a difficult topic. In fact, we are in the process of trying to understand it better ourselves and are certainly not experts. However, if we did not think that the emergence of HFT was an incredibly important development or that we could not present our analysis in approachable manner, we would not be stressing the issue. The truth is that HFT potentially affects all investors, not just those who are involved in the daily trading of the markets.

Investopedia.com defines HFT in the following manner²:

“A program trading platform that uses powerful computers to transact a large number of orders at very fast speeds. High-frequency trading uses complex algorithms to analyze multiple markets and execute orders based on market conditions. Typically, the traders with the fastest execution speeds will be more profitable than traders with slower execution speeds.”

So far, not so complicated. Basically, companies engaged in high frequency trading use trading speed and sophisticated computer programs to create an advantage over other traders. The specific strategy of many of these programs it to use their superior technology to make pennies or fractions of pennies on every trade. This process, which is kind of like collecting pennies in front of a steamroller, may not seem particularly lucrative until you realize that there are billions of trades executed on US stock markets each day. A billion pennies sure adds up over time.

If it sounds like these firms profit from an unfair and uneven market structure, it is because that is precisely the case. But why is this inequity tolerated and often cited as a positive thing? Well, the common defense of HFT is that these firms who run these algorithms are providing liquidity, a measure of the degree to which a stock can be bought and sold without affecting the price. Generally, the more liquid a stock is the easier it can be traded without causing huge swings in the price. As long as the liquidity is real and those who provide it are committed to it, greater liquidity can be very beneficial to investors. Specifically, it can lead to lower bid-ask spreads (which can lead to lower costs of trading) and a greater ability to move into and out of cash when investors so desire.

However, we believe that the problems created by HFT are twofold:

1. Increased volatility and the risk of extreme moves in the markets
2. Increased trading costs through predatory activities

The market roller coaster

First off, all of the evidence we find suggests that HFT creates unusual volatility in the markets. Let’s go back to the so called “Flash Crash” on May 6^th, 2010. The Dow Jones dropped 600 points in a matter of minutes, shares of Accenture (ACN) dropped from over $40 to a penny, and shares of Apple (APPL) rose to over $100,000 each. Even though the exchanges eventually cancelled these outlier trades, how is it possible that share prices can fluctuate so dramatically? The initial reaction to this dramatic move in the price of market indexes was the “fat finger” theory. This is the idea that some incompetent trader who meant to sell one thousand shares inadvertently added three extra zeroes and sold one million shares. However, we believe that such explanations are created in an attempt to obscure the fact that the markets are broken. Actually, these are not our words but basically what Larry Leibowitz, the COO of NYSE Euronext (owner of the New York Stock Exchange), said during his testimony in front of a House Financial Services Subcommittee five days after the Flash Crash ³. Specifically, this is what he said about the impact of technology on the functioning of our stock markets:

“The May 6 market drop certainly should inform the SEC’s [Security and Exchange Commission’s] current examination of the changes in the markets, and in particular how certain recent advances in technology may have fostered trading practices that negatively impact the entire market…As regulators seek to determine whether regulatory action is necessary to address the shifts in market structure resulting from technological change, the events of May 6 make it clear that the regulators also need to consider steps to avoid the types of extreme volatility our markets experienced that day.”

This indictment of the recent technological revolution in trading came from a man whose company thrives on market volatility since fees go up as volume increases. Additionally, NYSE Euronext jus opened a huge new $500 million data center in order to take advantage of co-location (where exchanges like NYSE allow traders to plug directly into their servers and increase their trading speed dramatically) revenue that is derived solely from firms who want quicker speeds for their electronic trading. So, despite his vested interest in the increased proliferation of HFT, Mr. Leibowitz is clearly concerned that the practice is a threat to the integrity of the U.S. stock markets.

Liquidity dries up

The problem arises when other market participants depend on liquidity that will only be present when the market is going up or trading sideways. Unfortunately, as we believe the Flash Crash proved, when the market declines rapidly the liquidity dries up as the algorithms shut down to avoid catching a falling knife. Essentially, our concern is that when the market plunges the HFT algorithms are programmed to stop trading so that the firms are not caught holding assets that are falling in value. But, this just exacerbates the drop in the market as there are subsequently fewer buyers remaining. A true liquidity provider would remain in the market in order to bid on assets even if they are declining in price and make an active market (one with both buyers and sellers) in stocks. But, if the HFTs flee the market at the first hint of weakness, the market can stop functioning. When this happens, stocks such as Accenture, which usually trade close to 4 million shares a day but saw volume spike to 10.3 million shares on the Flash Crash day⁴, can fall from over $40 to $.01. Unfortunately, this type of volatility can make stocks stray far away from their intrinsic values and cause retail investors to leave the market because they are unable to stomach the price swings.

The hidden HFT tax⁵

The following is the most technical portion of this analysis. However, we think that if you are willing to stay with us, you will understand why HFT likely costs you money. The best way to explain the HFT tax is through an example. Let’s say you are a mutual fund that wants to buy one million shares of Microsoft (MSFT). This is such a large order that you are worried that you may move the market up with your trade. Therefore, in order to make sure you don’t pay more than you want per share you put in a limit order. Let’s say the stock is trading at $24.95 but you put in a limit order (i.e. the most you are willing to pay) of $25. Many mutual funds use what are known as VWAP (Volume Weighted Average Pricing) trading algorithms to execute these large trades. The problem with these algorithms is that even if they break up the buy orders in smaller batches (i.e. not all one million shares in a single trade) they create patterns that the HFT algorithms can sniff out.

Think of a VWAP kind of like an 18-wheeler trying to switch lanes on the highway. It takes a long time to move and therefore a quicker vehicle has the opportunity to outmaneuver it. This is what the HFTs do when they sense a VWAP-based order. By exploiting the predictable patterns created by the VWAP, the HFT algorithm is fast enough to sense the limit order of $25 on the MSFT shares, buy the shares at $24.95 and then sell them to the mutual fund at $25. No harm, right? The mutual fund got its trade executed at $25 and no one ever thinks twice. Wrong! The problem is that the HFT basically engaged in what is known as front running by jumping in front of the VWAP and causing the mutual fund to pay $.05 too much for each share. If this only happened every once in a while it might not be a big deal. But imagine the costs to mutual fund shareholders if this dynamic played out each and every day with thousands of stocks. We are talking about billions of dollars in potential profits for the HFTs. If you are wondering why the NYSE pre-sold ALL of its co-location spots for its new data center within a short period of time, you now have the answer.

Want to know who the major players are? Well, according to NASDAQ’s website, the top five liquidity providers for the NYSE as of July 2010 were Wedbush Morgan Securities, GETCO, Citadel Securities, Merrill Lynch and UBS Securities⁶.

How does HFT affect the price of stocks?

West Coast Asset Management engages in bottom’s up value investing. Our belief is that if you buy shares of a company at a price less than their intrinsic value, the market will eventually appreciate the fundamentals of the company and bid the price up near the stock’s true value. But what does it mean if 50% to 75% of trading comes from predatory robots trading shares back and forth? It means that shares are not necessarily trading based on economic or company-specific factors in the short term. The irony is that this dynamic may actually create opportunities for value investors. We invest based on the notion that markets are often inefficient in the short run but that the market’s pricing mechanism functions properly in the long run and allows us to profit from our contrarian strategy. Accordingly, if the presence of the HFTs causes temporary dislocations in price of individual securities, we may be able to take advantage and generate excess returns for our clients. Additionally, if the HFT algorithms begin to focus on a stock that previously had not been particularly liquid, investors who own that stock could benefit from the increased tradability of the security.

What should be done about HFT?

Unlike many of the problems we face as investors, this one seems easily solvable. Specifically, it is our position that HFT should be banned. By disallowing co-location the regulators could level the playing field in terms of speed and thus limit the ability of the HFTs to outrun other investors. The SEC is currently looking at the issue and we hope they come to the conclusion that the increased clout of the HFTs is not good for our markets. As we have illustrated in the preceding discussion, HFT does not appear to serve any purpose from an overall public welfare perspective. In fact, it seems as though these algorithms extract rents directly from smaller investors who do not have the same technological advantages. We also can’t forget the violent swings in market prices that the HFT facilitates and the associated potential for a severe market crash. When all of these issues are combined it becomes unambiguous that high frequency trading presents a real threat to the vitality of our stock markets and to investor confidence. Therefore, we hope that the U.S. regulators do something proactive to protect the investing public as opposed to catering to the powerful financial “services” industry. Let’s stop this practice before we all are forced to look back at a debilitating market crash and say, “we knew this was going to happen all along.”

For more information on the subject of HFT we highly recommend reading the second quarter shareholder letter from Iridian Asset Management ($7.1 billion assets under management) available here: http://www.zerohedge.com/article/more-are-waking-hft-terrorism-iridian-asset-managements-latest-investor-letter-blasts-high-f. We would also like to thank the authors, Jeff Silver and Ben Hunt, as their explanations helped frame our analysis.

Sources:

1. http://www.nytimes.com/2010/05/07/business/economy/07trade.html
2. http://www.investopedia.com/terms/h/high-frequency-trading.asp
3. http://www.house.gov/apps/list/hearing/financialsvcs_dem/leibowitz_5.11.10.pdf
4. http://www.google.com/finance?q=NYSE:ACN
5. http://www.zerohedge.com/article/more-are-waking-hft-terrorism-iridian-asset-managements-latest-investor-letter-blasts-high-f
6. http://www.nasdaqtrader.com/trader.aspx?ID=topliquidity