While ‘Flash Boys’ may capture the complex execution framework of the US equities market, Michael Lewis does not portray the full story. The market may not be perfect, but it’s not rigged.
This article originally was published on March 31, 2014.
While Michael Lewis’s new book, “Flash Boys,” is an amusing read and does talk about the very complex execution framework of the US equities market, he has not portrayed the full story of the US equities market, leaving much on the cutting-room floor.
[Download a PDF of Larry Tabb's complete commentary at the end of this article.]
Flash Boys portrays an overly complex market hell-bent on speed and traders willing to ’sell their grandmother for a millisecond.’ The opportunity Mr. Lewis paints comes at the expense of unwitting investors who are being taken advantage of by high-frequency traders in conjunction with colluding brokers and exchanges. He talks about latency arbitrage between consolidated data fees and direct feeds, as well as distances between exchanges, dark pools and cable lines. While most of the physical infrastructure is adequately described, its purpose, how it is being used and its impact are dramatically misstated.
While our markets are fragmented, there is significant benefit to having a fragmented market: competition. While economic theory represents that the most efficient market is one where all orders interact and compete in a central limit order book, this theory falls down when it runs headlong into a market devoid of competition. This was shown when market makers were caught colluding in 1998 on NASDAQ and on the NYSE in 2003. In both of these instances, market makers and specialists were taken away in handcuffs.
Out of both of these scandals came SEC rules to facilitate competition – not just between orders, but between markets. The SEC enabled the development of three major non-exchange-type matching mechanisms: internalization – where brokers could internally match buyers and sellers; ECNs’ (electronic communications networks’) alternative central limit order books (less-regulated, quasi-exchanges); and dark pools, opaque broker-owned matching venues that work like exchanges but do not display limit orders (hence, “dark”). During this time the SEC developed the Order Handling Rules, Regulation ATS, and Regulation NMS, which codified how orders needed to be treated in this fragmented market structure.
Today, while fragmented, equity execution is much less expensive, faster (generally sub-millisecond compared to more than 10 seconds in 2005), and more open. Retail brokerage fees are generally under $10 a trade, and institutions can pay under 1 penny a share (closer to .8 cents per share) for electronic execution. In addition, average effective spreads are down, and investors are much more in control of their executions than ever before.
The development of multiple execution venues has changed the economics of trading. If we look back on equity trading even as recent as a decade ago, the brokers and exchanges were standalone profitable powerhouses. Today, equity exchanges are not in the same financial shape. Derivative exchanges are driving exchange growth, and equity exchanges need to be lean and mean to survive. Brokers are not prospering either, as traders and experienced sales people are being swapped for machines and less experienced sales support. ETFs, self-empowering technology and investor pressure have reduced the cost of execution and have caused brokers to reduce their staffs.
So where is all of this value going? To high-frequency traders? We don’t see them doing much better than the exchanges or brokers. The pressure to invest in expensive technology and infrastructure, colocation and connections to many more markets, as well as improvements in vendor-based solutions, have caused a hit to their revenues. TABB Group estimates that US equity HFT revenues have declined from approximately $7.2 billion in 2009 to about $1.3 billion in 2014. Looking at recent public data, the profitability of HFT firms in the US equities market has declined, just as the number of players has decreased.
If the exchanges, brokers and HFTs are not reaping the rewards, then where is this leakage going? This money is going back to investors in the form of better and cheaper executions, as few if any institutional investors we have interviewed – and we have interviewed thousands – have ever expressed that their equity implementation costs have increased, meaning … trading just becomes cheaper and cheaper. That cost comes from somewhere: market makers, speculators, brokers and exchanges.
Risk and Reward
Everyone hates speculators. That is a given. They are viewed as parasites sucking the alpha out of investors’ brilliant ideas. While intermediaries do step in the middle of investors’ trading strategies, speculators/intermediaries do serve a true purpose: They facilitate price discovery – meaning they provide quotes. That is a very important (if not the most important) function of a market: determining the price. A market without price discovery becomes an expensive and illiquid market. While most major investors know the intrinsic value of an asset they are willing to trade, the quoting process not only crystalizes the price for all to see, it provides tradable quotes for even the largest investors.
To fully understand this, think of a store. A store that doesn’t display or advertise its prices doesn’t get much business. Think of walking into a store filled with merchandise with nary a price to be seen. For each product, you need to ask a salesperson, who may or may not give you an accurate price. While a store can advertise that it will beat all competitors’ prices, if it doesn’t display a price, it puts the onus on buyers to find the best price, bring proof into the store and haggle with the storekeeper to book a deal.
The same is true with displayed markets. A market without a pricing mechanism isn’t much of a market.
The people who provide these prices are market makers, speculators, or what most people call HFT. These actors quote product bids and offers across a wide spectrum of markets (exchanges, ECNs, and dark pools). Collectively, it is their business model to try to provide the most aggressive price they can provide to buy or sell a stock. These firms also generate their revenues from two sources: the spread between which they can buy and sell stock, and any incentives that exchanges, ECNs, or dark pools may give them to quote in their markets.
While trading venues may provide incentives to quote (generally up to $.00029 per share), venues do not share in liquidity providers’ trading profits or losses. This means that any trading house that improperly gauges supply and demand has to bear the entire cost of any losses itself.
Let me rephrase this: To have tight markets, many firms (mostly HFT) need to compete to set the best market price. These firms are competing to capture the spread (for liquid stocks, this is 1 cent per share) plus any incentive, minus any trading cost. If these firms miscalculate supply and demand, as Knight did one fateful morning, they will not only have a bad trading day, they could go bust.
So how do these firms manage risk?
Quotes equate to risk. Any time a trader (asset manager, retail investor, market maker or HFT) puts a quote into the market, it is an option for the market to trade. The quoter provides the option – I would like to buy 100 shares of IBM at $190 a share. Just because a buyer wants to acquire IBM at $190 doesn’t mean that someone is out there willing to sell IBM at $190; however, if someone is, unless the quoter cancels the order, the person quoting is committed to trade. While a longer-term investor may have a time horizon for the trade of days, weeks, months or years, generally a market maker, speculator, and/or HFT is looking at a horizon of seconds to minutes. If my whole business model is predicated off quoting to earn a spread, then I need to understand all of the market influences that could make IBM go up or down during my investment time horizon (seconds to minutes).
So what makes a stock go up or down in the short term? Certainly there are company fundamentals such as sales, earnings or management changes; but typically that information doesn’t change second to second. There also is research, news, information, and other data that gets released by analysts, media, or people simply expressing their opinions online. Lastly, and most important, in the very short term, supply and demand impacts price the most – how many people want to buy vs. sell and, more important, how much?