Anti-Algorithmic Trading

Algorithmic trading is the use of computer systems, programs and advanced mathematical models for entering trading orders.

Algorithms, not humans decide on aspects such as the timing, price and the quantity of orders.

Some algorithms initiate orders based on information received electronically, understood by the algorithms only.

On the positive side, they are quick, so they can exploit opportunities (arbitrage, statistical arbitrage, trend following).

I like statistical arbitrage, and I remember that I liked some algorithmic trading systems that really helped, but these days there are so many sophisticated systems and algorithms competing to exploit the same opportunities, that we have to find something more creative.

On the negative side, more and more trades are driven by automatic programs, and algorithms replace traders.

At the London Stock Exchange for example, over 50% of all orders were entered by algo traders.

American markets have an even higher proportion of algo trades (estimates range as high as 80% proportion in some markets). 

Electronic platforms were supposed to execute simple trades, and leave hedge fund managers or traders at the financial firms and brokerages free to come up with new ideas for making money.

These days electronic platforms tend to execute all trades, and leave humans free to find another job. Which one? Technical staff, as more and more firms have more people working in their technology area than people on the trading desk.

Computers not only learn what is new from firms such as Reuters, Dow Jones, Bloomberg and Thomson Financial, but also decide if the news is good or bad so that automated trading can work directly on the news stories.  

“There is a real interest in moving the process of interpreting news from the humans to the machines” said Kiristi Suutani, global business manager of algorithmic trading at Reuters. Jobs once done by human traders are being switched to computers.

Every day we read about the speed and the processing power of computers and networks, and their ability for “lightning-quick trades”.

When we read success stories about humans, like hedge fund managers, we also read about their high management and performance fee. We rarely speak about the cost of the systems that replace humans (tens of billions).

I do not like certain algorithms called “sniffers”, that sniff out algorithmic trading by others and the algorithms being used by them. They can “game” the system, and may trigger buy orders to generate a better market price into which to sell.

These algorithms can be very dangerous.

We move towards Information Operations and Information Warfare-like environment.Information is no longer a staff function but an operational one. It is deadly as well as useful.

---

Executive Summary, Air Force 2025 report

No, I am not kidding.

Information Operations is the integrated employment of the core capabilities of electronic warfare, computer network operations, psychological operations, military deception and operations security, in concert with specified supporting and related capabilities, to influence, disrupt, corrupt or usurp adversarial human and automated decision making while protecting our own.

The above definition of Information Operations should have nothing to do with trading. But it has.

If you read the definition carefully, you will see that trading is very similar to war, and information is always a weapon.

Hedge funds and financial organizations of both, the buy side and the sell side, must remember that computers should help humans, not make decisions.

Traders must not forget that they are not IT or Information Security experts, and that mathematicians are usually not born for risk management. So many firms rely on systems they do not understand.

No, these risks are not covered by your risk models. They are 15 standard deviations from the mean (nowhere).

They are High Impact / Low Likelihood events, hidden under the "fat tail" of the distribution.

Systems should help humans, not replace them. I really like strategies and approaches that can not be programmed into systems.

Creative, non-formulaic, anti-algorithmic.

---

There is no excuse, it has happened, and it will happen again. the scale will be dirrerent. We must take steps now.

FINDINGS REGARDING THE MARKET EVENTS OF MAY 6, 2010
REPORT OF THE STAFFS OF THE CFTC AND SEC TO THE JOINT ADVISORY COMMITTEE ON EMERGING REGULATORY ISSUES



This is a report of the findings by the staffs of the U.S. Commodity Futures Trading Commission and the U.S. Securities and Exchange Commission.

The Commissions have expressed no view regarding the analysis, findings or conclusions contained herein.

This report presents findings of the staffs of the Commodity Futures Trading Commission (“CFTC”) and the Securities and Exchange Commission (“SEC” and collectively, the “Commissions”) to the Joint CFTC-SEC Advisory Committee on Emerging Regulatory Issues (the “Committee”) regarding the market events of May 6, 2010.

This report builds upon the initial analyses of May 6 performed by the staffs of the Commissions and released in the May 18, 2010, public report entitled Preliminary Findings Regarding the Market Events of May 6, 2010 – Report of the Staffs of the CFTC and SEC to the Joint Advisory Committee on Emerging Regulatory Issues (the “Preliminary Report”).

Readers are encouraged to review the Preliminary Report for important background discussions and analyses that are referenced but not repeated herein.

EXECUTIVE SUMMARY

On May 6, 2010, the prices of many U.S.-based equity products experienced an extraordinarily rapid decline and recovery.

That afternoon, major equity indices in both the futures and securities markets, each already down over 4% from their prior-day close, suddenly plummeted a further 5-6% in a matter of minutes before rebounding almost as quickly.

Many of the almost 8,000 individual equity securities and exchange traded funds (“ETFs”) traded that day suffered similar price declines and reversals within a short period of time, falling 5%, 10% or even 15% before recovering most, if not all, of their losses.

However, some equities experienced even more severe price moves, both up and down.

Over 20,000 trades across more than 300 securities were executed at prices more than 60% away from their values just moments before.

Moreover, many of these trades were executed at prices of a penny or less, or as high as $100,000, before prices of those securities returned to their “pre-crash” levels.

By the end of the day, major futures and equities indices “recovered” to close at losses of about 3% from the prior day.

WHAT HAPPENED?

May 6 started as an unusually turbulent day for the markets.

As discussed in more detail in the Preliminary Report, trading in the U.S opened to unsettling political and economic news from overseas concerning the European debt crisis.

As a result, premiums rose for buying protection against default by the Greek government on their sovereign debt.

At about 1 p.m., the Euro began a sharp decline against both the U.S Dollar and Japanese Yen.

Around 1:00 p.m., broadly negative market sentiment was already affecting an increase in the price volatility of some individual securities.

At that time, the number of volatility pauses, also known as Liquidity Replenishment Points (“LRPs”), triggered on the New York Stock Exchange (“NYSE”) in individual equities listed and traded on that exchange began to substantially increase above average levels.

By 2:30 p.m., the S&P 500 volatility index (“VIX”) was up 22.5 percent from the opening level, yields of ten-year Treasuries fell as investors engaged in a “flight to quality,” and selling pressure had pushed the Dow Jones Industrial Average (“DJIA”) down about 2.5%.

Furthermore, buy-side liquidity3 in the E-Mini S&P 500 futures contracts (the “E-Mini”), as well as the S&P 500 SPDR exchange traded fund (“SPY”), the two most active stock index instruments traded in electronic futures and equity markets, had fallen from the early-morning level of nearly $6 billion dollars to $2.65 billion (representing a 55% decline) for the E-Mini and from the early-morning level of about $275 million to $220 million (a 20% decline) for SPY.

Some individual stocks also suffered from a decline their liquidity.

At 2:32 p.m., against this backdrop of unusually high volatility and thinning liquidity, a large fundamental5 trader (a mutual fund complex) initiated a sell program to sell a total of 75,000 E-Mini contracts (valued at approximately $4.1 billion) as a hedge to an existing equity position.

Generally, a customer has a number of alternatives as to how to execute a large trade.

First, a customer may choose to engage an intermediary, who would, in turn, execute a block trade or manage the position.

Second, a customer may choose to manually enter orders into the market.

Third, a customer can execute a trade via an automated execution algorithm, which can meet the customer’s needs by taking price, time or volume into consideration.

Effectively, a customer must make a choice as to how much human judgment is involved while executing a trade.

This large fundamental trader chose to execute this sell program via an automated execution algorithm (“Sell Algorithm”) that was programmed to feed orders into the June 2010 E-Mini market to target an execution rate set to 9% of the trading volume calculated over the previous minute, but without regard to price or time.

The execution of this sell program resulted in the largest net change in daily position of any trader in the E-Mini since the beginning of the year (from January 1, 2010 through May 6, 2010).

Only two single-day sell programs of equal or larger size – one of which was by the same large fundamental trader – were executed in the E-Mini in the 12 months prior to May 6.

When executing the previous sell program, this large fundamental trader utilized a combination of manual trading entered over the course of a day and several automated execution algorithms which took into account price, time, and volume.

On that occasion it took more than 5 hours for this large trader to execute the first 75,000 contracts of a large sell program.

However, on May 6, when markets were already under stress, the Sell Algorithm chosen by the large trader to only target trading volume, and neither price nor time, executed the sell program extremely rapidly in just 20 minutes.

This sell pressure was initially absorbed by:

• high frequency traders (“HFTs”) and other intermediaries8 in the futures market;

• fundamental buyers in the futures market; and

• cross-market arbitrageurs9 who transferred this sell pressure to the equities markets

by opportunistically buying E-Mini contracts and simultaneously selling products like SPY, or selling individual equities in the S&P 500 Index.

HFTs and intermediaries were the likely buyers of the initial batch of orders submitted by the Sell Algorithm, and, as a result, these buyers built up temporary long positions. Specifically, HFTs accumulated a net long position of about 3,300 contracts.

However, between 2:41 p.m. and 2:44 p.m., HFTs aggressively sold about 2,000 E-Mini contracts in order to reduce their temporary long positions.

At the same time, HFTs traded nearly 140,000 E-Mini contracts or over 33% of the total trading volume.

This is consistent with the HFTs’ typical practice of trading a very large number of contracts, but not accumulating an aggregate inventory beyond three to four thousand contracts in either direction.

The Sell Algorithm used by the large trader responded to the increased volume by increasing the rate at which it was feeding the orders into the market, even though orders that it already sent to the market were arguably not yet fully absorbed by fundamental buyers or cross-market arbitrageurs.

In fact, especially in times of significant volatility, high trading volume is not necessarily a reliable indicator of market liquidity.

What happened next is best described in terms of two liquidity crises – one at the broad index level in the E-Mini, the other with respect to individual stocks.

LIQUIDITY CRISIS IN THE E-MINI

The combined selling pressure from the Sell Algorithm, HFTs and other traders drove the price of the E-Mini down approximately 3% in just four minutes from the beginning of 2:41 p.m. through the end of 2:44 p.m.

During this same time cross-market arbitrageurs who did buy the E-Mini, simultaneously sold equivalent amounts in the equities markets, driving the price of SPY also down approximately 3%.

Still lacking sufficient demand from fundamental buyers or cross-market arbitrageurs, HFTs began to quickly buy and then resell contracts to each other – generating a “hot-potato” volume effect as the same positions were rapidly passed back and forth.

Between 2:45:13 and 2:45:27, HFTs traded over 27,000 contracts, which accounted for about 49 percent of the total trading volume, while buying only about 200 additional contracts net.

At this time, buy-side market depth in the E-Mini fell to about $58 million, less than 1% of its depth from that morning’s level.

As liquidity vanished, the price of the E-Mini dropped by an additional 1.7% in just these 15 seconds, to reach its intraday low of 1056.

This sudden decline in both price and liquidity may be symptomatic of the notion that prices were moving so fast, fundamental buyers and cross-market arbitrageurs were either unable or unwilling to supply enough buy-side liquidity.

In the four-and-one-half minutes from 2:41 p.m. through 2:45:27 p.m., prices of the E-Mini had fallen by more than 5% and prices of SPY suffered a decline of over 6%.

According to interviews with cross-market trading firms, at this time they were purchasing the E-Mini and selling either SPY, baskets of individual securities, or other index products.

By 2:45:28 there were less than 1,050 contracts of buy-side resting orders in the E-Mini, representing less than 1% of buy-side market depth observed at the beginning of the day.

At the same time, buy-side resting orders in SPY fell to about 600,000 shares (equivalent to 1,200 E-Mini contracts) representing approximately 25% of its depth at the beginning of the day.

Between 2:32 p.m. and 2:45 p.m., as prices of the E-Mini rapidly declined, the Sell Algorithm sold about 35,000 E-Mini contracts (valued at approximately $1.9 billion) of the 75,000 intended.

During the same time, all fundamental sellers combined sold more than 80,000 contracts net, while all fundamental buyers bought only about 50,000 contracts net, for a net fundamental imbalance of 30,000 contracts.

This level of net selling by fundamental sellers is about 15 times larger compared to the same 13-minute interval during the previous three days, while this level of net buying by the fundamental buyers is about 10 times larger compared to the same time period during the previous three days.

At 2:45:28 p.m., trading on the E-Mini was paused for five seconds when the Chicago Mercantile Exchange (“CME”) Stop Logic Functionality was triggered in order to prevent a cascade of further price declines.

In that short period of time, sell-side pressure in the E-Mini was partly alleviated and buy-side interest increased.

When trading resumed at 2:45:33 p.m., prices stabilized and shortly thereafter, the E-Mini began to recover, followed by the SPY.

LIQUIDITY CRISIS WITH RESPECT TO INDIVIDUAL STOCKS

The second liquidity crisis occurred in the equities markets at about 2:45 p.m.

Based on interviews with a variety of large market participants, automated trading systems used by many liquidity providers temporarily paused in reaction to the sudden price declines observed during the first liquidity crisis.

These built-in pauses are designed to prevent automated systems from trading when prices move beyond pre-defined thresholds in order to allow traders and risk managers to fully assess market conditions before trading is resumed.

After their trading systems were automatically paused, individual market participants had to assess the risks associated with continuing their trading.

Participants reported that these assessments included the following factors: whether observed severe price moves could be an artifact of erroneous data; the impact of such moves on risk and position limits; impacts on intraday profit and loss (“P&L”); the potential for trades to be broken, leaving their firms inadvertently long or short on one side of the market; and the ability of their systems to handle the very high volume of trades and orders they were processing that day.

In addition, a number of participants reported that because prices simultaneously fell across many types of securities, they feared the occurrence of a cataclysmic event of which they were not yet aware, and that their strategies were not designed to handle.

Based on their respective individual risk assessments, some market makers and other liquidity providers widened their quote spreads, others reduced offered liquidity, and a significant number withdrew completely from the markets.

Some fell back to manual trading but had to limit their focus to only a subset of securities as they were not able to keep up with the nearly ten-fold increase in volume that occurred as prices in many securities rapidly declined.

HFTs in the equity markets, who normally both provide and take liquidity as part of their strategies, traded proportionally more as volume increased, and overall were net sellers in the rapidly declining broad market along with most other participants.

Some of these firms continued to trade as the broad indices began to recover and individual securities started to experience severe price dislocations, whereas others reduced or halted trading completely.

Many over-the-counter (“OTC”) market makers who would otherwise internally execute as principal a significant fraction of the buy and sell orders they receive from retail customers (i.e., “internalizers”) began routing most, if not all, of these orders directly to the public exchanges where they competed with other orders for immediately available, but dwindling, liquidity.

Even though after 2:45 p.m. prices in the E-Mini and SPY were recovering from their severe declines, sell orders placed for some individual securities and ETFs (including many retail stop-loss orders, triggered by declines in prices of those securities) found reduced buying interest, which led to further price declines in those securities.

Between 2:40 p.m. and 3:00 p.m., approximately 2 billion shares traded with a total volume exceeding $56 billion. Over 98% of all shares were executed at prices within 10% of their 2:40 p.m. value.

However, as liquidity completely evaporated in a number of individual securities and ETFs,11 participants instructed to sell (or buy) at the market found no immediately available buy interest (or sell interest) resulting in trades being executed at irrational prices as low as one penny or as high as $100,000.

These trades occurred as a result of so-called stub quotes, which are quotes generated by market makers (or the exchanges on their behalf) at levels far away from the current market in order to fulfill continuous two-sided quoting obligations even when a market maker has withdrawn from active trading.

The severe dislocations observed in many securities were fleeting.

As market participants had time to react and verify the integrity of their data and systems, buy-side and sell-side interest returned and an orderly price discovery process began to function.

By approximately 3:00 p.m., most securities had reverted back to trading at prices reflecting true consensus values.

Nevertheless, during the 20 minute period between 2:40 p.m. and 3:00 p.m., over 20,000 trades (many based on retail-customer orders) across more than 300 separate securities, including many ETFs,12 were executed at prices 60% or more away from their 2:40 p.m. prices.

After the market closed, the exchanges and FINRA met and jointly agreed to cancel (or break) all such trades under their respective “clearly erroneous” trade rules.

LESSONS LEARNED

The events summarized above and discussed in greater detail below highlight a number of key lessons to be learned from the extreme price movements observed on May 6.

One key lesson is that under stressed market conditions, the automated execution of a large sell order can trigger extreme price movements, especially if the automated execution algorithm does not take prices into account.

Moreover, the interaction between automated execution programs and algorithmic trading strategies can quickly erode liquidity and result in disorderly markets.

As the events of May 6 demonstrate, especially in times of significant volatility, high trading volume is not necessarily a reliable indicator of market liquidity.

May 6 was also an important reminder of the inter-connectedness of our derivatives and securities markets, particularly with respect to index products.

The nature of the cross-market trading activity described above was confirmed by extensive interviews with market participants (discussed more fully herein), many of whom are active in both the futures and cash markets in the ordinary course, particularly with respect to “price discovery” products such as the E-Mini and SPY.

Indeed, the Committee was formed prior to May 6 in recognition of the continuing convergence between the securities and derivatives markets, and the need for a harmonized regulatory approach that takes into account cross-market issues.

Among other potential areas to address in this regard, the staffs of the CFTC and SEC are working together with the markets to consider recalibrating the existing market-wide circuit breakers – none of which were triggered on May 6 – that apply across all equity trading venues and the futures markets.

Another key lesson from May 6 is that many market participants employ their own versions of a trading pause – either generally or in particular products – based on different combinations of market signals.

While the withdrawal of a single participant may not significantly impact the entire market, a liquidity crisis can develop if many market participants withdraw at the same time.

This, in turn, can lead to the breakdown of a fair and orderly price-discovery process, and in the extreme case trades can be executed at stub-quotes used by market makers to fulfill their continuous two-sided quoting obligations.

As demonstrated by the CME’s Stop Logic Functionality that triggered a halt in E-Mini trading, pausing a market can be an effective way of providing time for market participants to reassess their strategies, for algorithms to reset their parameters, and for an orderly market to be re-established.

In response to this phenomenon, and to curtail the possibility that a similar liquidity crisis can result in circumstances of such extreme price volatility, the SEC staff worked with the exchanges and FINRA to promptly implement a circuit breaker pilot program for trading in individual securities.

The circuit breakers pause trading across the U.S. markets in a security for five minutes if that security has experienced a 10% price change over the preceding five minutes.

On June 10, the SEC approved the application of the circuit breakers to securities included in the S&P 500 Index, and on September 10, the SEC approved an expansion of the program to securities included in the Russell 1000 Index and certain ETFs.

The circuit breaker program is in effect on a pilot basis through December 10, 2010.

A further observation from May 6 is that market participants’ uncertainty about when trades will be broken can affect their trading strategies and willingness to provide liquidity. In fact, in our interviews many participants expressed concern that, on May 6, the exchanges and FINRA only broke trades that were more than 60% away from the applicable reference price, and did so using a process that was not transparent.

To provide market participants more certainty as to which trades will be broken and allow them to better manage their risks, the SEC staff worked with the exchanges and FINRA to clarify the process for breaking erroneous trades using more objective standards.

On September 10, the SEC approved the new trade break procedures, which like the circuit breaker program, is in effect on a pilot basis through December 10, 2010.
Going forward, SEC staff will evaluate the operation of the circuit breaker program and the new procedures for breaking erroneous trades during the pilot period.

As part of its review, SEC staff intends to assess whether the current circuit breaker approach could be improved by adopting or incorporating other mechanisms, such as a limit up/limit down procedure that would directly prevent trades outside of specified parameters, while allowing trading to continue within those parameters.

Such a procedure could prevent many anomalous trades from ever occurring, as well as limit the disruptive effect of those that do occur, and may work well in tandem with a trading pause mechanism that would accommodate more fundamental price moves.
Of final note, the events of May 6 clearly demonstrate the importance of data in today’s world of fully-automated trading strategies and systems.

This is further complicated by the many sources of data that must be aggregated in order to form a complete picture of the markets upon which decisions to trade can be based.

Varied data conventions, differing methods of communication, the sheer volume of quotes, orders, and trades produced each second, and even inherent time lags based on the laws of physics add yet more complexity.

Whether trading decisions are based on human judgment or a computer algorithm, and whether trades occur once a minute or thousands of times each second, fair and orderly markets require that the standard for robust, accessible, and timely market data be set quite high.

Although we do not believe significant market data delays were the primary factor in causing the events of May 6, our analyses of that day reveal the extent to which the actions of market participants can be influenced by uncertainty about, or delays in, market data.

Accordingly, another area of focus going forward should be on the integrity and reliability of market centers’ data processes, especially those that involve the publication of trades and quotes to the consolidated market data feeds.

In addition, we will be working with the market centers in exploring their members’ trading practices to identify any unintentional or potentially abusive or manipulative conduct that may cause system delays that inhibit the ability of market participants to engage in a fair and orderly process of price discovery.