In reproducing this article, some editorial licence has been exercised to make it more readable, removing uneccessary ramble.
For the purpose of this topic -
A mechanical system is an automated set of rules and decisions operated to make a profit.
A buy side algorithm is an automated set of rules used for accumulation.
A sell side algorithm is an automated set of rules used for distribution.
Buy side is mainly fund managers.
Sell side is mainly prime-brokers.
Most readers have probably seen at least one installment of the three "Terminator" movies. In the world of Sarah Connor, the present is juxtaposed against a dystopian future where machine battles machine with humans on the sidelines just holding on. Murderous-turned-lovable cyborgs aside - it isn’t too difficult to draw parallels between the world of the T-1000 and trading the markets: machines pitted against machines with humans barely in control. Conversations with a number of experienced traders about the radical changes in price action over the past three years inspired this article.
In a T-1000 Second
In the course of an extended discussion on price action, most veteran traders will mention how
quickly and radically price moves occur compared to a few years ago.
There have always been examples of "quick and radical" price movements. Today, "quick and radical" is the norm rather than the exception. The reasons for this change are many:
• All market participants are aware of technical levels.
• Everyone sees them and plays for or against those levels.
• Everyone sees the same patterns and, jumping in or out as the break unfolds.
• Information flows at the speed of light.
• The effects caused by new information is assimilated and acted upon by market participants in increasingly shorter timeframes.
• The number and power of automated trading systems ("black boxes") has increased exponentially .
• The amount and power of trade execution algorithms ("icebergs") has also increased.
• The number of participants in any given market has grown due to globalization of markets, exchanges and money flows.
• The amount of capital available has risen thanks to easy money policies of many central banks.
In this article, I address the effects of these developments, while focusing primarily on the impact of algorithms on trading styles. I do not profess expertise in this subject - I am simply writing as a market participant and observer who feels the impact of these changes. I believe there is value in understanding the reasons and drivers behind some of these changes - it can provide insight into adapting, identifying and taking advantage of new opportunities in the market.
Terms of Judgment Day
Before continuing, I must make a distinction between "black boxes" and "algorithmic trading".
Articles related to computerized trading, by some authors make a distinction regarding these two terms. I was surprised, because instinctively I thought all computerized trading could be categorized as black-box trading. But for the purposes of this article, the terms "algorithm" and "black box" are taken to mean different categories (albeit related).
Algorithmic trading refers to trade-execution-only algorithms. The job of the algorithm is to get the best price over a particular period of time. It is not trying to determine trend or try to obtain a profit based on buying and selling. In other words, it's job is to buy 100,000 shares of ABC and get the best average price possible over the course of 15 minutes, an hour, or a day. The decision to buy (or sell) is someone (or something) else’s. The execution of that decision is the job of the algorithm.
Algorithms that aren't execution-only and involve decision making (trend, entries, exits, profits and losses), can be categorized as black boxes. Their job is to try to turn a profit on a strictly mechanical basis. This means determining what the trend is, when to buy or sell, what the stop level is and what the exit levels should be.
Please note, distinction is made between those terms only for the purposes of this article. I am not sure I agree or that everyone agrees that there should be a distinction between the two terms. But for my limited purposes here, the distinction works.
Effects of Algorithms
The job of the market is to bring demand and supply into balance and, in the process, determine the market price of a commodity or stock. One of the consequences of this function is that price moves from one level to another. Prior to 2002, price movements tended to be gradual. A rising market would be filled with retracements, zigging and zagging toward its new price level. Traders could count on those retracements, and make a good living playing them.
That is no longer the case. Today, the movement between price levels, or more accurately value areas, tends to be more abrupt. There are fewer retracements and the time it takes to move from one level to another has become shorter and continues to compress. In other words, the market has become more "efficient."
There are multiple reasons, related to system and algorithmic trading, for this:
• In equities markets more and more sell-side brokerage houses use algorithmic trading to process client orders.
• Increasingly, buy-side institutions are internalizing their execution, using cheap computing power and proprietary algorithms.
• In all markets, there are more index funds or ETFs where the Fund Manager tries to match the overall index.
• There has been a large increase in the number of venues where the same equity can be traded
• Computers are needed simply to find sources of liquidity, especially in equities.
• It is almost impossible for a trader to efficiently hunt for, and place orders, at all of those sources.
These changes affect the game permanently for every player in the market.
Rise of the Machines
In the "old" days, two distinct roles existed on Wall Street - those who bought (or shorted) financial instruments (shares, futures, options, bonds) and those who brokered the transactions. Respectively these two camps are known as the buy side and the sell side. The buy side is mainly fund managers (and other brokerage customers); the sell side is mainly brokerage firms. In those old days, the buy side gave an order to the sell side (brokerage), who then filled that order using human ingenuity. The sell side is a competitive business, however, so as electronic trading became more prevalent, the sell side started to use simple algorithms to fill orders more efficiently and to provide an edge. This allowed them to guarantee their clients (the buy side) a better fill price for large orders and ensured the brokers that they would win more business. Obviously, all sell-side firms had to get into the algorithmic business or they would go the way of the buggy whip. Thus, the foundations for the first wave of "robot" battles were laid within the industry.
The second wave is a result of the explosion of cheap computing power and the continued rise of electronic execution. This allowed for more intelligent algorithms and made possible software that was easy for buy-side firms to use. Thus today, a buy-side firm can purchase or lease software with prebuilt algorithms for order execution. The software can easily be customized to use a proprietary fill algorithm as necessary. Suddenly, instead of humans competing against each other, traders have super-fast, buy-side algorithms competing for fills. The sell-side firms have been relegated to supplying clearing, customer service and brokerage services at rock-bottom rates. Some have morphed into technology vendors of sorts - providing algorithms, connectivity and technical know-how. Overall, though, it has become a free for all. Bots fighting bots to try to get the best fill.
Robot Battles
To understand the kinds of battles being waged by these order-fulfillment algorithms, we have to get into the psyche of index-fund and ETF managers. Many of these funds are indexed to the overall performance of the market or a segment of the market. Thus, managers have done their jobs simply by meeting the performance of the segment against which the funds are indexed.
So in practical terms, what does this mean? If the market or the market segment is going up, the managers have to buy - the price at which they buy is not necessarily a consideration as long as their final price is an acceptable average over some time period. As long as this average is similar to the average that other fund managers obtain everything is OK. Let me be clear about something, because it is important: Usually, the final price is not a consideration—it is the average price obtained over a period compared to the average trading price over that time that counts. In fact, one of the biggest growth areas for some of the technology vendors right now relates to products that measure and monitor the effectiveness of these algorithms.
For many of these managers, it is simply not acceptable to miss the trade - if their indexed market is going up, they have to be in. Thus, many execution algorithms are designed to ultimately execute their buys and sells regardless of price. Of course, these algorithms try to get better prices, but if the market starts to move, then they simply execute at the market, because they have to get the orders filled. This adds fuel to the fire as each algorithm successively starts to submit what are effectively market orders. The net effect is markets that flood in one direction with no let-up. Spikes are more frequent and more pronounced with prices returning back to original prespike levels just as rapidly as they moved once the algorithms are done with their games.
What about hedge funds and other actively traded funds? It’s no secret that there has been an explosion of these players. Many of them are trend followers. Thus, if it looks like a trend is about to begin, be assured that a large number of players want in on that trend. This means that more money than ever is poured into (or taken out of) a market in a much smaller timeframe and that markets can be easily driven far above or way below their true values more often. Plus markets can stay at those levels for far longer than before, because there is ever more money to sustain the trend beyond rational limits.
New World Order
The effect of all this can easily be seen in today’s markets. What starts off as a small creeper mode quickly turns into a crescendo and then everything just peters out. There are no retracements - price moves up (or down) in one shot and then goes sideways for what seems like forever. There are more v-spike reversals than ever before. It’s a big, fast game of musical chairs - everyone jumps in and then quickly retreats. If you’re not fast enough, you are left without a chair.
Another major side effect is the lack of respect for support or resistance points. Major violations of support and resistance points are common now. I firmly believe that this is related to algorithmic execution. An algorithm that needs to buy will buy - it has no knowledge of support and resistance zones. Its primary purpose is to get the best average price—even if that average price drives the market above what looks like resistance (or below what looks like support).
Further, stop sizes have to change. Because these algorithms introduce extreme volatility into markets, stop levels have to be much further away than ever before. For the same account size, traders now have to play with reduced size. It used to be that two ATRs (average true range) could be considered "outside the noise." Now, it’s three ATRs and in many cases 3.5. Ouch! If a trader takes a three ATR stop on the same unit size he or she was trading four years ago, the trader could be hurting.
Not all the news is bad. The volatility introduced by these algorithms (and other changes) means that a trader can day trade more markets than ever. The really old hands will remember when corn - when the range was less than 5 cents - sugar or even gold could not be day traded. Now, the length of line is so much larger and provides many opportunities, including just "playing the noise" if a trader so desires.
Survivial Techniques
Probably the best trading technique that will work in this environment is the breakout. More false breakouts will appear, but the risk-reward ratios will more than make up for them. And traders will be guaranteed to be in on every move. It will just be far more frustrating, especially if a trader’s normal bread and butter is retracements after a breakout.
To make up for the numerous small losses, traders may have to get used to pyramiding when the break is finally for real. If he or she wants to play the retracement game, then the trader will be forced to look for retracements on a much shorter timeframe. If the breakout is from a five-minute formation, the first five-minute retracement may not occur until the move is almost complete. Instead, the trader will have no choice but to look for retracements on charts as low as 30 seconds or one minute.
The Arsenal
Since markets move so much more rapidly today, individual discretionary traders are having a more difficult time watching and managing the same number of markets and positions as they did just a few years ago. New weapons are needed, and software vendors are rising to the challenge.
Proprietary firms are rolling out their own algorithms to help with trade execution. Trading platforms are introducing more robust chart trading so that the user will not have to turn away from the screen in order to place and manage trades.
And new semi-automated software products are increasingly available to make it easier to manage one side of a trade. For example, the discretionary trader could enter a position manually and then let the software manage the exit using a trader-defined algorithm such as a parabolic, fixed ATR, keltner bands or combinations. This frees the trader from monitoring the position, allowing him or her to focus on finding more opportunities.
Even black-box building tools are getting easier to implement, increasing the number of potential traders who can use them.
Far from Terminated
Probably the only guarantee in the trading game is that it will change. Over the past three or four years, the markets have survived many battles, and the effects are staggering. Once a trader understands the drivers behind these changes, it is easier to react and take advantage of them. Algorithms and black-box trading is here to stay. Their use will grow - some estimates suggest that 50 percent of equity trading will be done using algorithms by 2010 up from 25 percent today.
But, as with anything else in the markets, the abundant use of software to extract maximum value from the markets will itself create numerous pockets of inefficiencies that can be exploited. The smart, adaptable individual trader will be able to seek out and exploit these new opportunities. So, as Sarah Connor says in "Terminator 2," "The unknown future rolls toward us. I face it, for the first time, with a sense of hope." Long live algorithms!
