Chapter 2-1 Technical Analysis and Electronic Trading

One of the most common methods for determining supply and demand in any market is through technical analysis.  Technical analysis is a security evaluation method that analyzes price and volume trends to determine future price action.  The main weapon in a technical analyst’s arsenal is the chart that depicts price and volume action in specific intervals over a predetermined length of time.  Technical analysts study charts and look for patterns in the price action in an attempt to predict future price action.  Patterns may present themselves on a minute by minute, day by day, or even month by month basis.  For this reason it is important to study securities across a variety of time frames before making an investment decision based on technical analysis.  Furthermore, the expected length of a trade should be based on the time frame of the chart studied.  Identifying a pattern on a 1 minute chart and expecting a trade to last 2 weeks is a surefire way to misuse technical analysis.

The two most important factors in technical analysis are the assumptions that price moves in trends and that securities will behave in the present as they have behaved in the past.  If a currency has been appreciating .01% every day for a week, it is fair to assume that this is going to continue, or at the very least that the currency is not going to depreciate.  This is known as a trend, and although trends change, any successful trader will agree that trading with the trend is safer that trading against it.  Price action is depicted in intervals.  If a security is behaving in such a fashion that the high and low prices for each individual time frame are increasing, it is known to be in an uptrend.  Conversely, if a security is making lower highs and lower lows, it is said to be in a downtrend.  Here are some charts depicting this price action:

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Trends generally exist as either short-term trends or long-term trends.  The synergy between big picture and small picture is one of the most important things to consider when making technical investment decisions.  Let’s consider a security that has been down four out of the last five days.  Investors would consider this to be a sign of weakness and might consider taking a short position.  However, this same security has been up eight of the last nine weeks, so much so that investors who are long are simply locking in some profits to protect their gains.  This is known as a pullback, and is a completely natural price movement for every type of security.  Taking a short position is not necessarily wrong, but an investor must consider that the overall trend is upwards and manage the trade accordingly.  Taking smaller positions or using stricter risk management criteria are common ways of managing counter trend trades.  Here is an example of what this might look like:

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While price action is the focus of technical analysis, the observation of volume and volume trends is every bit as important.  Volume analysis is the charting and interpretation of the number of shares traded, or dollars exchanged, of a security or currency that have traded over a time interval.  The greater the volume traded the more active the security is.  Volume analysis is used for two main functions:  comparing one security or currency to another, and comparing a security or currency to itself.  Using volume to compare currencies to one another is a good way of identifying which currencies are the more actively traded.  Actively traded currencies are likely to be more liquid and follow trends in a more predictable nature.  Comparisons can be made on a daily basis, an average basis, or a relative basis.  Here is a quick example that demonstrates all three of the above using currency futures:

Australian Dollar:                                         Euro:

Today – 115,000                                             Today – 385,000

Average – 90,000                                            Average – 560,000

Relative – (120000/90000) = 1.278                Relative – (385000/560000) = .6875

The above example demonstrates the interaction between the three volume variables.  The Euro has done significantly more volume of the Aussie dollar indicating that almost 3 times as many futures contracts have traded hands on this particular day.  On an average day, the Euro trades 560,000 contracts while the Aussie trades 90,000; this indicates that traders are more concerned with the Euro, and the contracts are likely to exhibit greater liquidity.  When compared to the average, the Aussie is doing 1.278 times its daily whereas the Euro is doing .6875; this indicates that on this particular day traders are paying more attention to the Aussie than normal and less attention to the Euro.  Many traders use relative volume as a strong signal to involve themselves with a security on a particular day; if identical setups presented themselves, conventional wisdom would dictate that the Aussie is a higher probability trade.

Due to the growing presence of electronic trading in the FX market, algorithmic trading volume has increased significantly.  Recent volume analysis has shown that algorithmic trading now makes up at least 25% of all trading volume.  Algorithmic trading, or automated trading, is a method of trading that uses a computer program to make investment decisions.  Programs that are used to generate buy and sell signals which are then manually executed are known as grey-boxes.  Algorithmic trading that occurs without any human intervention is known as black-box trading.  Trading with a computer program gives investors the ability to scan the markets in a way that no human being could ever hope to replicate.  Computer algorithms analyze millions of data points a second to identify predetermined trade setups and then make execution decisions based on time, price, and size.

There are two main components to algorithmic trading:  design and implementation.  During the design phase investors conduct research to quantify investment strategies in a way that can be standardized across all securities in an asset class.  Quantifying can be as simple as “buy company A if earnings are an x% improvement over last quarter” to incredibly complex signals based on price action that occurs on a sub-penny price level on a millisecond time frame.  The most complicated form of algorithmic trading is known as quantitative investing and is practiced by the most sophisticated investors, often hedge funds, and designed by PhD researchers in the fields of physics, mathematics, and statistics.  Many of these “quants” look for disparities amongst the relationships between multiple securities to perform statistical arbitrage, a method of generating risk free profits.

The more complex a design is in nature, the more complex the implementation will be in practice.  Implementing an algorithmic program often requires the assistance of a computer programmer who can translate your investing ideas into a language the computer can operate off of.  There are two aspects to implementation to consider:  signal generation and order execution.  Signal generation occurs when an algorithm scans incoming data and generates buy and sell signals based on current market conditions.  Once a buy or sell signal is generated it must be sent to a broker/dealer to be executed.  This often involves another computer program that can receive the generated signals and manipulate trading software accurately and quickly so that the appropriate transactions occur.  As financial markets are constantly changing it is paramount that execution takes place quick enough to capitalize on a signal before markets change adversely.  The entire process from data scan to signal generation to market execution takes place in under a second.

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