What is Technical Analysis?

What is Technical Analysis?

It refers to the study of the action of the market itself as opposed to the study of the goods in which the market deals. Technical Analysis is the science of recording, usually in graphic form, the actual history of trading (price changes, volume of transactions, etc.) in a certain stock or in “the Averages” and then deducing from that pictured history the probable future trend.

John J. Murphy: Technical analysis is the study of market action, primarily through the use of charts, for the purpose of forecasting future price trends. The term “market action” or “price action” includes the three principal sources of information available to the technician – price, volume and open interest.

Market price tends to lead known fundamentals. Market price acts as a leading indicator of the fundamentals or the conventional wisdom of the moment.

Three Main Premises:

  • Price Discounts Everything
  • Prices Move In Trends
  • History Repeats Itself

Additional premise: Markets are fractal, meaning that patterns (in this case resulting from the psychology of market participants), appear at every scale. This is the reason why using a 200 period moving average or 14 period RSI will produce similar results, regardless of the timeframe they’re used on (i.e. daily vs weekly chart, 5 minute vs 65 minute chart).

One of the largest advantages technicians have is the ability to apply our tools to any liquid asset class, giving us the ability to analyze and invest in thousands of liquid products across the globe. Additionally, as technicians we’re not concerned with the “why”, but rather the “what”, “when” and “how long?”



Sentiment is another factor that is widely used by technicians in their analysis. Concensus can be right for a long time, but is usually wrong at extremes. There are a number of tools that can be used to gauge sentiment for a specific security. It is important to remember that sentiment is secondary to price action and should not be used as the sole reason for an entry / exit into a position. Large unwinds in sentiment can lead to aggressive moves in the opposite direction of the initial trend.


There are a variety of polls that are put out by different institutions that look to gague sentiment of different types of market participants. The idea is to watch these polls for extreme bullish or bearish readings, relative to historical norms that is. What happens in the middle of those polls is mostly noise, but the extreme readings can by very helpful in a technician’s analysis.

Commitment of Traders Report:

The commitment of traders report shows the net positions of futures and options for commercial hedgers, large speculators (institutions), and small speculators. This data is important because commercial hedgers are said to be the “smart money” because they are the ones whose businesses deal with the goods in which they are trading. They are essentially the insiders of the futures markets, whereas companies are the insiders of the stock market. There are also indicators that can be constructed using these data points including the C.O.T. Move Index and the C.O.T. Index.  I won’t get into this much further, but this is just another report to be aware of and made use of in your analysis. Check out timingcharts.com for on this subject.

Options Market:

The options market is a valuable tool in identifying the biases of institutions. By analyzing where the largest open interest is as well as scanning for large block trades and heavy volume, we can identify where the “smart money”, or institutional traders, are expecting the stock to go. The caveat here is that we although we may be able to see what position they are putting on in the options market, we do not know who the players are, nor do we know what role that position is playing in their overall portfolio.

Short Interest / Days to Cover:

The largest moves occur at extremes, which is why it is important to pay attention to short interest. This data can be found at Nasdaq.com and is reported twice monthly. How significant an amount of short interest is really is all relative to what it was for that particular security in the past. There are two numbers that are important.

  1. Shorts as a % of float: The float is the amount of shares available to be traded in the public (secondary) markets. If a security has a large percentage of its available shares (float) sold short, it can signal that concensus is overly pessimistic and that under the right conditions, a short squeeze may insue.
  2. Days to cover: Days to cover is used to determine how many days on average daily volume would it take for all the shares that are sold short to be covered. I usually use the 10 day average, but it really is a matter of preference.

Sell Side Analyst Coverage:

Another important indicator of how optimistic or pessimistic concensus is about a security is to look at how many sell side analysts that cover the stock have it as a buy rating. If a large percentage of the analysts are rating a stock a sell or hold, that presents what may be an overly bearish concensus view. The same applies if a large percentage of the analysts are rating a stock a buy, that presents what may be an overly bullish concensus view. Looking at this type of information may assist you in identifying extremes that may present good risk/reward scenarios if price confirms this secondary data.

Stocktwits / Twitter: 

Both stocktwits and twitter provide valuable information on how individuals are currently viewing the market or a particular security. Although it can be hard to quantify what the views actually mean, it may be helpful to use this info as anecdotal evidence to support your thesis. If you think that there’s no value in this, just try to post something bullish about a stock that nobody likes and see the hate and flack you get. Everyone hated treasuries to start the year, and now they’re on of the best performing asset classes of  2014.

Relative Strength Index

The Relative Strength Index, or RSI, is a popular momentum indicator used throughout the field of TA.

Rather than get into the definition and construction of this indicator, I think it’d be more helpful to go into how I personally use the indicator. If you need a refresher or are new to this topic, I suggest heading over to stockcharts chart school to familiarize yourself with it.

First off, I use a 14 period RSI for all the timeframes I look at because markets are fractcal, meaning that repeating patterns occur at all scales / timeframes.

The two main ways I use RSI are as follows:

1. Determining Bull / Bear Ranges

2. Identifying Divergences

Determining Momentum Ranges: If I can help it, I want to be trading in the direction that momentum is leaning. So how exactly do I define a bull or bear range? Well, it’s slightly subjective but anytime something hits overbought or oversold conditions and does not reach the opposite extreme on price consolidations or pullbacks I think of it as being bullish or bearish based on the original confirmation above 70 or below 30.

Bullish Range Example: When momentum is consistently hitting overbought, without reaching oversold.

bull rangeAs we can see from the chart above, after momentum transitioned into a bullish range by hitting overbought conditions in July 2013, AAPL continued higher in a nice uptrend. Since momentum never hit oversold conditions on pullbacks, that weakness ended up being a buying opportunity rather than a reason to be concerned if long or trying to be short.

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Relative Performance

An important part of any technician’s analysis should be how the security he/she is analyzing is performing relative to the broader market, its sector, or another security. The way to do this is by creating a ratio chart of one security divided by another. The same analysis done to price charts can be applied to ratio charts.

To provide some perspective, absolute performance is the value determined by looking solely at how an individual security behaves in terms of its price change over a given period of time.

The Math Behind The Ratio:

To plot a ratio chart, you take one security and divide it by another. As an example we’ll use SPY/IWM. This ratio would give you a chart showing how the S&P 500 is performing relative to the Russell 2000.

What causes the ratio to rise?

  1. If SPY rises while IWM stays flat or moves lower.
  2. If both go down but SPY goes down less than IWM.
  3. If both rise but SPY rises more than IWM.

What causes the ratio to fall?

  1. If IWM rises while SPY stays flat or moves lower.
  2. If both go down but IWM goes down less than SPY.
  3. If both rise but IWM rises more than SPY.

Relative Strength:

Relative strength is when the underlying security being studied is outperforming the security it is being compared to. The below chart is a ratio chart of FB/SOCL. This shows that facebook has outperformed the social media ETF since it put in a higher low and began an uptrend in mid 2013.

Relative Strength

Relative Weakness:

Relative weakness is when the underlying secruity being studied is underperforming the security it is being compared to.  The chart below shows the ratio of SPY/IWM on a weekly basis. This shows that since the year 2000, the S&P 500 has underperformed the Russell 2000.


Other Methods Besides Ratio Charting:

Another, more simple way to determine relative strength and weakness is by looking at the absolute performance of two charts side by side. For example, if SPY is up 5% for the year, but IWM is down 5% for the year, it is showing weakness relative to SPY. The ratio chart just makes it easier to visualize this relationship.

Moving Averages

A moving average is a smoothing mechanism that helps to identify the price trend over a given period of time. This is considered a lagging indicator because it is generated using past prices. Technicians use this indicator for a variety of strategies and signals. Additionally, there are a variety of settings that can be applied to this indicator to produce the desired effect appropriate for the strategy being employed. Lastly, moving averages are an important component of a variety of indicators and oscillators including the popular momentum indicator, moving average comvergence divergence (MACD).


1. Period:

Most moving averages are based on the closing prices of whatever time period the chart you are looking at, whether it be daily, weekly, monthly or intraday time-frames. The most common periods used for moving averages are the 50, 150, and 200 period moving averages. Other popular periods used include the 8, 21, 55 and 144 period moving averages due to their significance as fibonacci numbers. None of these settings are inherently correct or better than others so it really is a matter of preference.

2. Simple / Weighted / Exponential: 

A simple moving average (SMA) is also known as the arithmetic average and is a common average of the price values in the specified period. Each price in the series is equally weighted.

A weighted moving average (WMA) assigns a weighting factor to each value in the data series according to its age. The most recent data gets the greatest weight and each price value gets a smaller weight as we count backward in the series.

An exponential moving average (EMA) is calculated in a way to give more weight to the recent prices in an attempt to make the smoothing mechanism more responsive to new information. As we count backwards in the series of prices in the period, each one is assigned an exponentially smaller weighting in the calculation, hence giving more recent prices more weight.

The benefit, and potential drawdown, of a weighted moving average is that more signals are generated because the moving average follows price more closely. That can help because there is less of a lag but there may be a lot of false signals generated because of the increase in amount of crossovers and slope changes.

Common Uses:

1.  Slope of the Moving Average:

If the moving average is sloping higher, the trend is higher.

If the moving average is flat, there is no current trend. This may be a consolidation of the prior trend or the start of a trend reversal.

If the moving average is sloping lower, the trend is lower.

2. Moving Average Crossovers

Traders often use moving average crossovers as buy or sell signals. When a moving average of a shorter period crosses above or below that of a longer period, it may be the signal of a new trend emerging. For example, the golden cross is when the 50 day moving average crosses above the 200 day moving average, signaling that the trend in price is now higher. On the flip-side, the death cross is when the 50 day moving average crosses below the 200 day moving average, signaling that the trend in price is now lower.

Crossovers are helpful in determining the overall trend, but it is important to remember that moving averages are lagging indicators. Strategies based on crossovers are likely to catch the middle of the trend, but give back some of the gains at the tops and bottoms of trends.

3. Support / Resistance

In addition to helping technicians identify the price trend, moving averages may also act as support and resistance. In certain circumstances a particular moving average may prove to be a significant price level when analyzing a security.

4. Momentum

The slope of a moving average can also provide important information about the momentum present in the security being analyzed. By plotting short term, medium term, and long term moving averages on one chart you can see whether or not the majority of them are moving in the same direction. If they are all confirming a trend in the same direction, momentum is moving in that direction as well. For example, if the 20 day, 50 day, and 200 day simple moving averages are all sloping and trending lower, momentum is clearly favoring the downside.

5. Moving Average Seperation:

When a short term moving average gets too far extended from a long term moving average it may signal that the current trend is unsustainable and that price needs to consolidate. For example, if the 50 day simple moving average is 20% higher than the 200 day simple moving average, it may signal that price has become too extended to the upside and needs to pull back or consolidate to allow the longer term moving average to catch up. This is often referred to as a reversion to the mean, or average for the period being studied.