Where has all the Volume Gone?

Monday this week we saw the markets test their January and February highs only to pull back and continue their sideways “trend”. The most notable factor in this recent sideways move has been the completely lack of volume which also means the absence of big players in the markets. When I noticed this theme a couple days ago I wasn’t completely sure what to make of it, initially I assumed it was a bearish signal but I decided to run a back test to see how these situations had played out in the past.

I designed a system that would buy if we saw a 3 percent rise in the S&P 500 over a 5 day period followed by a day in which the volume was at its lowest point in the last 30 days. The blue arrows on the chart below show examples of entry points for this system.


and here are the results:


As you can see we had rather negative short term results (2 and 3 days out) with the market lower 60% of the time during that period. One thing that did surprise me however was the high percentage of profitable trades as we moved further out in the study. This most likely means that in the past low volume days have served as a period of consolidation after the previous market move, during this time institutional investors sit on the sidelines before reentering on the next leg up.

If this test is any indication investors should be cautious near term while looking out for potential upside in the weeks ahead.

Andrew

Small Cap Short Interest

Friday topped off a rather nice week for all the major indices with the DOW marking its highest point in over three months. Any time I see a decent short term rally amidst longer term downward/sideways action I begin to wonder what affect short covering had in the rally. In addition to looking at the typical metrics (breadth, net A/D, new highs/new lows) I like to run through some of the data for small cap names with high short interest. Below is spreadsheet for the 30 small cap securities that had the highest short interest as of April 1.


As you can see I have included their percent change from April 1 to April 18 as well as the overall change in short interest.

In running this screen I am looking for a couple things:

- Stocks which have seen a swift rise in price coupled with a decline in short interest. A situation like this could signal a nice re-entry point for many shorts as the weak short holders have been pushed out and buying has dried up.

Stocks to note: NTRI, SPF, CTCT

- I also look for stocks which have declined significantly with increased short interest. These stocks could be prone to strong short covering rallies if solid earnings or good news hit the stock.

Stocks to note: DSL, CROX

- Lastly I like to check for irregularities, something like CONN, where the stock has risen over 10 percent and yet the short interest is up almost 30. Again this gives us no clear indication of future direction but I would expect to see some sharp moves in the stock going forward.

Of course all of this analysis should be done in the context of both fundamental and technical analysis for any of these companies. But often times including other forms of analysis can help improve an investor’s insight into the overall direction of a security.


Andrew

KBE System (Part 1)

This week the theme of correlation among banking names has once again presented itself, and as I noted in my last post I have begun programming a strategy that I believe could take advantage of these correlations and mean reverting tendencies. Here is a breakdown of my strategy as it stands:

Purpose

First and foremost I designed this strategy exclusively for short term intra day trading as a complement to my other trading strategies. For the time being I am using discretionary execution of the strategy and so far have only traded it in simulated accounts.

Setup

I first look for a defined intra day trend in the KBE etf, I choose to identify this market state with a simple two moving average crossover.
(below is the KBE chart for last Friday 4-11-2008)

I am currently using a longer 20 period SMA and a shorter 8 period SMA, these were selected because my back tests indicated those values to be efficient as a preliminary filter for trend.

I next apply Keltner channels to each of the 24 components of the KBE etf, an alert is set to notify me anytime one of the components touches a Keltner band on a strong counter trend move. At this point I am using a moving average of 5 for the center of the Keltner bands and an average true range of 2.05, again these values were selected based on my back tests and fell within a range of values that I deemed acceptable.

Entry

Once these conditions have been met I set a stop limit order at the current value of the average true range, this is done to ensure a reasonable entry price and to minimize the effects of slippage.

As the strategy develops I shall incorporate a pyramiding entry system, however for my initial testing I am limiting myself to only a one time entry.


Above is an example of two triggered signals (indicated by the red arrows) that occurred last Friday (4-11-2008), this is the same date as the KBE chart in this post so you can compare the component to the index.

In my next post in this series I will discuss my stop placements, profit targets, and position sizing.


Andrew

Rise or Fall the Banks Tell It All

As I mentioned in my previous post I have begun testing a basic system that I think might be able to take advantage of the herd like behavior (i.e. inter-market and intra-sector correlations) that seems to have increased significantly in recent months.

For inter-market correlations I refer you to a great post by Brett Steenbarger which discusses current inter-market themes.

As for intra-sector correlations, anyone who has been following the market the past couple months has certainly noticed that the banking industry has quickly become a very good short term metric for the health of the overall market. Not surprisingly both the volatility and severity of movement within the industry (KBE etf) has increased significantly as the index’s components get crushed on down days and spike up when we see optimism in the broader indices. I have also noticed qualitatively what seems to be a much greater correlation within the 24 components of the KBE etf along with fewer sustained countertrend divergances from the overall industry trend on an intra day basis.

above is a weekly chart of the KBE etf and the average true range over that time which illustrates the significant rise in intraday volitility.

These observations gave me the basis for the system I am currently testing. My working theory is as follows:

The current fears of CDO write downs, counterparty risk, capital ratio’s and the opacity of bank balance sheets have caused many short term investors to treat all banks as one in the same, especially during intraday sell offs and rallies. This increased correlation if valid should cause short term counter trend price movements of the etf's components to have a greater probability of reverting back to the overall trend of the etf. My intention is to identify these countertrend price movements and then enter trades (either long or short) that would profit from the reversion to the mean.

This weekend I will post some of the statistics of my findings and how I plan to identify and profit from the previously mentioned price movements.


Andrew

Fighting the Herd

Today I had the opportunity to listen to a great podcast interview with Barry Burns. Barry is a pure technician and has a Ph.D. in hypnotherapy which seemed to give him a very holistic view of the markets which I found very insightful.

In the interview Barry made one very salient point regarding how human psychology leads to herd like behavior in many circumstances and especially in markets. I will do my best to reiterate his main point and flow of thought as I found it to be most valuable.

Burns takes the idea of herd mentality in human psychology and applies it to the financial markets, noting that the vast majority of people who attempt to succeed in trading ultimately fail. However everyone who attempts to trade in the financial markets thinks of himself as the exception, HE will be the one who consistently takes money from other traders, speeding in his Ferrari on the road to opulent riches. Yet by establishing that belief and mentality traders are in effect succumbing to the mentality of the herd and as we all know, most traders are unsuccessful.

So how does one overcome this contradiction? How can a trader go into trading without expecting to be one of the winners? If we did not expect to win there would be no point. Burns believes the answer lies in shades of grey; all too many traders go into the markets looking for the “holy grail” or the sure thing, the system either discretionary or mechanical that will continue to work no matter what. Unfortunately for those folks trading is much harder than that, there is no definitive certainty in the markets and the best we have are mere probabilities (i.e. shades of grey). In Burn's mind it is the way that we approach these probabilities as traders relative to the herd that will determine a large part of our success. So the question becomes how does one look at the markets without becoming part of the herd?

This implicit question along with Burn's analysis of the aggregate desires of trader's to be successful stimulated my thoughts about what other beliefs we take for granted in trading and how that could lead us to be more like the herd than we think.

My next post will detail my ideas for a system I am beginning to test that I think may be able to take advantage of some of the herd mentality we are seeing in specific sectors of the market these days.

Andrew



Disclosure: I have no association with either Barry Burns or tradinginterviews.com

Bubble Smell Test

In its most basic form a bubble is merely a rapid and excessive financially speculative frenzy in which prices of a given asset class skyrocket beyond their historical trend and underlying fundamental value. This is then followed by a swift crash and depression of asset prices in the given market.

So basically short term differences in supply and demand, first A LOT more buyers then sellers followed by A LOT more sellers than buyers. A little overly simplistic but you get my drift. The real question however when it comes to bubbles is where is the capital coming from that is fueling a given speculative craze?

Hundreds of years ago during two of history’s most famous bubbles (the Belgian tulip bubble and the English south sea bubble) the capital that fueled financial speculation and price appreciation came from reallocation by wealthy investors and the flood of new participants into these markets, both of whom were willing to pay any price to play part in this financial “gold rush”.

In the hundreds of years since human psychology has not changed much and technology has only facilitated the growth and occurrence of bubbles. In general most of these bubbles can be sniffed out by following the flow of capital and keeping an eye on market participants.

In 2000 after hearing of the substantial riches to be made in the ‘new economy’ and internet stocks thousands quit their day jobs to become full time day traders only to lose all or most of their savings in the process. This increase in participants was compounded by the reallocation of assets by wealthy investors who didn’t want to miss out on this ‘once in a lifetime’ trend. As a result we saw the NASDAQ 100 appreciate 140% from March 1999 to March 2000 only to see it fall 75% from that point in the following 12 months. Investors poured money in without asking questions and they pulled it right on in the exact same way.

The collapse of the stock market was followed closely by the begging of a new bubble, real estate. Appreciation was slow at first but as greed increased builders started developing faster and faster which continued to drastically increase market supply. At the same time average middle class Americans became professional house flippers, putting down sizable chunks of their net worth in the prospect of sizable gains. This flow of capital drove up the price until individuals realized that prices couldn’t keep going up forever and those who bought in with that expectation were left holding the bag. This is turn led to fear which only adds fuel to downside acceleration. Credit problems aside nobody wants to risk buying at a top and if nobody wants to buy there is only one way for prices to go.

Now let’s use that same lens to look at the current commodity markets. Rapid price appreciation was first caused by fear due to instability in the global financial markets, this fear was then followed by greed as more investors sought returns in this outperforming sector. Large institutions like CALPERS began allocating billions into these arenas in the hopes of increased returns and etf’s like GLD, DBA, and MOO have given retail investors, many of whom have limited experience or knowledge of the commodities markets, the ability to invest directly in such assets. It seems that all the pieces are coming together for history to repeat itself.

Now don’t misunderstand my simplistic bubble smell test, I know the there are strong fundamentals supporting the price of gold and that it is the alternative currency in times of financial turmoil. I also know that agriculture is experiencing increased demand due to governmental policy decisions, demand for ethanol, and worldwide growth of a middle class. But in my mind those demand factors do not support charts like these (GLD and DBA respectively).

(Charts are set to same time scale at QQQQ)

And let’s not forget in 2000 we were in the midst of a ‘new economy’ where the internet ruled the day, or the period that followed in which individuals believed real estate could never experience price depreciation. Now days there is the belief that commodity demand will continue at a near exponential clip. I completely agree that demand has risen but after looking at the increase in demand relative to the increase in price the risk/reward in these asset classes seems far less than attractive.

Andrew