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Years ago, a big box office supply store came up with the slogan, “that was easy”. I have even seen plastic battery powered buttons that vocalize the phrase when pressed. Wall Street and many individual investors have adopted this concept when incorporating chart analysis to the investment process. A myth I have heard for years is, “there’s nothing more bullish than a breakout to new highs”. Like all myths, there is some truth in the statement.

Believing successful investing is as simple as buying breakouts and selling breakdowns can be a dangerous endeavor.

Back in late October 1987, I was stinging from recent losses in the stock market from that fateful day a week or two earlier. With a bruised ego but determination, I perused a local bookstore and found “Secrets for Profiting in Bull and Bear Markets” by Stan Weinstein. The market’s crash through support levels and uptrend lines meant the beginning of a bear market – everybody knows that! Right? After reading the book, a bright light emitted forth from the pages and I could hear the angels singing. As it turned out, the book was my first look at Technical Analysis, or, using charts to gauge future possible movements. Patterns such as Head & Shoulders Tops and Double Bottoms, were detailed, as well as the basics of moving averages. My thirst for knowledge was unquenched so I bought another book, “Technical Analysis of Stock Trends” by Edwards and Magee. First published in 1948, many consider it a foundational work for Technical Analysis as it has over 600 pages dedicated to chart patterns and trend lines and the phenomenon of how crowd psychology is conveyed in the patterns. For decades, the concepts in these books as well as numerous others have been learned by the public, professional and non-professional. Examples in the books and in real time, in my opinion, supported the theories of how chart patterns and basic tools such as moving averages and trend lines can play helpful roles within investing. Remember, myths are usually based on some degree of fact.

So much of Technical Analysis is based on human reactions that reoccur throughout time in strikingly similar ways. From the early days of the investment markets until the mid-2000’s, investors received information at different rates. Newspapers provided quotes and stories that could spark investor reaction. Institutions had quick access to information through the best available technology. Many, if not most investors had stock and bond brokers with various levels of speed regarding news through the use of ticker tapes early on and later, through rudimentary computers. Brokers could reach only so many of their clients in a day and even then, there was probably some pecking order in which larger clients were called first. This sort of flow of information was at the core of how many, if not most, chart patterns were created and did so with enough reliability to spawn chart analysis as a worthwhile endeavor to pursue.

Before 2000 there was a greater tendency of follow-through after break outs.” – Chart below

A “breakout” is perhaps the most well-known Technical Analysis 101 concept, repeated so often even investors that focus on non-charting methods know what a breakout is. The logic is that when a stock (index, bond, commodity, etc), breaks out of a trading range and to a new short-term or longer-term high, investors naturally have a favorable perspective towards it. Whether true or not, a stock making new highs is commonly perceived to represent a company doing something right, something enough to attract the attention and money of investors. Additionally, breaks to new highs lack the potential selling pressure of those waiting to sell at breakeven levels – a commonly held belief based on logic and past observation. With the psychology of a breakout covered, now the more mechanical side of the picture can be covered. The news flow process detailed earlier comes into play regarding how patterns develop. The initial surge has to start someplace. The strongest argument, at least for the pre-2000ish time frame, is that breakouts from sideways patterns occur out of fundamental or company specific news events. Perhaps that is not always the case but mostly. Buying demand is the fuel that propels stocks higher. Such demand builds as news flows from the better informed to the lesser informed. This used to take days or even weeks. Can you now picture the wave of demand working into a stock, propelling it higher? No wonder people have believed there is nothing more bullish than a stock breaking out to new highs!

Or is there?

For decades and decades, pattern development and analysis relied on how information flowed to those putting in the buy or sell orders. That all changed with the development and public adoption of the internet and also with some regulatory changes. Today, information flow has become lightning fast and available to most all parties. Fast, non-discriminating data and news has had a major impact to chart pattern analysis. Without a governor on the speed of information, investor reaction is so swift that traditional patterns have changed shape or are no longer seen.

Currently buying breakouts and selling break downs or trend line breaks can be disastrous.” – Chart below

Breakout/breakdown and trend line traders that relied on slower-to-the-party investors no longer have the underlying logic to support such methods with the level of reliability seen years ago. With so much more intense buying demand compressed in such a short time frame, investors with the technology available to see the movements may attain profits so quickly that selling demand can now come from those with the quick profits – bought days, minutes, seconds, or micro-seconds earlier. Who are those people with the technology that can allow them to see their stocks move up so quickly?

EVERYBODY! We all have access to this information through our computers, cell phones, and tablets. There is a sense of irony that the very technology allowing investors to trade their own account has played a major impact in increasing the difficulty of analysis.

Most of these concepts can be transferred to other long-standing introductory charting concepts. One is the long-standing assumption that breakdowns below support are warnings of additional negatives to come. Trend line analysis also changed character tremendously since the information flow alteration of the internet. Technical analysis indicators and methodologies are primary components to active portfolio management but relying on breakouts and breakdowns or trend line breaks to be a simple path to success is a Wall Street myth.

Disclosures

S&P 500 TR Index: is a capitalization weighted index of 500 stocks representing all major domestic industry groups and assumes the reinvestment of dividends and capital gains. It is not possible to directly invest in any index.

This writing is for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation regarding any securities transaction, or as an offer to provide advisory or other services by Spectrum Financial, Inc. in any jurisdiction in which such offer, solicitation, purchase or sale would be unlawful under the securities laws of such jurisdiction. The information contained in this writing should not be construed as financial or investment advice on any subject matter. Spectrum Financial, Inc. expressly disclaims all liability in respect to actions taken based on any or all of the information on this writing. For full disclosure please see disclosures page here.

Bond Types and Characteristics part II

By Christopher P. Hendrix, CMT

On August 2, 2016

In Market Research

Several weeks ago, we began to dismantle the argument commonly perpetuated by the media that if the Federal Reserve begins a tightening interest rate cycle, the “bond market” could have headwinds and possibly shift into a bear market. Our comments were not focused on debating the future direction of the bond market but to encourage investors to see the bond market not as a singular entity, but having categories and sub-groups. Each can have enough distinctive characteristics that serve as the foundation of bond rotation concepts and strategies.

Previously, we covered some broad topics, followed by zooming in on one practical aspect in regards to rotation. We will do that again but zoom in on a different key characteristic.

Various bond categories exist and within each, trading characteristics of individual category and sub-group can change based on rating quality and shorter or longer maturity.

Correlation and beta are two statistics deserving a deeper dive. Afterward, we can back away from some of the technical geek-speak and look at practical uses of the concepts. The chart below displays 3-year, monthly-based correlation and beta figures obtained from Bloomberg.

Generally speaking, correlation tells us how often two entities move in the same direction. It does not measure the intensity of the movements, rather, if they move in the same direction. Settings can be adjusted, but comparison of monthly direction is commonly displayed over multiple time frames (3-year, 5-year, 10-year, etc) but only 3-year is displayed above. Correlation is also referred to as R-squared by statisticians and is often labeled as such in financial reports. The numbers are most often reported as decimals but tend to make more sense if converted into percent. For example, in the table above, the Bank Loan correlation to the S&P 500 Index is 0.310, meaning over the last three years, 31% of the months in which the S&P was up, the S&P U.S. Leveraged Loan 100 Index was up too. Correlations are often displayed compared to broad market indexes such as the S&P 500 Index as well as benchmarks more closely related to the specific group being assessed. The table below displays categories within the bond market and on the right side, displays correlations to the Barclays Aggregate Bond Index. That index is a common comparison to bond groups because the “AGG” as it is commonly called, is an index designed to display a mix of all the investment-grade bond classes (below investment grade high yield is excluded).

Correlations to the S&P 500 Index are commonly displayed because most investors are familiar with the index and its “personality” which makes it a useful baseline for assessment. Correlations can change over time but the general tendencies are used by investors as rules-of-thumb. Notice how the various bond categories have correlations to the S&P 500 Index that are quite different from each other. That is an important characteristic. The table below has been sorted to help bring out those differences.
Correlations of the top three (high yield, bank loan, and preferred) may not seem extremely high but are significantly higher than the other bond groups. The primary reason behind higher correlations of the high yield, bank loan, and preferred categories to the S&P 500 Index is because the ability of the underlying payers of the obligation tend to have greater sensitivity to economic conditions. If the economy is growing, bank loans tend to get paid, companies that tap into financing through the high yield market have an easier time to make their debt payments, and companies with preferred stock have less odds of cutting dividend amounts. These growth economy bond classes tend to be more attractive when investors are seeking higher risk in order to potentially gain higher return. These categories, relative to the next group discussed, are commonly referred to as “Risk-On” bond categories.

Government, mortgage backed, investment grade and high yield municipal bonds, and general investment grade corporate bonds have less sensitivity to the economy for various reasons. If the economy is in a recession or contraction phase, the government has taxing authority which reduces risk of missing bond interest payments. Most municipalities also have taxing authority. Mortgage payers may have some stress making payments during tougher economic times but generally speaking, one’s mortgage is a high priority and thus, lower risk to the mortgage holder/investors. Investment grade is a larger category which includes subgroups of each category (investment grade municipals, governments, mortgage backed). Keep in mind the “investment grade” is an opinion from independent rating agencies regarding the ability to pay even under weaker economic conditions. These categories, therefore, as often referred to as “Risk-Off” bond categories.

At the risk of oversimplifying it, beta measures the intensity of the movement by the index (stock, etc) being assessed versus another index. Based on the 3-year period in this case, beta refers to the typical percentage participation of a 1% change in the target index. For example, the S&P U.S. Leveraged Loan 100 Index would typically move higher by 0.16% if the S&P 500 Index were to be up 1.00%. (see chart below)It is important to realize correlations and betas not only evolve over time but can be different in a rising market environment versus a falling market environment. Also, betas can be misleading if the index has been extended to the upside or downside and a mean reversion snap-back takes place. Indexes that have low beta readings can become uncharacteristically volatile well beyond the noted beta metric. The point is not to rely too heavily on correlations and betas in a legalistic manner by assuming strict adherence to the implications of the metrics. Correlations and betas are simply rules-of-thumb when learning about the tendencies of the indexes. The chart below displays the major bond categories for the trailing twelve months.

From July 2015 through January 2016, the “Risk-On” bond categories of the high yield (corporate), leveraged loan, and preferred, each suffered but did so with differing volatilities. The “Risk-Off” categories worked higher and also with differing volatilities. That time period is more representative of common characteristics. Since February of this year, however, “Risk-On “ and “Risk-Off” have both trended higher for various fundamental reasons. We can’t say with certainty but odds favor a return to the rule-of-thumb characteristics of at some point, the “Risk-On” and “Risk-Off” categories with begin to trend in opposite directions but with differing volatilities within the categories.

“Risk-On/Risk-Off” analysis of the bond market can be an efficient way to narrow investment choices.

Investors that lean heavily on economic or fundamental analysis may possibly conclude a growth phase is just around the corner. In that case, further analysis focused on the “Risk-On” categories would be in order. Practitioners of technical analysis could use various forms of relative strength models on the two paths of bond risks in a top-down path within bond rotation. A foundational step to greater understanding of the bond market is to first recognize individual categories have “personalities”. Further separation of characteristics is possible with risk-on/off assessment. As those characteristics become learned, investors should be able to better match specific bond investments to investment objectives within portfolios.

Disclosures

Barclays US High Yield Very Liquid Index: This benchmark includes publicly issued U.S. dollar denominated non-investment grade, fixed-rate taxable corporate bonds that have a remaining maturity of at least one year, regardless of optionality. The bonds are rated high yield (Ba1/BB+/BB+ or below) using the middle rating of Moody’s, S&P, and Fitch, respectively (before July 1, 2005, the lower of Moody’s and S&P was used). Included issues consist of only the three largest bonds from each issuer that has a minimum amount outstanding of $500 million or more (face value) and less than five years from issue date.

S&P/LSTA U.S. Leveraged Loan 100 Index: This benchmark is designed to reflect the performance of the largest facilities in the U.S. dollar leveraged loan market. Term loans from syndicated credits must meet the following criteria at issuance to be eligible for inclusion. 1) senior secured 2) minimum initial term of one year 3) minimum initial spread of LIBOR +125 basis points 4) U.S. dollar denominated 5) all constituents must have a publicly assigned CUSIP

Barclays U.S. AGG: Bond Index: The Barclays U.S. Aggregate Bond Index measures performance of the total U.S. investment grade bond market. It is a market value-weighted index that tracks the daily price, coupon, pay-downs, and total return performance of fixed-rate, publicly placed, dollar-denominated, and non-convertible investment grade debt issues with at least $250 million par amount outstanding and with at least one year to final maturity.

SPMBST: The S&P U.S. Mortgage-Backed Securities Index is a rules-based, market-value-weighted index covering U.S. dollar-denominated, fixed-rate and adjustable-rate/hybrid mortgage pass-through securities issued by Ginnie Mae (GNMA), Fannie Mae (FNMA) and Freddie Mac (FHLMC).

SAPIMAIN: The S&P U.S. Municipal Bond Index is a broad, market value-weighted index that seeks to measure the performance of the U.S. municipal bond market.

SAPIHY: The S&P U.S. Municipal Bond High Yield Index consists of bonds in the S&P Municipal Bond Index that are not rated or are rated below investment grade.

SPTREFTR: The S&P U.S. Preferred Stock Index is designed to measure the performance of the U.S. preferred stock market. Preferred stocks pay dividends at a specified rate and receive preference over common stocks in terms of dividend payments and liquidation of assets.

SPBDUSBT: The S&P U.S. Treasury Bond Index is a broad, comprehensive, market-value weighted index that seeks to measure the performance of the U.S. Treasury Bond market.

Wall Street Myth vs. Market Reality II

Bond Types and Characteristics part II