Everything is Relative: Florida COVID – 19 Trend Update

June 19, 2020 By Mike Shell in Asymmetric Thinking, Critical Thinking, Empirical Observation, Independent Thinking, Quantitative Evidence-Based Rearch, Trend Following

“It doesn’t matter what we think about a trend, it matters what the crowd thinks about it, but more importantly, how they will respond to it.”
– Mike Shell

For a quick update on the Coronavirus COVID – 19 trend, I’ll use my home state of Florida as the example.

The first cases of Coronavirus (COVID-19) were confirmed on March 1st, 2020, which occurred in Manatee and Hillsborough County. During the initial outbreak of Coronavirus in the United States, Florida’s public beaches and theme parks were under scrutiny as being areas of large crowds. Some in the news media criticized Florida for being relatively late in issuing a “Shelter-At-Home” order, finally putting it in place beginning April 3rd, 2020. Cases ramped quickly from 2 on March 4th, to over 5000 by the end of the month. Since then, however, the number of cases in Florida has leveled off, slowing the rate of change.

I focus on the direction of the trend and its rate of change.

The COVID Tracking Project has now tracked 85,826 cumulative Florida Coronavirus cases , up from 82,719 Thursday. This is a change of 3.88%. Here, I show the standard arithmetic scale on the chart.

The concern I see in the above chart is it seems to be forming a rough S-shaped curve. That is, cases trended up though April and May around the same pace, but this month the rate of change is notably stronger in the linear price scale of an arithmetic chart. The arithmetic or linear chart doesn’t illustrate or scale movements in relation to their percent change, but instead, the linear price scale plots price level changes with each unit change according to a constant unit value. So, there is an equal distance between the data points as each unit of a change on the chart is represented by the same movement up the scale, vertical distance, regardless of what the level when the change happened. The arithmetic chart is the standard basic chart, especially over shorter time series, and it shows absolute trends.

To see how the time series unfolds with a focus on percentage of change, we changed the scale to logarithmic. The logarithmic chart is plotted so that two equal percent changes are plotted as the same vertical distance on the scale. Logarithmic scales are better than linear scales for normalizing less severe increases or decreases. Applying a logarithmic scale, the vertical distance between the data on the scale the percent change, so we can better identify changes in rates of change. Here, we see a strong uptrend in March, then the rate of change has since leveled off. The trouble, however, is it is still trending up and at its high.

Florida Coronavirus Tests Administered is at a current level of 1.5 million, which up from 1.486 million the day before, an increase of 1.72%.

COIVD – 19 Deaths have increased 1.4% since Thursday. Deaths are obviously an essential factor to track. Florida Coronavirus Deaths is at a current level of 3,154.00, up from 3,110.00 yesterday.

The steep uptrend in deaths is scary looking using the arithmetic scale showing the absolute trend in cumulative deaths. In the next chart, we observe the same trend as a log scale, which shows the rate of change is in an uptend, but has been slowing. I labeled the highest high (now) and the average over the period for reference.

Florida Coronavirus Hospitalizations is at 12,862, up from 12,673 the prior day, which is a change of 1.49%. To focus on the rate of change, here is the log scale chart.

Keep in mind, my objective here isn’t to rehash the research of others, but instead to share what I see in the trends and rates of change. As such, this isn’t a complete analysis of the virus. It’s my observations, as a quant and trend system developer and operator. The data source is The COVID Tracking Project which can only report the data as provided by the states.

ZOOMING IN TO PER DAY

The per day trends are important if we want to spot a change in trend quickly. As I warned in “In addition to the equity markets entering a higher risk level of a drawdown and volatility expansion, we now have a renewed risk of the scary COVID narrative driving more fear” a week ago, the uptrend got some attention last week. It doesn’t matter what we think about a trend, it matters what the crowd thinks about it, but more importantly, how they will respond to it.

The uptrend in Florida Coronavirus cases per day has indeed continued and with a notable new high.

I don’t like to see an uptrend like this because it’s a virus, and viruses are contagious, so they spread. In the case of Coronavirus, we can get an idea of the speed and rate of spread by the reproductive number (R₀), or ‘R-naught’, represents the number of new infections estimated to stem from a single case. The reproductive number (R₀) is relatively high, according to a research paper on the CDC: Assuming a serial interval of 6–9 days, we calculated a median R₀ value of 5.7 (95% CI 3.8–8.9).

I’m not going into the details here, but, with a reproductive value of 5.7, an increase in new cases is material in my opinion. That is, once it trends up as we are seeing now, it seems more likely to continue.

Are new cases a function of increased testing?

Some say the increase in new cases per day is a result of more testing. That doesn’t seem to be the case. Below is a charge of cases per day with a time series of tests administered per day under it. Visually, we see no correlation. However, there are many caveats to the data. So, anyone who wants to make a cased leaning one way or another can find ways to skew it, but it is what it is. We have a material increase in cases in Florida.

QUANTIATIVE ANALYTICS

Now, we’ll take a deeper dive and apply some analytics to the trends by observing some ratios.

The Florida COVID – 19 Death Rate has been gradually trending down. Florida Coronavirus Death Rate is at 3.67%.

In the past two weeks of May, the death rate was 4.6%, so it is falling.

In our investment management, I’ve been drawing ratio charts for over two decades to determine which market or stocks has greater trend momentum than another. When the numerator (top) is trending stronger than the denominator (bottom value) we say it has stronger relative strength or momentum. In this case, I have used Florida Coronavirus Cases Per Day as the numerator (top value) and Florida Coronavirus Tests Per Day as the denominator (bottom value), which shows a clear uptrend in the cases per day relative to the tests per day. This concerns me because of the rate of spread. As you look at the ratio chart, consider that a value of 0 would mean new cases per day is the same as new tests per day. Instead, new cases is currently trending higher than testing.

Florida cumulative cases relative to tests administered is also showing some change in trend. the past few weeks. Again, not of the date collected is perfect, but it’s still representative of a statistically significant sample of the population.

My objective for trend following is to identify a trend early in its stage to capitalize on it until it changes.

Comparing per day cases to other states doesn’t mean a lot, since the data needs to be normalized. For example, what President Trump said a few weeks ago is a true statement: the number of cases are a function of testing. If we didn’t test and didn’t categorize a case as COVID, there would be no “COVID cases.” Some people, politically motivated, seem to have difficult understanding that simple statement. I’m not politically motivated, so I just say it like it is. With that said, California is winning the match of the most cases per day followed by Texas. Florida is above Arizona.

Again, this doesn’t tell us anything aside from the absolute number. A relative comparison is often necessary and this is an example. For example, we could first calculate per day cases relative to tests or population, then compare them. That’s beyond the scope of my objective today.

Here are the states that reported over 500 new cases. We are seeing some large bubbles in the southwestern United States right now.

The bottom line is, we want to see these levels drifting down, not up. We want to see this trend down.

People who are at high risk should continue to operate according to the risks, but also keep it in perspective that at this point, it isn’t yet so wide spread.

In the big picture, the population in Florida is 22 million and about 86 thousand cases have been labeled COVID 19. 86,0000 out of 22 million is about 4 tenths of a percent, or 0.40%.

That’s 40 cents of $100.

Our changes of contracting COVID 19 in Florida, then, is less than half of 1% at this point.

Everything is relative.

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Mike Shell is the Founder and Chief Investment Officer of Shell Capital Management, LLC, and the portfolio manager of ASYMMETRY® Global Tactical. Mike Shell and Shell Capital Management, LLC is a registered investment advisor focused on asymmetric risk-reward and absolute return strategies and provides investment advice and portfolio management only to clients with a signed and executed investment management agreement. The observations shared on this website are for general information only and should not be construed as advice to buy or sell any security. Securities reflected are not intended to represent any client holdings or any recommendations made by the firm. Any opinions expressed may change as subsequent conditions change. Do not make any investment decisions based on such information as it is subject to change. Investing involves risk, including the potential loss of principal an investor must be willing to bear. Past performance is no guarantee of future results. All information and data are deemed reliable but is not guaranteed and should be independently verified. The presence of this website on the Internet shall in no direct or indirect way raise an implication that Shell Capital Management, LLC is offering to sell or soliciting to sell advisory services to residents of any state in which the firm is not registered as an investment advisor. The views and opinions expressed in ASYMMETRY® Observations are those of the authors and do not necessarily reflect a position of Shell Capital Management, LLC. The use of this website is subject to its terms and conditions.

Systems trading is ultimately discretionary. The manager still has to decide how much risk to accept, which markets to play, and how aggressively to increase and decrease the trading base as a function of equity change. These decisions are quite important – often more important than trade timing.”

August 1, 2016 By Mike Shell in Absolute Return Investment, Empirical Observation, Hiring a Portfolio Manager, Independent Thinking, Investor Behavior Modification, Quantitative Evidence-Based Rearch, Systematic Global Macro Tags: Systematic Trend Following, Systematic vs. Discretionary Leave a comment

–Ed Seykota in Market Wizards: Interviews with Top Traders By Jack D. Schwager

Market Wizards Interviews with Top Traders

Low Volatility Downside was the Same

August 31, 2015 By Mike Shell in Absolute Returns, Alternative Investment, Alternative Trading Strategy, Asymmetric Information, Asymmetric Investment Returns, Asymmetric Thinking, Empirical Observation, ETF Strategist, Global Directional Trends, Managed Volatility, Sector Rotation, Tactical ETF Managed Portfolio, Volatility Trading Leave a comment

In Low Volatility and Managed Volatility Smart Beta is Really Just a Shift in Sector Allocation I ended with:

“Though the widening range of prices up and down gets our attention, it isn’t really volatility that investors want to manage so much as it is the downside loss of capital.“

As a follow-up, below we observe the PowerShares S&P 500^® Low Volatility Portfolio declined in value about -12% from its high just as the SPDRs S&P 500^® did. So, the lower volatility weighting didn’t help this time as the “downside loss of capital ” was the same.

Source: http://www.ycharts.com

Why Index ETFs Over Individual Stocks?

August 8, 2015 By Mike Shell in Absolute Return, Actively Manage Risk, Adapting to Change, Alternative Investment, Asymmetric Observation, Asymmetric Payoff, Asymmetric Risk, Asymmetric Risk Reward, Asymmetric Sector Exposure, Empirical Observation, ETF Strategist, Global Asset Allocation, Global Directional Trends, Managed Momentum, Managed Volatility, Momentum Relative Strength, Sector ETF, Sector Rotation, Sector Trends, Tactical Asset Allocation, Tactical ETF Portfolio Management, Trend Following Leave a comment

A fellow portfolio manager I know was telling me about a sharp price drop in one of his positions that was enough to wipe out the 40% gain he had in the stock. Of course, he had previously told me he had a quick 40% gain in the stock, too. That may have been his signal to sell. Biogen, Inc (BIIB) recently declined about -30% in about three days. Easy come, easy go. Below is a price chart over the past year.

Source: Shell Capital Management, LLC created with http://www.stockcharts.com

Occasionally investors or advisors will ask: “Why trade index ETFs instead of individual stocks?“. An exchange-traded fund (ETF) is an investment fund traded on stock exchanges, much like stocks. Until ETFs came along the past decade or so, gaining exposure to sectors, countries, bond markets, commodities, and currencies wasn’t so easy. It has taken some time for portfolio managers to adapt to using them, but ETFs are easily tradable on an exchange like stocks. Prior to ETFs, those few of us who applied “Sector Rotation” or “Asset Class Rotation” or any kind of tactical shifts between markets did so with much more expensive mutual funds. ETFs have provided us with low cost, transparent, and tax efficient exposure to a very global universe of stocks, bonds, commodities, currencies, and even alternatives like REITs, private equity, MLP’s, volatility, or inverse (short). Prior to ETFs we would have had to get these exposures with futures or options. I saw the potential of ETFs early, so I developed risk management and trend systems that I’ve applied to ETFs that I would have previously applied to futures.

On the one hand, someone who thinks they are a good stock picker are enticed to want to get more granular into a sector and find what they believe is the “best” stock. In some ways, that seems to make sense if we can weed out the bad ones and only hold the good ones. It really isn’t so simple. I view everything a reward/risk ratio, which I call asymmetric payoffs. There is a tradeoff between the reward/risk of getting more detailed and focused in the exposure vs. having at least some diversification, such as exposure to the whole sector instead of just the stock.

Market Risk, Sector Risk, and Stock Risk

In the big picture, we can break exposures into three simple risks (and those risks can be explored with even more detail). We’ll start with the broad risk and get more detailed. Academic theories break down the risk between “market risk” that can’t be diversified away and “single stock” and sector risk that may be diversified away.

Market Risk: In finance and economics, systematic risk (in economics often called aggregate risk or undiversifiable risk) is vulnerable to events which affect aggregate outcomes such as broad market declines, total economy-wide resource holdings, or aggregate income. Market risk is the risk that comes from the whole market itself. For example, when the stock market index falls -10% most stocks have declined more or less.

Stock and Sector Risk: Unsystematic risk, also known as “specific risk,” “diversifiable risk“, is the type of uncertainty that comes with the company or industry itself. Unsystematic risk can be reduced through diversification. If we hold an index of 50 Biotech stocks in an index ETF its potential and magnitude of a large gap down in price is less than an individual stock.

You can probably see how holding a single stock like Biogen has its own individual risks as a single company such as its own earnings reports, results of its drug trials, etc. A biotech stock is especially interesting to use as an example because investing in biotechnology comes with a unique host of risks. In most cases, these companies can live or die based on results of drug trials and the demand for their existing drugs. In fact, the reason Biogen declined so much is they reported disappointing second-quarter results and lowered its guidance for the full year, largely because of lower demand for one of their drugs in the United States and a weaker pricing environment in Europe. That is a risk that is specific to the uncertainty of the company itself. It’s an unsystematic risk and a selection risk that can be reduced through diversification. We don’t have to hold exposure to just one stock.

With index ETFs, we can gain systematic exposure to an industry like biotech or a sector like healthcare or a broader stock market exposure like the S&P 500. The nice thing about an index ETF is we get exposure to a basket of stocks, bond, commodities, or currencies and we know what we’re getting since they disclose their holdings on a daily basis.

ETFs are flexible and easy to trade. We can buy and sell them like stocks, typically through a brokerage account. We can also employ traditional stock trading techniques; including stop orders, limit orders, margin purchases, and short sales using ETFs. They are listed on major US Stock Exchanges.

The iShares Nasdaq Biotechnology ETF objective seeks to track the investment results of an index composed of biotechnology and pharmaceutical equities listed on the NASDAQ. It holds 145 different biotech stocks and is market-cap-weighted, so its exposure is more focused on the larger companies. It therefore has two potential disadvantages: it has less exposure to smaller and possibly faster growing biotech stocks and it only holds those stocks listed on the NASDAQ, so it misses some of the companies that may have moved to the NYSE. According to iShares we can see that Biogen (BIIB) is one of the top 5 holdings in the index ETF.

Source: http://www.ishares.com/us/products/239699/ishares-nasdaq-biotechnology-etf

Below is a price chart of the popular iShares Nasdaq Biotech ETF (IBB: the black line) compared to the individual stock Biogen (BIIB: the blue line). Clearly, the more diversified biotech index has demonstrated a more profitable and smoother trend over the past year. And, notice it didn’t experience the recent -30% drop that wiped out Biogen’s price gain. Though some portfolio managers may perceive we can earn more return with individual stocks, clearly that isn’t always the case. Sometimes getting more granular in exposures can instead lead to worse and more volatile outcomes.

Source: Shell Capital Management, LLC created with http://www.stockcharts.com

The nice thing about index ETFs is we have a wide range of them from which to research and choose to add to our investable universe. For example, when I observe the directional price trend in biotech is strong, I can then look at all of the other biotech index ETFs to determine which would give me the exposure I want to participate in the trend.

Since we’ve observed with Biogen the magnitude of the potential individual risk of a single biotech stock, that also suggests we may not even prefer to have too much overweight in any one stock within an index. Below I have added to the previous chart the SPDR^® S&P^® Biotech ETF (XBI: the black line) which has about 105 holdings, but the positions are equally-weighted which tilts it toward the smaller companies, not just larger companies. As you can see by the black line below, over the past year, that equal weighting tilt has resulted in even better relative strength. However, it also had a wider range (volatility) at some points. Though it doesn’t always work out this way, you are probably beginning to see how different exposures create unique return streams and risk/reward profiles.

Source: Shell Capital Management, LLC created with http://www.stockcharts.com

In fact, those who have favored “stock picking” may be fascinated to see the equal-weighted SPDR^® S&P^® Biotech ETF (XBI: the black line) has actually performed as good as the best stock of the top 5 largest biotech stocks in the iShares Nasdaq Biotech ETF.

Source: Shell Capital Management, LLC created with http://www.stockcharts.com

Biotech indexes aren’t just pure biotech industry exposure. They also have exposures to the healthcare sector. For example, iShares Nasdaq Biotech shows about 80% in biotechnology and 20% in sectors categorized in other healthcare industries.

Source: www.ishares.com

The brings me to another point I want to make. The broader healthcare sector also includes some biotech. For example, the iShares U.S. Healthcare ETF is one of the most traded and includes 23.22% in biotech.

Source: https://www.ishares.com/us/products/239511/IYH?referrer=tickerSearch

It’s always easy to draw charts and look at price trends retroactively in hindsight. If we only knew in advance how trends would play out in the future we could just hold only the very best. In the real world, we can only identify trends based on probability and by definition, that is never a sure thing. Only a very few of us really know what that means and have real experience and a good track record of actually doing it.

I have my own ways I aim to identify potentially profitable directional trends and my methods necessarily needs to have some level of predictive ability or I wouldn’t bother. However, in real world portfolio management, it’s the exit and risk control, not the entry, the ultimately determines the outcome. Since I focus on the exposure to risk at the individual position level and across the portfolio, it doesn’t matter so much to me how I get the exposure. But, by applying my methods to more diversified index ETFs across global markets instead of just U.S. stocks I have fewer individual downside surprises. I believe I take asset management to a new level by dynamically adapting to evolving markets. For example, they say individual selection risk can be diversified away by holding a group of holdings so I can efficiently achieve that through one ETF. However, that still leaves the sector risk of the ETF, so it requires risk management of that ETF position. They say systematic market risk can’t be diversified away, so most investors risk that is left is market risk. I manage both market risk and position risk through my risk control systems and exits. For me, risk tolerance is enforced through my exits and risk control systems.

The performance quoted represents past performance and does not guarantee future results. Investment return and principal value of an investment will fluctuate so that an investor’s shares, when sold or redeemed, may be worth more or less than the original cost. Current performance may be lower or higher than the performance quoted, and numbers may reflect small variances due to rounding. Standardized performance and performance data current to the most recent month end may be obtained by clicking the “Returns” tab above.

What You Need to Know About Long Term Bond Trends

June 6, 2015 By Mike Shell in Absolute Return, Absolute Returns, Actively Manage Risk, Adapting to Change, Alternative Investment, Asymmetric Risk Reward, Average Length of Bull Bear Market, Business Cycle, Counter trend, Empirical Observation, ETF Strategist, Global Asset Allocation, Global Directional Trends, Global Macro, Global Tactical Rotation, Hiring a Portfolio Manager, Mean Reversion, Momentum Relative Strength, Quantitative Evidence-Based Rearch, Risk Asymmetry, Sector Trends, Tactical ETF Managed Portfolio, The Fed (FOMC) Leave a comment

There is a lot of talk about interest rates and bonds these days – for good reason. You see, interest rates have been in a downtrend for decades (as you’ll see later). When interest rates are falling, the price of bonds go up. I wrote in “Why So Stock Market Focused?” that you would have actually been better off investing in bonds the past 15 years over the S&P 500 stock index.

However, the risk for bond investors who have a fixed bond allocation is that interest rates eventually trend up for a long time and their bonds fall.

This year we see the impact of rising rates and the impact of falling bond prices in the chart below of the 20+ year Treasury bond. It’s down -15% off its high and since the yield is only around 2.5% the interest only adds about 1% over this period for a total return of -14.1%. Up until now, this long term Treasury index has been a good crutch for a global allocation portfolio. Now it’s more like a broken leg.

But, that’s not my main point today. Let’s look at the bigger picture. Below is the yield (interest rate) on the 10-Year U.S. government bond. Notice that the interest rate was as high as 9.5% in 1990 and has declined to as low as 1.5%. Just recently, it’s risen to 2.62%. If you were going to buy a bond for future interest income payments, would you rather invest in one at 9.5% or 1.5%? If you were going to lend money to someone, which rate would you prefer to receive? What is a “good deal” for you, the lender?

I like trends and being positioned in their direction since trends are more likely to continue than reverse, but they usually do eventually reverse when inertia comes along (like the Fed). If you care about managing downside risk you have to wonder: How much could this trend reverse and what could its impact be on fixed bond holdings? Well, we see below that the yield has declined about -70%. If we want to manage risk, we have to at least expect it could swing the other way.

One more observation. Germany is one of the largest countries in the world. Since April, the 10-year German bond interest rate has reversed up very sharp. What if U.S bonds did the same?

As I detailed in “Allocation to Stocks and Bonds is Unlikely to Give us What We Want” bonds are often considered a crutch for a global asset allocation portfolio. If you care about managing risk, you may consider that negative correlations don’t last forever. All trends change, eventually. You may also consider your risk of any fixed positions you have. I prefer to actively manage risk and shift between global markets based on their directional trends rather than a fixed allocation to them.

The good news is: by my measures, many bond markets have declined in the short term to a point they should at least reserve back up at least temporarily. What happens after that will determine if the longer trend continues or begins to reverse. The point is to avoid complacency and know in advance at what point you’ll exit to cut losses short…

As they say: “Past performance is no guarantee of the future“.

Asymmetric Nature of Losses and Loss Aversion

April 8, 2015 By Mike Shell in Absolute Return, Absolute Return Fund, Absolute Return Investing, Absolute Return Investment, Absolute Return Objective, Absolute Return Strategy, Absolute Returns, Absolute vs. Relative Return, Actively Manage Risk, Adapting to Change, Alternative Investment Strategy, Alternative Trading Strategy, Asymmetric Hedging, Asymmetric Investment Returns, Asymmetric Observation, Asymmetric Payoff, Asymmetric Risk, Asymmetric Risk Reward, Asymmetric Thinking, Critical Thinking, Dynamic Hedging, Empirical Observation, ETF Strategist, Global Directional Trends, Global Macro, Hedge Funds, Hiring a Portfolio Manager, Independent Thinking, Investor Behavior Modification, Investor Sentiment, Liquid Alternative, Managed Volatility, Positive Asymmetry, Quantitative Evidence-Based Rearch, Risk Asymmetry, Symmetry Tags: Loss Aversion, Prospect Theory 3 Comments

Loss Aversion:

“In prospect theory, loss aversion refers to the tendency for people to strongly prefer avoiding losses than acquiring gains. Some studies suggest that losses are as much as twice as psychologically powerful as gains. Loss aversion was first convincingly demonstrated by Amos Tversky and Daniel Kahneman.”

For most people, losing $100 is not the same as not winning $100. From a rational point of view are the two things the same or different?

Most economists say the two are the same. They are symmetrical. But I think that ignores some key issues.

If we have only $10 to eat on today and that’s all we have, if we lose it, we’ll be in trouble: hungry.

But if we have $10 to eat on and flip a coin in a bet and double it to $20, we may just eat a little better. We’ll still eat. The base rate: survival.

They say rationally the two are the same, but that isn’t true. They aren’t the same. The loss makes us worse off than we started and it may be totally rational to feel worse when we go backward than we feel good about getting better off. I don’t like to go backward, I prefer to move forward to stay the same.

Prospect Theory, which found people experience a loss more than 2 X greater than an equal gain, discovered the experience of losses are asymmetric.

Actually, the math agrees.

You see, losing 50% requires a 100% gain to get it back. Losing it all is even worse. Losses are indeed asymmetric and exponential on the downside so it may be completely rational and logical to feel the pain of losses asymmetrically. Experience the feeling of loss aversions seems to be the reason a few of us manage investment risk and generate a smoother return stream rather than blow up.

To see what the actual application of asymmetry to portfolio management looks like, see: Shell Capital Management, LLC.

Asymmetric Sector Exposure in Stock Indexes

March 24, 2015 By Mike Shell in Absolute Return, Asymmetric Observation, Asymmetric Payoff, Asymmetric Risk, Asymmetric Risk Reward, Asymmetric Sector Exposure, Asymmetric Thinking, Data Driven Rearch, Empirical Observation, ETF Strategist, Global Directional Trends, Independent Thinking, Quantitative Evidence-Based Rearch, Risk Asymmetry, Sector ETF, Sector Rotation, Sector Trends, Tactical ETF Portfolio Management Leave a comment

When you look at the table below and see the sector exposure percents, what do you observe? Do these allocations make sense?

That is the sector exposure of the S&P 500 stock index: I used the iShares S&P 500 ETF for a real-world proxy. The source of each image is the index website on iShares, which you can see by clicking on the name of the index ETF.

Asymmetric is an imbalance. That is, more of one thing, less of another.
A sector is a specific industry, like Energy (Exxon Mobil) or Telecom (Verizon).
Exposure is the amount of the position size or allocation.

Most of the sector exposure in the S&P 500 large company stock index is Technology, Financials, Healthcare, and Consumer Discretionary. Consumer Staples, Energy, Materials, Utilities, and Telecommunications have less than 10% exposure each. Exposure to Materials, Utilities, and Telecommunications are almost non-existent. Combined, those three sectors are less than 10% of the index. Industrial has 10% exposure by itself. But this index is 500 large companies, what about mid size and small companies?

Below is the iShares Core S&P Mid-Cap ETF. Most of the sector exposure in the S&P Mid size stock index is Technology, Financials, Industrial. Healthcare, and Consumer Discretionary. Consumer Staples, Energy, Materials, Utilities, and Telecommunications have less than 10% exposure each. Exposure to Materials, Utilities, and Telecommunications are almost non-existent.

We see this same asymmetric sector exposure theme repeat in the iShares S&P Small Cap index. Half of the sectors are make up most of the exposure, the other very little.

This is just another asymmetric observation… the next time you hear someone speak of the return of a stock index, consider they are really speaking about the return profile of certain sectors. And, these sector weightings may change over time.

Trends, Countertrends, in the U.S. Dollar, Gold, Currencies

March 19, 2015 By Mike Shell in Actively Manage Risk, Adapting to Change, Alternative Investment Strategy, Asymmetric Observation, Asymmetric Risk, Asymmetric Risk Reward, Counter trend, Data Driven Rearch, Empirical Observation, ETF Strategist, Fed Decision, Global Directional Trends, Global Macro, Market efficiency, Momentum Relative Strength, Quantitative Evidence-Based Rearch, Sector Trends, Tactical ETF Portfolio Management, The Fed (FOMC), Theory Driven Rearch, Trend Following Tags: Euro, Fed, Gold, Swiss Franc, U.S. Dollar Leave a comment

Trend is a direction that something is moving, developing, evolving, or changing. A trend is a directional drift, one way or another. When I speak of price trends, the directional drift of a price trend can be up, down, or sideways.

Trends trend to continue and are even more likely to continue than to reverse, because of inertia. Inertia is the resistance to change, including a resistance to change in direction. It’s an important physics concept to understand to understand price trends because inertia relates to momentum and velocity. A directional price trend that continues, or doesn’t change or reverse, has inertia. To understand directional price trends, we necessarily need to understand how a trend in motion is affected by external forces. For example, if a price trend is up and continues even with negative external news, in inertia or momentum is even more significant. Inertia is the amount of resistance to change in velocity. We can say that a directional price trend will continue moving at its current velocity until some force causes its speed or direction to change. A directional trend follower, then, wants keep exposure to that trend until its speed or direction does change. When a change happens, we call it a countertrend. A countertrend is a move against the prior or prevailing trend. A countertrend strategy tries to profit from a trend reversal in a directional trend that has moved to such a magnitude it comes more likely to reverse, at least briefly, than to continent. Even the best long-term trends have smaller reversals along the way, so countertrend systems try to profit from the shorter time frame oscillations.

“The one fact pertaining to all conditions is that they will change.”

—Charles Dow, 1900

One significant global macro trend I noticed that did show some “change” yesterday is the U.S. Dollar. The U.S. Dollar has been in a smooth drift up for nearly a year. I use the PowerShares DB US Dollar Index Bullish (UUP). Below, I start with a weekly chart showing a few years so you can see it was non-trending up until last summer. Clearly, the U.S. Dollar has been trending strongly since.

Next, we zoom in for a closer look. The the PowerShares DB US Dollar Index Bullish (UUP) was down about -2% yesterday after the Fed Decision. Notice that I included a 50 day moving average, just to smooth out the price data to help illustrate its path. One day isn’t nearly enough to change a trend, but that one day red bar is greater in magnitude and had heavy volume. On the one hand, it could be the emotional reaction to non trend following traders. On the other, we’ll see over time if that markets a real change that becomes a reversal of this fine trend. The U.S. Dollar may move right back up and resume it’s trend…

chart source for the following charts: http://www.stockcharts.com

I am using actual ETFs only to illustrate their trends. One unique note about PowerShares DB US Dollar Index Bullish Fund (Symbol: UUP) is the tax implications for currency limited partnership ETFs are subject to a 60 percent/40 percent blend, regardless of how long the shares are held. They also report on a K-1 instead of a 1099.

Why does the direction of the U.S. Dollar matter? It drives other markets. Understanding how global markets interact is an edge in global tactical trading. Below is a chart of Gold. I used the SPDR Gold Trust ETF as a proxy. Gold tends to trade the opposite of the U.S. Dollar.

When the U.S. Dollar is trending up, it also has an inverse correlation to foreign currencies priced in dollars. Below is the CurrencyShares Euro ETF.

Foreign currencies can have some risk. In January, the Swiss Franc gaped up sharply, but has since drifted back to where it was. Maybe that was an over-reaction? Markets aren’t so efficient. Below is a chart of the CurrencyShares Swiss Franc to illustrate its trend and countertrend moves.

None of this is a suggestion to buy or sell any of these, just an observation about directional trends, how they interact with each other, and countertrend moves (whether short term or long term). Clearly, there are trends…

To see how tactical decisions and understand how markets interacts results in my real performance, visit : ASYMMETRY^® Managed Accounts

Fed Decision and Market Reaction: Stocks and Bonds

March 18, 2015 By Mike Shell in Actively Manage Risk, Adapting to Change, Asymmetric Observation, Counter trend, Crowd Psychology, Empirical Observation, Fed Decision, Global Directional Trends, Global Macro, Independent Thinking, Investor Behavior Modification, Investor Sentiment, Quantitative Evidence-Based Rearch, Sector Rotation, Systematic Global Macro, Tactical ETF Portfolio Management, The Fed (FOMC) Leave a comment

So, I’m guessing most people would expect if the Fed signaled they are closer to a rate hike the stock and bond markets would fall. Rising interest rates typically drive down stocks along with bonds. Not the case as of 3pm today. Stocks were down about -1% prior to the announcement, reversed, and are now positive 1%. Even bonds are positive. Even the iShares Barclays 20+ Yr Treas.Bond (ETF) is up 1.4% today.

So much for expectations…

Below is snapshot of the headlines and stock price charts from Google Finance:

Source: https://www.google.com/finance?authuser=2

Diversification Alone is No Longer Sufficient to Temper Risk…

March 9, 2015 By Mike Shell in Absolute Returns, Actively Manage Risk, Adapting to Change, Alternative Investment, Alternative Trading Strategy, Asymmetric Hedging, Asymmetric Investment Returns, Asymmetric Observation, Asymmetric Payoff, Asymmetric Risk, Asymmetric Risk Reward, Asymmetric Thinking, Business Cycle, Critical Thinking, Empirical Observation, ETF Strategist, Global Asset Allocation, Global Directional Trends, Global Macro, Global Tactical Rotation, Hiring a Portfolio Manager, Independent Thinking, Investor Behavior Modification, Liquid Alternative, Managed Momentum, Managed Volatility, Momentum Relative Strength, Quantitative Evidence-Based Rearch, Risk Asymmetry, Sector ETF, Sector Rotation, Systematic Global Macro, Tactical Asset Allocation, Tactical ETF Managed Portfolio, Tactical ETF Portfolio Management, Trend Following Leave a comment

That was the lesson you learned the last time stocks became overvalued and the stock market entered into a bear market.

In a Kiplinger article by Fred W. Frailey interviewed Mohamed El-Erian, the PIMCO’s boss, (PIMCO is one of the largest mutual fund companies in the world) he says “he tells how to reduce risk and reap rewards in a fast-changing world.” This article “Shaking up the Investment Mix” was written in March 2009, which turned out the be “the low” of the global market collapse.

It is useful to revisit such writing and thoughts, especially since the U.S. stock market has since been overall rising for 5 years and 10 months. It’s one of the longest uptrends recorded and the S&P 500 stock index is well in “overvalued” territory at 27 times EPS. At the same time, bonds have also been rising in value, which could change quickly when rates eventually rise. At this stage of a trend, asset allocation investors could need a reminder. I can’t think of a better one that this:

Why are you telling investors they need to diversify differently these days?

The traditional approach to diversification, which served us very well, went like this: Adopt a diversified portfolio, be disciplined about rebalancing the asset mix, own very well-defined types of asset classes and favor the home team because the minute you invest outside the U.S., you take on additional risk. A typical mix would then be 60% stocks and 40% bonds, and most of the stocks would be part of Standard & Poor’s 500-stock index.

This approach is fatigued for several reasons. First of all, diversification alone is no longer sufficient to temper risk. In the past year, we saw virtually every asset class hammered. You need something more to manage risk well.

But, you know, they say a picture is worth a thousand words.

Since we are talking about downside risk, something that is commonly hidden when only “average returns” are presented, below is a drawdown chart. I created the drawdown chart using YCharts which uses total return data and the “% off high”. The decline you see from late 2007 to 2010 is a dradown: it’s when the investment value is under water. Think of this like a lake. You can see how the average of the data wouldn’t properly inform you of what happens in between.

First, I show PIMCO’s own allocation fund: PALCX: Allianz Global Allocation Fund. I include an actively managed asset allocation that is very large and popular with $55 billion invested in it: MALOX: BlackRock Global Allocation. Since there are many who instead believe in passive indexing and allocation, I have also included DGSIX: DFA Global Allocation 60/40 and VBINX: Vanguard Balanced Fund. As you can see, they have all done about the same thing. They declined about -30% to -40% from October 2007 to March 2009. They also declined up to -15% in 2011.

Charts are courtesy of http://ycharts.com/ drawn by Mike Shell

Going forward, the next bear market may be very different. Historically, investors consider bond holdings to be a buffer or an anchor to a portfolio. When stock prices fall, bonds haven’t been falling nearly as much. To be sure, I show below a “drawdown chart” for the famous actively managed bond fund PIMCO Total Return and for the passive crowd I have included the Vanguard Total Bond Market fund. Keep in mind, about 40% of the allocation of the funds above are invested in bonds. As you see, bonds dropped about -5% to -7% in the past 10 years.

Charts are courtesy of http://ycharts.com/ drawn by Mike Shell

You may have noticed the end of the chart is a drop of nearly -2%. Based on the past 10 years, that’s just a minor decline. The trouble going forward is that interest rates have been in an overall downtrend for 30 years, so bond values have been rising. If you rely on bonds being a crutch, as on diversification alone, I agree with Mohamed El-Erian the Chief of the worlds largest bond manager:

“…diversification alone is no longer sufficient to temper risk. In the past year, we saw virtually every asset class hammered. You need something more to manage risk well.”

But, don’t wait until AFTER markets have fallen to believe it.

Instead, I apply active risk management and directional trend systems to a global universe of exchange traded securities (like ETFs). To see what that looks like, click: ASYMMETRY^® Managed Accounts

Sectors Showing Some Divergence…

March 4, 2015 By Mike Shell in Actively Manage Risk, Adapting to Change, Alternative Investment Strategy, Asymmetric Investment Returns, Asymmetric Payoff, Asymmetric Risk, Asymmetric Risk Reward, Asymmetric Thinking, Empirical Observation, ETF Strategist, Global Asset Allocation, Global Directional Trends, Global Macro, Global Tactical Rotation, Liquid Alternative, Managed Momentum, Managed Volatility, Momentum Relative Strength, Sector ETF, Sector Rotation, Sector Trends, Systematic Global Macro, Tactical Asset Allocation, Tactical ETF Managed Portfolio, Trend Following Leave a comment

So far, U.S. sector directional price trends are showing some divergence in 2015.

Rather than all things rising, such divergence may give hints to new return drivers unfolding as well as opportunity for directional trend systems to create some asymmetry by avoiding the trends I don’t want and get exposure to those I do.

For more information about ASYMMETRY^®, visit: http://www.asymmetrymanagedaccounts.com/global-tactical/

Chart source: http://www.finviz.com/groups.ashx

This is When MPT and VaR Get Asset Allocation and Risk Measurement Wrong

January 27, 2015 By Mike Shell in Absolute Returns, Actively Manage Risk, Adapting to Change, Alternative Investment, Alternative Trading Strategy, Asymmetric Investment Returns, Asymmetric Observation, Asymmetric Risk, Asymmetric Risk Reward, Asymmetric Thinking, Critical Thinking, Data Driven Rearch, Empirical Observation, ETF Strategist, Global Directional Trends, Global Macro, Global Tactical Rotation, Hiring a Portfolio Manager, Independent Thinking, Investor Behavior Modification, Investor Sentiment, Managed Momentum, Managed Volatility, Market efficiency, Mean Reversion, Quantitative Evidence-Based Rearch, Risk Asymmetry, Symmetry, Tactical ETF Portfolio Management, Trend Following Tags: Modern Portfolio Theory (MPT), Value at Risk (Var) Leave a comment

I was talking to an investment analyst at an investment advisory firm about my ASYMMETRY® Global Tactical and he asked me what the standard deviation was for the portfolio. I thought I would share with you how the industry gets “asset allocation” and risk measurement and management wrong.

Most people have poor results over a full market cycle that includes both rising and falling price trends, like global bull and bear markets, recessions, and expansions. Quantitative Analysis of Investor Behavior, SPIVA, Morningstar and many academic papers have provided empirical evidence that most investors (including professionals) have poor results over the long periods. For example, they may earn gains in rising conditions but lose their gains when prices decline. I believe one reason is they get too aggressive at peaks and then sell in panic after losses get too large, rather than properly predefine and manage risk.

You may consider, then, to have good results over a long period, I necessarily have to believe and do things very differently than most people.

On the “risk measurement” topic, I will share with you a very important concept that is absolutely essential for truly actively controlling loss. The worst drawdown “is” the only risk metric that really matters. The risk is not the loss itself. Once we have a loss, it’s a loss. It’s beyond the realm of risk. Since risk is the possibility of a loss, how often it has happened in the past and the magnitude of the historical loss is the expectation. Beyond that, we must assume it could be even worse some day. For example, if the S&P 500 stock index price decline was -56% from 2007 to 2009, then we should expect -56% is the loss potential (or worse). When something has happened before, it suggests it is possible again, and we may have not yet observed the worst decline in the past that we will see in the future.

The use of standard deviation is one of the very serious flaws of investors attempting to measure, direct, and control risk. The problem with standard deviation is that the equation was intentionally created to simplify data. The way it is used draws a straight line through a group of data points, which necessarily ignores how far the data actually spreads out. That is, the standard deviation is intended to measure how far the data spreads out, but it actually fails to absolutely highlight the true high point and low point. Instead, it’s more of an average of those points. However, for risk management, it’s the worst-case loss that we really need to focus on. I believe in order to direct and control risk, I must focus on “how bad can it really get”. Not just “on average” how bad it can get. The risk in any investment position is at least how much it has declined in the past. And realizing it could be even worse some day. Standard deviation fails to reflect that in the way it is used.

Consider that as prices trend up for years, investors become more and more complacent. As investors become complacent, they also become less indecisive as they believe the recent past upward trend will continue, making them feel more confident. On the other hand, when investors feel unsure about the future, their fear and indecisiveness is reflected as volatility as the price swings up and down more. We are always unsure about the future, but investors feel more confident the past will continue after trends have been rising and volatility gets lower and lower. That is what the peak of a market looks like. As it turns out, that’s just when asset allocation models like Modern Portfolio Theory (MPT) and portfolio risk measures like Value at Risk (VaR) tell them to invest more in that market – right as it reaches its peak. They invest more, complacently, because their allocation model and risk measures tell them to. An example of a period like this was October 2007 as global stock markets had been rising since 2003. At that peak, the standard deviation was low and the historical return was at its highest point, so their expected return was high and their expected risk (improperly measured as historical volatility) was low. Volatility reverses the other way at some point

What happens next is that the market eventually peaks and then begins to decline. At the lowest point of the decline, like March 2009, the global stock markets had declined over -50%. My expertise is directional price trends and volatility so I can tell you from empirical observation that prices drift up slowly, but crash down quickly. The below chart of the S&P 500 is an example of this asymmetric risk.

At the lowest point after prices had fallen over -50%, in March 2009, the standard deviation was dramatically higher than it was in 2007 after prices had been drifting up. At the lowest point, volatility is very high and past return is very low, telling MPT and VaR to invest less in that asset. This is a form of volatility targeting: investing more at lower levels or historical volatility and less at higher levels.

In the 2007 – 2009 decline in global markets, you may recall some advisors calling it a “6 sigma event”. That’s because the market index losses were much larger than predicted by a standard deviation. For example, if an advisors growth allocation had an average return of 10% in 2007 based on its past returns looking back from the peak and a standard deviation of 12% expected volatility, they only expected the portfolio would decline -26% (3 standard deviations) within a 99.7% confidence level – but the allocation actually lost -40 or -50%. Even if that advisor properly informed his or her client the allocation could decline -26% worse case and the client provided informed consent and acceptance of that risk, their loss was likely much greater than their risk tolerance. When they reach their risk tolerance, they “tap out”. Once they tap out, when do they ever get back in? do they feel better after it falls another -20%? or after it rises 20%? There is no good answer. I want to avoid that situation. I prefer to reduce my exposure to loss in well advance.

You can see in the chart below, 3 standard deviations is supposed to capture 99.7% of all of the data if the data is a normal distribution. The trouble is, market returns are not a normal distribution. Instead, stock market gains and losses present an asymmetrical return distribution. Market returns experience much larger gains and losses than expected from a normal distribution – the outliers are critical. However, those outliers don’t occur very often: historically it’s maybe every 4 or 5 years, so people have time to forget about the last one and become complacent.

Source: http://en.wikipedia.org/wiki/68%E2%80%9395%E2%80%9399.7_rule

My friends, this is where traditional asset allocation like Modern Portfolio Theory (MPT) and risk measures like Value at Risk (VaR) get it wrong.

These methods are the most widely believed and used . You can probably see why most investors do poorly and only a very few do well – an anomaly.

I can tell you that I measure risk by how much I can lose and I control my risk by predefining my absolute risk at the point of entry and my exit point evolves as the positions are held. That is an absolute price point, not some equation that intentionally ignores the outlier losses.

As the stock indexes have now been overall trending up for 5 years and 9 months, the trend is getting aged. In fact, according to my friend Ed Easterling at Crestmont Research, at around 27 times EPS the stock index seems to be in the range of overvalued. In his latest report, he says:

“The stock market surged over the past quarter, adding to gains during 2014 that far exceed underlying economic growth. As a result, normalized P/E increased to 27.2—well above the levels justified by low inflation and interest rates. The current status is approaching “significantly overvalued.”

At the same time, we shouldn’t be surprised to eventually see rising interest rates drive down bond values at some point. It seems from this starting point that simply allocating to stocks and bonds doesn’t have an attractive expected return.

I believe a different strategy is needed, especially form this point forward.

In ASYMMETRY® Global Tactical, I actively manage risk and shift between markets to find profitable directional price trends rather than just allocate to them.

Mike Shell is the Founder and Chief Investment Officer of Shell Capital Management, LLC, and the portfolio manager of ASYMMETRY® Global Tactical.

The observations shared on this website are for general information only and are not specific advice, research, or buy or sell recommendations for any individual. Investing involves risk including the potential loss of principal an investor must be willing to bear. Past performance is no guarantee of future results. The presence of this website on the Internet shall in no direct or indirect way raise an implication that Shell Capital Management, LLC is offering to sell or soliciting to sell advisory services to residents of any state in which the firm is not registered as an investment advisor. Use of this website is subject to its terms and conditions.

“There is always a disposition in people’s minds to think that existing conditions will be permanent …

January 12, 2015 By Mike Shell in Actively Manage Risk, Adapting to Change, Asymmetric Hedging, Asymmetric Risk, Asymmetric Risk Reward, Business Cycle, Counter trend, Crowd Psychology, Dynamic Hedging, Empirical Observation, Global Directional Trends, Global Macro, Investor Sentiment, Mean Reversion, Momentum Relative Strength, Risk Asymmetry, Tactical Asset Allocation, Trend Following Leave a comment

“There is always a disposition in people’s minds to think the existing conditions will be permanent,” Dow wrote, and went on to say: “When the market is down and dull, it is hard to make people believe that this is the prelude to a period of activity and advance. When the prices are up and the country is prosperous, it is always said that while preceding booms have not lasted, there are circumstances connected with this one, which make it unlike its predecessors and give assurance of permanency. The fact pertaining to all conditions is that they will change.” – Charles Dow, 1900

Source: Lo, Andrew W.; Hasanhodzic, Jasmina (2010-08-26). The Evolution of Technical Analysis: Financial Prediction from Babylonian Tablets to Bloomberg Terminals (Kindle Locations 1419-1423). Wiley. Kindle Edition.

You can probably see from Dow’s quote how trends do tend to continue, just because enough people think they will. However, price trends can continue into an extreme or a “bubble” just because people think they will continue forever. I like to ride a trend to the end when it bends and then be prepared to exit when it does finally reverse, or maybe reduce or hedge off some risk when the probability seems high of a change.

Image source: Wikipedia

Charles Henry Dow; November 6, 1851 – December 4, 1902) was an American journalist who co-founded Dow Jones & Company. Dow also founded The Wall Street Journal, which has become one of the most respected financial publications in the world. He also invented the Dow Jones Industrial Average as part of his research into market movements. He developed a series of principles for understanding and analyzing market behavior which later became known as Dow theory, the groundwork for technical analysis.

The Mistake is Not Taking the Loss: Cut Your Losses and Move on

November 15, 2014 By Mike Shell in Actively Manage Risk, Adapting to Change, Asymmetric Risk, Book Review, Empirical Observation, Great Quotes, Hiring a Portfolio Manager, Investor Behavior Modification, Position Sizing, Risk Asymmetry, Tactical Asset Allocation, Trend Following Leave a comment

One of the keys to managing investment risk is cutting losers before they become large losses. Many people have difficulty selling at a loss because they believe it’s admitting a mistake. The mistake isn’t taking a loss, the mistake is to NOT take the loss. I cut losses short all the time, that’s why I don’t have large ones. I’ve never taken a loss that was a mistake. I predetermine my risk by determining before I even buy something at what point I’ll get out if I am wrong. If I enter at $50, my methods may determine if it falls to $45 that trend I wanted to get in is no longer in place and I should get out. So when I enter a position in any market, I know how I’ll cut my loss short before I even get in. It’s the exit, not the entry, that determines the outcome. I don’t know in advance which will be a winner or loser or how much it will gain or lose. For me, not taking the loss, would be the mistake.

I thought of this when a self-proclaimed old-timer admitted to me he still holds some of the popular stocks he bought the late 90’s. Many of those stocks are no longer in business, but below we revisit the price trend and total return of some of the largest and most popular stocks promoted in the late 90’s. The black line is Cisco Systems (CSC), Blue is AT&T (T), Red is Pfizer (PFE), and green is Microsoft (MSFT). AT&T’s roots stretch back to 1875, with founder Alexander Graham Bell’s invention of the telephone. Pfizer started in 1849 “With $2,500 borrowed from Charles Pfizer’s father, cousins Charles Pfizer and Charles Erhart, young entrepreneurs from Germany, opened Charles Pfizer & Company as a fine-chemicals business”. At one point during the late 90’s “tech bubble” Microsoft and Cisco Systems were valued more than many countries. But the chart below shows if you did buy and held these stocks nearly 20 years later you would have held losses for many years and many of them are just now showing a profit.

chart courtesy of http://www.stockcharts.com

The lesson to cut losses short rather than allow them to become large losses came from a book published in 1923.

“Money does not give a trader more comfort, because, rich or poor, he can make mistakes and it is never comfortable to be wrong. And when a millionaire is right his money is merely one of his several servants. Losing money is the least of my troubles. A loss never bothers me after I take it. I forget it overnight. But being wrong – not taking the loss – that is what does the damage to the pocketbook and to the soul.”

-Reminiscences of a Stock Operator (1923)

If you are unfamiliar with the classic, according to Amazon:

Reminiscences of a Stock Operator is a fictionalized account of the life of the securities trader Jesse Livermore. Despite the book’s age, it continues to offer insights into the art of trading and speculation. In Jack Schwagers Market Wizards, Reminiscences was quoted as a major source of stock trading learning material for experienced and new traders by many of the traders who Schwager interviewed. The book tells the story of Livermore’s progression from day trading in the then so-called “New England bucket shops,” to market speculator, market maker, and market manipulator, and finally to Wall Street where he made and lost his fortune several times over. Along the way, Livermore learns many lessons, which he happily shares with the reader.

Small vs. Large Stocks: A Tale of Two Markets (Continued)

November 13, 2014 By Mike Shell in Adapting to Change, Asymmetric Observation, Counter trend, Critical Thinking, Data Driven Rearch, Empirical Observation, Global Directional Trends, Global Tactical Rotation, Hiring a Portfolio Manager, Managed Momentum, Momentum Relative Strength, Tactical Asset Allocation, Tactical ETF Managed Portfolio, Trend Following Leave a comment

A quick follow up to my recent comments about the down trend in smaller company stocks in Playing with Relative Strength and Stock Market Peak? A Tale of Two Markets below is a chart and a few observations:

Source: Bloomberg/KCG

A few observations of the trend direction, momentum, and relative strength.

The S&P 500 index (the orange line) of large company stocks has been in a rising trend of higher highs and higher lows (though that will not continue forever).
The white line is the Russell 2000 small company index has been in a downtrend of lower highs and lower lows, though just recently you may observe in the price chart that it is at least slightly higher than its August high. But it remains below the prior two peaks over the past year. From the time frame in the chart, we could also consider it a “non-trending” and volatile period, but its the lower highs make it a downtrend.
The green chart at the bottom shows the relative strength between S&P 500 index of large company stocks and the Russell 2000 small company index. Clearly, it hasn’t taken all year to figure out which was trending up and the stronger trend.
Such periods take different tactical trading skills to be able to shift profitability. When markets get choppy, you find out who really knows what they’re doing and has an edge. I shared this changing trend back in May in Stock Market Peak? A Tale of Two Markets.

If you are unsure about the relevance of the big picture regarding these things, read Playing with Relative Strength and Stock Market Trend: reverse back down or continuation? and Stock Market Peak? A Tale of Two Markets.

Are investors getting overly optimistic again?

November 5, 2014 By Mike Shell in Actively Manage Risk, Adapting to Change, Counter trend, Crowd Psychology, Dynamic Hedging, Empirical Observation, Investor Behavior Modification, Investor Sentiment Leave a comment

Just as I was observing U.S. stocks getting to a point that I would expect to see stock indexes pull back at least a little or drift sideways, I noticed that investor sentiment readings last week were unusually bullish. 49.4% of investors polled by AAII last week believe stocks will rise in the next 6 months. Only 21.1% were bearish, believing stocks would fall.

That’s an unusual asymmetry between the percent of individual investors believing stocks will rise over those who believe they will fall. You can see the historical averages below.

source: http://www.aaii.com/sentimentsurvey?adv=yes

Investors tend to get more bullish about stocks after they have risen recently (and they have). They tend to get more bearish after stocks have fallen and they are losing money – and fear losing more.

It isn’t a perfect indicator, but the majority tends to feel the wrong feelings at the wrong time. That presents an advantage for those of us who don’t, and are aware of how behavior signals trends, but a challenge for advisers and individual investors as they try to modify their behavior to avoid it.

Stock Market Trend: reverse back down or continuation?

October 22, 2014 By Mike Shell in Actively Manage Risk, Adapting to Change, Asymmetric Hedging, Asymmetric Observation, Asymmetric Thinking, Business Cycle, Counter trend, Empirical Observation, Global Directional Trends, Global Macro, Tactical ETF Managed Portfolio Leave a comment

I normally don’t comment here on my daily observations of very short-term directional trends, though as a fund manager I’m monitoring them every day. The current bull market in stocks is aged, it’s lasted much longer than normal, and it’s been largely driven by actions of the Fed. I can say the same for the upward trend in bond prices. As the Fed has kept interest rates low, that’s kept bond prices higher.

Some day all of that will end.

But that’s the big picture. We may be witnessing the peaking process now, but it may take months for it all to play out. The only thing for certain is that we will only know after it has happened. Until then, we can only assess the probabilities. Some of us have been, and will be, much better at identifying the trend changes early than others.

With that said, I thought I would share my observations of the very short-term directional trends in the stock market since I’ve had several inquiring about it.

First, the large company stock index, the S&P 500, is now at a point where it likely stalls for maybe a few days before it either continues to trend up or it reverses back down. In “Today Was the Kind of Panic Selling I Was Looking For” I pointed out that the magnitude of selling that day may be enough panic selling to put in at least a short-term low. In other words, prices may have fallen down enough to bring in some buying interest. As we can see in the chart below, that was the case: the day I wrote that was the low point in October so far. We’ve since seen a few positive days in the stock index.

All charts in this article are courtesy of http://www.stockcharts.com and created by Mike Shell

Larger declines don’t trend straight down. Instead, large declines move down maybe -10%, then go up 5%, then they go down another -10%, and then back up 7%, etc. That’s what makes tactical trading very challenging and it’s what causes most tactical traders to create poor results. Only the most experienced and skilled tactical decision makers know this. Today there are many more people trying to make tactical decisions to manage risk and capture profits, so they’ll figure this out the hard way. There isn’t a perfect ON/OFF switch, it instead requires assessing the probabilities, trends, and controlling risk.

Right now, the index above is at the point, statistically, that it will either stall for maybe a few days before it either continues to trend up or it reverses back down. As it all unfolds over time, my observations and understanding of the “current trend” will evolve based on the price action. If it consolidates by moving up and down a little for a few days and then drifts back up sharply one day, it is likely to continue up and may eventually make a new high. If it reversed down sharply from here, it will likely decline to at least the price low of last week. If it does drift back to last weeks low, it will be at another big crossroads. It may reverse up again, or it may trend down. Either way, if it does decline below low of last week, I think we’ll probably see even lower prices in the weeks and months ahead.

Though I wouldn’t be surprised if the stock index does make a new high in the coming months, one of my empirical observations that I think is most concerning about the stage of the general direction of the stock market is that small company stocks are already in a downtrend. Below is a chart of the Russell 2000 Small Cap Stock Index over the same time frame as the S&P 500 Large Cap Stock Index above. Clearly, smaller companies have already made a lower low and lower highs. That’s a downtrend.

Smaller company stocks usually lead in the early stage of bear markets. There is a basic economic explanation for why that may be. In the early stage of an economic expansion when the economy is growing strong, it makes sense that smaller companies realize it first. The new business growth probably impacts them in a more quickly and noticeable way. When things slow down, they may also be the first to notice the decline in their earnings and income. I’m not saying that economic growth is the only direct driver of price trends, it isn’t, but price trends unfold the same way. As stocks become full valued at the end of a bull market, skilled investors begin to sell them or stop investing their cash in those same stocks. Smaller companies tend to be the first. That isn’t always the case, but you can see in the chart below, it was so during the early states of the stock market peak in 2007 as prices drifted down into mid 2008. Below is a comparison of the two indexes above. The blue line is the small stock index. In October 2007, it didn’t exceed its prior high in June. Instead, it started drifting down into a series of lower lows and lower highs. It did that as the S&P 500 stock index did make a prior high.

But as you see, both indexes eventually trended down together.

As a reminder to those who may have forgotten, I drew the chart below to show how both of these indexes eventually went on to lower lows and lower highs all the way down to losses greater than -50%. I’m not suggesting that will happen again (though it could) but instead I am pointing out how these things look in the early stages of their decline.

If you don’t have a real track record evidencing your own skill and experience dealing with these things, right now is a great time to get in touch. By “real”, I’m talking about an actual performance history, not a model, hypothetical, or backtest. I’m not going to be telling you how I’m trading on this website. The only people who will experience that are our investors.

VIX® gained 140%: Investors were too complacent

October 16, 2014 By Mike Shell in Actively Manage Risk, Adapting to Change, Asymmetric Hedging, Asymmetric Payoff, Asymmetric Risk, Crowd Psychology, Dynamic Hedging, Empirical Observation, Global Directional Trends, Global Macro, Investor Sentiment, Managed Volatility, Mean Reversion, Risk Asymmetry, VIX CBOE Volatility Index, Volatility Trading 1 Comment

Several months ago I started sharing some of my observations about the VIX ( CBOE Volatility Index). The VIX had gotten to a level I considered low, which implied to me that investors were too complacent, were expecting too low future volatility, and option premiums were generally cheap. After the VIX got down to levels around 11 and 12 and then started to move up, I pointed out the VIX seemed to be changing from a downward longer term trend to a rising trend.

As I was sharing my observations of the directional trend and volatility of VIX that I believed was more likely to eventually go up than down, it seemed that most others were writing just the opposite. I know that many volatility traders mostly sell volatility (options premium), so they prefer to see it fall.

As you can see in the chart below, The VIX has increased about 140% in just a few weeks.

Chart courtesy of http://www.stockcharts.com

For those who haven’t been following along, you may consider reading the previous observations:

A VIX Pop Then Back to Zzzzzzzz? We’ll see

Asymmetric VIX

VIX Shows Volatility Still Low, But Trending

VIX Back to Low

The VIX is Asymmetric, making its derivatives an interesting hedge

Is the VIX an indication of fear and complacency?

What does a VIX below 11 mean?

What does the VIX really represent?

The VIX, my point of view

The VIX, as I see it…

Volatility Risk Premium

Declining (Low) Volatility = Rising (High) Complacency

Investors are Complacent

Fear is Driving Stocks Down, or is Declining Stocks Driving Fear?

October 13, 2014 By Mike Shell in Actively Manage Risk, Adapting to Change, Asymmetric Risk, Counter trend, Dynamic Hedging, Empirical Observation, Fear and Greed Index, Global Directional Trends, Investor Sentiment Leave a comment

The last time I pointed out a short-term measure of extreme investor sentiment was August 4, see “Extreme Fear is Now the Return Driver“. At that time, popular stock indexes had declined -3% or more and as prices fell, investor fear measures increased.

As stocks rise, investors get complacent and brag about their profits. After prices fall, investor fear measures start to rise.

Since I pointed out “Extreme Fear is Now the Return Driver”, the Dow Jones Industrial Average went on to trend back up 5% by mid September. Below is a price chart for the Dow year to date. I marked August 4th with a red arrow. You can see how the price trend had declined sharply, driving fear of even lower prices, then it reversed back up. Fear increases after a decline and when fear gets high enough, stocks often reverse back up in the short term. They get complacent and greedy after prices rise to the point there are no buyers left to keep bidding prices up, then prices fall. Investors oscillate between the fear of missing out and the fear of losing money.

Source: http://www.stockcharts.com

Since mid September, the price trend has drifted back down over 4% from the peak. As you can see, the Dow has made no gain for the year 2014. It is no surprise that investor sentiment readings are now at “Extreme Fear” levels, as measured by the Fear & Greed Index below.

Source: Fear & Greed Index CNN Money

So, the last time investor fear levels got this high, stocks reversed back up in the weeks ahead. However, it doesn’t always work out that way. These indicators are best used with other indications of trend direction and strength to understand potential changes or a continuation. For example, we commonly observe 4% to 5% swings in stock prices a few times a year. That is a normal range and should be expected. However, eventually prices will decline and investors will continue to fear even more losses. As prices fall, investors sell just because they’re losing money. Some sell earlier in the decline, some much later. You may know people who sold after they were down -50% in 2008 or 2002. The trouble with selling out of fear is: when would they ever get back in? That’s why I manage risk with predefined exit points and I know at what point I would reenter.

My point is: fear always has the potential to become panic selling leading to waterfall declines. Panic selling can take weeks or months to drive prices low enough that those who sold earlier (and avoided the large losses and have cash available) are willing to step in to start buying again. Those who stay fully invested all the time don’t have the cash for new buying after prices fall. It’s those buy and hold (or re-balance) investors who also participate fully in the largest market losses. It’s those of us who exit our losers soon enough, before a large decline, that have the cash required to end the decline in prices.

Selling pressure starts declines, new buying ends them.

We’ll see in the weeks ahead if fear has driven prices to a low enough point that brings in new buying like it has before or if it continues into panic selling. There is a chance we are seeing the early stages of a bear market in global stocks, but they don’t fall straight down. Instead, declines of 20% or more are made up of many cycles of 5 – 10% up and down along the way. So, we shouldn’t be surprised to see stock prices drift up 5% again, maybe even before another -10% decline.

Declining stocks drive fear, but fear also drives stocks down.

Let’s see how it all unfolds…

Trend Change in Dollar, International Stocks, Gold?

October 3, 2014 By Mike Shell in Counter trend, Empirical Observation, Global Directional Trends, Global Tactical Rotation, Mean Reversion, Momentum Relative Strength, Tactical ETF Portfolio Management, Trend Following Leave a comment

Directional trends tend to persist. When a price is trending, it’s more likely to continue than to reverse. A directional trend is a drift up or down. For example, we can simply define a uptrend by observing a price chart of higher highs and higher lows. A downtrend is an observation of lower highs and lower lows. For a trading system, we need to be more precise in defining a direction with an algorithm (an equation that mathematically answers the question). The concept that directional trends tend to persist is called “momentum“. Momentum is the empirically observed tendency for rising prices to rise further. Momentum in price trends have been exploited for decades by trend following traders and its persistence is now even documented in hundreds of academic research papers. Momentum persists, until it doesn’t, so I can potentially create profits by going with the trend and then capturing a part of it.

But all trends eventually come to an end. We never know in advance when that will be, but we can determine the probability. Sometimes a trend reversal (up or down) is more likely than others. If you believe markets are efficient and instead follow a random walk, you won’t believe that. I believe trends move in one direction, then reverse, then trend again. When I look at the charts below, I see what I defined previously as “a trend”. I have developed equations and methods for defining the trend and also when they may bend at the end. More importantly, I observe them when they do bend. For example, to capture a big move in a trend, say 20% or more, we can’t get out every time it drops -2%, because it may do that many times on its way to that 20%. So, trend following means staying with the trend until it really bends. Counter-trend trading is trying to profit from the bends by identifying the change in the trend. Both are somewhat the opposite, but since my focus is these trends I observe them both.

Inertia is the resistance to change, including a resistance to change in direction. I could say then, that it takes inertia to keep a trend going. If there is enough inertia, the trend will continue. Trends will almost always be interrupted briefly by shorter term trends. For example, if you look at a monthly chart of a market first, then view a weekly chart, then a daily chart, you’ll see different dimensions of the trend and maybe left with a different observation than if you just look at one time frame.

Below I drew a monthly charge going back nearly 12 years. As you can see, the U.S. Dollar ($USD) has been “down” as much as -40% since 2002. It’s lowest point was 2008 and using my definition for trend, it’s been rising since 2008 though with a lot of volatility from 2008 to 2011. We could also say it’s been “non-trending” generally since 2005, since it has oscillated up and own since then without any meaning breakout.

All of charts are courtesy of http://www.stockcharts.com

Next we observe the weekly price trend. In a weekly chart we see the non-trending period, but ultimately over this time frame the Dollar gained 9%. The Dollar has been at a relatively low price range during this time. For those who want to understand why a trend occurs: A low currency is a reflection of the U.S. debt burden and lack of economic growth. We can only say that in hindsight. Most of the time we don’t actually know why a trend is a trend when it’s trending – and I don’t need to know.

You can probably begin to see how “the trend” is a function of “the time frame”. The most recent trend is observed in a daily chart going back less than a year. Here we see the U.S. Dollar is rising since July. I pointed out in “Interest Rates and Dollar Rising, Commodities Falling” how the Dollar is driving other markets.

The Dollar is now at a point that I mathematically expect to see it may reverse back down some. Though a trend is more likely to persist and resist change (inertia), trends don’t move straight up or down. Instead, they oscillate up and down within their larger trend. If you look at any of the price trend charts above, you’ll see smaller trends within them. It appears the Dollar is now likely to change direction at least briefly, though maybe not very much. As I mentioned in “Interest Rates and Dollar Rising, Commodities Falling”, it seems that rising interest rates are probably driving the Dollar higher. The market seems to be anticipating the Fed doing things to increase interest rates in the future. Let’s look at some other trends that seem to be interacting with the Dollar and interest rates.

The MSCI EAFE Index is an index of developed countries. You can observe the trend below. International stocks tend to decline when the Dollar rises, because this index is foreign country stocks priced in Dollars.

Below is the MSCI Emerging Markets index, which are smaller more emerging countries. MSCI includes countries like Russia, Brazil, and Mexico as “emerging”, but some may be surprised to hear they also consider China an emerging market. The recent rising Dollar (from rising rates) has been partly the driver of falling prices.

Another market that is directly impacted by the trend in the Dollar is commodities. Below we see the S&P/GSCI Commodity Index.

I am sharing observations about global macro trends and trend changes. We previously saw that the Dollar was generally in a downtrend and at a low level for years. When the Dollar is down, commodities priced in Dollars may be up. One commodity that became very popular when it was rising was Gold. When the Dollar was falling and depressed, Gold was rising. Below is a more recent price trend of gold.

I wouldn’t be surprised to see the Dollar trend to reverse back down some in the short-term and that could drive these other markets to reverse their downtrends at least briefly. Only time will tell if it does reverse in the near future and by how much.

In the meantime, let’s watch it all unfold.

Stock Market Peak? A Tale of Two Markets

May 15, 2014 By Mike Shell in Actively Manage Risk, Adapting to Change, Empirical Observation, Global Directional Trends, Global Macro, Market Breadth Tags: Dow Jones Industrial, Russell 2000 Index Leave a comment

One of the early warning signs that a bull market in stocks is nearing its end is increasing selectivity. As more investors begin to believe a peak may be near based on statistical analysis or valuation, they may get positioned more defensively. Eventually we observe some stocks participating in a rising trend as others trend down early. Over the past several weeks we have observed a material divergence between large company stocks like those in the Dow Jones Industrial Average (DIA) vs. small company stocks like those in the Russell 2000 Index (IWM). As you can see below, the Russell 2000 index has declined nearly 9% while the Dow Jones Industrial has gained about 2%. Since the Dow Jones Industrial is more popularly quoted in the media, most investors probably believed “the market was still rising”. But unless you only have positions in the largest company stocks, you’re noticing that isn’t the case in terms of the broad market. Small company stocks tend to lead on the downside, so we shouldn’t be surprised if we see the larger companies follow them down at some point. You can probably see how this basic observation leads to further study of market breadth: looking at what percent of stocks are rising vs. falling.

Is this the “tail” of two markets?

Data: http://www.stockcharts.com

Of course, the direction of the overall market is interesting to monitor, but it only matters what positions we have at risk.

Fun with Weather Graphs: A Quant View of Knoxville Relative to Tampa

May 13, 2014 By Mike Shell in Adapting to Change, Critical Thinking, Data Driven Rearch, Empirical Observation, Quantitative Evidence-Based Rearch Tags: Florida, Knoxville, Tampa, Tennessee Leave a comment

I recently compared the climate differences between two places I call home: Knoxville, Tennessee and Tampa, Florida. They have very different climates, Knoxville is in the Tennessee mountains, the Tampa Bay/Clearwater/St. Pete area is home of the best beaches in America. Some of us consider the two the best of both worlds. What you believe depends on your own experience. Knoxville is one of the gateways to the Great Smoky Mountains National Park, the most visited national park in America. It had about 10 million visitors in 2013, which was double the Grand Canyon, the second most visited. The two cities have very different climates in the summer and winter months. We think of Tampa, Florida as hot and sunny. Knoxville is cooler in the summer, chilly in the winter. But that’s just my opinion and description. If we really want to understand the absolute level of temperature, humidity, and sunshine, and relative differences we can apply some quantitative methods and draw some visual graphs between them. Here you will see how I see and understand how I make decisions and draw distinctions. For those who otherwise have difficultly understanding data and graphs, you may find it more interesting to apply the same concepts to the weather. I’ll share with you my study of Knoxville vs. Tampa weather which I think is a good example of applying historical data to understand what to expect. To do this weather comparison, I used this tool with data from the NOAA Comparative Climate Data.

Summer in Knoxville, Winter in Tampa?

Initially, we can compare the average temperature between Knoxville and Tampa to get a quick visual. We can see some positive asymmetry between the winter and summer months. The average temperature in January is in the 60’s in Tampa and only the 30’s in Knoxville: a 30 degree spread. Yet, the average summer months is only a 10 degree spread. I call that positive asymmetry, because we don’t want it too hot in the summer and we don’t want it too cool in the winter. Tampa has the better tradeoff. But, the flaw of averages is that the actual high and low range can be much wider than we realize, so can gain a better understanding by looking specifically at the highs and lows.

AVERAGE TEMP

Although Knoxville is in the south, it still gets cold in the winter months. If we wanted a “winter home” to avoid those cold winter months, we would first focus on the average low temperature. That is, “how cold does it get”? Comparing the lows allows us to understand how cold it gets. As we see in the chart below, January and February are the coldest months in Knoxville when the low is around freezing. On the other hand, in Tampa the average low is above 50. 50 is chilly, not really cold. Notice the other extreme on the chart is the peak, when the average low in Tampa is over 70 during starting in June through September. We could say that that weather in Knoxville is more volatile throughout the year since it has a wider range of temperatures. We can see the visually by how quickly the data spreads out or how steep it is between the summer months and colder months. Clearly, the average lows of Tampa are more comfortable if you enjoy the outdoors.

AVERAGE LOW

What about summer?

We know that the further south we go, the hotter the summers we can expect. To see that visually, we can graph the average high temperatures. In Tampa, the average high is above 70 year around. The cold months in Knoxville have an average high around or below 50. When we consider the average low in Knoxville is in the 30’s and average high is the 50’s, that’s a material difference from an average low in Tampa in the 50’s and average high in the comfortable 70’s. In fact, you may observe the average low in Tampa is the average high in Knoxville.

But what about too much heat? While the average high in Knoxville is in July and just short of 90, Tampa stays as hot as Knoxville hottest month from May up to October. For some, Tampa may be too hot in the summer. But humidity has a lot of do with how hot it feels, we’ll get to that.

AVERAGE HIGH

What about extreme cold?

When we analyze data, we want to look at it in different ways to carve out the things we want (warm weather) and carve away the things we don’t (cold and hot weather). Below we graph for a visual to see the average days below freezing (32F). Clearly, Knoxville experiences some freezing days that are rare in Tampa, Florida. Some of you are probably laughing at my calling below 32F “extreme cold”, thinking it should be instead below zero. What you consider extreme depends on your own judgment and experience.

AVERAGE DAYS BELOW 32F

What about extreme heat?

When we state an extreme, we have to define what we mean by extreme quantitatively. I used 90F to define an extremely hot day. As we see below, while Knoxville has many more days below freezing in the winter, Tampa has many more days of extreme heat in the summer. We are starting to discover when we want to be in Knoxville, Tennessee and when we may want to be in Tampa, Florida. As with investment management, timing is everything.

AVERAGE DAYS ABOVE 90F

What about Precipitation?

It doesn’t matter if the weather feels great if it’s raining all the time. Tampa experiences a lot of rainfall in inches starting in May through September. Knoxville rainfall is actually a little less in the summer months. So, we could describe Tampa as hot wet summers and Knoxville as warm dry summers.

AVERAGE PRECIPITATION

A little rain is one thing and may not be significant. What if we define a “significant rain” as greater than 0.10 inches? The stand out is that Tampa has “significant rain” in the summer months and little in the winter.

AVERAGE DAYS OF PRECIPITATION LESS GREATER THAN 0.10 INCHES

What about Humidity?

If you’ve ever experienced a place like Vail, Colorado in the winter were you can sit outside for lunch in the snow without a coat on when it’s 32F, you’ll have a unique understanding of humidity. We can say the same for south Florida in July. Humidity is the amount of water vapor in the air. Humidity may take more explanation to better understand. According to Wikipedia:

Higher humidity reduces the effectiveness of sweating in cooling the body by reducing the rate of evaporation of moisture from the skin. This effect is calculated in a heat index table or humidex, used during summer weather.

There are three main measurements of humidity: absolute, relative and specific. Absolute humidity is the water content of air. Relative humidity, expressed as a percent, measures the current absolute humidity relative to the maximum for that temperature. Specific humidity is a ratio of the water vapor content of the mixture to the total air content on a mass basis.

Relative humidity is an important metric used in weather forecasts and reports, as it is an indicator of the likelihood of precipitation, dew, or fog. In hot summer weather, a rise in relative humidity increases the apparent temperature to humans (and other animals) by hindering the evaporation of perspiration from the skin. For example, according to the Heat Index, a relative humidity of 75% at 80.0°F (26.7°C) would feel like 83.6°F ±1.3 °F (28.7°C ±0.7 °C) at ~44% relative humidity.

The temperature alone isn’t the full measure of how hot and uncomfortable the climate can be. We can break down humidity into morning and afternoon. Morning humidity in Knoxville is highest in the winter months, which leads to a cold, wet feeling winter. Morning humidity in Tampa is highest in the summer, making hot feel even hotter.

AVERAGE MORNING HUMIDITY

As we see below, afternoon humidity is much higher in Knoxville during the summer months.Tampa stays above 82% humidity on average. By now you have probably began to spot directional trends in the data as well as mean reversion. For example, in the chart below the red line (Knoxville) trends upward sharply from March to August. Then it reverses back down to retrace about half the prior gain. I see the same patterns and trends in global markets, though they are more difficult based more on social science than the science of climate and seasons. Yet, there are seasonal patters in global markets, too, such as “sell in May and go away” and “January Effect”. But unlike weather changes, they seasonal changes in the stock market aren’t as sure as the transition from summer to fall to winter to spring to summer again in Tennessee.

AVERAGE AFTERNOON HUMIDITY

Tampa has a Breeze

Below we see the average wind speed. Tampa has a breeze to help cool us down compared to Knoxville.

What about Sunshine?

Warm dry weather is nice, but what about sunshine? Below we see why they say “Sunny Florida”. You may notice that Tampa is more sunny in the winter months then even the summer months. Knoxville has a greater possibility of sunshine March through October with a sharp downtrend on both ends.

AVERAGE SUNSHINE POSSIBLE

What about Cloudy Days?

If you live in the north, you are familiar not only with cold wet winters, but cloudy grey skies. The outliear that stands out on this graph is that Knoxville is cloudy half of the days of each month in the winter. Tampa, on the other hand, has few cloudy days throughout the year, but its highest is the July. You may have noticed some climate patterns between Tampa and Knoxville are negatively correlated. That is, Knoxville tends to be cloudy in January and least cloudy in July and Tampa is nearly the opposite.

AVERAGE DAYS CLOUDY

In the late 1990’s I remember listening to Steven Covey audiobook of “7 Habits of Highly Effective People” when he would say: “proactive people carry weather with them”. That is an example of Projection makes perception: seek not to change the weather, but to change your mind about the weather. That may work for some of us for many years, but eventually we may instead decide to “rotate instead of allocate”. That is, we may decide a warm sunny place like Tampa, Florida is a great place when its cold, wet, and cloudy in a place like Knoxville. Though, Knoxville may be better to spend the summer months with its more mild summer than the hot humid wet Tampa summer.

You can “carry weather with you” by perceiving it how you want, or you can carry (rotate) yourself to the weather you prefer. You can probably see how this quantitative data study helps visualize the absolute climate ranges and relative differences to make the decision with a greater understanding of what to expect.

2013 Asset Allocation Returns

January 22, 2014 By Mike Shell in Empirical Observation Leave a comment

2013 was a big year for U.S. stocks and a losing year for other markets like bonds and emerging market countries. Though many people like to talk about how much the Dow Jones Industrial Average or the S&P 500 stock index gained, in reality few people actually invest all of their capital in U.S. stocks. That is probably more true the more money an investor has. If they want to have it all in stocks, it’s probably after a big year, not before it.

The true way to determine what return investors’ as a group earned in funds or ETFs is to create an asset-weighted composite of all the funds available. Such a composite would weight each fund based on how much money is actually invested in it, so if 50% were in bond funds that lost -2% and 50% was in stock funds that gained 20%, the composite would show an asset-weighted return of (50% x -2% = -1%) + (50% x 20% = 10%) = 9%. You can probably see how arbitrary it is to speak of calendar year returns, but the actual return investors earn is dependent on how much capital was invested in the funds and their gain or loss.

I don’t know of a data source that does that for all available funds, but below is a table from Morningstar that presents a category returns of mutual funds in their “allocation” category. I highlighted the 1 year return which approximates the calendar year 2013 and horizontally I highlighted two categories that are likely most represent investors’ allocation. The “Moderate Allocation” is like a 60/40 balance of 60% stocks and 40% bonds, which is popular. The “World Allocation” includes global allocation funds which have been some of the best performing funds long term. The Moderate Allocation category gained over 13% and the World Allocation gained about 8%. And, like the stock indexes, most of these mutual funds are fully exposed to loss at all times.

Source: Morningstar

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