Tadas Viskanta, whose well-respected and heavily-followed blog Abnormal Returns is a blend of aggregation and analysis, has entered the world of print. I am happy to say that Abnormal Returns: Winning Strategies from the Frontlines of the Investment Blogosphere (McGraw-Hill, 2012) lives up to the high standards of his blog. It manifests his keen curatorial skills; he knows how to sift the wheat from the chaff and to present the reader/investor with what he needs to know, no more and no less.
Viskanta won me over already on p. xi when he wrote, “becoming a merely competent investor seems like a worthy goal.” When I first started trading I decided I needed a mantra and chose “competence.” I overlaid the word on a chart, printed it out, and put it in a cheap little frame. A friend stopped by and inquired what it was all about. When I explained, she said, “Well, you certainly have set a lofty goal for yourself!” Actually, I think my goal was lofty. After all, two key meanings of competence are “a specific range of skill, knowledge, or ability” and “sufficient means for a comfortable existence.” So don’t knock the goal of becoming a competent investor.
In about 200 pages of text Viskanta discusses risk, return, equities, fixed income, portfolio management, active investing, exchange-traded funds, global investing, alternative assets, behaviors and biases, smarter media consumption, and lessons from a lost decade. His 20 pages of notes are a great bibliography for those who want to dig a little deeper into particular topics. I, for instance, followed up on his discussion of skill versus luck by reading the sources he cited (papers, blog entries, not books).
I think that what distinguishes Abnormal Returns from most books on investing is that Viskanta rarely talks in generalities. He zeroes in things that trip investors up and provides concrete examples to help the investor. For instance, referencing Atul Gawande’s work The Checklist Manifesto in his chapter on active investing, Viskanta writes: “Checklists don’t dictate what a trader does; rather they ensure that what a trader is supposed to do in a trade gets done.” And, he continues, “The hallmark of a well-designed trading system may be the actuality that a checklist can be created.” (p. 90)
In a section on noise, the author moves almost seamlessly from Fisher Black’s article “Noise” to the noise of business news channels and then on to the personal finance magazines that “have been running articles with titles like ‘10 Stocks to Buy Now’ for ages. These articles are not much different from the ‘10 Ways to Drive Your Man/Woman Crazy in Bed’ articles that festoon the magazine covers next to your checkout aisle at the grocery store. Both magazine covers appeal to our more base instincts: in one case greed, the other lust.” (p. 165)
Although I would never go so far as to say that an investor should have only a single book in his financial library, Abnormal Returns (plus an Internet connection to flesh out many of the ideas presented here) might satisfy the minimalist book collector. It definitely should be a core holding in an investing library.
Monday, April 30, 2012
Friday, April 27, 2012
Mayer, World Right Side Up
Investors in international markets would do well to read Christopher Mayer’s World Right Side Up: Investing Across Six Continents (Wiley, 2012). It is a thoroughly researched, carefully crafted book with a host of investing ideas.
Mayer, an inveterate traveler himself, takes his reader on an investing journey to Colombia, Brazil, Nicaragua, China, India, the Emirates, South Africa, Australia and New Zealand, Southeast Asia (Thailand, Cambodia, and Vietnam), and, in a potpourri chapter, Mongolia, Argentina, Russia, Turkey, and Central Asia. And finally back to Canada and the United States.
I debated what country I should highlight in this review. My first instinct, for purely sentimental reasons, was South Africa; I began my investing career many moons ago in an effort (yes, it was successful) to finance a trip to Africa. But in large measure because of the complex social and political risks in the region, Mayer wimped out and recommended a fund, admittedly an incredibly successful one (the Africa Opportunity Fund). So I moved on.
Then there’s Mongolia, which is rich in natural resources and “sits next to the world’s most voracious consumer of those resources, China.” (p. 209) In 2010 its stock market was the best performer worldwide, up 125%. For those willing to venture into pink sheets and to chase momentum, Mongolia Growth Group is a possibility; it focuses on everything except mining.
Well, call me stuck in the mud, but I’ve decided to return to North America and introduce you to, if you aren’t already familiar with, pulses. Pulses are “crops harvested for the dry seed. They include lentils, chickpeas, peas, and a variety of beans. They are an efficient source of protein by weight, giving you almost as much protein as chicken and more than beef. … Most importantly, pulses require far less water. It takes only about 40 gallons of water to produce one pound of pulses. Compare that to the nearly 2,000 gallons of water to produce one pound of beef.” (p. 238) Oh, and did I mention, they’re inexpensive, good for you, and very tasty. And, as every home gardener who grows peas knows, they have nitrogen-fixing properties, so they naturally replenish nitrogen in the soil. “Since nitrogen fertilizers make up half the energy costs of most North American farms, planting pulses makes good sense.” (p. 239)
With demand for pulses growing in the emerging markets, they are a promising investment story. But how exactly does one play the pulses? Mayer recommends Alliance Grain Traders (TSE: AGT), a Saskatchewan-based company that is one of the largest lentil- and pea-splitting companies in the world. Its stock performance over the course of the last year has been dismal, but Mayer suggests that AGT “is not a quarterly earnings story; this is about long-term wealth creation.” (p. 242)
World Right Side Up is a stimulating read. It gets the investor on the “right side” of global trends and offers up some ways to play these trends. I thoroughly enjoyed it.
Mayer, an inveterate traveler himself, takes his reader on an investing journey to Colombia, Brazil, Nicaragua, China, India, the Emirates, South Africa, Australia and New Zealand, Southeast Asia (Thailand, Cambodia, and Vietnam), and, in a potpourri chapter, Mongolia, Argentina, Russia, Turkey, and Central Asia. And finally back to Canada and the United States.
I debated what country I should highlight in this review. My first instinct, for purely sentimental reasons, was South Africa; I began my investing career many moons ago in an effort (yes, it was successful) to finance a trip to Africa. But in large measure because of the complex social and political risks in the region, Mayer wimped out and recommended a fund, admittedly an incredibly successful one (the Africa Opportunity Fund). So I moved on.
Then there’s Mongolia, which is rich in natural resources and “sits next to the world’s most voracious consumer of those resources, China.” (p. 209) In 2010 its stock market was the best performer worldwide, up 125%. For those willing to venture into pink sheets and to chase momentum, Mongolia Growth Group is a possibility; it focuses on everything except mining.
Well, call me stuck in the mud, but I’ve decided to return to North America and introduce you to, if you aren’t already familiar with, pulses. Pulses are “crops harvested for the dry seed. They include lentils, chickpeas, peas, and a variety of beans. They are an efficient source of protein by weight, giving you almost as much protein as chicken and more than beef. … Most importantly, pulses require far less water. It takes only about 40 gallons of water to produce one pound of pulses. Compare that to the nearly 2,000 gallons of water to produce one pound of beef.” (p. 238) Oh, and did I mention, they’re inexpensive, good for you, and very tasty. And, as every home gardener who grows peas knows, they have nitrogen-fixing properties, so they naturally replenish nitrogen in the soil. “Since nitrogen fertilizers make up half the energy costs of most North American farms, planting pulses makes good sense.” (p. 239)
With demand for pulses growing in the emerging markets, they are a promising investment story. But how exactly does one play the pulses? Mayer recommends Alliance Grain Traders (TSE: AGT), a Saskatchewan-based company that is one of the largest lentil- and pea-splitting companies in the world. Its stock performance over the course of the last year has been dismal, but Mayer suggests that AGT “is not a quarterly earnings story; this is about long-term wealth creation.” (p. 242)
World Right Side Up is a stimulating read. It gets the investor on the “right side” of global trends and offers up some ways to play these trends. I thoroughly enjoyed it.
Wednesday, April 25, 2012
Radkay, The RDS Forex System
Michael and Stephanie Radkay are the founders of the trading education company RDS Trader. The RDS Forex System: A Breakthrough Method to Profiting from Market Turning Points (Wiley, 2012) is a companion piece to, and I assume an advertisement for, their services. But at least it’s a self-contained book, not one of those teasers. It’s a chatty, easy read.
Since The RDS Forex System is not the book most novice traders would turn to for a primer, even though it has the standard chapters on risk management and trading psychology, I’m going to focus on their trading system—the rotating directional system. The authors describe it as a forex system, but with slight modifications it is applicable to any market. And although it is essentially a day trading system (using 15-minute charts), it can be used for swing trading as well.
The basic premise is that traders need a reference point to guide them. In the RDS system it’s the 50-yard line, or—in trader lingo—the midpoint of the previous day’s range that is replaced with the midpoint of the current day’s range once price begins to get established. This line is adjusted every time a market makes a new high or new low. Look to get long if price is above the midpoint, short if it is below the midpoint. A simple concept that obviously can’t stand on its own and is insufficient even when, as the authors recommend, a weekly 50 percent line is added.
So comes rule two, the so-called neutral rule, which uses the previous close as a reference point. In tandem with this rule we have a further division of the day’s range into eighths. And a skewing of that division to use the previous close as the midpoint, what the authors call adjusting the field to neutral.
With rule three the idea of rotation enters the scene. The basic idea is that you want to consider going long/short when price is above/below the (unskewed) midpoint line and the previous close and when price has fallen/risen two levels. The profit target is four levels.
Two more rules complete the picture. First is the window of opportunity—a flip in trend—with three choices: patient, acceptable, and aggressive. This is obviously the most discretionary part of the system. And finally RSI (25/75 levels).
The system is pretty straightforward and, for those far more talented than I, even seems to be programmable. If anyone wants to write his own version (in particular defining what constitutes a flip in trend) and backtest it on the market of his choice, I’d be curious about the results.
Since The RDS Forex System is not the book most novice traders would turn to for a primer, even though it has the standard chapters on risk management and trading psychology, I’m going to focus on their trading system—the rotating directional system. The authors describe it as a forex system, but with slight modifications it is applicable to any market. And although it is essentially a day trading system (using 15-minute charts), it can be used for swing trading as well.
The basic premise is that traders need a reference point to guide them. In the RDS system it’s the 50-yard line, or—in trader lingo—the midpoint of the previous day’s range that is replaced with the midpoint of the current day’s range once price begins to get established. This line is adjusted every time a market makes a new high or new low. Look to get long if price is above the midpoint, short if it is below the midpoint. A simple concept that obviously can’t stand on its own and is insufficient even when, as the authors recommend, a weekly 50 percent line is added.
So comes rule two, the so-called neutral rule, which uses the previous close as a reference point. In tandem with this rule we have a further division of the day’s range into eighths. And a skewing of that division to use the previous close as the midpoint, what the authors call adjusting the field to neutral.
With rule three the idea of rotation enters the scene. The basic idea is that you want to consider going long/short when price is above/below the (unskewed) midpoint line and the previous close and when price has fallen/risen two levels. The profit target is four levels.
Two more rules complete the picture. First is the window of opportunity—a flip in trend—with three choices: patient, acceptable, and aggressive. This is obviously the most discretionary part of the system. And finally RSI (25/75 levels).
The system is pretty straightforward and, for those far more talented than I, even seems to be programmable. If anyone wants to write his own version (in particular defining what constitutes a flip in trend) and backtest it on the market of his choice, I’d be curious about the results.
Monday, April 23, 2012
Miller, Mathematics and Statistics for Financial Risk Management
Mathematics and Statistics for Financial Risk Management by Michael B. Miller (Wiley, 2012) doesn’t take the reader from 0 to 60 in 300 pages; the acceleration is probably more in the range of 25 to 50. Miller assumes that “readers have a solid grasp of algebra and at least a basic understanding of calculus.”
Ten chapters cover the following topics: some basic math, probabilities, basic statistics, distributions, hypothesis testing and confidence intervals, matrix algebra, vector spaces, linear regression analysis, time series models, and decay factors.
In each chapter Miller explains the key concepts and frequently illustrates them with sample problems (answers included). For instance, in the section on correlation the sample problem is: “X is a random variable. X has an equal probability of being -1, 0, or +1. What is the correlation between X and Y if Y = X2?” (p. 56) At the end of each chapter is a set of problems; the answers are given at the end of the book. A companion website provides further Excel examples.
Although this book carefully and clearly explains the basic math and statistics at the heart of risk management, it does more. It also uses math and statistics to explain the shortcomings of some financial risk management tools. VaR is an obvious candidate. One criticism of VaR is that it is not a subadditive risk measure. “Subadditivity is basically a fancy way of saying that diversification is good, and a good risk measure should reflect that.” (p. 120) Miller offers a sample problem that demonstrates a violation of subadditivity. Here’s the question: “Imagine a portfolio with two bonds, each with a 4% probability of defaulting. Assume that default events are uncorrelated and that there is a recovery rate of 0%. The bonds are currently worth $100 each. If a bond defaults, it is worth $0; if it does not, it is still worth $100. What is the 95% VaR of each bond separately? What is the 95% VaR of the bond portfolio?” It turns out that in this case VaR “seems to suggest that holding $200 of either bond would be less risky than holding a portfolio with $100 of each. Clearly this is not correct. For this portfolio, VaR is not subadditive.” (pp. 120-21)
At every turn this book shows the relevance of mathematical and statistical concepts to risk management. They are no longer the desiccated notions found in most textbooks but assume a sense of vibrancy. So, if you’re trying to hone your skills, this book is a great place to start.
Ten chapters cover the following topics: some basic math, probabilities, basic statistics, distributions, hypothesis testing and confidence intervals, matrix algebra, vector spaces, linear regression analysis, time series models, and decay factors.
In each chapter Miller explains the key concepts and frequently illustrates them with sample problems (answers included). For instance, in the section on correlation the sample problem is: “X is a random variable. X has an equal probability of being -1, 0, or +1. What is the correlation between X and Y if Y = X2?” (p. 56) At the end of each chapter is a set of problems; the answers are given at the end of the book. A companion website provides further Excel examples.
Although this book carefully and clearly explains the basic math and statistics at the heart of risk management, it does more. It also uses math and statistics to explain the shortcomings of some financial risk management tools. VaR is an obvious candidate. One criticism of VaR is that it is not a subadditive risk measure. “Subadditivity is basically a fancy way of saying that diversification is good, and a good risk measure should reflect that.” (p. 120) Miller offers a sample problem that demonstrates a violation of subadditivity. Here’s the question: “Imagine a portfolio with two bonds, each with a 4% probability of defaulting. Assume that default events are uncorrelated and that there is a recovery rate of 0%. The bonds are currently worth $100 each. If a bond defaults, it is worth $0; if it does not, it is still worth $100. What is the 95% VaR of each bond separately? What is the 95% VaR of the bond portfolio?” It turns out that in this case VaR “seems to suggest that holding $200 of either bond would be less risky than holding a portfolio with $100 of each. Clearly this is not correct. For this portfolio, VaR is not subadditive.” (pp. 120-21)
At every turn this book shows the relevance of mathematical and statistical concepts to risk management. They are no longer the desiccated notions found in most textbooks but assume a sense of vibrancy. So, if you’re trying to hone your skills, this book is a great place to start.
Thursday, April 19, 2012
Fogarty and Lamb, Investing in the Renewable Power Market
The history of wealth in nineteenth-century America in large part paralleled the history of the energy markets. I grew up in a town that once boasted more millionaires per capita than any other town in the United States, thanks to coal mining. By the middle of the twentieth century most of the coal was gone; what had once been a 100-acre estate became home to the Sisters of St. Basil the Great; the town was in visible decline (and has only declined further).
Tom Fogarty and Robert Lamb take us into the twenty-first century, and into a new energy dynamic, with Investing in the Renewable Power Market: How to Profit from Energy Transformation (Wiley, 2012). Let’s put it this way, don’t start flipping through the Sotheby’s real estate listings, at least not in the near term. Unless, of course, you’re the genius who can finally solve the seemingly indomitable battery problem; at the moment battery technology can store electricity for at most four hours. Despite the fact that the authors believe that renewable energy must be a part of our energy future, Fogarty and Lamb, a practitioner and an academic, are realistic about the daunting challenges it faces.
Start with the fact that prices for renewable energy are priced off of natural gas, which has broken below $2 per million Btu. (In the summer of 2008 it traded at $13.57.) As a result, “in the short term it makes sense to bet against renewables as opposed to developing or investing in new projects.” (p. 3)
Who would want to invest in renewable energy projects? For the most part, not you or me, not even private equity. Corporations looking for tax credits are likely candidates, as are those groups seeking to purchase projects at distressed prices. “Some of the very best investment opportunities in the entire energy industry today are in purchasing at fire-sale prices many abandoned or distressed municipal bond waste-to-energy power plants in our very low interest rate market.” (p. 54) But in the final analysis, the authors conclude, “only the U.S. government can fund and take on the risk of new energy technology.” (p. 176)
The bogey man for the renewable power market, as the authors repeat frequently, is shale natural gas. Right now it is so abundant and so cheap that renewable energy can often seem like a futile dream. Moreover, as governments, especially in Europe, impose austerity measures and decide that subsidies for renewable energy are obvious candidates for the chopping block, they undermine the already fragile renewable energy stocks. Only this week First Solar announced that it was downsizing in the face of a solar panel glut and a cutback in European government support (especially Germany and Italy) for utility-scale solar installations. Its stock rallied on the news, but that was small comfort to those who bought a year ago: they’re looking at a 83% loss.
If ultra-cheap nat gas and government cutbacks were not enough, renewable energy also faces serious structural problems. Unlike traditional power plants that produce energy 24/7, wind is effective only about 30 percent of the time; solar, 16 percent. So a solar plant or wind energy farm needs a backup energy supply plant fueled by gas, oil, or coal. A backup plant “usually is much more expensive to run per hour than any normal standard power plants that are always on, running steadily.” (p. 55) A possible solution to this problem is a virtual power plant.
The authors devote separate chapters to both renewable and traditional power plants (solar, wind, natural gas, coal-fired, biomass, nuclear power, hydropower, and geothermal). They lay out the economics and environmental impacts of each and some of the regulatory hurdles each faces.
Investing in the Renewable Power Market is a sober, carefully researched analysis. Anyone contemplating investing in renewable energy stocks or ETFs—or even in traditional energy stocks—will get a solid introduction to the field.
Tom Fogarty and Robert Lamb take us into the twenty-first century, and into a new energy dynamic, with Investing in the Renewable Power Market: How to Profit from Energy Transformation (Wiley, 2012). Let’s put it this way, don’t start flipping through the Sotheby’s real estate listings, at least not in the near term. Unless, of course, you’re the genius who can finally solve the seemingly indomitable battery problem; at the moment battery technology can store electricity for at most four hours. Despite the fact that the authors believe that renewable energy must be a part of our energy future, Fogarty and Lamb, a practitioner and an academic, are realistic about the daunting challenges it faces.
Start with the fact that prices for renewable energy are priced off of natural gas, which has broken below $2 per million Btu. (In the summer of 2008 it traded at $13.57.) As a result, “in the short term it makes sense to bet against renewables as opposed to developing or investing in new projects.” (p. 3)
Who would want to invest in renewable energy projects? For the most part, not you or me, not even private equity. Corporations looking for tax credits are likely candidates, as are those groups seeking to purchase projects at distressed prices. “Some of the very best investment opportunities in the entire energy industry today are in purchasing at fire-sale prices many abandoned or distressed municipal bond waste-to-energy power plants in our very low interest rate market.” (p. 54) But in the final analysis, the authors conclude, “only the U.S. government can fund and take on the risk of new energy technology.” (p. 176)
The bogey man for the renewable power market, as the authors repeat frequently, is shale natural gas. Right now it is so abundant and so cheap that renewable energy can often seem like a futile dream. Moreover, as governments, especially in Europe, impose austerity measures and decide that subsidies for renewable energy are obvious candidates for the chopping block, they undermine the already fragile renewable energy stocks. Only this week First Solar announced that it was downsizing in the face of a solar panel glut and a cutback in European government support (especially Germany and Italy) for utility-scale solar installations. Its stock rallied on the news, but that was small comfort to those who bought a year ago: they’re looking at a 83% loss.
If ultra-cheap nat gas and government cutbacks were not enough, renewable energy also faces serious structural problems. Unlike traditional power plants that produce energy 24/7, wind is effective only about 30 percent of the time; solar, 16 percent. So a solar plant or wind energy farm needs a backup energy supply plant fueled by gas, oil, or coal. A backup plant “usually is much more expensive to run per hour than any normal standard power plants that are always on, running steadily.” (p. 55) A possible solution to this problem is a virtual power plant.
The authors devote separate chapters to both renewable and traditional power plants (solar, wind, natural gas, coal-fired, biomass, nuclear power, hydropower, and geothermal). They lay out the economics and environmental impacts of each and some of the regulatory hurdles each faces.
Investing in the Renewable Power Market is a sober, carefully researched analysis. Anyone contemplating investing in renewable energy stocks or ETFs—or even in traditional energy stocks—will get a solid introduction to the field.
Wednesday, April 18, 2012
Clayman et al., Corporate Finance
This second edition of Corporate Finance: A Practical Approach, part of the CFA Institute Investment Series (Wiley, 2012), was edited by Michelle R. Clayman, Martin S. Fridson, and George H. Troughton. In more than 500 pages its contributors cover corporate governance, capital budgeting, cost of capital, measures of leverage, capital structure, dividends and share repurchases, working capital management, financial statement analysis, and mergers and acquisitions.
The book is assembled from texts used in the CFA Program curriculum, a global graduate-level self-study program for those aspiring to become chartered financial analysts. Each chapter concludes with a set of problems. An accompanying workbook, which I haven’t seen, is also available.
I’m going to focus on a single concept for this post, leverage, since it is understood somewhat differently in the corporate context than it is in the trading context. First, the definition: “Leverage is the use of fixed costs in a company’s cost structure. The fixed costs that are operating costs (such as depreciation or rent) create operating leverage. Fixed costs that are financial costs (such as interest expense) create financial leverage.” (p. 171)
Leverage is a key component in assessing a company’s risk and return characteristics. “Leverage increases the volatility of a company’s earnings and cash flows and increases the risk of lending to or owning a company.” (p. 172)
Assume that two companies have the same net income, produce the same number of units, and sell each unit for the same price but have significantly different cost structures. Company A has a much lower variable cost per unit and a much higher fixed operating cost per unit than does company B. If unit sales drop, A will be harder hit than B; if sales rise, A will turn a higher profit than B. In brief, “The greater the fixed operating costs relative to variable operating costs, the greater the operating risk.” (p. 174)
Without going into the nitty-gritty of calculating the degree of operating leverage (in the simplest of terms it’s the percentage change in operating income divided by the percentage change in units sold), let’s skip to a general conclusion. “Industries that tend to have high operating leverage are those that invest up front to produce a product but spend relatively little on making and distributing it. Software developers and pharmaceutical companies fit this description. Alternatively, retailers have low operating leverage because much of the cost of goods sold is variable.” (p. 180)
Business risk is comprised of operating risk and sales risk (“the uncertainty with respect to the price and quantity of goods and services”). But investors also have to worry about financial risk, associated with how the company finances its operations. “If a company finances with debt, it is legally obligated to pay the amounts that make up its debts when due. By taking on fixed obligations, such as debt and long-term leases, the company increases its financial risk. If a company finances its business with common equity, generated either from operations (retained earnings) or from issuing new common shares, it does not incur fixed obligations. The more fixed-cost financial obligations (e.g., debt) incurred by the company, the greater its financial risk.” (p. 182)
Trust me, you couldn’t correctly answer questions about leverage on the CFA exam based on my summary. But I think it will give you some idea of the way topics are covered (sans math) in this very thorough book. It is valuable reading not only for grad students and CFA wannabes but also for sophisticated investors and professional managers who want to understand what corporate finance is all about.
The book is assembled from texts used in the CFA Program curriculum, a global graduate-level self-study program for those aspiring to become chartered financial analysts. Each chapter concludes with a set of problems. An accompanying workbook, which I haven’t seen, is also available.
I’m going to focus on a single concept for this post, leverage, since it is understood somewhat differently in the corporate context than it is in the trading context. First, the definition: “Leverage is the use of fixed costs in a company’s cost structure. The fixed costs that are operating costs (such as depreciation or rent) create operating leverage. Fixed costs that are financial costs (such as interest expense) create financial leverage.” (p. 171)
Leverage is a key component in assessing a company’s risk and return characteristics. “Leverage increases the volatility of a company’s earnings and cash flows and increases the risk of lending to or owning a company.” (p. 172)
Assume that two companies have the same net income, produce the same number of units, and sell each unit for the same price but have significantly different cost structures. Company A has a much lower variable cost per unit and a much higher fixed operating cost per unit than does company B. If unit sales drop, A will be harder hit than B; if sales rise, A will turn a higher profit than B. In brief, “The greater the fixed operating costs relative to variable operating costs, the greater the operating risk.” (p. 174)
Without going into the nitty-gritty of calculating the degree of operating leverage (in the simplest of terms it’s the percentage change in operating income divided by the percentage change in units sold), let’s skip to a general conclusion. “Industries that tend to have high operating leverage are those that invest up front to produce a product but spend relatively little on making and distributing it. Software developers and pharmaceutical companies fit this description. Alternatively, retailers have low operating leverage because much of the cost of goods sold is variable.” (p. 180)
Business risk is comprised of operating risk and sales risk (“the uncertainty with respect to the price and quantity of goods and services”). But investors also have to worry about financial risk, associated with how the company finances its operations. “If a company finances with debt, it is legally obligated to pay the amounts that make up its debts when due. By taking on fixed obligations, such as debt and long-term leases, the company increases its financial risk. If a company finances its business with common equity, generated either from operations (retained earnings) or from issuing new common shares, it does not incur fixed obligations. The more fixed-cost financial obligations (e.g., debt) incurred by the company, the greater its financial risk.” (p. 182)
Trust me, you couldn’t correctly answer questions about leverage on the CFA exam based on my summary. But I think it will give you some idea of the way topics are covered (sans math) in this very thorough book. It is valuable reading not only for grad students and CFA wannabes but also for sophisticated investors and professional managers who want to understand what corporate finance is all about.
Monday, April 16, 2012
Osband, Pandora’s Risk
Kent Osband explores both the philosophical underpinnings of financial risk management and its statistical rigor in Pandora’s Risk: Uncertainty at the Core of Finance (Columbia Business School Publishing, 2011). To accommodate those who want to pursue ideas without constantly tripping over formulas he has divided the book into two parts: the text proper and a 100-page, math-laden appendix. Naturally, I will focus on the first part of the book.
Osband, an economist by training who spent some time in academe and more in the financial world--most recently at Fortress before striking out on his own, is a challenging thinker. And that by self-description. He expects his readers to reject some of his ideas because, as he readily admits, “Some of what I’m saying is surely wrong; I just don’t know which some.” (p. 6) Theories about uncertainty are sometimes uncertain themselves.
Although Osband writes at some length about such concepts as money, debt, credit ratings, and regulatory oversight, these sometimes provocative discussions are intended to illustrate and advance his central arguments about the nature of financial markets. First, finance is characterized by uncertainty: “Finance deals, in effect, with dice that are not fair, might get switched between rolls, and are subject to freak interference. The objectively measurable risk, if there is one, gets shrouded with subjective uncertainty.” (p. 11) Second, “markets measure the beliefs about risk rather than risk itself. And risk changes often enough that beliefs rarely have time to converge on the truth.” As Osband contends, “Twentieth-century finance theory focused too much on risk, too little on changes in risk, and hardly at all on beliefs about changing risk.” (p. 90) Third, markets are learning machines.
Market risk can never be tamed. “Our predictors are bound to falter because of tiny doubts or errors that mount over time. … Just as the change in mean is proportional to the variance, and the change in variance is proportional to the skewness, so too the change in skewness is proportional to the kurtosis. All these measures are known as cumulants. In general, each cumulant changes proportionally to the cumulant of next higher order, which gets progressively harder to identify and control.” (p. 88) In physics the cumulant hierarchy is essential to understanding turbulence. Osband claims to be the first to apply it to beliefs and dubs it Pandora’s Equation.
VaR, we all know by now, is not the be-all and end-all of risk management tools. In fact, the author argues, “using standard VaR to tame financial risk is like using cigarette filters to tame cancer risk.” (p. 119) Curiously, for someone who is so completely at home in the world of statistics, Osband reaches out to discretionary traders to find a better way of estimating risk.
The answer lies in trading channels and the adjusted trading range (the vertical distance between the two channel lines). In general, Osband shows, “range-based estimators of volatility are far more precise than ordinary standard deviation estimators.” (p. 134) In particular, “the width of the current day’s trading channel can, in principle, estimate volatility better than ten days of closing prices, even when the regime stays the same.” (p. 136)
Osband asks a lot of his readers: they “ought to have a sound grounding in economic history, finance theory, and statistics. They should be interested in economic policy. They should enjoy mathematical modeling. They should love thinking outside the box.” (p. 6) Even for me, who is deficient on almost all fronts except perhaps the last, Pandora’s Risk was decidedly a worthwhile read. Just think how much better it would be for the qualified, or maybe I should say, “quant”-ified reader.
Osband, an economist by training who spent some time in academe and more in the financial world--most recently at Fortress before striking out on his own, is a challenging thinker. And that by self-description. He expects his readers to reject some of his ideas because, as he readily admits, “Some of what I’m saying is surely wrong; I just don’t know which some.” (p. 6) Theories about uncertainty are sometimes uncertain themselves.
Although Osband writes at some length about such concepts as money, debt, credit ratings, and regulatory oversight, these sometimes provocative discussions are intended to illustrate and advance his central arguments about the nature of financial markets. First, finance is characterized by uncertainty: “Finance deals, in effect, with dice that are not fair, might get switched between rolls, and are subject to freak interference. The objectively measurable risk, if there is one, gets shrouded with subjective uncertainty.” (p. 11) Second, “markets measure the beliefs about risk rather than risk itself. And risk changes often enough that beliefs rarely have time to converge on the truth.” As Osband contends, “Twentieth-century finance theory focused too much on risk, too little on changes in risk, and hardly at all on beliefs about changing risk.” (p. 90) Third, markets are learning machines.
Market risk can never be tamed. “Our predictors are bound to falter because of tiny doubts or errors that mount over time. … Just as the change in mean is proportional to the variance, and the change in variance is proportional to the skewness, so too the change in skewness is proportional to the kurtosis. All these measures are known as cumulants. In general, each cumulant changes proportionally to the cumulant of next higher order, which gets progressively harder to identify and control.” (p. 88) In physics the cumulant hierarchy is essential to understanding turbulence. Osband claims to be the first to apply it to beliefs and dubs it Pandora’s Equation.
VaR, we all know by now, is not the be-all and end-all of risk management tools. In fact, the author argues, “using standard VaR to tame financial risk is like using cigarette filters to tame cancer risk.” (p. 119) Curiously, for someone who is so completely at home in the world of statistics, Osband reaches out to discretionary traders to find a better way of estimating risk.
The answer lies in trading channels and the adjusted trading range (the vertical distance between the two channel lines). In general, Osband shows, “range-based estimators of volatility are far more precise than ordinary standard deviation estimators.” (p. 134) In particular, “the width of the current day’s trading channel can, in principle, estimate volatility better than ten days of closing prices, even when the regime stays the same.” (p. 136)
Osband asks a lot of his readers: they “ought to have a sound grounding in economic history, finance theory, and statistics. They should be interested in economic policy. They should enjoy mathematical modeling. They should love thinking outside the box.” (p. 6) Even for me, who is deficient on almost all fronts except perhaps the last, Pandora’s Risk was decidedly a worthwhile read. Just think how much better it would be for the qualified, or maybe I should say, “quant”-ified reader.
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