Tag Archives: apple

Will The Supreme Court Alter Your Utility Investment Strategy?

An obscure legal case could impact several electric utilities in states where wholesale power pricing is controlled by Regional Transmission Organizations, such as PJM Interconnect. Demand Response technology is at the heart of the issue. Is the Federal Government overreaching into the territory of state’s rights? The US Supreme Court SCOTUS could be intruding into your electric utility investment strategy. In an obscure case entitled Federal Energy Regulatory Commission v. Electric Power Supply Association (FERC v EPSA), SCOTUS will settle a long standing dispute between the FERC and power producers. At the heart of the conflict is the implementation and impact of Residential Demand Response (DR) technology. Pricing for electricity and hence the profitability of several electric utilities hang in the balance. Demand Response is the ability of specific electric appliances to turn off during times of high cost power, also known as “smart” appliances. Stated more clearly: Conservation implies whether to consume energy; Efficiency deals with how to consume energy; Demand Response concerns when to consume energy. Oilprice.com offers an interesting recap of the issue: Demand-responders argue that a megawatt saved is financially equal to a megawatt produced by a power generator. The power generators who comprise EPSA recognize that DR will hurt them, reducing both power prices and their profitability, to the benefit of consumers. Adding DR to a power market is the competitive equivalent of adding more generators. Either way, added competition lowers prices. The issue before the court is whether the FERC can compel regional power producers to pay consumers who reduce their use of power at peak times and if so, at what price. An interesting analogy could be the government program to pay farmers for not planting crops. In this case, power companies would pay consumers not to use electricity from the grid during times of peak demand. Daily peak demand varies based on location. For example, in Arizona where air conditioning is a large portion of demand, Arizona Public Service bills customers the following schedule: The plans billed on an off-peak and on-peak basis, with a super peak period in the summer billing months of June – August. Off-peak hours are weekdays from 7 pm to noon and all day Saturday and Sunday, as well as 6 major holidays; on-peak hours noon – 7 pm weekdays are billed at a higher rate; super-peak hours (3-6 pm weekdays during June – August) are billed at the most expensive cost per kWh. Save money when you use more energy on weekends and weekday mornings before noon or evenings after 7 pm. From their rate card , APS off-peak hours are billed at $0.05517 per kWh while on-peak rates vary from $0.19847 in April and $0.24477 in May, with super-peak costing $0.46517 in June. FERC Order 745 implements a program where power producers pay retail customers the going purchase rate for power not consumed, if the demand response is economical and helps balance the energy load on the Grid. The power producers contend this overcompensates as the variable cost to generate electricity is less than the retail price. In addition, the power producers claim the Order is an over-reach by the FERC as retail power rates are set by individual state utility commission boards, some of which are elected by the general population. In May 2014, the DC Federal District Court of Appeals ruled in favor of the power producers, resulting in FERC’s appeal to the SCOTUS. The Circuit threw out FERC Order 745’s compensation calculation and found that FERC has no jurisdiction over Demand Response, placing jurisdiction back on the states. The amount of money Demand Response could represent are not insignificant. The table below is an estimate from GTM Research for the forecast of the U.S. demand response market – with and without FERC Order 745. Source In a review of Con Ed (NYSE: ED ), I discussed the implementation of the “Clean Virtual Power Plant” where ED is developing a network of solar panels and electricity storage to supply the Grid with power when the solar panels are ineffective. If this becomes a viable business model in connection with higher Demand Response expansion and the FERC Order 745 of paying the highest prices for DR, wholesale power prices controlled by Regional Transmission Organizations, such as PJM in the Mid-Atlantic and eastern Midwest, could alter profitability for power producers. Which electric utilities could affected? GTM Research offers the following map of the highest kW replacement from DR, by Regional Transmission Organization: (click to enlarge) As shown, 68% of the Demand Response reduction in MW demand comes from areas under the jurisdiction of PJM and MISO, and includes a large swath of 31 states. Utilities with power generation in these states affected include Exelon (NYSE: EXC ), FirstEnergy (NYSE: FE ), American Electric Power (NYSE: AEP ), Dominion Resources (NYSE: D ), and Duke Energy (NYSE: DUK ). More information can be found in an interesting article published by utilitydive.com. Investors should keep an eye out for the ruling by SCOTUS concerning FERC Order 745. The impact could affect the profitability of many utilities selling wholesale power in various RTO jurisdictions. Author’s Note: Please review disclosure in Author’s profile.

Why PE Ratios Are Not A Good Measure Of Value

Summary PE ratios are commonly used as a metric to determine “value”. However, PE ratios are unreliable for a number of reasons and earnings actually have no correlation with valuations. Return on invested capital is a better measure of value and has significant correlation with valuation. We’ve pointed out the flaws in the price to earnings (PE) ratio many times before. Chief among these flaws is the fact that the accounting earnings used in the ratio are unreliable for many reasons: Accounting rules can change, shifting reported earnings without any real change in the underlying business. The large number of accounting loopholes makes it easy for executives to mislead investors. PE ratios overlook assets and liabilities that have a material impact on valuation. It should come as no surprise that empirical research shows accounting earnings have almost no impact on long-term valuations. No Correlation Between Earnings And Value If accounting earnings actually drove valuations, then companies with high EPS growth should command higher multiples, and companies with low or negative EPS growth should have lower PE multiples. As Figure 1 shows, this correlation is nearly nonexistent. Figure 1: EPS Growth Has Almost No Impact On Valuation (click to enlarge) Sources: New Constructs, LLC and company filings. The r-squared value of 0.0006 in Figure 1 shows that EPS growth over the past five years explains less than one tenth of one percent of the difference in price between stocks in the S&P 500. Stocks can see their PE multiples expand and contract in a manner that has almost nothing to do with changes in EPS, which makes looking at these metrics a poor indicator of valuation or future returns. The Market Cares More About ROIC Many other studies have found the same lack of correlation between earnings growth and stock price. Instead, we find that valuations tend to be driven largely by return on invested capital ( ROIC ). Figure 2 shows that ROIC is highly correlated with Enterprise Value/Invested Capital (a cleaner version of price to book). Figure 2: ROIC Is The Primary Driver Of Stock Price (click to enlarge) Sources: New Constructs, LLC and company filings. ROIC explains nearly two thirds of the difference in valuations between various companies. That means companies that can improve their ROIC are more likely to grow their stock price in the market. Short Term Vs. Long Term Drivers “But wait!” you might be saying. “I know accounting earnings have an impact on valuations. I’ve seen stock prices rise and fall dramatically based on a company’s quarterly earnings report.” This is true. It’s clear that headline numbers can have an immediate and sometimes dramatic influence on stock prices. The key word in that sentence is “immediate”. A big increase in EPS might drive short-term gains in stock prices, but it won’t create long-term value. To understand the cause of this divergence, you have to understand the different types of investors in the market. Brian Bushee from the Wharton School of Business wrote an excellent paper back in 2005 that highlighted the behavioral differences among institutional investors. His research found that: 61% of institutional investors are “Quasi-Indexers”. They hold many small stakes with low turnover, so they have little impact on market valuations. 31% of institutional investors are “Transients”. They have small stakes but a high turnover, so their high volume of trading can impact valuations in the short term. 8% of institutional investors are “Dedicated”. They take large stakes and hold them for a very long time. These are the investors that drive long-term valuations. A big earnings beat might cause a lot of “Transient” investors to buy that stock, pushing up the price, but most of these investors will sell their stakes not long after, pushing the price back down. They can create spikes, but their impact on the long-term performance of the stock is next to nothing. Instead, it’s that small percentage of “Dedicated” investors that are responsible for the majority of long-term performance. These are highly sophisticated individuals that take a long time evaluating stocks before taking large positions that they hold through bouts of volatility. Why You Have To Look At The Balance Sheet And Cost Of Capital The central flaw of the PE ratio holds true for many of the other common ratios such as: Enterprise Value/EBITDA Price to Earnings Growth (PEG) Price to Operating Cash Flow Price to Sales All of these ratios ignore the cost of the capital that the company uses to drive profits. To understand why cost of capital is so important, imagine this hypothetical scenario: you have an infinitely wealthy investor who is willing to offer you an unlimited source of equity capital. You take the money from this investor and put it in a low-yielding savings account. The more money you take from this investor, the more your interest payments, or “earnings”, will grow, but you’re not actually creating any value. In fact, by earning such a low return on that money compared to what they could earn elsewhere, you’ve actually destroyed value. The use of these flawed metrics perpetuates the irrelevant distinction between growth and value investing . Earnings growth without an ROIC above the weighted average cost of capital ( WACC ) destroys value, and value without growth limits upside. While ROIC is, by far, the most important driver of value, it is not the only factor. One must also consider revenue growth and duration of profit growth, i.e. growth appreciation period ( GAP ). These three drivers comprise everything that defines the profitability and, therefore value, of a company. PE and PEG are driven by these drivers, not the other way around. The same concept applies to companies that grow EPS by deploying capital at suboptimal rates of return. As we discussed in ” The High-Low Fallacy “, an acquisition can be accretive to earnings but destructive to shareholder value. Recent Danger Zone pick Expedia (NASDAQ: EXPE ) has managed significant EPS growth through $3.2 billion in acquisitions, but these acquisitions have actually hurt the long-term interests of shareholders by earning an ROIC that falls short of WACC. For that reason, investors need to be looking at ROIC rather than EPS, and they need to recognize that a PE multiple tells you next to nothing about the actual value of a stock. Disclosure: David Trainer and Sam McBride receive no compensation to write about any specific stock, sector, style, or theme.

An Unexpected Reason Behind This Strategy’s Outperformance

One of the great anomalies of investing: the historical long-term outperformance of certain smart beta or factor-based strategies relative to the broader equity market (think choosing stocks based on their valuations, momentum, low volatility or quality metrics such as profitability). For example, according to data from MSCI, the MSCI USA Minimum Volatility (USD) index’s Sharpe ratio, a common way to measure risk-adjusted returns, was 0.61 for the last ten years, above the benchmark MSCI USA Index’s 0.44 ratio. The persistence of smart beta strategies’ outperformance relative to the broader market is surprising, because it doesn’t line up with the idea of an efficient market, one in which investors shouldn’t be able to simultaneously buy and sell securities for a profit without taking extra risk (the so-called “no arbitrage” principle ). In other words, in an efficient market, equity portfolios exhibiting low volatility, for instance, shouldn’t be able to earn comparable returns to their higher-risk counterparts. It’s no wonder, then, that numerous academic and financial industry research papers have been written on this topic, and there are various explanations for factor strategies’ outperformance. According to BlackRock’s smart beta experts, including my fellow Blog contributor Sara Shores, this outperformance can generally be attributed to a risk premium, structural impediment or behavioral anomaly. In other words, the outperformance is to compensate investors for taking on what’s actually a higher level of risk, a reflection of market supply-and-demand dynamics or the result of common decision-making biases. Personally, no shocker for my regular readers, I think explanations for this return performance anomaly rooted in behavioral finance add valuable insights to the discussion. In today’s highly connected world, where we can follow each other’s every move via social media, where we’re bombarded by data from every angle – including information on other investors’ positioning and trades – and where it can be hard to tune out the noise, human behavior may be a stronger performance driver than ever. Put another way, I believe investor behavior likely has a lot to do with the strategies’ outperformance. Behavioral explanations focus on investors’ cognitive biases, and the human tendency to use simple rules of thumb to make quick intuitive decisions, with individuals’ collective decision-making mistakes translating into security price distortions. Here’s a look at explanations for the outperformance of four commonly used equity factors. Value: Value stocks are ones that appear cheap in light of their sales, earnings and cash flow trends. Their returns, according to proponents of the efficient market hypothesis, have to do with investors rationally requiring extra compensation for investing in value firms, which tend to be procyclical, have high leverage and have uncertain cash flows. From a behavioral finance perspective, the outperformance of the value factor may have to do with a common decision-making mistake: people’s tendency to look at recent data trends and believe those trends will continue . If investors extrapolate past positive sales or earnings growth data into the future, they may overpay for growth stocks and underpay for value stocks. As a result, the prices of growth stocks may become too high relative to their fundamentals, predicting future reversal and the outperformance of value stocks. Alternatively, some researchers believe people’s tendency to strongly prefer avoiding losses over achieving gains (known as loss aversion) can help explain this anomaly . They hypothesize that loss-averse investors may perceive value stocks as riskier than they truly are, given the stocks’ recent underperformance, and may therefore require a higher future return from these investments. Momentum: This factor focuses on stocks that have strong price momentum , i.e., they have performed well over the past 6-12 months, and strong fundamental momentum, i.e. their earnings have recently been revised upward by security analysts. One explanation for this factor’s outperformance: Investors rationally demanding a higher return for investing in momentum stocks, which tend to be highly correlated and are perceived to perform poorly in times of distress. The behavioral finance explanation for this equity factor’s outperformance, on the other hand, has to do with analysts and investors putting too much weight on their prior beliefs at the expense of new information, leading to slow dissemination of firm-specific information , delayed price reactions to news and price continuation. For example, if investors like a stock and believe it has high earnings growth potential, they tend not to immediately adjust their beliefs sufficiently in light of new negative information – an investing mistake arising in behavioral finance from ” the anchoring-and-adjustment heuristic .” In other words, investors frequently drive price trends by projecting past wins onto future investments, creating a ” herding effect .” Quality: Quality generally describes financially healthy firms with high return on equity, with stable earnings growth and low financial leverage. They can effectively be characterized as having less risk based on their fundamentals . Behaviorally, people may ignore these potentially profitable, yet also perhaps more boring, companies, and instead, veer toward potentially more exciting, yet also less stable, growth and lottery-like stocks (for example, because the more exciting stocks tend to be featured in colorful news stories). As a result, they may end up overpaying for the less-stable stocks, which quality strategies seek to avoid. This predicts future reversal and potential outperformance of quality stocks. Low volatility: The low, or minimum volatility, factor loads up on stocks with low volatility. Low volatility stocks’ excess returns may be rationally explained by leverage constraints. In the absence of access to leverage, investors may overpay for high-volatility stocks in an attempt to increase risk in their portfolios, potentially leading lower-volatility stocks to become more attractively valued and outperform in the future. From a behavioral perspective, these stocks’ outperformance may be due people’s tendency to overestimate small, and underestimate, large probabilities . The idea is that this tendency leads to a preference for lottery-like stocks with a small chance of a very high payoff, and this preference, in turn, drives up the prices of high-volatility stocks disproportionately, suggesting future underperformance. Further, overconfident individuals may veer toward riskier securities in expressing their outsized faith in their own investing and stock-picking abilities, exacerbating the anomaly. To be sure, while focusing on factor and smart beta strategies has historically, over longer periods of time, earned higher risk-adjusted returns relative to the broader market, there have been stretches, even long ones, when factor-based approaches underperformed (think value during the 1990s), according to data accessible via Bloomberg . Finally, while in an efficient market, these anomalies should diminish in size and ultimately disappear, a widespread belief in the factors’ outperformance may also become a self-fulfilling prophecy. This post originally appeared on the BlackRock Blog.