Tag Archives: portfolio

The Dangers Of Non-GAAP Earnings

Summary Non-GAAP earnings are not quality measures of business success. We’ve identified over 18 items that are removed from GAAP earnings, many of which are standard operating expenses. The exploitation of non-GAAP earnings only makes analyzing a company a more difficult task. It’s no secret that non-GAAP earnings allow management to directly manipulate their performance metrics. Investors must look past non-GAAP metrics to protect their portfolios. While non-GAAP tricks may provide some short-term boosts to stock prices, eventually reality sets in and the true economics of the business rule the day. Why Non-GAAP Can’t Be Trusted We spend lots of time explaining how GAAP earnings are not reliable measures of corporate profits, and non-GAAP earnings are worse. Most of the time non-GAAP earnings are blatant misrepresentations of profits for the benefit of corporate insiders at the expense of regular shareholders . Case in point is one of Bill Ackman’s favorites: Valeant Pharmaceuticals (NYSE: VRX ). That stock has cratered recently on the heels of long overdue coverage of its questionable accounting practices, about which we warned investors back in July 2014 . While arguments may persist over the future of Valeant, one thing is clear: the company’s use of non-GAAP earnings, or as they call it, “cash earnings”, has only misled investors while serving executives in four distinct ways . Since management wants investors to focus on cash, not earnings, we find the discrepancy between Valeant’s “cash earnings” and the company’s true cash flows alarming. Figure 1 shows: while the company’s “cash earnings” have been highly positive and grown from $421 million to $3.55 billion from 2010 thru the latest trailing-twelve-months (TTM), free cash flow has been highly negative with a cumulative -$38.4 billion in losses over the same time frame. Cumulate non-GAAP earnings, during the same time, are $11.2 billion. Figure 1: Valeant’s Non-GAAP Tricks Have Tells For Those Who Look Closely (click to enlarge) Sources: New Constructs, LLC and company filings Non-GAAP Leads Investors Farther Away From The Truth About Profits The key point for investors to remember about non-GAAP earnings is they are like lipstick on a pig. They only cover up the ugly, and they cannot change it. The more managers have to adjust GAAP, the worse the situation is likely to end for investors. Non-GAAP tricks may work for a while, but they cannot disguise a bad business forever. Another example is Demandware (NYSE: DWRE ). After rising 160% from January 2013 to June 2015, DWRE is down 30% since we placed it in the Danger Zone in July 2015 . Figure 2 shows how much Demandware tried to fool investors by peddling non-GAAP earnings while GAAP and economic earnings were headed in the opposite direction. Only after the stock has cratered do we see non-GAAP earnings decline. Note that the current decline in non-GAAP sets management up for an easier comparison in subsequent reporting periods as well. Figure 2: Demandware’s Non-GAAP Creates Illusion of Profits (click to enlarge) Sources: New Constructs, LLC and company filings Expenses Management Excludes To Create Non-GAAP Earnings Because non-GAAP earnings are entirely at the discretion of management, any number of items can be removed from traditional GAAP earnings. The following are just some of the items we have come across that companies remove from GAAP earnings to calculate non-GAAP or “adjusted earnings”: Stock based compensation Payroll tax expense related to stock based compensation Compensation expense related to contingent retention bonuses Acquisition related expense Depreciation and amortization Foreign exchange effect on revenue Purchases of property and equipment/ property and equipment purchased under capital lease Unrealized gain/loss on fuel price derivatives Deferred loan costs associated with extinguishment of debt Gains on divestiture Preopening expenses Management recruiting expenses Management and consulting fees General and administrative expenses Litigation expenses Integration costs Restructuring costs Gross profit deferred due to lease accounting As should be clear, companies are removing not only a large amount of items, but also items that should most certainly be included when determining a business’s profitability. We find it hard to accept any argument for the removal of certain, natural costs of doing business like consulting fees, recruiting costs and compensation costs. Details On How Companies Exploit Non-GAAP Earnings The following examples are just a sampling of how management is creating the illusion of higher profitability. Wex, Inc. (NYSE: WEX ) – Click here to see the non-GAAP reconciliation Wex adds back certain acquisition expenses, non-cash tax adjustments, stock based compensation, and amortization of intangible assets to calculate adjusted net income. The company also removes certain income items such as the unrealized gain on derivatives and gain on divestitures. When totaled in 2014, the adjustments actually caused adjusted net income to be lower than GAAP net income. While this may seem counter intuitive, this is not a problem because the magnitude of beating targets is not nearly as important as just beating targets when using non-GAAP earnings to boost executive pay. In addition, this lowered adjusted earnings number will set up an easy comp in 2015. Marketo, Inc. (NASDAQ: MKTO ) – Click here to see the non-GAAP reconciliation Marketo is very transparent about all the items it removes from GAAP earnings and actually breaks down how each item is removed from cost of revenues, gross profits, operating expenses, and net income. However, this doesn’t detract from the fact that Marketo removes these items to appear less unprofitable than they truly are. Marketo removed $25 million in stock based compensation in 2014, or nearly 17% of revenue to derive non-GAAP net income. Tesla Motors (NASDAQ: TSLA ) – Click here to see the non-GAAP reconciliation In addition to some of the other items mentioned above, such as removing $156 million in stock based compensation in 2014, Tesla treats its non-GAAP calculation in a unique manner. Rather than just removing expenses to derive a non-GAAP net income, Tesla adds back deferred profits due to lease accounting. By adding this profit to net income, Tesla was able to report a non-GAAP net income of $20 million in 2014, compared to a GAAP net loss of $294 million. Demandware ( DWRE ) – Click here to see the non-GAAP reconciliation As shown above, Demandware uses non-GAAP net income to appear profitable when GAAP income and economic earnings both would prove otherwise. In 2014, Demandware removed $26 million in stock based compensation (16% of revenue) and $3 million in compensation expense related to contingent retention bonuses. Overall, Demandware reported a GAAP loss of $27 million in 2014, despite a non-GAAP profit of $4 million. How Non-GAAP Could Harm Your Portfolio Look at the stocks in Figure 3 for a few more examples of how bad your portfolio can be burned if you trust companies using misleading non-GAAP results. Figure 3: Non-GAAP Only Delayed The Inevitable (click to enlarge) Sources: New Constructs, LLC The stock market can be a dangerous place if you do not do your homework. Wall Street and corporate insiders are not afraid to trick you, and I think we have shown they have the lawful right-of-way to trick you. Investors need to do their homework in order to make the right investments consistently. To learn even more about the Dangers of Non-GAAP Earnings, watch our recent webinar and ensure you don’t get burned by non-GAAP earnings. Disclosure: David Trainer and Kyle Guske II receive no compensation to write about any specific stock, sector, style, or theme.

What You Don’t Own

By Andy Hyer What a year it’s been for Energy. Its rout can be seen in the chart of XLE shown below: Price return only, not inclusive of dividends. Updated through 12/8/15 However, it is not just 2015 where Energy has been weak. Consider the relative strength chart below of the Energy Sector SPDR ETF (NYSEARCA: XLE ) versus the S&P 500 (SPX): (click to enlarge) Price return only, not inclusive of dividends. Updated through 12/8/15 As shown above, Energy has been weaker than the S&P 500 for the majority of the time since June 2008 – although the worst of the relative performance has clearly come in the last year or so. When a sector is weak, a relative strength strategy seeks to underweight that sector. After all, what you don’t own is every bit as important as what you do own . Consider the chart below of the Energy exposure in the Dorsey Wright Technical Leaders Index (used for the PowerShares DWA Momentum Portfolio ETF (NYSEARCA: PDP )): As of 10/1/15 This index is constructed by taking a universe of approximately 1,000 U.S. mid- and large-cap stocks and ranking them by their PnF relative strength characteristics. The top 100 stocks make it into this index. Each quarter, the index is reconstituted to kick out any stocks that have lost sufficient momentum and to replace them with stronger names. One of the unique characteristics of this index is there are no sector constraints. If a sector is weak, it may have little or no exposure in the index. This quarter is now the 4th quarter in a row where PDP has had zero Energy exposure. Much is made of how momentum strategies seek to own the “hottest” stocks. Perhaps, more should be made of momentum strategies seeking to avoid the biggest losers. In the end, that matters every bit as much. The relative strength strategy is NOT a guarantee. There may be times where all investments and strategies are unfavorable and depreciate in value. See www.powershares.com for a prospectus on PDP.

Dynamic Asset Allocation

Identifying the right asset classes and proportions to diversify is difficult for an investor. The scientific methods for diversification, namely Markowitz’s Mean Variance Optimization have not been practically applicable. Investing in all asset classes evenly at all times will reduce risk but lower returns too. A diversification strategy that reduces exposure to asset classes trending down long term has historically outperformed the stock market both in terms of overall return and volatility. Diversification is widely accepted as the most important aspect in building a portfolio. For investors looking to accomplish their long term financial goals, diversification helps reduce risks and volatility as market and economy go through various expansion, contraction cycles. However the specifications on how much to diversify and in what asset classes are often vague and left to the judgment of an individual investor. There aren’t many established or prevalent public tools that would take investor characteristics as an input (for example risk tolerance, time horizon etc.) and output a recommended model portfolio. A recommended portfolio that provides a list of specific asset classes (mutual funds, ETFs or stocks) and propose percentage weights for investor to review and consider as a starting point. Further, the primary goal for diversification is looked at as risk minimization or reduced volatility in your portfolio. That comes at a cost since lower risk leads to lower return. Could diversification lead to lower risk and yet outperform the market in terms of returns? This article proposes a diversification strategy that has historically outperformed the market, with lower drawdowns and can be used by investors to build a long term asset allocation strategy. Background: Let’s start with understanding the history and state of financial theory on diversification. Harry Markowitz’s Mean Variance Optimization (MVO) method developed in 1952 forms the core backbone of financial theory on diversification. The core insight of Markowitz’s work was that by combining assets that are negatively correlated (i.e. they typically move in different directions) one can reduce the overall volatility of a portfolio without impacting the expected return. Markowitz provided a mathematical algorithm that can use this insight to generate the ideal portfolio (named as Markowitz Efficient Portfolio ) with lowest risk/volatility possible. This was a powerful algorithm and Markowitz rightfully won a Nobel Prize in 1990 for it. Unfortunately even though this was a powerful algorithm, it has not turned out to be practically applicable (Reference papers: 1 , 2 , 3 ). It entails complicated mathematics sensitive to minor changes in the input and requires accurate future forecast on potential assets. Historical returns are very poor forecasts. Variations of Markowitz’s algorithm like Black Litterman model have been proposed to overcome these limitations, however even these require sophisticated inputs (like asset market weightings, volatilities and correlations) that may not be easy to provide for by an average investor. Diversification Strategy Options: To build a model that is simple to understand, compute and specific in terms of output recommendations, we start with Markowitz’s key insight: incorporate assets that are negatively correlated in a portfolio. However correlation between two assets can change over time and rather quickly so we don’t want to assume future correlation will be same as past. Instead we incorporate asset classes that have the potential to have negative future correlation. Thus we include assets in the portfolio that are fundamentally or significantly different from each other. To illustrate this with an example, let’s start with Stocks, Gold and Bonds as three available asset classes that are fairly different from each other. Let’s pick a mutual fund or index from each of these to start with diversification in asset class itself and not be exposed to individual stock risk. I picked the Vanguard 500 Index Fund (MUTF: VFINX ), the V anguard Long Term Investment Grade Fund (MUTF: VWESX ) and the Franklin Gold and Precious Metals Fund (MUTF: FKRCX ) to represent stocks, bond and gold in this test portfolio. We could have picked ETFs like the SPDR S&P 500 Trust ETF ( SPY), the SPDR Gold Trust ETF ( GLD) and the i Shares 20+ Year Treasury Bond ETF ( TLT) but those have historical data only since 2002. Using VFINX, VWESX and FKRCX as proxies for stock, bond and gold allowed me to back test on historical data going all the way back to 1985 from Yahoo Finance. The simplest diversification without making any future assumptions on expected returns would be to allocate equal one third percentage to each asset class. How would this constant equally diversified portfolio would have worked as compared to staying 100% invested in stocks? Overall, stocks would have generated better returns but they’d have also seen larger volatility as seen in the higher drawdown in table below. The graph below shows how the two portfolios would have grown and the table shows annualized return and drawdown numbers for the duration. (click to enlarge) (click to enlarge) Looking at the above numbers, a simple strategy of equal breakdown across multiple asset classes provided a good start for reasonable growth and yet lower drawdowns. However, could we have generated better returns than being in stocks alone? We can take advantage of being in an asset class rather than an individual stock. Individual stocks can go through wild up and down swings, but asset classes do show longer bull – bear trend. For example, the graph below shows that “Gold – Precious metal equities” have been a 4 year long bear market since 2011. Similarly U.S. stocks went through 2-3 year bear market in 2000 and 2008. (click to enlarge) One improvement that we can make in our diversification strategy is to exclude any asset class that is in its longer term bear market and equally invest in all other asset classes. An asset class can be marked in bear market if its 52 week return is less than -2%. We could use any other indicator too like simple moving average or 52 week minima drop. They will all work. The important thing is to classify it as a bear and exit or reduce your sizing in that asset class. Any heuristic that improves the accuracy of classifying an asset class is in bear market will improve the strategy further. In our proposed dynamic allocation strategy we simply reduce allocation to zero on an asset class which has lost more than 2% over the last one year. All other assets are held in equal proportions to make up 100% of portfolio and balanced weekly. For simplicity we have assumed balancing weekly has zero costs, in reality transaction costs may necessitate balancing over a longer time period like 1 or 3 months. Back testing this strategy on historical data since 1984 returns an annual return of 11.87% with an average drawdown of 3.73%. The worst case drop from a 52 week high was 31.35%. So an outperformance both in terms of returns as well as lower volatility. (click to enlarge) (click to enlarge) Conclusion: Investors who manage their portfolio on their own, can use the learning above to build their own long term portfolio management strategy. They can extend the above proposed strategy to cover a comprehensive set of asset classes to include all major sectors like real estate, commodities etc. as well as international economies. Including more asset classes should help reduce risk but too many asset classes will decrease the overall return. Investors can try a variations where instead of equal allocation across all asset classes, sectors that are booming have higher weighted allocation versus sectors that are underperforming. Catching a long term bull market in an asset class and over indexing on those asset classes is likely to help improve returns. They can adjust the maximum level of weighting in a single asset class based on their risk tolerance to limit over exposure in a single asset class. Investor can thus build their own diversified portfolio, test its historical performance on returns and drawdown and thus be equipped to make smarter investing decisions for the long term. Disclaimer: The author does not have any holdings in the mutual funds (VFINX, VWESX and FKRCX) used to test described diversification strategy. These funds have been used only for illustrative purpose and the author is not making any recommendations to buy them. We use a proprietary asset allocation technique across global stocks, bonds, commodities, commodities stocks, mutual funds, ETFs and other investment options in our portfolio.