Tag Archives: game

Worry, Worry, What? More Worry?

Summary Once again, stock prices seem headed down. How far? How long? Why? A competent answer to these questions calls for perspective as to where we are now, and where we have been, both recently and at prior extremes. Who can provide that perspective of the past? Our best candidate(s) are folks who bet big money, frequently and constantly, on the near future. Who can answer the questions of the future? Our best suggestion is: “No one, definitively, because surrounding circumstances keep changing.”. But continual monitoring of the near future prospects compared to similar data at prior extremes may be a help. Folks who bet big money constantly on future stock prices They are the market-making [MM] community, acting in the opportunity for their own profit by servicing the intentions of clients managing billion-$ equity investment portfolios. What makes that community different from their clients, besides their forecast time horizon, is that as a group they bet directly against one another at the present moment, and the market for that activity presents useful expectations information. The clients, meanwhile are making bets against one another, but with ill-defined forecast time horizons, in markets not addressed to anything but immediate price discovery – that price which will provide a supply~demand clearing transaction of the moment. One that will simply queue up the next transaction challenge immediately following. Expectations of the transactors are not revealed except as to their preference for cash in comparison to the transaction subject. Where the transactors’ cash has come from, or is going to is an un-answered question. The lack of an answer prevents any further analysis or clues from this line of pursuit. In contrast, it is almost perfectly known where the market-makers cash has come from and is going back to. It is from their own capital (and funding) resources, to be used in providing market liquidity time and again, as the opportunity for them to profit presents itself. It needs to be kept liquid, as unencumbered as possible so it repeatedly can be put to work. Market liquidity is provided both by the MM firms’ block trade desks temporarily positioning (owning, net long or short) the momentary imbalance between buyers and sellers, and by other MM speculators (proprietary trading desks) willing to protect the MM positioners by selling them price-change protection insurance in a hedging deal. The cost of the price-change protection is a market-liquidity cost that is borne by the MM client-fund stock transactors. It is wrapped into in the bid-offer spread required by the to-be-consummated block trade. Both buyers and sellers in the negotiated transaction are impacted by their acquiescence to the transaction. The size of that cost, and the way the hedge deal is structured tells the story of what expectations the market-making community holds about what the clients are likely to do next with the subject stock. They are in communication with their clients constantly during every trading day, as they usually have been on several fronts for many years. The MMs have a pretty good idea of client intentions and action targets, despite client attempts to be obscure. The MM community augments that understanding with the instantaneous communications from a world-wide, local people-supported, 24×7 information-gathering system designed to keep them a step ahead, or at least not materially behind, the clients. We systematically translate the MM hedging actions into near-term price range forecasts. Forecasts with time horizons of the periods required to unwind the several types of derivative security contracts that may be involved in the hedge transactions, often no more than two to three months. Those price range forecasts have the great benefit of simple comparability. The extremes of the forecasts, in conjunction with the current market price, define upside and downside price change prospect limits. The balance between those, as portions of the whole range, are useful indications of near-term future price changes for each subject. Our common denominator for that we label the Range Index [RI]. The RI numeric is the percentage of that subject’s current forecast range between the current price and its lower extreme. RIs can span from over 100 (above the top future forecast) to negative numbers (below the lowest likely price forecast) although such extremes are not common. The smaller the RI, the larger is its upside proportion. For that subject a low RI implies the stock is cheaply priced at this point in time. Let’s check out to what extent there may be some forecast ability in the RI for a given security. We choose as a good example the ProShares UltraPro DOW30 (NYSEARCA: UDOW ), because as an ETF tracking the Dow Jones 30 index it is based on stocks actively being traded by major investment funds. Because the ETF is highly (3x) leveraged, its price changes through time are accentuated and easy to recognize. We will take every market day of the last 5 years, and from each starting point measure by how much UDOW’s price changed progressively, week by week, 5 market days at a time, out to nearly 4 months – 16 weeks, or 80 market days. Those results will be shown in a table with a blue central row that is the average price change trend for the ETF over the last 1261 market days – 5 years. To make comparisons easier between time periods of different lengths, all of the averages will be stated in annual compound growth rates, or CAGRs. Then to see what effect might be provided by knowing what the current-day RI was, we will exclude the likely most frequent RIs, the ones where the upside to downside price change proportions on cheaper days are between 1:1 and 2:1, and for the more expensive forecast days are 1:2. Corresponding RIs would be 33 to 50, and 50 to 66. In our table of price change calculations we will aggregate all the price changes in days with forecast RIs of 33 or lower into a row just above the blue average row. For all the days having RIs above 66 we will create a row of average price changes just below the blue average of all days. Please see Figure 1. Figure 1 (click to enlarge) By continuing this process we can fill out our table of annual rates of price changes at different levels of beginning forecast RIs from zero to one hundred, with those beyond contained in the 100:1 and 1:100 rows. Just don’t get overconfident; it’s not shooting fish in a barrel. The data of Figure 1 are averages of annual rates, meaning some are larger, some smaller, and some are even negative where the data are positive (profits), or may be positive where the data is negative. Figure 2 tells what proportion of the experiences indicated by the #BUYS column are in fact positive. For the whole 5 years’ days, that is a bit better than two of every three measures which offer a long investor the chance to make money. But a loss is taken in every third. Figure 2 (click to enlarge) Yes, the nearly half of forecast days (553 of 1258) with twice as much or more downside price change prospect (1:2 RWD:RSK) have worse odds for gain then the average, as well as negative payoffs. But far better PAYOFFS under better ODDS exist for the long-position players. That doesn’t make investing in UDOW an easy task, even with the MMs help. They’re not GOD. One troublemaker in the assignment is TIME. A great philosopher (at least) once observed: “You only have from now on.” No do-overs in most stock investing. It may be interesting, reassuring, (or scary) to study history, but we can’t go back. Do it NOW or tomorrow, or not at all. But yesterday is out. Another troublemaker was identified by the great philosopher, POGO: “We have met the enemy and he is us.” Stock investing is a more challenging game than chess, because moves by the pieces are not tightly defined. There are rules, and over time they may change some, usually well announced. But the true challenge is in trying to guess what the other side will do, and when they may do it. Each side attempts to anticipate the other, some more stridently. That, combined with time, keeps the game alive. Here is a two-year illustration of how the expectations for coming prices of UDOW by the MM community (the vertical lines) have been followed by actual market quotes (the heavy dots splitting each vertical) Figure 3 (click to enlarge) (used with permission) The colors reflect the imbalances between upside and downside price prospects in each forecast, as defined by the contemporary market quote. When current price is at or close to the bottom of the range, green is seen, and at the top, red. Caution lights appear when price is nearing the top of the range. That guidance is helpful, but not perfect. Please note the “go” signals in mid-August this year before UDOW dropped from mid-60’s to mid-40’s. Still, we perform our standard behavioral analysis on the actions of the MM community because it provides another forward-looking evidence of how significant players in this serious game evaluate not only the other investor players, but all of the fundamentals that go into their decisions and probable actions as well. And by providing a disciplined analysis of their conclusions in a wealth-maximizing portfolio setting, we have an historical background of whether and when the behavioral analysis has provided useful guidance. Here is the update of that analysis for UDOW to Monday’s close, November 16, 2015. Figure 4 (click to enlarge) (used with permission) Figure 4 provides a recalculation of MM forecasts indicating a Range Index of 26, or some three times as much upside price change prospect as price drawdown exposure. The row of data between the pictures tells that past UDOW 26 RIs, 38 0f them in the past 5 years of daily forecasts, have actually experienced worst-case price drawdowns averaging -10.3%. Of those 38, 34 or 89% of them, recovered in price over the next 32 market days sufficient to produce profits (along with the 4 losers) of +6.6%, a CAGR of +65%. Conclusion UDOW is an interesting gauge of market sentiment since its price is driven by a market index of 30 huge-cap stocks making up a part of market capitalization that cannot be ignored in market valuations. Its structured price leverage forces additional attention to the ETF, and conversely back from the ETF onto the market as a whole. No question of which is driven by the other, but they must accompany one another. The perspective UDOW provides at this point in time is that UDOW is an odds-on ETF likely to provide a capital gain at a high rate of CAGR over the next 2-3 months. The question of whether a better opportunity may soon be present is ever present, since prior experiences at present forecast levels have seen -10% further price drawdowns. In terms of unleveraged market indexes, that might be -3% to -3.5%. But there is no sign that a more serious concern is present among folks continuously and seriously addressing the matter. Save powder for a better shot, or go for a bird in hand? It’s your capital; it should be your call.

The 4 Dimensions Of Value Investing

Summary Value investing can be much more than just calculating the intrinsic value of a business. The more traditional value investing tends to focus only on quantitative metrics, such as P/E, P/B, EV/EBIT or EV to maintenance cash flow. Buffett and his followers introduced a new value investing approach which is more scalable and in longer term, which I call “quality-value investing”. Besides quantitative metrics and qualitative factors, there is the 3rd dimension: the certainty or the information edge. Finally, the 4th dimension is not about monetary gains, but about the emotional gains in the investment process, as well as an investment in the investor himself/herself. The Two Camps in Value Investing When Benjamin Graham wrote his famous book “The Security Analysis” 82 years ago, he built the foundation of value investing approach. This book became a timeless piece, and is still being followed everyday by many famous value investors. Interestingly, although all the value investors seem to be under the same title of “value investment”, their approaches could be dramatically different. One major and obvious difference is the focus on quality. Graham had his deep belief that any forecast is unreliable, and therefore we should always fallback to the “facts”, which are the numbers we have seen in the past. Apparently, this is a pure quantitative approach. On the other hand, Buffett and his followers started to deviate from Graham’s traditional approach, and started to focus on the quality side of the business. As Buffett said, he would rather invest in a great business at a fair price, than invest in a fair business at a great price. In reality, deep value investors (Graham’s followers) would not only invest in a fair business, but also often invest in a poor business with a poor management. Another difference is on the time horizon. While value investors are usually the long term investors, and have much longer time horizon than the other market participants, Buffett usually has even longer time horizon than the deep value investors. As he said, his favorite holding period is “forever”. However, many famous deep value investors clearly said they would sell when the stock price reaches its intrinsic value. Some of these deep value investors even criticized Buffett’s saying, or at least didn’t really understand the logic behind it. In my understanding, this difference comes from the roots of different focus. Deep value focus on pure quantitative metrics, such as P/B, P/E, EV/FCF, EV to maintenance cash flow, current ratio, debt ratio, growth rates, and dividend yield. There are two benefits of this kind of pure quantitative approaches: 1. It is objective. In investing, one of the biggest enemies of investors is their emotion, or their behavioral bias. Not only we are emotionally influenced by the price actions, the changes of fundamentals and recent events can also have a great influence on the perception of investors. Because of this influence, investors tend to focus more on the recent events, or more on the outlooks, and less on the historical facts. This kind of over-reaction or behavioral bias is often the reason why deep value investing worked. There are numerous research papers which showed that simple quantitative metrics such as P/B or P/E can generate a significant edge for investors. The pure quantitative approach is not limited to Graham’s formulas either. The famous “Magic Formula” only had two quantitative metrics in it: P/E and ROE. 2. It is easy to be well diversified. Since it is a pure quantitative approach, it doesn’t really need to analyze the business or understand the industry. Therefore, it is very easy to pick many different stocks and achieve high diversification. While I acknowledge the merits of deep value investing, it is also my belief that the pure quantitative approaches will be less effective in the future. This is because information is more available today, and there are more quantitative algorithms being created by backtesting the historical data. It is also easier to implement these investment approaches in an automated algorithm, which takes emotions completely out of the game. In other words, the competition on the deep value approach will be more intensive, and any deep value investment opportunity you can find is more likely to be a value trap, especially when that stock is a large cap or mid-cap. That said, Graham’s basic philosophy is still valid today: we have to focus on facts and avoid any over-confidence in our ability to forecast. This fact makes the first dimension (the quantitative metrics) to be the most important and most basic element of value investment. Without these metrics, we should not talk about “value” at all. While the quantitative metrics are important, we should also not underestimate the importance of qualitative factors (the 2nd dimension), such as the competitive advantages, the management’s ability and integrity, the pricing power of a business, and the industry outlooks. Not only these qualitative factors can give us more assurance of the business’ future, it also makes an exit strategy less important. As we all know, it takes a lot of work to understand an industry and a business. If we have to constantly find new opportunities after exiting the previous investment, it could be very tiring and it also increases the risks of misunderstanding the new opportunity. Beyond that, there is also the impact of taxes when you realize the capital gains. That is why Buffett said his favorite holding period is forever. After all, it is very hard to find a really good investment opportunity, and it takes a lot of effort to truly understand it. Plus, if you know you have to find the best exiting point, you will be tempted to sell too soon. When you increase your investment time horizon, it can also help to create a more scalable strategy, since you only need to slowly build the positions, and not worry too much about the need of liquidating the position with the best timing, or responding to any events quickly. The longer time horizon can also make qualitative factors much more important than quantitative factors. For example, if a stock is being traded at P/E 5, a deep value investor might get it and fetch a quick 100% gain within 1-2 years when the sentiment recovers. However, when you have to hold onto a poor business for 10 years, the poor business, even if it is not bleeding (losing money) every year, could be destroying value by reinvesting earnings with very low ROIC. So over a long period of time, any discount can be superficial and eventually get wiped out by the poor economics or poor management of the business. That is why when Buffett said “if you don’t want to hold it for 10 years, you shouldn’t hold it for 10 minutes”, many deep value investors couldn’t agree, simply because that philosophy doesn’t really apply to many deep value cases. On the other hand, for a good business with a good manager, even if you have to pay some premium for it, because of the good ROIC and high growth, your “sin” will often be more than covered by the good economics of the business when you hold it for many years. For example, a lot of investors were hesitating to buy Berkshire Hathaway (NYSE: BRK.A ) (NYSE: BRK.B ) 20 – 30 years ago, when its P/B was more than 2. But at least in retrospect, that seemingly overpayment would be more than paid off later. The same thing can be said for many great businesses in their early stages, such as Microsoft (NASDAQ: MSFT ), Google (NASDAQ: GOOG ) (NASDAQ: GOOGL ), and Wal-Mart (NYSE: WMT ). Even today, when Berkshire Hathaway is already too big to grow very fast, the smart capital allocation along with many high quality world class businesses in its holdings make it an attractive investment for people who seek stable growth. Therefore, I believe it still deserves some premium in its valuation. For sure, today’s deep value investment can be much more than just a pure quantitative strategy. Deep value investors do often understand the business very well, and they often pay attention to the quality factors as well. However, their primary focus is still on the quantitative metrics, and they don’t require the business being a high quality business and don’t often require the business having a good management. Furthermore, even Buffett himself still invested in some low quality businesses from time to time. For example, after he had remained pessimistic on newspaper industry for many years, he still purchased many small newspaper businesses a couple of years ago, knowing that these businesses would slowly decline and could eventually die. Still, when the valuation was attractive from a discounted cash flow perspective, he felt that was a sensible thing to do. The 3rd Dimension: Certainty and Edge If the quantitative metrics can give us a view of the past, the qualitative factors should give us a “flavor” of the future (of course, investment is all about estimating the future). However, these two views can be totally unreliable if we don’t know enough about the business and the industry, and all our calculations could be based on imagination rather than facts. That is why we need the 3rd dimension: the certainty and the information edge. Every investment thesis is about finding and filling-in the missing pieces of a big puzzle. Investment, like any other business, is also highly competitive. Good businesses are unlikely to be sold cheap, and cheap ones are very likely to be value traps. The key about solving this big puzzle is about collecting as much information as you can. It is also about interpreting the basic information you collected, which requires some insights of the economics and the industry. In order to beat the market, we should also have an information edge, some unique insight or deep understanding that can help us to find the value discrepancy, and help us to maintain the confidence when facing emotional challenges. Buffett likes to call this as “The Circle of Competence”. It is a field where we can have an edge, a field where we can have more certainty than the other investors. After all, the term “uncertainty” is not equivalent to “true randomness”. When you try to guess the color of a ball in a box, that color is not a “true” random variable, since it is already fixed and known to some people, but just not known to you because you don’t have that information. Therefore, “certainty” is directly related to how much information we have. One obvious question following this is: how can we invest if we don’t have any circle of competence? Or what if all the stocks in my circle of competence are too expensive? I think there are several answers to this question: The first and the most important method to tackle this problem is to learn as much as you can. After all, nobody started with a circle of competence. It is all about constant learning over one’s lifetime. Learning has also become increasingly easier in this internet era as more and more information becomes easily available online. If we don’t have time to learn a new field, we could also simply wait until the opportunity shows in our existing circle of competence. Or try to copy a “superinvestor”, but I am not sure if that approach really works or not. Finally, less certainty in an investment means that we need to rely more on diversification, which again falls back to the more quantitative approach I have mentioned above. As I said, this approach may still work, but I would expect its effectiveness gets weaken over time. The 4th Dimension: Emotional Rewards While investors are normally only concerned about the potential monetary rewards in any investment, there is another hidden element in the investment process which is just as important: the emotional rewards. As a human being, the ultimate goal an investor seeks or should seek is always the “happiness”. While the investment profits can help us to get more happiness, we shouldn’t forget that much of our happiness is not related to money at all. Much of our pleasure directly comes from a constructive process. Much like a businessman who enjoys building his/her business, investors like to find the next gold mine or solve the next grand puzzle. It is a game they love. But beyond that, investors are also partners in a business. They are the owners of a business, even if they may only own a small fraction of it, and may not have any control on the business decisions. Nevertheless, just like a fan of a NBA team, the investors can enjoy seeing the business growing, and enjoy seeing the constructive process of building a business. This also makes a “quality-value” approach more attractive than a deep value approach. When you invest in a high quality business with a good manager, you often end up being happier in your investment life. You would worry less about management cheating on you or destroying value. There are less uphill battles against a deteriorating industry trend, or poor economics of the business. There is less energy spent on a proxy fight with a bad management. Besides the emotional rewards, there is another important side effect coming out of happy investing: when you truly like a business or a industry (not just because of the potential profits), you will spend a lot more time to learn about that business and industry. This will boost your edge in the 3rd dimension: your information edge. More importantly, this will become a very rewarding learning process that will be beneficial in the long run. In other words, when you invest on something that is truly interesting to you, you also invest in yourself by increasing your expertise in that industry. This benefit can be as significant as any monetary gains you could get from the investment itself, because just as Buffett said, “the best investment is always investing in yourself, it is the investment in education.” Summary The reason I call these 4 elements as 4 dimensions is that they are mostly uncorrelated factors. As investors are busy hunting their next best opportunity every day, it is also important to sit back and think through the process on a very high level. After all, it is more important to head in the right direction than moving at an amazing speed.

PDP: Gutsy Momentum Investing For People Braver Than Me

Summary This ETF has a high expense ratio but they are running an aggressive momentum strategy that requires higher costs. The sector allocation combined with a momentum strategy would be enough to put me on edge when I wanted to sleep. If an investor wants to follow momentum investing, this seems like a fine choice. For that investor, I would suggest grabbing some utilities to get a better balance. Investors should be seeking to improve their risk adjusted returns. I’m a big fan of using ETFs to achieve the risk adjusted returns relative to the portfolios that a normal investor can generate for themselves after trading costs. One of the funds that I’m researching is the PowerShares DWA Momentum Portfolio ETF (NYSEARCA: PDP ). I’ll be performing a substantial portion of my analysis along the lines of modern portfolio theory, so my goal is to find ways to minimize costs while achieving diversification to reduce my risk level. Expense Ratio The expense ratio is .63%. I tend to be very frugal with my expense ratios, so I’m less than thrilled with the expense ratio. Of course, portfolios that require more active involvement from managers are going to generally have higher ratios. The question becomes whether the managers will be able to regularly deliver enough performance to justify that higher ratio. Largest Holdings The following chart shows the largest holdings for the fund: The allocations here are fairly interesting, but you expect that momentum portfolios are going to end up having a very strange allocation. It’ll be interesting to see how the various momentum ETFs perform over a sample size of several years during which investors are well aware of the strategy. The presence of ETFs buying stocks based on the stock price having already appreciated seems like it could end up distorting the performance. If the strategy was highly successful, then I would expect whichever ETFs designed their systems to move first to be the winners in the game since their purchases would further drive up prices and encourage other ETFs to buy into the same funds. All around momentum investing is strange beast to me. I’m just a fundamental analysts at heart with a focus on finding the intrinsic value of a company and figure out which factors will be headwinds or tailwinds. Sectors The following chart breaks down the allocation by sector: The consumer discretionary sector has a fairly massive 31.8% weighting. My first thought here is that I would be scared to hold this ETF if this prolonged bull market turned into a bear market. I’m not convinced that we will see that kind of huge drop off in the economy in the next few years because low interest rates can do a great deal to keep market prices high, but I don’t think I have the risk tolerance for this sector allocation. Utilities That utility allocation is credibly low. For an investor opting to use momentum investing and an ETF like PDP for a major position in their portfolio, I would suggest looking to a low fee utility index to add some diversification to the portfolio as a whole. That is, of course, unless you prefer having more volatility in your portfolio. I know some investors are going to be thinking: “Utilities are sensitive to interest rate movements so I don’t want to hold them when interest rates are clearly moving higher.” There is certainly a correlation there. The utilities may suffer if rates increase, but I think they’ll stay low much longer than some investors believe. The macroeconomic environment just doesn’t provide the situation necessary for a sustained increase in rates. I’ve been positioning my portfolio to hold plenty of instruments that are sensitive to interest rates because I really don’t see any high probability paths for interest rates to move higher. An Interesting Option It would be interesting to see a momentum investing strategy that placed caps on sector weightings so that the portfolio wouldn’t end up this heavy on one sector. I have nothing against the consumer discretionary sector; I just prefer the consumer staples for my portfolio. I feel the sector is substantially stronger at resisting a sell off when the market is crashing. All sectors would be likely to fall, but I would expect fewer losses in consumer staples. Conclusion For investors that are interested in momentum investing, this is one option to get that technique into your portfolio. In my opinion the risk of using this strategy is compounded by the aggressive consumer discretionary allocation. In a prolonged bull market this fund should be a solid choice. I’m not predicting a bear market in the near future, but I’m also not willing to make a play that is this aggressive. I just don’t think I’d sleep as well with such an aggressive allocation. If investors opt to use this ETF, I’d suggest checking at least monthly on the sector allocations so the investor can modify their portfolio weights as desired. If investors don’t adjust their portfolio in response they may find themselves going massively overweight on individual sectors.