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Best-Now Energy Stock Wealth-Builder Picks, Seen By Big-Money Fund Managers

Summary How do we know what the big boys are buying, and how far they may chase the prices up before they bail out? Answer: Ask their helpers, the market-makers. Fund manager [FM] focus on energy investment candidates, sharpened by oil price declines, gets defined by their big-volume stock trade orders, stretching market capacity beyond normal limits. Market-makers [MMs] expand capacity, putting firm capital at risk temporarily, but only when their exposure is hedged by skillful arbitraging of related equity derivatives. What the MMs will pay for that protection, its embedded cost accepted by FMs to get their trades filled, confirms (by using Intelligent Behavior Analysis) how far prices might range. Those ranges provide sound logic and prior experiences to use in choosing between investment candidates in everyday capital commitment contests. What energy stocks are most depressed now? We apply Intelligent Behavior Analysis to all energy-related stocks (as well as over 2,000 other stocks and ETFs) every day, deriving price-change prospects, not past changes, for all on a directly comparable basis. Only then do we look at how expectations similar to the current-day have in the past matched up with their actual market outcomes. That gives us quality measures of odds of performance and credibility of current outlooks. Measures that help rank the attractiveness of many alternative investment choices by differing dimensions for investors with their own preference emphasis and current opportunity/need tradeoff situations. Given the huge price declines in Crude Oil, the basic common denominator of the energy business, and the likelihood of its getting overdone and rebounding, the stocks most directly in that line of fire are the Exploration & Production [E&P] companies. But that is not taken as a certainty, since what counts is what may be the likely change coming in securities prices, and those are always a product of investor perceptions. So we look at expectations of stock price changes for the various involved energy groups, including 1) international integrated major producers [IIMPs], 2) E&Ps, 3) well drillers [WDs], 4) other oilpatch service providers [OSPs], 5) refiners and mid-line processors [MLPs]. We attempt to separate those companies with predominantly 6) natural gas extraction involvements [NGPs] and 7) energy fuel transporters [PPLs] from those delivering 8) directly usable energy products [UTLs]. It is a big, diverse investment space. Today’s focus is on the E&Ps, nearly 60 of them that provide acceptable inputs to our analysis (out of over 100), displayed in a multi-dimensional rank of preferences common to investing wealth-builders, but containing evaluations of several aspects helpful to different priorities. Here are their current investment dimensions for us to explore and compare in thinking about whether the stocks should be bought here: Figure 1 (click to enlarge) What are these (column) dimensions? Where did they come from? Welcome to the products of Intelligent Behavioral Analysis. Intelligent, because the analysis looks at what discriminating (a desirable term) people do that makes sense, not what humans at large do that is erroneous. Unfortunately, the bulk of “Behavioral Finance” concerns itself with the latter activities. Instead, we are interested in what assistance can be learned from highly successful professionals, to improve our investing performance. Not in finding trivial mistakes people might make so that we can take advantage of them. Columns (2) and (3) of Figure 1 are the price range extremes implied by what market-making professionals are paying to protect the firm capital they must put at risk to be able to reach a balance between buyers and sellers of volume trade orders placed by their big-money fund management clients. Column (5) is the upside percentage price gain between the market quote at the time of analysis (4) and the top of the forecast range (2). Its complement, the downside forecast, is not shown in price change terms, but is indicated as a proportion of the whole forecast range in (7). That Range Index [RI] number is the percentage of the forecast range that lies below the current price (4). The smaller the RI is, the better quality may be that upside calculation in (5). The RI provides a useful comparison device between stocks with quite different characters, and allows us to look at past forecast experiences of individual stocks across time to better understand how each is likely to behave in coming days, weeks and months. We use it in (12) to determine which of the past 5 years’ 1261 market days of forecasts had an upside to downside forecast like today’s. That sample allows us to apply a simple but effective Time-Efficient Risk Management Discipline [TERMD] to the similar forecasts. The discipline is to “buy” the stock at a cost of the following market day’s close and hold it until the (2) top forecast price is reached or exceeded by a day’s close, or until 3 months (63 market days) beyond the forecast date have passed. If that holding period patience limit is reached the position is closed out, regardless of resulting gain or loss. This simple discipline produces the other column results. (9) is the average (geometric) percentage gain (including losses) of all the sample experiences. (10) tells how long they required capital to be committed, and (11) shows the annual rate of return that produced. The true measure of risks encountered in those experiences is in (6), the average of each of the sample’s worst-case price drawdowns. They indicate the points where emotion is most likely to interfere with an ultimate price recovery. (8) shows what the odds (out of 100) have been that price drawdowns were fully recovered by close-out time of the several positions. These dimensions look to the past as an indication of the quality of the present expectations for the future. Other comparisons may also be compelling. (13) compares (5) with (9) as a measure of how realistic the size of today’s forecast may be in light of what the past accomplished. (14) matches up today’s upside with yesterday’s experienced downsides. How useful are all of these complicated calculations? Each of these measures will likely have varied significance, depending upon the investor’s situation, goals, and preferences. There is no consideration of dividends here, so the approach is of limited use where periodic income receipts are the principal objective. In situations where dividend yields are high because current prices are low, this form of analysis may be helpful in recognizing why the stock’s price is so low, and whether a recovery is likely or even lower prices may be ahead. This style of analysis focuses on price change because it is the most dynamic and productive part of the risk-reward tradeoff, and is most impacting in programs of investment wealth-building. It looks to the effectiveness of capital employment in reaching accumulative goals with the objective of providing for some personal major capital expenditure, such as home acquisition, college expenses for self or offspring, medical emergency/catastrophe, or prolonged retirement. It recognizes that, especially in times like these of political suppression of interest rates, which seriously limit stock dividends and bond interest, the 20th-century emphasis on income investing has become seriously crippled. The volume of capital now required to generate income sufficient to cover everyday needs in retirement has doubled or tripled, depending on one’s standards. Unfortunately, many pension funds, particularly defined-contribution 401-k types, have not produced what is needed. A different approach may be required. What do the E&P stocks offer today? Other stocks? The better-priced two dozen of this set of 60+ stocks (the blue subtotal row) are being hedged by MMs in ways that say higher prices of +21% or more on average can be seen in 3 months or less. Their past experiences at current expectations levels, typically at over 100 instances, have not been nearly as bountiful, with average gains of only +4%, achieved in typical holding periods of two months, for an annual rate of price returns of +31%. The gains are net of losses in one third of their experiences. In those ventures typical worst-case price drawdowns of about -10% were encountered. Here is how the current upside forecasts for all ~60 compare with those price drawdowns: Figure 2 (click to enlarge) (used with permission) Stocks with price drawdowns as large as their upside forecasts would be on the diagonal dotted line. Those with larger upside forecasts are below the diagonal, with those in the green area offering upsides at least 5 times as large as their prior forecast drawdown experiences. The best E&P stock in this comparison at today’s pricing is [22], Memorial Production Partners LP (NASDAQ: MEMP ), offering an 18% upside in the face of prior worst-case average price drawdowns of only -4%. One caution, only 3 experiences in less than 3 years produced the drawdown data for MEMP. A stronger candidate might be Atlas Energy LP (NYSE: ATLS ) at [27], where 49 experiences in nearly 4 years support a +19% upside against -7% drawdown stresses. We can use this Figure 2 comparison of ATLS vs. MEMP to illustrate additional dimensions in what we call the quality of each one’s prospects first suggested by this appropriately-labeled picture of “Reward~Risk TRADEOFFS “. What are the ODDS for success? Column (8) of Figure 1 reports how often each of these two choices have in the past, when being appraised as they are now, produced a price gain. That “score” is put in “times out of 100” terms to make it easier to compare with other alternatives. MEMP scores 100, it has always been a winner. ATLS has been profitable “only” 7 out of every 8 ventures. But how frequently can success be enjoyed? MEMP’s perfect record occurred 3 times out of 419 market days or 7/10ths of 1% of the time, properly viewed, a rarity. ATLS on the other hand gave rewards 43 of its 49 times in 937 evaluations, or 5 times as often as MEMP. And how big were the rewards, how long did it take to earn them? In the 3 opportunities that MEMP put capital to work at an average of +12.7% each (1.127^ 3 or 1.431), ATLS could have had 15 chances to produce a loss-including net gain of +8.8% (1.088^ 15 or 3.544). That looks like no contest, even though the annual rate for MEMP (71%) is significantly higher than for ATLS (55%). To reflect on those differences among all of the candidates for potential investment in this set of stocks, we have assembled a logical “figure-of-merit” measurement to use as a ranking device. The numeric values produced have no easy description, and are useful mainly in ranking desirability between alternative choices where wealth-building is the long-term objective, to be achieved by repeated active management of investments. Its results are shown in column (15), and each subgroup of the E&P stocks are ranked thereby. It turns out that ATLS ranks second-highest with a figure of merit of 6.9 after Carrizo Oil & Gas (NASDAQ: CRZO ) at 10. But are there better still other choices? Take a look at the blue totals and averages lines at the bottom of Figure 1. They provide a comparison for individual stocks with the group, and with our large population as a whole. There is also the current appraisal of the SPDR S&P500 ETF (NYSEARCA: SPY ) as an investible approximation of the equities market. The E&P set of 59 stocks offers a typical upside of +22.6%, almost twice that of the population as a whole, and three times SPY’ +7%. But SPY has had only 1/3rd of the E&P set’s worst drawdown experiences. Of more interest, the E&P set’s win odds as a group are dreadful at 58 out of 100, worse than the population’s 2 out of 3 and SPY’s ~8 out of ten. And the E&P set’s net payoff experiences (9) at less than 1/2 of 1% reflect the win odds. Their aggregate figure of merit, -8.9, in (15) tells the sad story of adventuring in all these stocks, especially at present levels of expectations. The best-ranked 23, in the blue row subtotal above, at least manages to convert that FOM to a +1.3. But even that is not competitive with SPY at 2.9. A strikingly better choice at this price and point in time may be the SPDR S&P Oil & Gas Exploration and Production ETF, (NYSEARCA: XOP ). Its analysis results are shown just below those of SPY. XOP has a 5-year, 59 prior forecasts with less than 1/4th of its forecast range to the downside. Buys at today’s forecast balance have been profitable 78 out of 100, about the same as SPY, but generated net gains of +6.1% in 2 1/2 month holding periods for an annual rate of +34% and a figure of merit far better than any of the others. The embedded advantage of diversification via the ETF instrument is quite clear here. Conclusions Now please remember this is not an appraisal of which E&P has the best resources in the ground, or in the management suite. Nor does it care about earnings per share or PEG ratios, or debt/EBITDA calculations. They are all important, but they are already embedded in the perceptions of the game’s players who have the money muscle and the intent of taking actions to move prices. Act now, because tomorrow’s prices will likely offer different odds and different payoffs in different investments. Each day is a new opportunity set, and we only have from now on. And it is how prices move that makes the difference to wealth-building investors. Those who, as “Adam Smith” described in “the Money Game”, are intent on “cuddling Comsat” will find ample reason to ignore all our complexities. And the well-fixed 1% that the “Occupy Wall Street” crowd railed over has typically ample capital to apply to trivial current dividend and bond yields, sufficient to fund their retirements and bequest their inheritors. It is the far more numerous less fortunate investing public that has hoped their 401-k plans would do more than be a piggy-bank for tax-sheltered savings that now is largely faced with this second job of investing. They have learned that if you want something important done, you better supervise it closely and intently. For most, that has not happened, and now time is closing in on an uncomfortable future. The kind of analysis we do is intended to escape the self-serving biases of the deliverymen while encapsulating essential minutia by relying on their logical motivations to provide informed guidance on price prospects that can be found nowhere else. The results can never be perfect, since not everyone can “win” in a zero-sum game. But for those that are motivated by desire, need, and obligation, to make the effort to improve their odds and their perspective, substantial improvement in their investment results is still probable. For the other investors, well, the profits have to come from somewhere.

3 Promising India Focused ETFs

Summary India will overtake China’s GDP growth rate in 201 according to IMF and I believe that Indian equities are positioned for a multi-year bull market. Infrastructure is India’s biggest challenge as well as the biggest opportunity and I believe that the sector will perform well amidst lower interest rates in the foreseeable future. India’s consumption story has just commenced and with very favorable demographics, India’s consumption is likely to grow at a robust pace making the consumer related ETF attractive. While the focus has been on large companies in the recent rally in Indian markets, the small companies hold immense long-term potential and the small-cap ETF looks attractive. India is poised to overtake China’s GDP growth in 2016 according to the IMF and I have been bullish on India since the new government came to power in 2014. Recently, I wrote an article on IMFs GDP outlook for 2015 and 2016 where I opined that India and the US are the bright spots in the global economy and I also opined that India is likely to be the best performing equity market in 2015. I had also provided two stock picks and one ETF for exposure to Indian markets. In this article, I will be discussing three more ETFs that look very interesting considering a 2-3 year time horizon. I believe that these ETFs can serve as catalyst for the portfolio and investors need to diversify to India in order to boost overall portfolio returns. EG Shares India Infrastructure ETF (NYSEARCA: INXX ) The India Infrastructure ETF is designed to measure the market performance of companies in the infrastructure industry in India. For 2014, the ETF provided returns of 20% and I believe that the ETF will provide returns in excess of 20% in 2015. The reasons are as follows – The Indian central bank cut interest rates by 25 basis points recently and another 75-100 basis points interest rate cut is likely. Lower interest rates will trigger upside for the interest rate sensitive infrastructure sector. As the chart below shows, India needs infrastructure investment of nearly $1.25 trillion over the next 10-years and as the pace of investment grows under the new government, infrastructure companies are likely to outperform. (click to enlarge) The ETF has high exposure to large and very large infrastructure companies in India and therefore the exposure is with companies having strong fundamentals. The trailing PE ratio of the ETF holdings is 17.9, which is lower than the broader NIFTY PE of 22.2. Therefore, on a relative basis, the sector is still undervalued and has upside potential. For these strong reasons, the EG Shares India Infrastructure ETF is an interesting ETF to consider not only for 2015, but with a long-term investment horizon. EGShares India Consumer ETF (NYSEARCA: INCO ) As the name suggests, the India Consumer ETF is focused on the consumption theme. For 2014, the ETF provided an extraordinary return of 48%. While the same performance might not be replicated in 2015, the fund still looks very promising for strong returns over the next 3-5 years and a return of 15% to 20% in 2015 on a conservative basis. The Indian consumption theme has just commenced and Amazon (NASDAQ: AMZN ) clocking gross sales of $1 billion in the first year of operation in India is an indication of the potential the broad consumption theme holds in India. The PwC report is also upbeat on the media and entertainment sector in India for the next 5 years. Further, India is set to become the youngest country in the world by 2020 and the favourable demographics mean that India has huge potential when it come to consumption themes such as personal goods, automobiles, media and entertainment. The India Consumer ETF provides exposure to all these sectors of the economy with exposure to all the big players in the respective industries. I therefore expect the ETF to provide stellar returns considering a time horizon of 3-5 years. India Small-Cap Index ETF (NYSEARCA: SCIF ) I believe that the Indian Small-Cap Index ETF, which has provided returns of 43% in the last one year, is another excellent ETF to consider for 2015 as well as for the next 3-5 years. The above mentioned ETFs would give investors exposure to large or very large companies in India in the respective sectors. However, there is immense potential in some of the small or mid-sized companies in India. The growth for these companies can be robust if overall economic growth and sector growth is strong. With the ETF currently having 30.1% exposure to the financial sector, 21.1% exposure to the consumer discretionary sector and 17.6% exposure to the industrials sector, the outlook for the ETF will certainly be robust in 2015. In particular, the financial sector will surge on low inflation and rate cuts and both these factors will also impact the consumer discretionary and industrials sector. As of December 2014, the ETF had a very low PE of 11.24 and I believe that the ETF has strong upside in the coming quarters. In general, the broad market rally is led by large-caps followed by mid-caps and small-caps. Therefore, I expect the ETF to start moving significantly higher based on current valuations. Conclusion India is certainly one of the most attractive markets for 2015 and I believe that the Indian economy is on a path to sustained and robust growth in the next 5-10 years. Therefore, investors need to have Indian stocks in their portfolio and the ETFs discussed have the potential of providing 15% to 30% annual returns if the government keeps its promise on drastic policy changes in the coming months.

Risk Parity: What It Is, How It Works, And Why It Matters

Summary Many of the world’s top hedge funds already utilize strategies based on a new investing concept called “risk parity,” including Bridgewater Associates and AQR. Risk parity is not yet well understood by the mainstream, even though in theory it should significantly improve the Sharpe ratio of a passive portfolio. We present an overview of what risk parity means, and analyze whether the theory makes sense in practice, across various timeframes and environments. We also present initial techniques for building your own risk parity portfolio, using SPY, TLT, and GLD. Introduction to Risk Parity: Re-Thinking Risk and Return Traditional portfolio theory categorizes assets into buckets of risk and return. International equities are higher risk, treasury bonds are lower risk, and so on. Depending on your personal risk profile and time horizon, you are usually recommended some mix of the assets which match. For most people investing over the long-run and seeking an annual return of 6-10%, this usually means a portfolio dominated by stocks. Risk parity advocates believe this approach is fundamentally flawed. By limiting your investments to the asset classes which match your desired return, you wind up with a portfolio overexposed in certain areas and poorly diversified as a whole. As a simple example, let’s say you had a choice of two portfolios. Portfolio A is 80% stocks and 20% bonds. Portfolio B is 50% stocks and 50% bonds. Which portfolio is better diversified? Though Portfolio B is the obvious choice, few would recommend such a mix over the long-run, since bonds do not have a high enough expected return. Suspending disbelief for a moment, suppose that you could manipulate Portfolio B such that it had the same expected annual return as Portfolio A. Would you change your opinion? This is essentially the core premise of risk parity, which breaks down into three principles: An asset’s expected risk and return can be manipulated using modern day financial techniques. Assets can thus be ‘adjusted’ to have the same level of expected risk. A portfolio balanced by risk will be better diversified than the traditional portfolio mix, resulting in a higher Sharpe ratio over the long run. If this is really true, it would have tremendous implications. It would suggest that the majority of passive portfolios are managed incorrectly, and that equities as a whole are oversubscribed. Examining the Risk Parity Theory First, let’s better understand the theory, and how it differs from traditional portfolio management. Typically, investment options are viewed as static points of risk and return. The following exhibits the historical standard deviation (X-axis) and total annual return (Y-axis) across a number of familiar assets, using a variety of publicly available pricing information. These returns account for all dividends and interest. Note that these data points simply represent a span of time, and are not necessarily indicative of future returns and standard deviations. Still, they were true at one point and likely informed a generation of portfolio managers. Historical Annual Return vs. Risk (click to enlarge) Sources: Yahoo Finance , Federal Reserve , The Wall Street Journal , Energy Information Administration , Hedgewise Internal Analysis. If you had a preference for higher risk and were targeting an annual return of 10%, a traditional portfolio mix would primarily include the assets which fall above that line. In this case, domestic and international stocks are the only assets that qualify. Diversification may still be a consideration, but mostly as it relates to equities. For example, perhaps you’d spread your investments across small and mid-cap sectors. Bonds, however, simply don’t meet the return threshold needed. Risk parity poses a new way to view this data. Imagine that you could set the annualized return for every asset class to whatever level you chose, so long as the risk also scales accordingly (i.e., the Sharpe ratio remains consistent). In the example above, let’s say every asset had achieved a 10% annualized return at its corresponding level of risk. Historical Annual Return vs. Risk, at 10% Return Level (click to enlarge) This graph now essentially illustrates the Sharpe ratio of each asset, from highest (at the far left) to lowest (at the far right). While most people would assume that the S&P 500 had the best Sharpe ratio historically, bonds were actually the top performer. Now, if you still had a 10% target annual return, how would you construct the portfolio? Stocks no longer seem like the obvious choice, but it would also be hard to make a case for holding 100% bonds (especially with interest rates near zero). Naturally, diversification seems like the best bet, especially now that you no longer have to exclude certain assets because they have returns that are either ‘too low’ or ‘too high’. This is the key to the ‘Risk Parity’ portfolio, which assumes that constructing a better diversified mix will result in a better Sharpe ratio. Traditional Diversified Portfolio vs. Risk Parity Portfolio, In Theory (click to enlarge) Put another way, risk parity is just an attempt to find the diversified portfolio with the best Sharpe ratio. Strangely, this sounds like exactly the same goal of financial theory for the past 50 years. There’s even a name for it: it’s called the Efficient Frontier, and the concept has been around for ages. So why isn’t the traditional diversified portfolio already ‘efficient’? The Efficient Frontier The Efficient Frontier is a concept core to Modern Portfolio Theory, developed by Harry Markowitz and others in 1952. Its purpose is to help identify the ‘optimally diversified’ portfolio by studying all possible combinations of all individual assets and then isolating the set with the best Sharpe ratio. Applying this concept to the assets initially presented above, the graph would look something like this. Efficient Frontier Illustration (click to enlarge) Again, emphasizing that this is in theory over a particular span of time, the blue line represents all possible diversified portfolios using a varied mix of the individual assets. Inevitably, there will be a single point on the blue line where the Sharpe ratio is maximized, which represents the ‘best’ portfolio during that period. This portfolio provided the maximum return at the minimum level of risk. Risk parity is really seeking this same point. It is just presenting the hypothesis that this point will also be the portfolio in which risk is balanced equally across asset classes. In other words, risk parity agrees with the Efficient Frontier, and just provides a convenient method for weighting a portfolio to get close to the ideal. In theory, this all sounds pretty uninteresting. We should be able to use the Efficient Frontier to find the right way to diversify, and risk parity should recommend something similar. Since the ‘traditional portfolio’ supposedly relies on this same model, you’d expect the portfolio mix of 80-90% stocks and 10-20% bonds to represent the same. In reality, this is where it gets very interesting. Using historical data, either this theory is wrong, or it is being very misapplied in practice. Mapping the Efficient Frontier with Historical Data, 1954-2015 We can use historical data to map the Efficient Frontier and examine how the theory has translated to reality. This exercise ignores nuances like the fact that the Efficient Frontier may change decade to decade, but still provides a broad indicator for an optimally diversified portfolio over the long-run. Initially, we limit the data to just two asset class benchmarks: the S&P 500 and 10 year Treasury bonds. These benchmarks have the longest amount of uninterrupted historical data available, and are also reasonable proxies for the assets generally included in most passive portfolios. We broaden the perspective to additional asset classes later in the article. We constructed nine different portfolios composed of different mixes of these two benchmarks, from 10% stocks / 90% bonds to 90% stocks / 10% bonds. These portfolios are rebalanced monthly and include all dividends and interest payments. Then, we plotted the total return and standard deviation of each of those portfolios, in additional to the individual benchmarks, to present a ‘real version’ of the Efficient Frontier. Historical Efficient Frontier, S&P 500 and 10yr Treasuries, 1954-2015 (click to enlarge) Sources: Yahoo Finance, Federal Reserve, Hedgewise Internal Analysis. There are a few fascinating takeaways from this graph. The Efficient Frontier theory really does exist in reality – the curve is amazingly similar to what you’d expect to find. Diversification clearly has a dramatic effect on the Sharpe ratio of a portfolio. The Sharpe ratios of the above data points range from 0.80 to 1.31. Surprisingly, the maximum Sharpe ratio occurs in the 30% Stocks, 70% Bonds portfolio. This all makes sense so far, except for the incredibly odd fact that almost no one in the world has been holding a portfolio of 70% bonds and 30% stocks for the past 60 years. The traditional portfolio mix is almost exactly the opposite – even though it claims to be a result of the Efficient Frontier, which we just mapped with real historical data! Before analyzing what these results mean, let’s also apply the risk parity approach for comparison. Again with the benefit of hindsight, risk parity would suggest you simply adjust the risk of each asset to be the same. In order to make this adjustment, we need to first define what it means to have the ‘same risk’. Risk can be thought of as the probability that you will make or lose a certain amount of money. To have the ‘same risk’, then, would be a case where you had the same probability of making or losing the same amount of money across each of your investments. To quantify this, we define a new concept called ‘dollars at risk’ for each asset. ‘Dollars at risk’ is equal to the total dollar investment in an asset multiplied by the probability of making or losing money on that investment. We use standard deviation as a reasonable uniform measure of this probability. (Note: this raises lots of additional questions about how to measure risk, whether a standard deviation makes sense, and how to account for assets with a positive expected return, but those are more advanced risk parity topics beyond the scope of this article.) For example, a $100 investment in an asset with a 10% standard deviation would have $10 at risk. With that in mind, we can figure out what percentage weight of the S&P 500 and 10yr Treasuries would result in an equal amount of dollars at risk. Over this period, 10yr Treasuries had a standard deviation of 6.5%, while the S&P 500 had a standard deviation of 14.7%. This means you should have about $2.3 in bonds for every $1.0 dollar you have in stocks. Converting this to a portfolio mix, the result is a recommendation of 30% Stocks and 70% Bonds. That’s right – exactly the same as the result using the Efficient Frontier. In fact, a complex math proof would actually show this was bound to be the case when using historical data and only two assets. (Note: this would no longer be true with multiple assets that have different correlations, but more on that later.) So what’s the deal with the traditional portfolio mix? Applying the Efficient Frontier: Theory vs. Practice At this point, either the assumptions behind the Efficient Frontier are incorrect, or it has been applied incorrectly by the majority of the investing world. This is currently the subject of raging debate in high finance circles, so we will not dare to settle it absolutely. However, most supporters of risk parity point out reasons why the Efficient Frontier has been misapplied. First, there is the problem of matching up aggressive return targets with the Efficient Frontier portfolio. If you have a target return of 10%, equities are the only asset class that qualifies. However, this is only true if you are not using any leverage. Using leverage is another way of saying ‘borrowing money’. In simple terms, say you had $100 and a friend would also lend you $100 at no interest for a year (what a guy!). If you put this full $200 into Treasury bonds, your personal return, and potential risk, would now be double what it would have been without the loan. The Efficient Frontier model already thought of this, too, and defined a portfolio using leverage as something called the ‘Capital Market Line’. It recommends picking the portfolio with the maximum Sharpe ratio, and then using leverage to scale it to your desired return target. The Capital Market Line (click to enlarge) The green line represents a single, optimal portfolio that is levered up or down. ‘Levered down’ means you would lend money to someone (e.g., put it in a savings account) while using the rest to invest in the optimal mix. ‘Levered up’ means you would borrow money so you could increase your exposure to the optimal mix. Thus, you could achieve whatever return you want while retaining the very best Sharpe ratio. This sounds nice, but is not necessarily intuitive. An investment manager that recommended keeping half your money in a savings account would have a hard time justifying his value. Vice versa, an investment manager that told you to go to the bank, take out a loan, and invest it in Treasury bonds would also seem pretty batty. Yet, if Efficient Portfolio theory were really taking place, this should be pretty common. The fact that this isn’t a familiar concept, and that most people don’t consider using leverage in their portfolios, indicates that the Efficient Frontier model is being misapplied. After all, it’s much easier just to pick stocks and invest all your money than to worry about what leverage means and how to use it. Enter Risk Parity: the Efficient Frontier Makes a Comeback In essence, the risk parity movement is just advocating for the correct application of the Efficient Frontier, with a few extra ideas on how to make it easier to construct on a day-to-day basis. For example, one of the classic problems with the implementation of the Efficient Frontier is that you can only build it in retrospect. This isn’t particularly useful. Risk parity introduces the ‘dollars at risk’ concept such that you can use expected standard deviation and correlation to approximate the optimal mix. The risk parity movement has also helped to call out potential inefficiencies in the market, and is beginning to give rise to firms making the ‘real’ Efficient Frontier far more accessible. While in the next section we provide a brief ‘do-it-yourself’ guide, more advanced implementation requires a relatively high degree of financial sophistication and effort. Bridgewater Associates is one of the biggest hedge funds advocating this strategy, but only serves institutions with a minimum $250mm investment. AQR is another firm offering a ‘risk parity’ mutual fund, but has an annual fee of over 1% and a $5mm minimum investment. There isn’t a great reason it should be so expensive or hard to access, though, and a few start-ups are already working on solving that problem. If the next 60 years winds up resembling anything close to the last 60 years of investment performance, there’s good reason to believe risk parity will continue to gather momentum. Building Your Own Risk Parity Portfolio: A Practical Guide and Sample Using SPY, TLT, and GLD As promised, we’ll build a real portfolio using real stocks to test whether risk parity can truly yield a better Sharpe ratio. For the more adventurous among you, we also provide a framework for how you could generate such a portfolio on an ongoing basis. First, a few guidelines on the implementation. To build a risk parity portfolio, you need: A measure for the future risk of each asset. If you use standard deviation, you need to be wary that historical standard deviation may not be predictive of future standard deviation. A prediction for the future correlation between different assets. For example, 10yr bonds and 20yr bonds are naturally highly correlated. A high correlation reduces the benefits of diversification. Also, the same warning as point (1) about using the past to predict the future. The knowledge and ability to generate leverage for your portfolio. At higher levels of return, a risk parity portfolio almost inevitably requires leverage. We’ve provided more information on one way to do this here . As it applies to this example, we are using a few relatively simple assumptions to make this easy to follow. We are using only three assets – the S&P 500, 20yr Treasuries, and Gold. These assets are often uncorrelated to one another for various reasons. We are estimating risk using a historical standard deviation that covers all data available before the year 2000. We are then using that risk estimate to set the portfolio weight for the years 2000-2015. Finally, we are not accounting for live trading costs such as spreads or commissions. As a result, this simulation should be considered a hypothetical only, and does not represent real trading performance. That said, the SPDR S&P 500 ETF (NYSEARCA: SPY ), the iShares 20+ Year Treasury Bond ETF (NYSEARCA: TLT ), and the SPDR Gold Shares ETF (NYSEARCA: GLD ) have closely tracked these benchmarks historically. With these assumptions in mind, creating the risk parity portfolio is relatively simple. Here are the historical standard deviation estimates for each of the asset classes: Gold: 22% 20yr Treasuries: 8% S&P 500: 14% Using the same ‘dollars at risk’ concept discussed earlier, you can determine that you’d want a ratio of $1 gold : $1.57 S&P 500 : $2.75 20yr Treasuries. The equivalent portfolio mix is: Gold: 19% 20yr Treasuries: 52% S&P 500: 29% Now we can study how a portfolio using this exact composition would have performed from 2000 until today, rebalanced monthly with all dividends reinvested. We can also compare this portfolio to the traditional mix, and even plot both on the actual Efficient Frontier over this timeframe. Performance of the ‘Risk Parity’ Portfolio vs. Traditional Mix, January 2000 to January 2015 (click to enlarge) Source: Hedgewise Internal Analysis. ‘Risk Parity’ Portfolio vs. Traditional Mix on the Efficient Frontier, January 2000 to January 2015 (click to enlarge) Source: Hedgewise Internal Analysis. The risk parity portfolio didn’t just outperform, it entirely obliterated the traditional mix. Now, there will be shouts of disagreement. The past 15 years have marked one of the longest bond bull markets in history, so of course stocks look bad relative to bonds right now. But remember, the weighting we used came from data going all the way back to the 1950s, and that whole period wasn’t a bond bull market. (check out this article for more on bond market history and what to expect moving forward) There’s also the fact that this is the simplest implementation of risk parity possible. It doesn’t use any kind of predictive algorithm for standard deviation, and it only accounts for three asset classes. It also uses a very basic idea of correlation, which could be vastly improved to account for different economic environments. Yet, even if you didn’t do any of that, this simple portfolio has still outperformed the traditional mix. If you are currently uncomfortable putting most of your money in the stock market, the composition used in this example provides an immediately available ‘risk parity’ alternative. Conclusion Risk parity has been gaining momentum in the past few years as a new investment philosophy, but may really just be pushing investors towards the same Efficient Frontier that has been around for decades. While many of the concepts are somewhat unfamiliar, like a portfolio using leverage and predictive volatility, modern day financial techniques are making them much easier to implement without great difficulty. The theory has always made sense, and has always recommended these same techniques, but it’s easy to see why investment managers preferred the familiarity of stocks and ‘tradition’. Risk parity is not saying Modern Portfolio Theory is wrong. In some ways, it’s really just affirming that it has always been right, but may be misapplied due to a few bad assumptions. At the very least, investors deserve to question the traditional portfolio mix and to understand that alternatives exist. There’s also no need for these concepts to be shrouded in mystery and hidden behind the closed doors of hedge funds. The implications may be radical, but the concepts are not. Regardless of whether you agree with this strategy, it is raising important questions about portfolio composition that deserve attention. A great amount of theoretical and practical evidence suggests that risk parity will be a big part of our future. Disclaimer: Hedgewise is a start-up making the Risk Parity strategy more accessible to individual investors. This article does not constitute investment advice or an offer to invest or to provide management services and is subject to correction, completion and amendment without notice. Hedgewise makes no warranties and is not responsible for your use of this information or for any errors or inaccuracies resulting from your use. To the extent that any of the content published may be deemed to be investment advice or recommendations in connection with a particular security, such information is impersonal and not tailored to the investment needs of any specific person. Hedgewise may recommend some of the investments mentioned in this article for use in its clients’ portfolios.