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Smart Beta And The Portfolio Construction Puzzle

The portfolio puzzle The Rubik’s cube has become a popular metaphor for the marketing teams of ETF providers. With good reason. For each client there’s a portfolio construction puzzle to be solved with building blocks, representing geographies, sectors, asset classes, factors and styles. There has been rapid expansion from providers of ETFs tracking main-market indices, with the largest institutional providers capturing the lion’s share of flows, owing to their ability to deliver on four key ETF governance criteria — consistency, liquidity, transparency and, of course, price. This means that ETFs for main market cap-weighted indices are increasingly commoditized. After all, there doesn’t seem to be anything overly smart about replicating market beta, other than the smartness of saving on fees relative to ‘closet-tracker’ active funds. Traditional cap-weighted index investing is a preference: either out of philosophy or necessity. Innovation Means Smarter? Hence R&D of institutional investors, index providers and ETF manufacturers alike has focused more on “smart beta.” This has triggered a slew of innovation – both superficial and substantive. At a superficial end, age-old alternative weighting strategies (e.g. value indices that screen stocks for low book values, or dividend-weighted indices) have been re-branded as being “smart.” In these cases, for “smart” read “non-market-cap weighted.” In fairness, this rebranding is part of broadening of alternative weighting strategies that are factor-based. More substantively, research programs such as EDHEC-Risk Institute’s Scientific Beta have been instrumental in promoting fresh thinking in the field of both factor-based and risk-based smart beta strategies. Factor-Based Approach As a result, providers are focusing on making building blocks smarter. Instead of relying on the ‘traditional’ factor of market capitalization for index inclusion, smart beta indices (and related ETFs) look at alternative factors: book value, dividend yield, volatility, for example. In that respect, the FTSE Russell 1000 Value Index launched in 1987 is probably the oldest factor index on the block. More recent factor indices are stylistic: Both iShares (Oct-14) and Vanguard (Dec-15) have launched global equity factor ETFs focusing on liquidity, minimum volatility, momentum and value. The sophistication of factor-based index construction will continue to increase with the increase in data availability and computing power. Risk-Based Approach Portfolio strategists meanwhile can apply quantitative rules-based approaches to portfolio construction, creating static or dynamic asset allocation strategies from a growing universe of both cap-weighted and alternatively weighted index tracking funds. These strategies — such as maximum Sharpe, minimum variance, equal risk contribution and maximum deconcentration — offer an alternative to the standard but troubled single period mean variance optimization (MVO) approach. MVO’s limitations The single-period MVO approach remains the traditional bedrock of very long-run investing in normal market conditions where the sequence of returns does not matter. However it runs into difficulty in the short-run when markets are non-normal and sequence of returns matters a lot. So unless you are a large endowment with an infinite time horizon, or perhaps can afford to invest for yourself and your family without ever needing to withdraw any capital, relying entirely on the MVO approach for asset allocation gives false comfort. For cases where there are constraints that challenge the MVO model – due to multiple or limited time horizons, expected capital withdrawals, risk budgets, and unstable risk/return/correlation profiles of asset classes (collectively known as real life) — portfolio construction requires a smarter, more adaptive approach that observes, isolates and captures the reward from shifting risk premia over time. Risk-based portfolio strategies attempt to achieve this and are designed to offer a liquid alternative approach to investing that is uncorrelated with traditional single-period MVO strategies. What’s the Problem to Solve? Whether assessing factor-based ETFs or risk-based ETF strategies, at best these new developments all seem very smart. At worst it’s just a bit different. However, as ETFs get smarter and the strategies that combine them become more sophisticated, there’s a risk that the key question in all of this gets lost in an incomprehensible barrage of Greek. The key question for portfolio managers nonetheless remains the same. What client outcome am I targeting? What client need am I trying to solve? For portfolio strategy, whether using a discretionary manager that relies on judgment, or a systematic rules-based approach that relies on quantitative inputs, the key client considerations remain return objective, time horizon, capacity for loss and diversification across asset classes and/or risk premia. Broadening the Toolkit A portfolio strategy has little meaning without an objective that focuses on client outcomes. Factor-based ETFs and risk-based ETF portfolio strategies offer an alternative or additional set of tools to help deliver on those outcomes, in a way that is systematic, liquid and efficient. Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article. Additional disclosure: This article has been prepared for research purposes only.

Crash Imminent Warning Removed By NIRP Crash Indicator

The NIRP Crash Indicator’s signal changed from its pre-crash or crash imminent Orange to its Yellow cautionary reading level on the close of the market on May 9, 2016. The signal had gone from Yellow to Orange prior to the U.S. stock market’s opening on April 28. During the eight day period that the indicator’s reading was Orange ended on May 9, 2016, the S&P 500 went from 2095.15 to 2058.69, a decline of 1.7%. The signal went to Orange from Yellow because the exchange rates of the yen versus both the euro and the US dollar had stabilized during the week ended May 6, 2016. Additionally, both the euro and the dollar appreciated by more than 1.1% versus the yen on Monday May 9, 2016. Please note: For the NIPR Crash indicator to change from the crash imminent Orange or a crash Red reading to Yellow requires that the exchange rate between the yen and dollar be stable for an extended period of time or that the dollar and euro advance significantly versus the yen. An increase in the indicator’s reading from Yellow to Orange requires a steady advance or a significant one day advance for the yen versus the dollar. The NIRP Crash Indicator was developed in February 2016, from my research on the Crash of 2008. My research revealed the metrics that could have been used to predict the Crash of 2008 and its V-shaped reversal off of the March 2009 bottom. See my Seeking Alpha “Japan’s NIRP Increases Probability of Global Market Crash” March 4, 2016 report. The metrics are now powering the indicator. Information about the NIRP Crash Indicator and the daily updating of its four signals ( Red: Full-Crash; Orange: Pre-Crash; Yellow: Caution; Green: All-Clear) is available at www.dynastywealth.com . Since inception the NIRP Crash Indicator’s signals have proven to be very reliable. Throughout the entire month of March, the signal for the NIRP Crash Indicator had remained at the cautionary Yellow and the S&P 500 experienced little volatility as compared to the extremely volatile first two months of 2016. For the month of March, the S&P 500 increased by 4%. The indicator’s reading went from Yellow to Orange after the market’s close on Friday April 1, 2016 . For the following week ended April 8, 2016, the S&P 500 experienced its most volatility since February of 2016 and closed down 1.5% for the week. The signal’s second Orange reading occurred before the market’s April 28, 2016 open. From the Thursday, April 28 open to the Friday, April 29 close, the S&P 500 declined by 1.2%. The S&P 500 (NYSEARCA: SPY ) and the Dow 30 (NYSEARCA: DIA ) ETFs closing at their lowest prices since April 12, 2016 on April 29. See also my SA post “NIRP Crash Indicator’s Sell Signals Very Reliable for April 2016″ May 3, 2016. The primary metric powering the NIRP Crash Indicator are sudden increases in volatility for exchange rates of the yen versus the dollar and other currencies. The significant appreciation in the yen versus the dollar in 2008 accurately predicted the crash of 2008, and the recent declines of the markets to multi-year lows in August of 2015 and February 2016. In my April 11, 2016 ” Yen Volatility Is Leading Indicator For Market Sell-Offs ” SA post and my video interview below entitled “Yen Volatility Causes Market Crashes”, I provide further details on the phenomenon of the yen being a leading indicator of market crashes. The rationale for the for yen volatility or its appreciating significantly versus the dollar being a leading indicator of crashes is because the Japanese yen and the U.S. dollar are the world’s two largest single country reserve currencies. For this reason, the yen is the best default safe-haven currency utilized by investors during any U.S. and global economic and market crises. When crises unfold, historically the U.S. dollar — by far the world’s most liquid and largest safe-haven currency — is susceptible to dramatic declines until the storm has passed. Savvy investors know that the U.S. is, unquestionably, considered the world’s leading economy and markets. They know that upon a crash of the U.S. stock market, the initial knee-jerk reaction would be a simultaneous crash of the U.S. dollar versus the world’s second leading single-nation currency. The yen is currently the default-hedge currency. Even though the euro, arguably, ranks with the U.S. dollar as the world’s top reserve currency, it is not the preferred hedge against the greenback. The euro is shared by 19 of the European Union’s member countries that have wide-ranging social and economic policies, and political persuasions. For this reason, and also because Japan is considered to be one of the most fiscally conservative countries on the planet, the default currency is the yen. The U.S. dollar does not experience extended crashes versus the Swiss franc and the British pound during times of crises because each of the underlying countries has economies much smaller than Japan’s. From my ongoing research coverage of the spreading negative rates and the devastating effect that they could potentially have on the global banking system, the probability is high that the major global stock indices including the S&P 500 will begin a significant decline by 2018 at the latest. My April 11, 2016 article entitled, “Negative Rates Could Send S&P 500 to 925 If Not Eliminated” , provides details about the potential mark down of the S&P 500 likely being in stages. I highly recommend you also watch my 9 minute, 34 second video interview with SCN’s Jane King entitled “Why Negative Rates could send the S&P 500 to 925”. In the video, I explain the math behind why the S&P 500’s declining to below 1000 may be the only remedy to eliminate the negative rates. The video also reveals some of my additional findings on the crash of 2008. Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.

Exits: Know When To Hold ’em, Know When To Fold ’em

Originally published March 29, 2016 We all focus a lot of attention, perhaps too much attention, on where to buy and sell a market, on where to enter trades. Today, let’s spend some time looking at the other side: where are you getting out? Some categories are useful here, and they are not complicated. First, we have exiting at a loss, or at a profit. (This is not necessarily the same as saying exiting on a stop or at a profit, because a (trailing) stop can often be a profit-taking technique.) Both of these can then be divided into two more categories: Exiting at the initial loss or a reduced loss, and profit taking against a stop or at a limit. Let’s spend a few moments thinking about each of these. Initial stops The most important think about initial stops is that you have one. Though so many trading axioms and sayings do not apply universally, one that does is “know where you’re getting out before you get in.” For every trade, you should have a clearly defined maximum loss, and you should work hard to make sure that loss is never exceeded. In practice, bad things will happen. You will have the (hopefully rare) experience of a nasty gap beyond your stop, and sometimes will see losses that are whole number multiples of your initial trade risk. (I remember one lovely -4.5x loss in Yahoo (NASDAQ: YHOO ) years ago. Though these events are rare, they are also a good reminder of we do not, for instance, risk 10% of our accounts on a trade. A 45% loss on a single trade would be a disaster, but 4.5x a reasonable risk (1%-2%) is merely annoying.) Initial stop placement is an art in itself, but, in general, I think too much of the material on the internet probably uses stops that are too tight. I’ve never seen anyone trade successfully with stops that are a few ticks wide. For me, initial stops usually end up somewhere around 3-4 ATRs from the entry. These stops are wide enough that many traders find them uncomfortable, but simply reducing position size to manage the nominal loss is an obvious solution. Taking losses is perhaps the most important thing you will do as a trader, so do it well and do it properly. Click to enlarge Reduced stops We have defined that initial “never to be exceeded” (ideally) stop at trade entry, but many traders find it effective to move that stop rather quickly. Another possibility to consider is the time stop, in which we take steps to limit the position risk if the trade does not move in some defined time. There are many possibilities here, ranging from tightening the stop, to reducing the position, to exiting completely. I have made a good case for not reducing the position at a loss because it effectively “deleverages” your P&L in the “loss space.” (See the chart above, which is drawn from pages 242 and 243 of my book.) Personally, I’ve found that simply taking whole, but smaller than initial, losses is more effective, but your experience may be different. A key point here is that all of this – entry, exit, position size, moving stops, taking targets, re-entries, adding to positions, partial exits, etc. – all of this must work together. You change one piece, and the whole system will change. This is why some techniques may be effective in some settings but not in others. To simplify, think of reduced stops as being moved when the trade does not immediately go far enough in your favor, and consider the use of time stops. Profit targets Profit targets are usually limit orders, as opposed to stops (which, not surprisingly, are usually stop orders). In general, I find that it makes sense to have profit taking limit orders working in 24-hour markets, though we may not wish to work stops in the same after-hours environments. People sometimes make mistakes or do silly things in after-hours, and I’m always happy to provide liquidity at the right prices. There is a school of thought that says that all trades should simply be exited at profit targets, while there is a conflicting school that says we must let our winners run. How to reconcile these two approaches? I think the answer lies in trading style. For trend traders, we must let our profits run. As countertrend traders, we must take quick profits, usually at pre-defined areas. I have not found chart patterns or points to be any more effective than simply setting a target 1x my initial risk on the “other side” of the entry. Many people like to use pivots or trendlines, but I’ve executed well tens of thousands of trades (one of the advantages of spending years as short-term trader) and have simply not found these to be that effective. (For intraday traders, highs and lows of the day do deserve respect.) Consider the tradeoffs in simplifying your approach. Trailing stops Trailing stops can be managed in many ways, and I have found these to be very effective in many types of trading. We can trail at some volatility-adjusted measure, and there are even times we trail a very tight stop, effectively hoping to be taken out of the trade. This is a good problem to have: sometimes you may trail a stop at yesterday’s low, and be shocked as the trade grinds in your favor week after week – there’s nothing to be done in these cases but be forced to stay in the trade and make more money, but guard against hubris: many of the times this has happened to me; I have been properly positioned into a climax move. When these moves end, they often end dramatically, so simply ring the register and step away from the market. Putting it all together This is certainly not an exhaustive list of all the possible ways to exit trades, but it will get you started in the right direction. I find that combining these techniques, using a pre-defined target for part of the trade, trailing the stop on the rest, and moving quickly to reduce initial risk on my rather wide initial stops, this works very well for swing trading the markets I follow. Consistency certainly matters, but consistently doing something that works will, not surprisingly, lead to consistently losing money. Make sure you have a well-designed system with an edge, and that the system is one you can follow in actual trading. Make sure you trade with appropriate size and risk, and that you monitor your performance accordingly. With these guidelines, you can be a few steps closer to developing your own system and approach to trading.