How I Created My Portfolio Over A Lifetime – Part IV
Summary Introduction and series overview. The parties involved in a flash crash. The mechanics of a flash crash and how unrelated activities can intensify the problem. Summary. How I Created My Portfolio – Part IV: Lifting The Hood on a Flash Crash Introduction and series overview The parties involved in turning a normal crash into a flash crash The mechanics of a flash crash and how unrelated activities intensify the problem Summary Back to Part III [ A] Introduction and Series Overview This series is meant to be an explanation of how I constructed my own portfolio. More importantly, I hope to explain how I learned to invest over time, mostly through trial and error, learning from both my successes and failures and those of others who chose to confide in me. Each individual investor has different needs and a different level of risk tolerance. At 66, my tolerance is pretty low. The purpose of writing this series is to provide others with an example from which each one could, if they so choose, use as a guide to develop or better organize their own approach to investing. You may not choose to follow my methods, but you may be able to understand how I developed mine and proceed to create a process more suitable for your own needs. The first article in this series is worth the time to read, in my opinion and several of the many comments made by readers, as it provides what many would consider a unique approach to investing and some very foundational concepts that I learned along my journey. Part II introduced readers to the questions that should be answered before determining assets to buy. I spent a good portion of that article explaining investing horizons, including an explanation of my own, to hopefully provoke readers to consider how they would answer those same questions. Once an individual or couple has determined the future needs for which they want to provide, he/she can quantify their goals. If the goals seem unreachable, then either the retirement age needs to be pushed further into the future or the goals need to become more attainable. In the next two articles, I then explained my approach to allocating between and within difference asset classes and summarized by listing my approximate percentage allocations as they currently stand. In this article, I will try my best to explain my understanding of a flash crash and how disparate entities, all working in their own best interests and unknowingly, enter into activities that tend to increase or decrease volatility in equities. I hope to keep things simple and easy to understand, but, this being a relatively complex subject, if my efforts to unravel the chain of events does not lift the fog as well as expected, please do not hesitate to ask questions in the comments section. Since we have experienced only two flash crashes in recent history (May 6, 2010 and August 24, 2015), there is not enough data to determine exactly what happens to create one. It is especially difficult to draw conclusions about how flash crashes start because the two instances came about quite differently. But understanding what occurs during a flash crash may explain why prices of ETFs can range so far below the respective net asset values [NAV]. The focus of my explanation will be on what happens to ETFs during a flash crash. That part seems rather apparent to me. How one starts or ends is more speculation on my part. If readers have a better explanation on these elements, please feel free to share with the rest of us in the comments section. The parties involved in turning a normal crash into a flash crash I want to point out right now that I have no intention of trying to identify who starts a flash crash or who should be blamed. That is not the focus of my explanation. Readers may reach some conclusions on their own, but they should not expect to find those answers here. Sorry, but the intent to create a flash crash is not my concern. I just want to remain out of the way and protected when occurs. That is why I chose to write this article (along with reader requests) and why I believe it belongs in this series. Building an investment portfolio is only one of the steps in successful investing; we need to guard against avoidable losses, as well. For those who want to trade mispriced ETFs should another flash crash occur, having an understanding of how ETFs are affected is imperative. While I do not recommend trading, I must admit that there were some great opportunities to be had on August 24th. But remember one thing: the next one could turn out to be different. The primary parties to a flash crash, to my feeble understanding, are: Exchanges ETF market makers High-frequency traders [HFT) Traders using stop loss orders Market orders to sell Fear/Panic I do not know if actions by any of the above parties actually starts a flash crash, but once one begins each plays a role. Exchanges try to slow it down. ETF market makers are in business to make money while performing their functions. HFTs definitely try to profit. Stop losses orders get executed automatically, because that is what they are supposed to do. Market orders get filled whatever the price, adding fuel to the fire. Fear turns to panic and more market orders hit the market by those who just want out. In the case of the recent flash crash on August 24th, I suspect that when each of the three major indices closed on or within a fraction of the day’s low on the previous Friday when the Dow Jones Industrial Average Index (DJI) was down almost 531 points, a lot of fear built up over the weekend. Many investors probably placed sell orders over the weekend and some place stop loss orders in hopes of protecting themselves if equities continue to descend on Monday. The DJI was set to open a thousand points lower on Monday when the moment finally came. Panic! The flash crash was set to occur. But how did the different parties listed above contribute to some parts of the market getting hit worse than others, especially some ETFs? It can be argued, and probably correctly, that the exchanges helped avoid a worse flash crash on that day. On December 6, 2007, the SEC approved Rule 48, which the exchanges invoke prior to the open or reopen of trading (after a halt in trading) when there is evidence of too much volatility in equities due to several factors (see this article from CNBC for more on Rule 48). Rule 48 allows exchanges to suspend the requirement that stock prices be announced at the market open. The rule was used on August 24th, but it is not apparent that this action had the intended affect. After the flash crash that occurred in May 2010, circuit breaker rules were put in place to slow down the markets when stocks or ETFs sell off by more than a certain percentage. The circuit breaker means that once a particular stock falls a specified percentage within a predetermined period of time (usually mere minutes, or even seconds) trading in the stock or ETF is halted for five minutes to let investors cool down. That day trading was halted more than 1,200 times by the exchanges (actually 1268 times according to BlackRock ) on various stocks and ETFs. The mechanics of a flash crash and how unrelated activities intensify the problem There is a saying that a picture is worth 10,000 words (it is also in a song titled “IF”) and the one below tells a very convincing story in my mind. This is a three-day chart comparing the S&P 500 ETF (NYSEARCA: SPY ) and the Guggenheim S&P 500 Equal Weight ETF (NYSEARCA: RSP ). The only difference between the two ETFs is the weighting. SPY is red and RSP is blue. (click to enlarge) Source: Google Finance As you can see at the beginning and the end of the period, these two ETFs tend to be highly correlated. Then the slight divergence occurred. SPY fell by 7.8 percent while RSP, at the worst point, fell by 42.6 percent. Since both ETFs contain the same stocks this would seem impossible. Stocks began to recover after the first half hour of trading. What happened to ETFs during that half hour and prior to the open is what I want to help us understand. Normally a market maker will keep the spread (difference between the bid and ask prices) narrowly around the NAV of the underlying assets of the fund. Under normal circumstances they will gladly buy the ETF for a little under the NAV and then sell it for a little more than the NAV when needed to keep shares trading efficiently. When trading in one of the stocks that make up the ETF is halted by an exchange, having hit its “limit” down as determined by the exchange, the market maker for that ETF must decide what the spread should be and place orders accordingly. Market makers are not in the business to lose money, so when they err it is always on the side of caution. In this case, not knowing what the NAV is (because trading in some stocks has been halted and when those stocks begin trading again the price may be different from when it was halted), the market maker most likely looked for price support levels in the stocks for which a value could not be determined and placed a bid to buy at an assumed NAV based upon those prices. When multiple stocks are halted at the same time, the market maker lowers the bid to make certain that a loss is not incurred. With the market falling so abruptly, the bids by the market makers were set significantly below actual (or the last known) NAV. Hopefully, that is clear enough to explain why some ETFs diverged significantly from the value of the underlying stocks that make up the funds. Now, why did SPY and RSP diverge so dramatically? Well, it wasn’t because a lot of the stocks in the S&P 500 traded down by that much. I checked a good number of the component stocks and found very few that were down more than 12 percent. Three of the four largest components by market cap were Johnson & Johnson (NYSE: JNJ ) down 12.6 percent, Apple (NASDAQ: AAPL ) down by as much as 10.3 percent and General Electric (NYSE: GE ) down by 10.6 percent. So, what did happen? My best guess is that the market maker for RSP considered its position to contain more risk since it did not have the protection of the weighting for the stable companies at the top. Thus, when several of the stocks that make up the S&P experienced a halt in trading at the same time, especially when many of those issues were of lesser capitalization, the market maker simply chose a technical support level for those shares that it could expect to hold up and set a bid based upon the much lower assumed NAV. In addition, the HFTs, sensing a rout and recognizing a thinly traded ETF in RSP, probably hit the sell button with bids even lower and then probably cancelled those orders before being filled. The HFTs could then place buy orders even lower and pick up shares at deep discounts when there were no other bids if sellers placed market orders. The HFT trading systems are automated so there are rarely humans involved. The programs are set to identify unusual market activity and to predict potential outcomes. They place thousands of orders and can cancel within a few thousandths of a second with the objective to move the price. They move with incredible speed and usually take pennies or fractions of a penny from many thousands or millions of transaction per day. On August 24, 2015, I suspect some HFTs made chunks instead of pennies. Volatility is the friend of HFTs. Summary Once the divergence was created, the HFTs and others were able to arbitrage the difference away in mere minutes. I cannot prove any of this, but I suspect that the halts in individual stocks created wider spreads as market makers attempted to keep from losing money while facilitating trading. With 1,268 halts that day, the spreads just kept getting larger and larger. At the same time the HFTs were taking advantage of stop loss orders and market orders that were flooding the exchanges. But the trading halts may also have kept the market from falling much further than it did. The problem was not the overall market drop, but the divergence from NAV that occurred in many ETFs that day. Market makers want to make money. HFTs want to make money. Traders were running for the exits in droves just trying to keep from losing any more money. Once again we witnessed a great redistribution of wealth from main street investors to the wealthy folks on Wall Street. This is my opinion and one that you may not share, but the divergence that can occur during a panic is why I do not use ETFs for long-term holdings, especially those that do not trade in large volumes. Thinly-traded ETFs have a higher probability of divergence than those that trade large volumes regularly. After the dust settles it may work out fine, but the turmoil during a crash is more than I want to experience. On the flip side, if one has the propensity to watch the markets throughout the day (which I do not) and can do so on days such as August 24th, one could conceivably identify the divergences and buy the laggard (in the example RSP would be the laggard). Eventually, the divergence will always converge again and either the lower priced ETF will rise or the higher one will fall. Assuming one buys the laggard, the risk of loss is relatively small and the potential gain can be very significant. Not my cup of tea, day trading, but for those who relish such activities, this is one of the better ones. Unfortunately, it is not one we can depend on to happen when we are ready to act. ETFs were supposed to add liquidity to the market and, thus, lessen volatility. I don’t think we’re there yet. As always I welcome comments and questions and will do my best to provide details and answers. This is one of the best aspects of the SA community. We can learn from each other and share our perspectives so that other readers can benefit from the comprehensive knowledge and experience represented here. Disclosure: I am/we are long AAPL, JNJ. (More…) I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.