Tag Archives: apple

Who Are The Market Makers? What Do They Do? WHY?

Summary We constantly talk about the market makers [MMs] and their activities. It is apparent from their comments, that many readers have varied, limited views about the function of MMs, their status, regulation, objectives, and their compensations. A late-August irregularity in securities markets functioning created knowledgeable analysis and comment discussing all that, much of which may help our perspective and understanding. The August 24 th Market Opening Problem The casual, intermittent user of US equities markets may not even be aware that there was a problem or the seriousness of its condition. By 10:30 am NYC time that Monday, things were pretty much back to near normal, and trading the rest of the day was being conducted about as usual. But the previous hour or two nearly shut down the ability of investors and speculators to carry out their planned transactions. Many unpublicized DK (don’t know) trades complicated the end of day settlement processes. Here is how one deeply involved observer firm described what happened: Recent Volatility in the US Equity Market In late August 2015, the US equity market experienced a rapid spike in volatility as global market sentiment weighed bearishly on stocks. During that period, the VIX volatility index doubled and equity-trading volumes surged as investors reassessed global growth prospects and inflation expectations. Market activity on August 24 was particularly extreme. Before the market opened, global equity markets were down 3% to 5% and the e-mini S&P 500 future was limit down 5% in pre-market trading before wider price curbs went into effect at 9:30 am. Due to these pre-opening factors, the morning began under selling pressure with substantial order imbalances at the open as investors reacting to global macro concerns flooded the marketplace with aggressive orders to sell (that is, orders to sell without any restrictions as to price or time frame such as market and stop-loss sell orders). According to the New York Stock Exchange (NYSE), the volume of market orders on August 24 was four times the number of market orders observed on an average trading day. Extensive use of market and stop-loss orders overwhelmed the immediate supply of liquidity, leading to severe price gaps that triggered numerous LULD (limit-up, limit-down) trading halts. The confluence of these factors contributed to aberrant price swings and volatility across the US equity market. For example, the S&P 500 index was at a low, down 5.3%, within the first five minutes of trading, then rallied 4.7% off the lows before selling off again late in the session to close down 3.9%. Bellwether stocks such as JPMorgan (NYSE: JPM ), Ford (NYSE: F ), and General Electric (NYSE: GE ) saw temporary price declines in excess of 20%. Individual stocks as well as ETPs (exchange traded products) and CEFs (closed end funds) experienced significant dislocations after the opening followed by unusual volatility. Transparency and Information Flow Price transparency and information flow in the US equity market were curtailed from the start, forming one of the key contributors to the day’s events. Anticipating widespread volatility, NYSE invoked Rule 48 prior to the open. NYSE Rule 48 suspends the requirements to make indications regarding a stock’s opening price and to seek approval from exchange floor officials prior to opening a stock. By suspending time-consuming manual procedures, this action should have permitted Designated Market Makers (DMMs) to open stocks more quickly and effectively. However, this rule had the unintended effect of limiting pre-open pricing information in securities, especially for any stocks experiencing delayed opens. Although DMMs actively worked to facilitate a prompt open for all securities, the opening auction was considerably delayed for an extensive number of stocks. At 9:40 am, nearly half of NYSE-listed equities had yet to begin normal trading. These delays, along with the absence of pre-open indications, impeded the normal flow of information, which market makers and other participants rely upon to perform their customary activities with respect to the market open. Without this information, and with many securities experiencing delayed openings, correlations snapped between prices for securities in the same industry or ETPs tracking identical benchmarks deviating significantly from one another. In financials, for example, JPMorgan experienced a sharp decline, while Morgan Stanley (NYSE: MS ) did not. The basis between futures and cash prices for the S&P 500 index also widened considerably – futures traded at a 1.66% discount to the corresponding equity basket. These dislocations heightened uncertainty in the market because the validity of automated pricing models becomes challenged when there are meaningful disparities between the prices of normally correlated securities. Additionally, since many of the computerized processes, which support market making, rely on futures as a reference asset, the ability of market makers to efficiently allocate capital and price risk was inhibited. Market makers faced further uncertainty on the cancellation of potentially “erroneous trades,” adding to their reluctance to trade. The lack of price transparency impaired the ETP “arbitrage mechanism” because market makers were unable to rely upon price information for individual stocks to determine when arbitrage opportunities exist between the ETP and its underlying basket, and to hedge their positions. In the absence of the necessary data, many market makers ceased arbitraging US equity ETPs. Exchange-Traded Products The market forces discussed above led to a temporary breakdown in the arbitrage mechanism of many ETPs. 327 ETPs experienced LULD halts on August 24. Many ETPs also experienced brief periods where they traded at significant discounts to the value of their underlying portfolio holdings. As a result, the events of August 24 left many investors dissatisfied with the prices at which trades were executed and raised concerns about the functioning of markets and ETPs. Further, like individual stocks, the confluence of order imbalances, lack of information flow, and opening issues contributed to differing experiences, even for comparable ETPs. Retail investors who had standing stop-loss orders were especially impacted – once the stop price was reached, the orders were converted into market orders, which were often executed at prices that were markedly lower than the stop price. As stop-loss orders are typically intended to be used to mitigate losses, investor education about the risks of stop-loss orders should be significantly increased. To that end, Figure 1 may be helpful. Figure 1 (click to enlarge) Now You Probably Know More Than You Want And there is even more complexity involved. But the necessary message is that in a trillion dollar a day market complex, lots of actions need to be coordinated. Computer programs that expedite actions have rigidities that need to be softened in some circumstances by human judgment. Often that is where market makers [MMs] get involved. Several of the key MM functions and responsibilities are outlined in Figure 2 Figure 2 (click to enlarge) Source: BlackRock Capital Management Figure 3 identifies the principal roles of MMs as providers of liquidity, the usual MM function thought of when the subject of market makers comes up. Figure 3 (click to enlarge) Source: BlackRock Capital Management Key to understanding these roles are the impact they have on prices and price trends. The size of capital involved in typical transactions is a principal determinant. That makes the first listed category of Liquidity Provider, the block trade facilitating broker-dealer, the most significant stock price impactors of MMs by far. These are irregular but frequently occurring, multimillion-dollar trades. Each one typically has the price impact potential to step away from the posted last trade and the current bid~offer quote by a full percent or more. Skillful execution may prevent such a change, or encourage it. Trade and market savvy are important resources, along with arbitrage experience. Firms engaging in the block trade business are often vertically integrated or diversified in their MM activities into several other or all of the roles listed. Exchange-registered market makers tend to be the traffic cops of the current day exchange world and have procedural influence that affords stature in the internal community. Their exposure to the public is usually quite limited, but their day-in, day-out functions may be essential. The remains of the exchange floor specialist system are here. Wholesale MMs serving regional brokers are essentially an internal function of the MM community and are among the least influential as to procedure or securities prices. Technology dominates the electronic MMs, earning them frequency and pervasiveness of presence in number of trades. The billions of shares regularly traded could not be exchanged without this support. But the typical price changes involved from last trade tends to be tiny and highly mechanistic. Their principal contribution is immediacy of executions at low cost. The high-frequency arbitrageurs or HFT players are the intellectual and market savvy step-outs of the electronic MM organizations. Their influence is in the bid~offer realm more than in the trade volume arena. They are constantly sniffing quotes to find risk-free arb opportunities, and individual investors rarely are aware of their presence. But their reach is extensive and they are a liquidity-providing influence. Competition hones their honesty, as a group. Their accomplishments financially tend to be a basis point at a time, just a million times over. They are expert exploiters of the leverage of time. For those interested in the full complexities of the market making process here is the complete BlackRock discussion and their recommendations for market operating revisions. Some of the underlying problems go back to the 1987 “portfolio insurance” market failure debacle. Conclusion Market makers come in a variety of flavors and perform many functions essential to the power and value of today’s equity markets. Where their influence to the advantage of individual investors is the greatest is in their service to those investment organizations that must trade in market-disrupting units because of their size. That limitation of size is unavoidable since the economic basis for their investing businesses is in the amount of capital under their management. They are active investors in order to utilize their info-gathering intelligence resources. But the advantage for us is that they use the arbitrage skills of trusted market making firms to provide the other side of those big trades and the temporary financial liquidity to acquire or dispose of the thousands of shares regularly involved. In the process of MMs hedging the risk to their capital, what is revealed is the extent of the risk believed to be present. Those self-protective actions and the implicit price-range forecasts prove to be useful guides as to future specific price moves, on a very comparable base among equity investments of wide diversity.

Should You Be Weary Of Inverse Commodity ETFs?

Last week, we touched on potential markets that might finally be breaking out of the slow moving commodities sell off that’s been going on for around a year. In that post, we do what we do every month, looking at the difference in performance between the commodity futures market (Dec. contract) to its commodity ETF counterpart. This time around, we got to thinking it might be interesting to look at the flipside of that…. How inverse ETFs have performed against those same futures markets. Here’s what we found: (click to enlarge) At first thought, you might think that the ETFs are outperforming the futures counterparts until you realize that those inverse ETFs should all be positive due to the fact that the futures contract they supposedly track are negative. So, technically, if you shorted the December 2015 futures market at the beginning of the year you would have made 22.57%, while the 3x inverse Crude ETN DWTI (NYSEARCA: DWTI ) is down -13.34% YTD. The same can be said about natural gas, but to a lesser extent; the inverse ETF is up 5%, while the futures contract is down -21.02% (Disclaimer: Past performance is not necessarily indicative of future results). Part of the reason for the major disparity in returns is because most of these ETFs follow the front month contracts while the ETF prices are affected by the role in contract each month. Here’s etf.com’s description of the inverse crude ETF DWTI . “Since DWTI tracks an excess return version of the S&P GSCI Crude Oil Index, returns will reflect both the changes in the price of WTI crude oil and any returns from rolling futures contracts.” Be careful though to go off of 10 month or even 12 month returns ( Ben Carlson on A Wealth of Common Sense has a great post on this ), because as an investor, if you would have picked the absolute perfect time to get out of the market (Aug. 24th) you would have been up 97.88%, while the futures contract would have been down -33.31% (you would be up that percentage if shorting). (Disclaimer: Past performance is not necessarily indicative of future results) Chart Courtesy: Barchart Our point: Unless you’re making a career out of trading these markets, trying to time when to enter and exit a commodity market is dangerous and can be costly. Case in point, the first sentence of the DWTI ETF… Like most geared inverse products, DWTI is designed to be used as a tactical trading tool, not as a buy-and-hold investment. But that doesn’t mean that you shouldn’t have access to strategies that allow you to reap the gains. If you haven’t guessed what’s coming next, we’re about to name drop Managed Futures. These strategies are built to seek return drivers off of rising and falling markets. This is how the industry did as a whole during crude’s collapse. (Disclaimer: Past performance is not necessarily indicative of future results) Source: Newedge Data through Jan. 12th, 2015 Our firm is dedicated to searching through the managed futures space in order to find the best strategies out there. Some managers will tell you where they think commodities are going; some will tell you they let the algorithms do the talking. In our experience, we like to know that they have a feel for the market but at the end of the day they leave the emotions out of the decision making. Ultimately, we, nor they, can tell you where commodities are going, but that’s the beauty of Managed Futures strategies; they don’t know, but it doesn’t matter if prices fall or rise, it’s more about capturing the trend as it continues to fall of rise. P.S. – To understand where Alternative Investment return drivers come from, download our whitepaper, ” The Truth and Lies in Alternative Investments. ”

Making Sense Of Long-Term Returns

By Michael Batnick, CFA All advisers face the same challenge: How can we best help investors understand what sort of long-term returns they can rationally expect? This is an extremely important topic. It forms the basis of Social Security projections, pension estimates, and determining how much a household needs to save to retire comfortably. What’s often absent from a discussion on stock returns is the many ways in which returns can be measured. There are a lot of questions: What is the appropriate time period? Does one year make more sense than three years? What about a rolling return versus an annual return? When do we start measuring? Should we include the Great Depression or look at post World War II numbers? If you can’t see the importance of this conversation yet, it may be time for a quick reminder. Let’s go over a couple of different ways that we could measure the return of the S&P 500 Index. Remember as you’re reading this that it’s our job to make sure investors understand these nuances. Price Return vs. Total Return If you invested one dollar in the S&P 500 in 1928 (no, this was not possible at the time), it would have been worth ~$109 by the end of August 2015. If you were to measure the total return, however, that $1 jumps from $109 to $3,362! Nominal Return vs. Real Return It’s always important to account for inflation. If we do that, our $1 invested in 1928 becomes $342 in 2015. Compounding at 6.8% after inflation is still an impressive long-term return, even if it is just a tenth of what the total return looks like before inflation is accounted for. Average Return vs. Compound Return The S&P 500 (total return) has averaged nearly 12% a year since the mid-1920s, however, investors’ wealth would have compounded at just under 10%. The reason there is such a large gap between arithmetic and compound returns is because the 12% average returns are not earned in a straight line. There were years like 2008, when the index fell 37%. Once stocks lose 37%, they need to gain 58% to get back to even. As we often find ourselves explaining to the investing public, there are major differences between average annual returns and the returns of any individual year. In the chart below, you’ll notice that the average return of 7.5% (price only) was rarely seen in any one year. Only about 5% of the time did investors generate returns even close to the average. S&P 500 (Price Only) Perhaps a better way to present this data is the distribution of returns. S&P 500 Distribution of Annual Returns (Price Only) This can provide investors with a better idea of what the range of possibilities is. Expecting an average return of X% over a 20-year period is one thing, but being prepared for the outlier years and surviving them is something else entirely. And, of course, these outlier years can happen one after another. How does it change the way that you look at the world if you learned about markets during a year when they performed terribly? It’s a helpful exercise to break returns into different time periods to demonstrate the life-cycle experience an investor might have had. The chart below shows “bull” (green) and “bear” (red) market regimes throughout history. S&P 500 (Log Scale) People born in 1900 would probably count the Great Depression as the formative experience of their investing life cycle. It’s hard to imagine that living and working through it would not leave an indelible impression. Although every period in history is unique, one thing we can say with certainty is that bull and bear markets are permanent features of investing. Take a look at the returns in the table below. In the last 90 years, there were several periods of time when investors’ wealth compounded at very low rates. Pointing to average historical returns is little comfort to investors in the depths of a protracted bear market. Likewise, when markets get overextended, people tend to throw caution to the wind, learning nothing from history. Of course, we have to consider the reliability of the data itself. In an eye-opening paper published in The Journal of Investing, entitled ” The Myth of 1926: How much Do We Know about Long-Term Returns on US Stocks ?” Edward McQuarrie looks at the Center for Research in Security Prices (CRSP) database , which many argue is the gold standard for historical stock returns. He writes: “1) The CRSP time frame, which begins in 1926, excludes more than 50% of the historical record of widespread, large-scale stock trading in the United States, which goes back almost 200 years; and 2) for more than 50% of its time frame, the CRSP dataset excludes the majority of stocks trading in the United States, especially the smaller and more vulnerable enterprises. Putting these two facts together, we may say that CRSP provides comprehensive price series data for less than 20% of the total US stock trading record, aggregating across time period and type of stock.” McQuarrie shares some interesting insights about the way we think about historical stock returns. While not suggesting that the CRSP has failed in its due diligence, he makes the point that there are listing requirements that have undoubtedly omitted stocks from the database. We have seen that different starting periods and different ways of measuring returns can have significant implications for investors. So what if anything can we conclude and suggest to our clients? Here are a few things to remember: Past performance is absolutely not predictive of future results. Data can be manipulated! Sticking with an investment plan during a bad year (or a series of bad years) is what will make them successful. The results of diversification are predictable even if the results of an investment are not. Having a command of these issues and laying them out for our clients beforehand will make for a much more enlightening – and realistic – presentation. Disclaimer: Please note that the content of this site should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute.