Tag Archives: cboe

Before The Fed Rate Hike, Buy These Stocks And ETFs

When the Fed meets for the final time in 2015, many investors are expecting them to do something that hasn’t been done in nearly a decade, raise rates. The last such rate hike came back in 2006 and brought us up to 5.25%, but it didn’t last long as rates soon cratered before finding bottom near zero in December of 2008 and staying there ever since. But now with an economy on more solid footing and inflation slowly starting to creep back towards a two percent target rate, it may be time to hike rates. After all, the whole idea of zero percent rates was predicated on a crisis situation. It is hard to say that we are still in a ‘crisis’ now, suggesting it is well past the time to consider a rate hike for the economy. Some investors still remain woefully underprepared for this reality, believing that a rate hike simply will not happen. But with a parade of Fed officials coming out lately to say otherwise, not to mention a CME Fed Watch reading approaching 80% chance for a hike , it is looking more and more likely that a hike is all but inevitable at this point. There is still plenty of time to prepare though. A closer look at financial stocks and also bond instruments which will not be hit by rising rates seems like a good plan for now. As such, I have taken a look at a few such good options below, any of which could make for solid choices ahead of a rate hike, no matter when the inevitable does strike: CBOE Holdings (NASDAQ: CBOE ) The Chicago Board Options Exchange may not be the first name you think of in a rising rate scenario, but it could actually be one of the better positioned – and more overlooked – choices in the space. That is because the company’s primary products, options on the S&P 500 and volatility-linked options, stand to see more trading as the Fed adjusts rates (with volatility coming especially into focus). Analysts have also begun to adjust their opinion of CBOE stock as we have seen broad analyst estimate increases in the past quarter. The full-year consensus estimate has increased from $2.21/share to $2.41/share in the past ninety days while we have also seen a positive trend for the next year time frame too. CBOE is also riding an earnings beat streak of three straight quarters and in each of these reports the company has beaten estimates by at least 4%. So not only has CBOE been an impressive pick as of late, but it could be a stealth choice for investors to play a Fed rate hike, and especially considering this is currently a Zacks Rank #2 (Buy) security right now. E-Trade Financial (NASDAQ: ETFC ) When the Fed raises rates, it is great news for investment brokers. Companies in this space make money off of the float, or invested capital that hasn’t been allocated to securities yet. And when rates increase, the return companies like E-Trade can generate is even greater. Though there are many names in the investment broker space, ETFC stands out as a great choice right now. The company is expected to see double-digit EPS growth this year while it currently has an earnings ESP of 6.9%. Best of all, analysts have begun to raise their estimates for the stock while all the recent estimates for the current year EPS have gone higher in the past two months. This has been enough to move ETFC to a Zacks Rank #1 (Strong Buy) making it a great pick ahead of a possible rate hike. WisdomTree Barclays U.S. Aggregate Bond Negative Duration Fund (NASDAQ: AGND ) A lot of investors like the safety of bonds and I can see how this can make up a decent size position of many portfolios. However, rising rates are generally bad news for bonds as bond prices have an inverse relationship with rates. Fortunately, WisdomTree’s ETFs in the bond space look to mitigate these worries with a lineup of negative duration products. These funds move higher when yields do and thus can be great bond choices for investors in this type of environment. Costs aren’t too bad here either at just 28 basis points a year, while yields come in at about 2%. And with an effective duration of roughly -4.5 years, this should benefit from rising rates but still won’t be too volatile either. Ex-Rate Sensitive Low Volatility Portfolio (NYSEARCA: XRLV ) If equities are more of your game but you are still concerned about volatility, than XRLV is definitely worth a closer look. This fund looks at 100 S&P 500 components that exhibit both low volatility, and low interest rate risk. This approach looks to exclude those that tend to perform the worst in rising rate environments, giving a tilt towards financials (28%), industrials (21.8%), and consumer staples (15%). There is definitely a large-cap focus here, but mid caps still make up nearly one-third of the portfolio too. XRLV will definitely be a lower risk choice to play the rising rate trend while it is a pretty cheap selection too at just 25 basis points a year in fees. And while volume isn’t great here, the product does have a pretty tight bid ask spread thanks to its focus on highly liquid securities trading in the U.S. market. Original Post

Is The SKEW Index Predictive For The S&P 500?

Summary It is difficult to understand exactly what the CBOE Skew Index means, and even more difficult to find a use for it. This has not prevented some commentators from using it as an indicator for the S&P 500, usually in conjunction with the better-known VIX Index. I find no reason to believe that the SKEW Index serves as a useful indicator, and not much logic for thinking that it would. SKEW is useful only to a rather restricted group of professional hedge traders, such as swaps dealers, and can safely be ignored by the rest of us. Given its inexhaustible creativity, it was only a matter of time before the CBOE created an indicator that challenges investors to find a use for it. Meet the SKEW Index ($SKEW:IND). Yet as obscure and difficult to interpret as this index is, there are some who believe it is an indicator for the S&P 500. This article disputes that contention. What is it? The CBOE Skew Index, unveiled in 2011, provides an index of traders’ vertical skew expectations, based on analysis of the volatility smile of deeply-out-of-the-money S&P 500 index options. All of which is jargon, except to option aficionados. But SKEW is just another way of measuring the extent to which investors expect the distribution of security returns to be non-normal. That is, it indicates the degree to which the median return is expected to differ from the mean, and the extent to which the distribution will include more and/or more extreme outliers. On the downside, the latter are known as “black swans” ─ a term I dislike, since it confuses empirical uncertainty with probability (the probability that black swans existed when probability theory was being developed was 100%; uncertainty based on Eurocentric data is a completely separate matter). In option terms, the non-normality of returns means that the assumptions about future volatility embedded in option prices are not symmetrical with respect to strike prices, so that the put and the call at the same strike price do not have the same implied volatility. Thus ─ since most (but by no means all) equity returns are negatively skewed ─ buyers of puts generally assume (and pay for) higher volatility than call buyers. If puts and calls at a given out-of-the-money strike have the same implied volatility, their graphic representation forms a “smile” that indicates that traders assume a normal distribution of returns from the underlying. In most cases, there is a difference between the implied volatility of puts and calls, and the “smile” is more like a smirk: The smirk tells us that option traders do not expect the returns on the underlying to be normally distributed, and in the case shown above, that the outliers will tend to be on the downside. How Has it Behaved? Since the beginning of 2010, the index has developed like this: It requires some explanation. A reading of 100 indicates an expected normal distribution of S&P 500 returns. The higher the reading, the more skewed to the right of the mean traders expect returns to be ─ and the more likely and/or more severe the negative outliers will be. A reading of 100 indicates that the expected probability of a ≥3σ negative outlier is 0.15% (roughly the likelihood of being dealt a full house in five card straight poker with no wild cards), while a reading of 145 indicates a 2.81% expected probability (a bit better than the chance of rolling a double six on a single throw of dice). The trend is disturbing ─ it suggests that traders expect an increasing number of negative outliers, or more damaging ones. It may be that they do, but I suspect that a better explanation is that, since the crash, there has been increased investor interest in “tail insurance,” demand for which is likely to have pushed the index upward. Thus, I believe that the trend does not represent investors’ response to a specific forecast of disaster, but a more widespread realization of the availability and perhaps advisability of insurance. This does not just represent the hedging activity of hedge funds and sophisticated institutions: any product that offers a downside floor, such as the structured notes popular with private bank clients, is hedged in the options market by its issuer. Not surprisingly, such products have become increasingly popular since the crash. What Does It Mean? This is the $64,000 question, because it is not at all clear what the extent to which a tail event might mean, since a tail event, by definition, is something unexpected. ‘Implied volatility’ is a portmanteau term, carrying the freight not contained in the other variables of the Black-Scholes model, all of which are much more precisely defined. It is in effect the bucket into which everything that determines the price of an option ─ other than those narrowly defined variables ─ is placed, including the price markup that options writers demand. This markup varies with market conditions. Put writers may demand higher prices based solely on their perception that they can get them, without reference to volatility forecasts, and purchasers may accommodate them because they are forced by their circumstances (for instance, as issuers of structured products) to hedge, regardless of whether they think the insurance is well priced. To suggest that every change in the volatility smile implies a change in risk perceptions is nonsense. This raises relatively few issues for interpreting the meaning of the VIX Index, because supply and demand for options is significantly determined by perceptions of the identifiable, near-term and “ordinary” risks that the VIX Index measures. But skew is a different matter: there would be no tail events if they were widely anticipated, and even the most extreme possible reading of SKEW implies only a 3% implied probability of one. While changes in demand for out-of-the-money puts is certainly related to fear of tail events, I believe that it is implausible to argue that it can be predictive of them. Much demand for deeply-out-of-the-money puts is inherently “lumpy,” as a new product is launched or a seasoned product’s hedge must be rolled. How Does SKEW Differ from the VIX? The relationship between SKEW and the VIX is an obvious question. The difference was quite significant in the period illustrated here: the linear regression on the VIX trended downward, so they had mildly negative correlation at -0.20, and the VIX was more volatile (σ = 8.0% vs. 2.5%): Over this 6½ year period, the S&P 500’s correlation with the VIX was -0.77, and 0.22 with SKEW, but over shorter periods correlation varied ─ not so dramatically for the VIX, which has a pretty stable correlation with the S&P 500 over time, but very considerably for SKEW: The low correlation between SKEW and the S&P 500, and especially the very substantial variability of the relationship (peak 0.63 and trough -0.17 around the 0.22 average) support my contention that SKEW has little predictive power for the S&P. This should not be so terribly surprising, since the skewness of S&P 500 returns is itself far from stable over time. Comparing this chart with the charts above suggests that SKEW is not even an especially strong indicator for S&P 500 skewness: Note that this chart uses a longer rolling time period. The 90-day results were so volatile as to be virtually unreadable ─ even using 260 data points, the standard error of skewness is 14.9%. The calculation of standard error of skewness is so generous to uncertainty that it constitutes yet another reason to be doubtful of the predictive value of the CBOE Skew Index. There are some other differences between SKEW and the VIX that have attracted comment ─ in particular, when the former spikes, it tends to do so in isolated, one-day spurts, and promptly returns to its earlier level, while the VIX tends to sustain elevated or depressed levels over the course of a week or two. Thus, when SKEW dropped 16 points on October 15 last year, it snapped back completely the next day. In contrast, the VIX spiked upward on the 9th, and did not recover its earlier level until the 23rd. This has been interpreted as the difference between expectation of elevated but still “normal” volatility (