Trade in Groups

Back in July 2008, I first noted that institutions were pulling back on options trading volume. Recently, Bloomberg has picked up on the story because the reduced supply has led to higher hedging costs – a simple application of Econ 101. The combo of less capital available to make markets in options and higher volatility from an ugly macro picture has, in turn, made options more valuable than ever before. So is this the best of times for options traders, or the worst? It depends on your willingness to be flexible with trading style.

Higher volatility, for example, leads to much wider zones of profits from a short straddle, as well as from selling naked options. But since we have been steadily beating the drum of using options not only for profit, but to effectively manage market risk, there is another strategy we have not touched on worth covering that relates to all this.

The argument against selling options naked, or being short a straddle, is that the losses will be very large if a significant move in the underlying takes place. While most people (at least, those in charge of risk management on Wall Street trading desks) seem to view market returns as normally distributed, they are in fact leptokurtotic – close to the mean more often than one would expect, but also with much bigger and frequently occurring “fat tails.” The intermediate moves get squeezed, and the overall distribution can be difficult to visualize; Part I and Part II of the “Fat Tails and Options Selling” series will help.

Buying a put or call means one is long “vega” – the measure of volatility and how it impacts option prices. The natural flip side is that being short an option means one is short vega. With volatility high, single long positions can be comparatively expensive, and the easiest way to reduce the net cost of an options position is to create a spread. There are four types of spreads:

Short Call Spread

Short Put Spread

Long Call Spread

Long Put Spread

Let’s assume we have a moderately bearish outlook on the S&P 500, and want to buy puts. Below is a chart of the S&P’s recent performance.

An outright put position might not be ideal – the March $84 SPY Put (SCZOF) trades for $4.85 as of the most recent market close. Buying that put and then selling a put with a lower strike price – say, the March $80 SPY Put (SZCOB) for $3.15 – gives a net debit to the trade of just $170. This is the maximum loss, and although it lowers the upside potential if SPY breaks below $80, the reward here ($230/spread trade) could be seen as outweighing the risk. Below is a payoff diagram for this sample trade.

Options spreads are an advanced strategy, but one that can be used to make defined bets at a reasonable cost. Traders frustrated by high options costs, or looking to expand the number of profit opportunities available to them, should become familiar with spreads.

Learn more about this and other options strategies.

Previously, we discussed how market returns are distributed by focusing on a single stock. This time, we are going to look at a focused but sector diversified ETF – the Financial SPDR (ticker: XLF). Remember, the tentative conclusions drawn before implied that historical volatility measures lose their value beyond a short time frame, and that returns display leptokurtosis – a fancy statistical term meaning that, unlike a classic Gaussian bell curve, more observations are clustered around the average, as well as more observations being very far from the average.

The first chart displays “leptokurtosis” visually, and shows how using a large amount of historical volatility data leaves one vulnerable to large moves.

As was demonstrated last time, modeling the distribution of returns is better done when used with only a small amount of very recent data about volatility. The chart below uses rolling 30-day volatility paired with randomly generated Gaussian variables to model expected daily fluctuations, and does a better job responding to increased volatility.

Zooming in to focus on the larger sigma events shows the value of the model using shorter, rolling volatility (graph 1) over a longer cumulative estimate (graph 2).

But, there is still the problem that returns cannot be modeled by a bell curve – we need much more advanced math than can be covered here. Hopefully for now, it will suffice to say that properly assessing volatility is a key determinant of risk management for selling options. Next time, we will apply the quantitative framework used above to discuss writing naked options – one of the most advanced, high risk/high reward strategies.

For now, consider the final chart below, which shows the two volatility measures used to generate the models above.

What is the best way to determine the fair value of volatility? As a major component of pricing options, volatility (and its effects) is something options traders need to be familiar with. Because volatility can vary wildly over short amounts of time, relative pricing of volatility on similar securities or across an options chain is generally the easiest method.

In an earlier example, we identified a covered call set-up to create cash flow from commodities based in part on month-to-month implied volatility. When that trade closes at this month’s options expiration, we will have a full re-cap – hopefully one that bears out the thesis that selling relatively cheap volatility is a good strategy. An options calculator makes calculations like implied volatility a breeze to find and analyze.

Returning readers will be familiar with our continued negative outlooks for many of the market’s problem children – financials, REITs, and certain commodities. A short while ago, we posted about an aggressive series of trades on that thesis, and promised to track the progress of both the underlying positions as well as a specific options play on each.

To recap, the positions are:

Long UltraShort Real Estate (SRS)

Long UltraShort Financials (SKF)

Long CBOE S&P Volatility (VIX)*

Short United States Oil (USO)

*You cannot directly “buy” the VIX

The returns on the first day were very good – on average, +4.78%. The options positions – a simple combination of long out-of-the-money calls and puts – performed even better. The contracts are:

UltraShort Real Estate $57 Call (SRSBE)

UltraShort Financials $140 Call (SKFBJ)

VIX $42.50 Call (VIXBV)

USO $29 Put (UBONC)

The average position returned +25.365% on the first day the trade was put on, but as is often the case in a choppy market, these positions were bounced around and lost value before today’s sell-off brought these positions strongly back to the green.

The listing below shows the closing prices of the underlying positions as of the last update, the closing price on February 10th, and the performance between the two dates.

Jan. 30 Close Price, Feb. 10 Close Price, % Change

SRS: $59.32, $62.60, +5.53%

SKF: $143.26, $145.53, +1.58%

VIX*: 44.84, 46.67, +4.08%

(Short) USO: $29.22, $26.91, -7.91%

Average change in the underlying positions since the Jan. 30 close: +4.78%.

Cumulatively, this gives an average change for the underlying of +10.71%.

As for the options:

Jan. 30 Close Price, Feb. 10 Close Price, % Change

SRSBE: $9.70, $8.60, -11.34%

SKFBJ: $23.30, $17.80, -23.60%

VIXBV: $6.00, $4.90, -18.33%

UBONC: $2.00, $2.65, +32.5%

Average change in the options position since the Jan. 30 close: -5.19%.

Cumulatively, this gives an average change for the options positions of +17.79%.

For comparison purposes, since the market open on January 30th, the S&P 500 has returned -2.20%, and the bets used here to take advantage of that outlook have paid off handsomely. Overall, this is a solid performance, but there are always lessons to be learned.

Here, it’s important to note how time decay affected the value of our options positions. The underlying positions all moved in our favor during the last week and a half, but the options positions (while still up nicely) have declined in value from their original highs. Below is TradeKing’s Options Calculator, which shows the Greeks for each of the options – notice the consistent erosion in option value due to theta, or the sensitivity of an option’s price to one less day to expiration. See here for more on the Greeks.

Again, purchasing out-of-the-money options is a simple way to express a long or short view on a particular stock, industry, or index (including broad market indices and volatility). Although this can be a surprisingly tough way to make money, with the proper trading discipline and timing, the rewards can be large.

One of the buzzwords in the financial community in 2008 was “fat tail” – the outlier that breaks price returns from a normal distribution. Perhaps the most famous comment came from David Viniar, CFO of Goldman Sachs (ticker: GS), who said their models “were seeing things that were 25-standard deviation moves, several days in a row.” For perspective, it would theoretically take several repetitions of the entire lifetime of our universe to have a reasonable chance of a 25-sigma event occurring.

It’s obvious that markets are not governed by a normal distribution, but just how much of a variance occurs in individual stocks? What about the diversification provided by a sector ETF? And how can this make you a better options trader?

Because financials have been at the heart of the storm, consider the daily change in the stock price of Citigroup (C) since the end of 1998 – over 2,500 trading days. The graph below shows a distribution of the real one-day percentage changes in Citigroup’s stock price, compared to a set of theoretical data created from a model that uses the rolling (trailing) 30-day volatility combined with a random Gaussian number generator. Real returns actually compare quite well with the model.

What happens if we zoom in, and focus on the supposed “fat tail” areas where models are supposed to break down? Again, the model is surprisingly accurate in sum.

Wasn’t modeling ability supposed to break down when stress-tested against large moves? Two points: first, no attempt was made to build the model to match reality; a reasonable recent period to estimate volatility was simply picked. Second, this is an average, so the actual error on a day-to-day basis could be significant.

Part of the reason the above model matched reality fairly well is that it actually used less data than the version you are about to see – the key factor is that by being entirely reliant on recent market signals, the model can adjust to rapidly rising volatility and account for the larger moves.

For comparison, here is a chart of cumulative volatility over the life of this Citigroup data set. Every day, we can say with increasing statistical significance that we understand the underlying volatility of Citigroup’s stock price.

Regenerating the original graph using new expected stock price changes based off the additional data yields the following – note how most of the returns clustered around the middle still match to some degree.

The real surprise, of course, comes from a zoom-in that focuses on the fat tail moves:

Using more data makes the forecasting worse, not better – an important principle to keep in mind across many disciplines. What does this say? The markets are not efficient, but they do typically have a good idea of near-term price action, and signal that quite clearly. We will more fully explore this phenomenon with diversified ETFs and its implications for options trading next time.

Step aside Abercombie (ticker: ANF), H&M, and all other prophets of all things young and hip. While other retailers saw sales predictably crumble in the face of a difficult consumer spending environment, Urban Outfitters (URBN) has been a bit of an outsider. During the fourth quarter, which included a subdued holiday shopping period, Urban Outfitters, operating under the brands Urban Outfitters, Anthropologie, Free People, and Terrain, posted record sales numbers for the fourth quarter, with a sales increase of 9% and bringing in $508 million.

While the other store brands have performed nobly, especially in this dismal economy, it has been the Urban Outfitters store brand that has been the saving grace of the company. During the fourth quarter, comparable store sales rose 3% at Urban Outfitters, compared to a decrease of 6% and 13% at Anthropologie and Free People, respectively. Total company comparable store sales decreased by just 1%, an incredible feat considering Abercrombie’s comps dropped 24%, and even J. Crew’s saw comps down in the mid-teens.Urban Outfitters’ apparel and products target a highly-specific consumer niche.   Everything about the brand is cool; it’s hip; it’s modern. Urban Outfitters is an all-encompassing lifestyle brand; not only can you dress yourself with Urban, you can also dress your significant other, as well as your apartment. A consumer can be Urban Outfitters, and that strategy has helped the brand develop a loyal fan base. Department stores, even with their lower prices, cannot compete with Urban’s message of involvement; those big stores are removed and detached from the consumer. This differentiating strategy makes it unique from many of its competitors.With the good financial news in mind, the company will continue its expansion. Urban Outfitters stores already have a prominent presence in Europe, even gracing the fashion-forward streets of London and positioning itself against slightly couture brands like Top Shop and New Look. The look is perfect for the region, with Urban’s emphasis on skinny jeans, long flowing shirts, and mod clothing, all evident hits on the London sidewalks. The first Anthropologie store, also a lifestyle brand, but exclusively for women, will open in late 2009 or early 2010 in a location as yet to be determined. Given Urban Outfitters’ success and extensive presence in the UK, the store will likely open there. As the UK’s economy suffers even more than its American counterpart, the move carries with it predictable risk. However, with its similarities to the Urban Outfitters brand, Anthropologie has a fighting chance at making itself relevant to British lifestyles.

URBN is testing the downtrend line, and whether it breaks out or not will be telling as to the market’s thoughts on apparel. As a company that has demonstrated staying power, and with a stock that typically traded for 30+x earnings, URBN should be a cautionary tale that good companies do not always make good stocks. Monitor support levels carefully, and be diligent in the usage of stops or put options to manage risk.

A while back, we demonstrated how high volatility relates to options premiums using a Geometric Brownian Motion (GBM) model. That might sound complicated, but the charts included in that article give a good visual depiction of volatility’s impact, so check it out. For a more simple explanation of why options are currently so valuable, consider this article from Bloomberg. Because many of the largest options market makers no longer have the capital to provide the same amount of liquidity, institutional volume in the options markets has declined. In simpler terms, supply has declined, while the demand still exists – so prices have moved higher, and individual investors have the flexibility to exploit these opportunities.

How can an options trader capitalize on this? The input in options pricing formulas that is above-average is implied volatility, so a willingness to sell IV (by being short puts or calls) may be a method to earn excess returns. Executing a short straddle is a way to sell this volatility in an options trade, earning profits if realized volatility is lower than anticipated in the underlying.

For example, the currently $85 strike February call price for the SPY is $2.35, and the put price is $2.89. With the Volatility Index (the VIX) above 43, volatility is certainly high by historical averages. The payoff diagram below shows that the range of profit at expiration ranges from $79.75 to $90.25, compared to a current price of $84.57. This means the S&P 500 can move about 6.2% in either direction, and this trade will still be profitable. 

How does the current situation compare to past levels of volatility? During quieter times, the VIX averaged around 15. If this level was applied to the same options prices, the range of profitability for this strategy would be from $82.90 to $87.10, or approximately 2.5% in either direction.

The high volatility of late has created opportunities not only for stock traders, but for people willing to use the full range of options strategies available to profit in all markets. For more, see the Options Playbook or general options strategies.

The bearish outlook given yesterday was based off a combination of general economic data (fundamental) as well as a handful of indicators about market internals (technical). The underlying theme here is that the leaders into this crisis – namely, real estate and financials – have not yet hit a bottom (or at least need to re-test lows).

The themed bets here are that it will be profitable to be short REITs and financials, as well as oil due to demand destruction, to be long volatility via options on the VIX, and have a covered call on the Gold ETF (ticker: GLD).

Typically, there has been an emphasis on trading long/short, and although this group of trades has a blend of longs and shorts, it is hardly uncorrelated. Below is a one month chart showing the performance of the UltraShort Real Estate ETF (ticker: SRS, blue), the UltraShort Financials ETF (ticker: SKF, orange), the S&P Volatility Index (the VIX, green), and the United States Oil Fund (ticker: USO, red). The first three have tended to increase together, while oil has declined – meaning being long SRS, SKF, and VIX calls with a short position in USO is not exactly hedged.

Purchasing out-of-the-money call options is normally one strategy used by beginning options traders because the options seem “cheap” – that is, they are inexpensive. And they are, because out-of-the-money options tend to expire worthless. For our purposes, we are using the February call with a strike 5% above the underlying’s opening price (or 5% below for USO puts) on Friday (1-30-2009), rounded down (up for the put position).

Part of this exercise is to compare the performance of a simple portfolio of ETFs against a portfolio with leverage from options, and the other is to add time pressure because of option value decaying. With that, the underlying positions, their opening price on Friday, and the percentage change:

UltraShort Real Estate (SRS): $54.86, +6.50%

UltraShort Financials (SKF): $133.66, +4.77%

CBOE S&P Volatility (VIX)*: 42.63, +5.18%

United States Oil (USO): $30.02, -2.66%

*There is no way to own the VIX directly, it must be done using options

Because we are short USO, all of these positions went in our favor on Friday. The average percentage change was +4.78%. Now on to the options positions, again with the opening price on Friday and the day’s percentage change:

UltraShort Real Estate $57 Call (SRSBE): $7.20, +34.72%

UltraShort Financials $140 Call (SKFBJ): $16.20, +43.83%

VIX $42.50 Call (VIXBV): $5.70, +5.26%

USO $29 Put (UBONC): $1.70, +17.65%

All of these options positions went in our favor, some substantially. The average position return was +25.365%, which shows how the leverage from options impacts returns. Initiating 100 share positions on the underlying would have cost roughly $26,000 (again, remembering one cannot “buy” the VIX), while buying one of each option contract could have been done for about $3,100.

One day does not do much to validate a trade idea, so we will revisit this occasionally between now and options expiration. Hopefully for now, however, it will suffice to say that buying out-of-the-money options is a strategy with value for the aggressive bettor, and not just the choice of inexperienced options traders.

This recent post on the TradeKing community site got me thinking about current sentiment among traders, and what implications (if any) it has for the markets going forward. Regular readers have seen bearish stances over the past several months on financials and energy, along with a focus on alternative strategies to earn profits when the market is not going up.

The current hope, it seems, is that we as a nation (or world) can struggle along in this economic malaise while the banking system fixes itself – and eventually debts will be worked off and lower on the whole, consumer spending can increase, and the job creation process can begin anew. So, will this happen?

Recent economic data, and the trends implied, indicate that the economy continues to deteriorate substantially. Recent industrial manufacturing and export readings around the world are terrible; in East Asian countries, December (non-oil) exports ranged from a 21% year-over-year decline in Singapore to a -35% change in Japan and a -42% change in Taiwan. One might consider Singapore to be the relatively “lucky” country here; GDP there declined at an annualized rate of -17%.

The story is the same in Germany, where November manufacturing orders (most recently released) were down 6%, and prior months are being revised lower. Almost three months ago I heard that the Asian manufacturers, in particular, were completely caught off-guard by the shocking decline in demand – that observation has been borne out.

Today’s news might be a bit obscure, but it helps paint a great picture of the global economic situation. Japan’s industrial production for November registered the largest drop in over 50 years, at -9.6%. Unemployment is also rapidly on the rise in the third largest economy in the world, and the Bank of Japan already has interest rates below that of the Federal Reserve.

Crossing continents, European Central Bank Chair Jean-Claude Trichet has insinuated that the ECB’s rates are already low enough. Perhaps we are looking at different data, but I politely disagree, and would not be surprised if short-term rates from all major central banks reach the zero-bound finish line before all is set and done.

In other words, I believe things are consistently getting worse, and the downward spiral has not been broken yet. Is this priced in? With the aggressive rallies we’ve seen, I’m not so sure.

Some people look to data to give them clues about the market will do, others look at the market to give clues about what the data will be. For those in the latter camp, copper is a very important industrial metal, and any notable increase in demand (coupled with existing tight supply) would likely be reflected in a price pop. Below is the Copper ETF (ticker: JJC) discussed previously.

Additionally, some technical indicators:

The TRIX on the S&P, as well as the McClellan Summation Index, have both “rolled over” and are now falling. This means the net pressure on the market is downward from here, and it typically takes the indicators a few weeks to reverse direction. Also, the number of stocks trading above their 50-day moving average is starting to ease off the extraordinarily high levels seen at the start of 2009.

In sum, this all seems to be pointing to a down market in the intermediate term. Next, over the weekend, I will present an options-heavy portfolio designed to capitalize on this bearish thesis through aggressively opportunistic bets - specifically on real estate, financials, commodities, and volatility.

This article is part of the Festival of Stocks.

This series on commodities has taken a detour or two, but the recent explanation of how to use a covered call strategy brings us back to one of the original points about commodities: when used in combination with other strategies, they can both provide income and change the correlation of a portfolio.

A problem traditionally associated with owning physical commodities is that they require funding costs (to store and insure) and throw off no cash flow until they are sold. As was discussed with covered calls, however, selling an out-of-the-money call can provide a steady income and boost to returns, while only giving away some upside in the case of a large rally.

Two of the most popular ETFs for directly owning commodities are United States Oil (ticker: USO), which tracks the spot price of WTI crude, and SPDR Gold Shares (ticker: GLD), which tracks the price of gold bullion. Below are the charts of USO and GLD, respectively, relative to the S&P 500 over the past year.

For this trade set-up, we will focus on a covered call on gold, using the Gold ETF (GLD). Many investors have become interested in gold lately because of fears about the value of the U.S. Dollar, and gold is seen as a natural hedge against fiat paper money.

From TradeKing’s Option Summary, the historical volatility of gold over the past 30 days is 29%. But looking at the February call option chain, with expiration 22 days away, the implied volatility (IV) of the $96 strike is 39.2%. Interesting enough, the volatility of the March $96 strike call is 39.5% - this is unusual because implied volatility typically increases over time.

As a comparison, the at-the-money call for February (the $88 strike) shows implied volatility of 34.6%, while the March $88 strike call shows implied volatility of 36.5%. Two main takeaways here: the market expects volatility going forward to exceed volatility in the recent past, and it seems that out-of-the-money options sellers are being well-compensated for giving away upside above 10% between now and mid-February.

So let’s say you go ahead and own 100 shares of GLD, and you decide to sell the February $96 strike call against the long position. This results in a credit of about $80 (given what the contract’s last bid/ask is at), with that premium being equal to 0.91% of the ETF position’s cost. That might seem like a small amount, but it is for an extremely short time period – annualizing that out gives an annual return of 14.6% in premium income, all for selling a call that is 10% out of the money with 22 days to expiration. Not a bad risk/reward trade-off for someone already long GLD, in this author’s opinion, and a fairly easy way to convert direct commodity holdings to an investment that throws off cash flow while hedging against inflation.

An area of opportunity for individual investors that we’ve only touched briefly on so far is traditional options. This article assumes you have a basic understanding of call options – if not, a few quick primers can get you up to speed – see here for a basic long call, and here for covered calls.

There can be different reasons to employ a covered call strategy, but a few general reasons for doing so:

-Implied volatility is high, translating to rich call premiums one wishes to capture. See more on how volatility translates to option values.

-A long-term bullish outlook, but a near-term belief the stock has little upside.

-Improve returns should the market trade lower.

One widely-followed stock that has earnings coming up is credit card processor Visa (V), which reports on February 4th. Visa is currently trading just above its IPO price at $44.15/share, and with earnings in one week the implied volatilities of the front month (February) calls are high. Below is a chart comparing Feb. IVs with March IVs.

One of Visa’s competitors, American Express (AXP), rallied almost 10% today following its earnings announcement. But Visa and American Express have very different business models, because AmEx retains its card members’ loans and Visa does not. This exposes AmEx to credit risk, whereas Visa is simply a payment processor that earns a fee from transactions.

The unique business model (similar only to MasterCard, ticker: MA) and strong competitive advantage makes Visa’s 20x trailing EPS multiple seem less overpriced than the rest of the credit-sensitive financial sector to which it is traditionally compared. Indeed, when most of the finance industry is going through a period of massive losses and liquidity concerns, analysts are debating how much money Visa will earn. Below is TradeKing’s Earnings Center analysis for Visa; showing current estimates and how Visa has traditionally beat expectations.

Visa’s huge competitive advantage is sustainable for the long-term, but with the market driven by short-term sentiments (especially around earnings time), Visa could go either way. Let’s say you own 100 shares of Visa and are confident in its long-term success, but want to reduce uncertainty going into earnings. You can sell one call option and collect the premium up front, and as an example we will use the $47.50 strike. This gives upside of 7.6% from the most recent close before the short call option begins to offset profits from the long stock position.

The $47.50 strike for the February Visa calls currently trades at a $1.35 bid/$1.45 ask. Taking the mid-point of that range implies a contract premium of $140, or 3.2% of a 100 share position in Visa stock. The graph below shows the payoff from initiating a covered call on Visa stock.

Two important points to note: first, the breakeven on the trade is lowered to $42.75 because of the option premium. This means that Visa stock could decline somewhat, and this strategy will still show a profit – whereas not selling the call and simply owning the stock would result in losses from any decline in share price. Second, the strategy begins to underperform simply owning Visa stock above $48.90, which is the strike price plus the option premium. Even though the chart shows flat profits above $47.50, the addition of the call premium to the comparison is crucial.

The premium to be collected from writing covered calls on long-term stock positions can add substantially to performance, especially in down markets or when volatility is high.

For more on covered calls, see the Options Industry Council explanation or the TradeKing Options Playbook.