This is an update of my A Look at Covered Calls - The Naked Truth project. A hypothetical portfolio of systematic covered call writing (AKA synthetic naked put writing) with a non-margin account.
***
I have now wrapped up cycle 4 of the covered call simulation and the results get more interesting, but not unexpected on my part. The motivation for this sim is the representation of easy money available through trading covered call. Although this is not a perfect example, it is generally representative of the ebb and flow of trading this strategy.
I've tried to represent an augmented version of CC trading, via rolling at times within the cycle, to pick up more premium if possible. Most times this works, but sometimes it screws up at we shall see below with FCX.
Let's start of with GS:
The stock is off 10% (relative to starting price in Dec 2011) and the cycle's movement is shown by the red box.
I was able to roll the calls dow, collect most of the original premium, plus the additional premium as it expired OTM. A 6.4% cash profit from the option premium. This is set against the 10% fall. Although the covered call outperformed buy an hold in this cycle, the covered calls still made an overall loss. Buy and hold over the four cycles is still outperforming covered calls at this stage.
FCX was the screw up for the month from a trading perspective. The stock is down just ~2.5% for the cycle:
This is CC manna; write calls get sideways movement collect the premium and buy a holiday to the Bahamas on the proceeds at the end of the cycle. But when this whipped down to around $36, I traded the April $40 calls for $36 calls (Which I neglected to record on the blog. Like GS above, it would have worked well if it lingered down there, but it didn't. It whipped back up again causing a loss when closing out ITM on the second lot of short calls.
C'est la vie.
Cash profit for the cycle 0.65%, less the loss on the stock and we are again behind a bit. Nevertheless, the covered call strategy is in front of the stock over the four months by an eyelash.
Lastly, NOV was down ~9% over the cycle:
I rolled this twice and closed the third lot as it was slightly ITM, getting nice chunks of premium from each resulting in ~5.6% cash profit. But like GS, the dumpage of the stock caused an overall loss for the cycle. Like GS, the covered calls are making gains on buy and hold, but after four months, buy and hold is still a few lengths in front.
The overriding point at this stage is that in a non-margined account, there is still no net cash income from the covered calls. That would be disconcerting for someone sold the dream of reliable cash income from covered call trading.
Saturday, April 21, 2012
Wednesday, April 18, 2012
Accuracy Of Market Estimates of Volatility
In a couple of recent posts viz, Is It Better To Buy Or Sell Options? and Buy/Sell Musings & Volatility, I've been looking at the trader's bias of being a either a buyer or seller of options, or at least being nett short or long gamma.
The conclusion I have reached, for whatever that is worth, is that the decision generically boils down to volatility. That is to say that the trader must examine the volatility priced into the option, AKA implied volatility, and decide whether the price is at, over, or under the odds; or in option parlance, whether the option is fair value, over, or undervalued.
Some writers suggest a comparison to historical volatility, but I wrote in Buy/Sell Musings & Volatility that I thought that was naive and an inappropriate way of determining relative value. Implied volatility looks forward; it is the collective markets guestimate of the volatility it thinks will be realized in the future, in other words the market's view of correct value for that option. It is not definitive, cannot be definitive, because we don't know what will happen in the future.
Historical volatility is definitive however because it measures actual prices traded in the market place over a set of past data of the analyst's choosing. This can be any period, but most commonly over the preceding 20 or 30 days of data. For the purposes of this article I am going to use 20 day historical volatility as this represents the approximate number of trading days in one month.
The VIX is an index of near term implied volatility on S&P 500 options and is quoted according to a formula, to smooth out implications of impending expiry etc. Details and method of calculation are available from the CBOE at this LINK. Essentially it is recording implied volatility one month henceforth.
As I have stressed up til now, it looks at past data, whereas implied volatility looks forward and what happens in the next 20 trading days may be vastly different to what happened on the last 20 trading days, volatility wise. It does have it's uses however. It allows the analyst to examine the 'normal' range of actual volatility for an underlying instrument, how it's cycles, what has been its upper and lower boundaries under various market conditions etc.
Historic volatility has a further use. We can use it to measure how accurately the market forecast one month volatility by looking at the actual volatility realized in on month's time, via the historical volatility calculation.
Let's have a look at the S&P500 using VIX as proxy for implied volatility available at a given date and realized volatility one month later.
As we can see in the above graphic, on the 1st of Feb the market overestimated volatility substantially, therefore we can say that on that date and with the benefit of hindsight, we would have been better to have been a seller of options, all other considerations aside.
Manipulating the historical volatility plot backwards by one month makes it easier to analyze by lining up the implied volatility with the volatility realized in one month later.
In the data that we can see in this graphic, the market collectively forecast volatility correctly, finally, in about the third week of March. So we can say, again with the benefit of hindsight, that S&P500 options at that point were fair value, though it is only today, one month later, that we can say that.
The displaced historical volatility plot gives us the opportunity to view the implied volatility at any point in the past and also in toto, to see how well the market forecasts volatility over the long term. The graphic below shows, on SPX options at least, that the market tends to over estimate forward volatility chronically.
That is it overestimates future volatility until it doesn't. Sellers at market tops get taken to the woodshed.
This evokes the 'picking up pennies in front of a steamroller' cliche for put sellers and synthetic equivalents (buy/write traders) and bull put traders. Put buyers who successfully pick tops score a big time try/touchdown/<or goal scoring nomenclature appropriate for your country> with the vega bomb that blew up in the seller's face. (With apologies for mixing metaphors there)
As intimated in the preceding paragraph, of course being short or long options is not the only consideration. Delta, gamma and theta also cohort the make the trade; or wreck it as the case may be. In markets swoons put buyers will be celebrating with festive dinners, Dom Perignon and Cuban cigars while quite obviously call buyers will be drowning their sorrows with rough red, despite being on the correct side of the buy/sell divide.
The overriding point here however is that market estimations of volatility aren't very accurate and I believe an edge can be obtained by being a better forecaster of volatility and I believe such analysis can help traders make better option trading decisions and not be stuck in a permanent buy or sell paradigm.
The conclusion I have reached, for whatever that is worth, is that the decision generically boils down to volatility. That is to say that the trader must examine the volatility priced into the option, AKA implied volatility, and decide whether the price is at, over, or under the odds; or in option parlance, whether the option is fair value, over, or undervalued.
Some writers suggest a comparison to historical volatility, but I wrote in Buy/Sell Musings & Volatility that I thought that was naive and an inappropriate way of determining relative value. Implied volatility looks forward; it is the collective markets guestimate of the volatility it thinks will be realized in the future, in other words the market's view of correct value for that option. It is not definitive, cannot be definitive, because we don't know what will happen in the future.
Historical volatility is definitive however because it measures actual prices traded in the market place over a set of past data of the analyst's choosing. This can be any period, but most commonly over the preceding 20 or 30 days of data. For the purposes of this article I am going to use 20 day historical volatility as this represents the approximate number of trading days in one month.
The VIX is an index of near term implied volatility on S&P 500 options and is quoted according to a formula, to smooth out implications of impending expiry etc. Details and method of calculation are available from the CBOE at this LINK. Essentially it is recording implied volatility one month henceforth.
As I have stressed up til now, it looks at past data, whereas implied volatility looks forward and what happens in the next 20 trading days may be vastly different to what happened on the last 20 trading days, volatility wise. It does have it's uses however. It allows the analyst to examine the 'normal' range of actual volatility for an underlying instrument, how it's cycles, what has been its upper and lower boundaries under various market conditions etc.
Historic volatility has a further use. We can use it to measure how accurately the market forecast one month volatility by looking at the actual volatility realized in on month's time, via the historical volatility calculation.
Let's have a look at the S&P500 using VIX as proxy for implied volatility available at a given date and realized volatility one month later.
Click To Enlarge |
Manipulating the historical volatility plot backwards by one month makes it easier to analyze by lining up the implied volatility with the volatility realized in one month later.
Click To Enlarge |
The displaced historical volatility plot gives us the opportunity to view the implied volatility at any point in the past and also in toto, to see how well the market forecasts volatility over the long term. The graphic below shows, on SPX options at least, that the market tends to over estimate forward volatility chronically.
Click To Enlarge |
This evokes the 'picking up pennies in front of a steamroller' cliche for put sellers and synthetic equivalents (buy/write traders) and bull put traders. Put buyers who successfully pick tops score a big time try/touchdown/<or goal scoring nomenclature appropriate for your country> with the vega bomb that blew up in the seller's face. (With apologies for mixing metaphors there)
As intimated in the preceding paragraph, of course being short or long options is not the only consideration. Delta, gamma and theta also cohort the make the trade; or wreck it as the case may be. In markets swoons put buyers will be celebrating with festive dinners, Dom Perignon and Cuban cigars while quite obviously call buyers will be drowning their sorrows with rough red, despite being on the correct side of the buy/sell divide.
The overriding point here however is that market estimations of volatility aren't very accurate and I believe an edge can be obtained by being a better forecaster of volatility and I believe such analysis can help traders make better option trading decisions and not be stuck in a permanent buy or sell paradigm.
Sunday, April 15, 2012
Buy/Sell Musings & Volatility
In a recent post I was discussing the question of whether it is generally better to be a buyer or seller of options. My conclusion was that theoretically there is no inherent advantage in either buying or selling, if options are priced correctly; it depends on the situation.
The oft repeated mantra out there in options land is to sell when options are overpriced and to buy when underpriced. Wise advice, but of course the sixty four thousand dollar question is - when is an option overpriced and when is it underpriced?
Of course if you know your option theory, you'll know the great variable in option pricing is volatility, all other inputs being known definitively.
We can measure the volatility of the underlying by looking back over a set number of days and applying a formula to determine the statistical volatility over that time frame. This is also definitive, but unfortunately may bear no relation to the volatility realized over the same number of days henceforth.
This is the volatility option traders want to know, future volatility. As it lies in the future, it cannot be known. Therefore the market collectively makes a forecast of future volatility and prices options accordingly, hence the measure derived by a little bit of algebra, 'implied volatility'.
Some folks suggest comparing implied volatility to statistical volatility to determine over or under valuation. I say that's naive. As discussed, statistical volatility looks backward, but implied volatility looks forward and as I've already pointed out, the volatility realized going forward can be markedly different to the preceding period.
What the individual trader must therefore do, is to make a call on future volatility and decide whether options are fairly valued or not, according to his or her own projections. Statistical volatility may be a tool that can be used in this analysis, but ultimately he who guesses best, wins.
Of course there are other dynamics at play depending on the specific strategy which may sink or save any one position, but good forecasters of volatility have a huge edge.
In the next post, I want to have a look at how accurately 'the market' forecasts volatility.
The oft repeated mantra out there in options land is to sell when options are overpriced and to buy when underpriced. Wise advice, but of course the sixty four thousand dollar question is - when is an option overpriced and when is it underpriced?
Of course if you know your option theory, you'll know the great variable in option pricing is volatility, all other inputs being known definitively.
We can measure the volatility of the underlying by looking back over a set number of days and applying a formula to determine the statistical volatility over that time frame. This is also definitive, but unfortunately may bear no relation to the volatility realized over the same number of days henceforth.
This is the volatility option traders want to know, future volatility. As it lies in the future, it cannot be known. Therefore the market collectively makes a forecast of future volatility and prices options accordingly, hence the measure derived by a little bit of algebra, 'implied volatility'.
Some folks suggest comparing implied volatility to statistical volatility to determine over or under valuation. I say that's naive. As discussed, statistical volatility looks backward, but implied volatility looks forward and as I've already pointed out, the volatility realized going forward can be markedly different to the preceding period.
What the individual trader must therefore do, is to make a call on future volatility and decide whether options are fairly valued or not, according to his or her own projections. Statistical volatility may be a tool that can be used in this analysis, but ultimately he who guesses best, wins.
Of course there are other dynamics at play depending on the specific strategy which may sink or save any one position, but good forecasters of volatility have a huge edge.
In the next post, I want to have a look at how accurately 'the market' forecasts volatility.
Tuesday, April 10, 2012
A Look At Covered Calls - April 11 Update
This is an update of my A Look at Covered Calls - The Naked Truth project. A hypothetical portfolio of systematic covered call writing (AKA synthetic naked put writing) with a non-margin account.
***
Just as this market was getting so complacent (relatively) that I was starting to doze off a bit, it throws in a half decent swoon, startling me from my daydreams. Now I find that the stocks I follow... and the index itself at levels of time and price support, I find myself pondering upon some adjustments.
As my covered call stock sell off, the extrinsic value of the call options have reduced, my positive theta is now relatively less, and the positions have built up some extra deltas. I can buy them back at a profit and re-sell ATM again to pick up more premium or leave them to expire .
If indeed the market does get some support here and we get a bounce going into expiry, those extra deltas are going to help the overall position. On the other hand if the market steps of into the abyss, they're going to hurt.
Writing new calls ATM will bring in more extrinsic, reduce delta and will partially hedge downside. On the other hand it opens the risk of taking it once again on the intrinsic value of those short calls if the market bounces.
This introduces a new question: Does the systematic covered call writer want to be an analyst as well, or just write premium at points where he can get it most. If I hark back to the original idea of this, it was to show a hypothetical portfolio to collect premium. .
Well as it's a hypothetical account, it doesn't matter much and the idea is to see different scenarios in real time, so I did record some adjustments earlier.
With GS trading at 116.13 I bought back the April 125 call for 56c and sold the April 15 for $3.40
I also adjust the NOV position; with the underlying at $78.33 I bought back April 80 call for 57c and sold the April 77.50 for $1.32.
***
Just as this market was getting so complacent (relatively) that I was starting to doze off a bit, it throws in a half decent swoon, startling me from my daydreams. Now I find that the stocks I follow... and the index itself at levels of time and price support, I find myself pondering upon some adjustments.
As my covered call stock sell off, the extrinsic value of the call options have reduced, my positive theta is now relatively less, and the positions have built up some extra deltas. I can buy them back at a profit and re-sell ATM again to pick up more premium or leave them to expire .
If indeed the market does get some support here and we get a bounce going into expiry, those extra deltas are going to help the overall position. On the other hand if the market steps of into the abyss, they're going to hurt.
Writing new calls ATM will bring in more extrinsic, reduce delta and will partially hedge downside. On the other hand it opens the risk of taking it once again on the intrinsic value of those short calls if the market bounces.
This introduces a new question: Does the systematic covered call writer want to be an analyst as well, or just write premium at points where he can get it most. If I hark back to the original idea of this, it was to show a hypothetical portfolio to collect premium. .
Well as it's a hypothetical account, it doesn't matter much and the idea is to see different scenarios in real time, so I did record some adjustments earlier.
With GS trading at 116.13 I bought back the April 125 call for 56c and sold the April 15 for $3.40
I also adjust the NOV position; with the underlying at $78.33 I bought back April 80 call for 57c and sold the April 77.50 for $1.32.
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