Posted by Mark on January 30, 2015 at 06:18 | Last modified: May 7, 2015 12:18
Since many people believe IV is mean-reverting, I discussed the idea of generating trade ideas by looking for stocks at IV extremes. Today I will continue that discussion.
We want to look for stocks with high IV. Once we have found these candidates, we can then plan trades that take advantage of an anticipated IV drop from these extremely levels back toward average levels.
Here is a key point to differentiate, though: we want stocks with high IV relative to their own average IV as opposed to high on an absolute basis (i.e. compared to other stocks). I will call this IV percentile: where current IV falls within the low-high IV range over the past year. IV percentile of 100 (0) means current IV is at its highest (lowest) level over the past 12 months.
We can also invoke that second trade consideration and determine whether we have a forecast for the underlying stock price. If we are wrong with IV forecast then we might still make money if we are right on stock movement (and vice versa). For the latter, we would look to use bullish or bearish premium-selling strategies (e.g. naked options or credit spreads) if we are decidedly bullish or bearish, respectively. If we believe that price will remain in a range then we can use strategies that are short premium to the upside and downside: short straddles, short strangles, or iron condors.
Any option scanning tool should allow us to scan for IV. You can choose whatever specific criteria you like. Since I have no reason to think any one set of criteria will perform better than any other, here is a generic screen:
1. Last stock price at least $15 (low-priced stocks may have wide strike increments)
2. Average daily volume of the underlying > 1,000,000 (liquidity requirement)
3. Average true range of price between 1-8%
4. IV Percentile > 95
I will conclude with the next post.
Categories: Option Trading | | Permalink
Posted by Mark on January 27, 2015 at 07:06 | Last modified: May 7, 2015 10:42
Today I will discuss one approach to trading options: screening by implied volatility (IV).
The sheer volume of option trading possibilities can be overwhelming. To find good trading candidates, I need to keep in mind the three sources of option profits: price movement of the underlying stock, option supply and demand (IV), and time decay.
Time decay is largely a function of option supply and demand. As demand for options increases, option prices increase. IV measures how expensive options are in terms of expectations for the underlying stock movement. Higher-priced options have more value to lose over time. This decay is value lost by option buyers and value gained by option sellers.
Profitability is therefore a function of two main factors: price movement of the stock and supply/demand for the options. To make money with an option trade, I can either look for stocks whose prices I can predict or look for stocks whose IV changes I can predict. When I choose stock price change or IV as the primary consideration, IV or stock price change will be the secondary consideration, respectively.
Some people believe changes in IV are easier to forecast than directional movement of the stock. IV is believed to have strong mean-reverting tendencies. Whether or not this is true is something we could research (topic for another day). For now, though, it will be sufficient to say those in this camp believe IV to oscillate around an average value and return to that average quickly when IV strays too far away.
Based on this philosophy, screening for stocks that are at higher-than-average IV levels should be a good source of option trading ideas.
I will continue discussion of this trading approach in the next post.
Categories: Option Trading | | Permalink
Posted by Mark on January 22, 2015 at 05:08 | Last modified: May 6, 2015 09:49
Reports on Google’s 2013 Q4 earnings announcement left me utterly confused. This is the main reason I wonder whether earnings are another case of optionScam.com.
A whole sub-industry has been made out of providing earnings data, using fundamental analysis to calculate price projections, and determining what stocks to buy and sell based on those fundamentals (earnings). Ultimately, if fundamental parameters are not objectively quantifiable (i.e. no consensus!) then who is providing the right data? Surely we should be using the right data to make accurate stock picks, right?
Aside from the whole issue of data accuracy, I am not even certain any statistically significant correlation between earnings results and subsequent stock price movement exists. Certainly the people at Tasty Trade don’t. I have not replicated their backtesting results but what they have presented suggests stock price to be somewhat correlated with direction of the overall market. They actually claim the distribution of directional moves to be pretty much random +/- a bit of positive drift. That would be about 53% up and 47% down, which is consistent with overall market movement.
It would be very difficult to perform a comprehensive analysis of post-earnings stock price changes stratified by good/bad earnings results. The biggest challenge would probably be determining consensus as to whether the results are good or bad. What estimates should be used? How do we define consensus? Should we look at earnings? Revenue? Something else? Do we factor in a margin of error?
As mentioned above, looking at the post-earnings price changes independent of any estimates makes a decent argument for “randomness” despite a limited number of tickers studied.
Let’s review:
1) Many companies specialize in selling information about earnings estimates and earnings analysis.
2) Data are now available to suggest nothing about earnings may actually be predictive of subsequent stock price changes.
3) The sub-industry described in 1) makes lots of money at the expense of investors who don’t know or understand 2).
That’s a pretty good formula for optionScam.com, folks!
Categories: optionScam.com | | Permalink
Posted by Mark on January 20, 2015 at 06:13 | Last modified: May 6, 2015 09:21
I find pretty much everything about these reports on Google’s 2013 Q4 earnings announcement to be confusing.
My review suggests different media outlets can interpret corporate earnings differently.
Poor writing can make it seem like one media outlet doesn’t even agree with itself!
Also confusing is the post-earnings stock movement. Intuitively, I would expect a stock to go up (down) following a good (bad) earnings report. Sometimes it may be hard to say what is good or what is bad, though.
I do believe that eventually (i.e. within a few days), the media usually does a pretty good job of retroactively explaining stock price reaction. They do this by pointing out something in the announcement that is either good or bad. This can be done because rarely, if ever, is every fundamental measure revealed from an earnings announcement good or bad. The media can always cite something to support its report whether it be positive or negative in tone.
I don’t believe any of this retrospective analysis to be actionable, however, in terms of developing potentially profitable trading strategies. I am also not convinced that any fundamental measure is significantly correlated with subsequent stock price changes. Show me the data if you believe otherwise.
Can you see why this is categorized under optionScam.com? I will take one more blog post to explicitly state that argument.
Categories: optionScam.com | | Permalink
Posted by Mark on January 16, 2015 at 07:13 | Last modified: May 6, 2015 08:51
Last time, I began to discuss three reports on Google’s 2013 Q4 earnings announcement and ended up somewhat confused. Today I will focus closer on the numbers to see if we can gain some clarity.
Report #1 said Google made $9.93 in Q4, which missed the consensus estimate by $0.41. This implies the consensus estimate to be $10.34. Report #3 said they made $12.01, which missed the consensus estimate of $12.26. The two reports are inconsistent with regard to the consensus estimate. I’m not sure how that can be since I understand “consensus” to be the average of all published analyst estimates. What’s worse, though, is that the two reports don’t agree on Google’s actual earnings! Maybe one reporter was sick or had excessive wax build-up preventing him/her from hearing on that day?
Once again, I am confused.
I suspect Report #3 is poorly written. The last sentence says “last quarter, Google… earned $10.47.” As mentioned above, Report #3 said they made $12.01: in the same paragraph! Did they just state two different earnings numbers just three sentences apart?! That can’t be. I must be misunderstanding. I can only surmise that “last quarter” means 2013 Q3 while the current report covers 2013 Q4. In other words, “last quarter” is Q3 and “this quarter” would be Q4.
Focusing on the revenue numbers provides a bit more clarity. Reports #1 and #3 say Google posted revenue of $16.86 billion. Report #2 says revenue was $16.9 billion, which is equal to the others taken to one decimal place. Finally we get some consistency! Report #2 does say that revenue was for “last quarter,” though. Evidently for Report #2, “last quarter” is 2013 Q4 and maybe 2013 Q3 would have been “the quarter before last.” This is different syntax than applied in Report #3 where “last quarter” referred to 2013 Q3 as discussed above.
Deep breaths…
I will continue in the next post.
Categories: optionScam.com | | Permalink
Posted by Mark on January 13, 2015 at 06:21 | Last modified: May 6, 2015 08:34
Last time, I presented three reports on Google’s 2013 Q4 earnings announcement. Today I will discuss them.
First question: was this a good or bad earnings report?
Headline for Report #1: “Google misses, shares up.” That sounds like a bad report but a good outcome. On the other hand, if shares are up then maybe it’s a good report. “Misses” has a negative connotation though.
Right out of the gate, I’m confused.
Report #2 says “Google earnings top expectations.” This seems contradictory to Report #1, which said Google “missed.” Topping expectations is more consistent with the stock moving higher but then is Report #1 wrong about the miss? Maybe the judgment call refers to different measures (e.g. revenue, earnings, margins). Is the writing sloppy because the antecedent was not specified? Report #2 later clarifies by saying “Google’s earnings figures were pretty hot,” which tells us that earnings, at least, were good.
Report #3 says “strong revenue growth,” which suggests that revenue was good. Earnings and revenue were good, then, so what “missed” according to Report #1? Actually, Report #3 says revenue growth was strong but it says nothing about estimates. Maybe Google still missed its revenue estimates despite revenue being strong?
Report #3 goes on to say: “the search giant missed earnings expectations by a wide margin but wasn’t punished by traders.” Report #2 said earnings topped expectations. Which is it: did they top or did they miss by a wide margin? There’s no fuzziness with this comparison: they are in stark contrast with one another!
I will take a closer look at the numbers in the next post.
Categories: optionScam.com | | Permalink
Posted by Mark on January 8, 2015 at 06:54 | Last modified: May 5, 2015 14:19
Earnings just don’t make sense to me with regard to stock price movement.
While I have seen many anecdotal instances to support this hypothesis, I will use one example to keep this blog series short: Google 2013 Q4 results, which were reported on January 31, 2014. I will present three reports on the earnings announcement.
In no particular order, here is Report #1 from Zacks:
> Google Misses, Shares Up Regardless
>
> Google Inc (GOOG) reported fourth-quarter earnings of $9.93,
> missing the Zacks Consensus Estimate by 41 cents, or 4.1%…
> shares jumped 4.1% after-hours, after rallying 2.6% during
> the day. Google’s gross revenue came in at $16.86 billion…
Here is Report #2 from The Motley Fool:
> Google and Amazon Earnings
>
> Google earnings top expectations. Google this: Shares of
> the search engine that you probably used two minutes ago
> jumped more than 4% in after-hours trading Thursday, after
> Google (NASDAQ: GOOG ) reported a projection-beating
> $16.9 billion in revenues last quarter.
>
> The takeaway is that Google’s earnings figures were
> pretty hot…
Here is Report #3 from The Verge:
> Google Q4 2013: strong revenue growth driven by Play
> Store and hardware sales
>
> The search giant missed earnings expectations by a
> wide margin but wasn’t punished by traders.
>
> It seems like Google can do no wrong with the markets
> these days. The consensus estimate on Wall Street was
> that Google would deliver $16.75 billion in revenue
> and earnings of $12.26 a share. It hit the top of that
> line, with $16.86 billion in revenue, but missed on
> the bottom with earnings of $12.01 a share. Still,
> the stock was up slightly in after-hours trading.
> Google made $14.4 billion in revenue and earned
> $8.62 a share for this same period a year ago. Last
> quarter Google brought in $14.8 billion and earned
> $10.47 a share.
I will compare and contrast Report #1, Report #2, and Report #3 in the next post.
Categories: optionScam.com | | Permalink
Posted by Mark on January 5, 2015 at 07:06 | Last modified: May 5, 2015 09:32
Disclaimer: except for the title, this post has nothing to do with the last one.
About one year ago, I saw this in a trading forum:
> Hey guys,
>
> We’re giving away 5 free subscriptions to Born To Sell’s
> covered call screener on Feb 22. One of them will be
> based on skill and the other 4 are random drawings.
>
> To win the skill-based contest, you have to guess the
> closing value of the DJIA on Feb’s option expiration
> day (Feb 21). The other 4 prizes will be chosen at
> random from among the submissions.
>
> Enter on or before Feb 1 here…
This post captured my eye because of its flawed differentiation between “random drawings” and “based on skill.” How could we possibly tell if guessing the DJIA on a particular date was a matter of skill or a matter of random luck? Based on one instance we absolutely could never do so.
Statistically speaking, in order to demonstrate “skill” that is significantly better than chance (randomness) we would need a sufficiently large sample size of correct predictions. The winner may certainly make claims about his/her prowess based on one prediction but these claims would be premature. To truly be a skill, the requisite sample of correct predictions must not be retrospective and must not make use of hindsight. Predictions made in advance must be verifiable, too. To be sure, con artists have historically used any and all of these means to dupe unsuspecting customers.
I make no claims about the reliability or accuracy of the “Born to Sell” service because I know nothing about it. I do not, in any way, shape, or form, endorse the product. I only mean to provide a brief commentary on “skill” vs. “luck/randomness:” two concepts that are often confused, sometimes deliberately, for the sake of advertising and marketing.
Be on guard for optionScam.com!
Categories: optionScam.com | | Permalink
Posted by Mark on January 2, 2015 at 06:45 | Last modified: May 5, 2015 09:04
I have recently been catching up with blog ideas that, at one point or another, struck me as particularly noteworthy. Today’s installment is but a snippet that offers some relevant material for us hopeful traders. Today’s post was inspired by some writing from January 2014:
> Quite often I have read technically-based
> trading strategies that advertise quite well.
> Do they really work, though? Certainly we’re
> brainwashed to think they work (technical
> analysis books, educational seminars, etc.),
> but in trading many things work just by
> random luck alone (like 95% of all cash
> secured puts over the last two years).
>
> Ultimately, I believe the only way to
> determine if a trading idea has merit
> is to put it through the exhaustive steps
> of trading system development. Most people
> don’t know a thing about this so they feel
> comfortable trading in a discretionary
> manner until they experience a catastrophic
> loss that knocks them out of the game or
> leaves them walking quietly into the night
> with tail between their legs.
>
> Admittedly, some things are difficult/impossible
> to backtest. As an example, perhaps I might
> look at S&P 500 stocks in the upper half of
> their Bollinger Bands vs. those in the lower
> half and look at the distribution of price
> changes over the following days to see if
> there’s a difference. If I can’t make a
> statistical determination then I may wonder
> “am I confident trading this idea even though
> I have no more reason to think it works than
> randomness alone?”
>
> If I am then great! If not then I won’t.
>
> Bottom line: I should be honest with myself
> when trading an idea that I have no more
> reason to believe works than randomness alone.
> I think many traders are deluded into thinking
> they know something works based on definitive
> principle when they actually have no good
> reason to believe it at all.
Categories: System Development | | Permalink