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The Financial Grynch

I have renamed myself The Financial Grynch.  7qjvKyi[1]A grinch or grynch is generally thought of as a combination of the following:

  • Moaner
  • Pessimist
  • Moaner
  • Wet Blanket
  • Grouch
  • Doomsdayer
  • Partypooper
  • Prophet of Doom
  • Whiner

I am all of those things but I try not to let it get to me.  There is a great deal about the world that I dislike and it is not getting any better as I settle into my role as grumpy old man.

There is genuine good, beauty and charm in the world but it is well hidden under a two mile thick, glacial layer of greed, ignorance and (to go all buddhist) unconsciousness.

Nowhere is greed, ignorance and lack of morality more readily discoverable than in the financial markets – a vast, Leviathan network, set up to defraud the foolish.


I have been using “twatter” for a couple of years and allow it to go in and out of my focus.  Recently it has been in focus. As some will have read, I have recently spent months (wasted my time) down the options rabbit hole and lo: there is an entire industry designed to swell the coffers of the sly and empty the pockets of the stupid and the gullible.


One or two giants of propriety and reason stand out. The providers of vanilla index tracking products for instance; but even there “Smart Beta” usually strays into the arena of financial charlatanism.

I describe “commerce” as being ritualised combat and nowhere is this more evident than in the financial sector. Nowhere does Darwin’s evolutionary principal get a better airing. As soon as life developed teeth and an anus, combat began – and it has become progressively bloodier.

So yes: I am a Financial Grynch. I do NOT like salesmen, I do not like the vast majority of financial, trading and “investment” products. I have a particular loathing of financial salesmen. And within that category those sly cretins who push trading systems and products are among the worst.  Especially since most of them don’t eat their own cooking.

Cigarettes have been stamped out in the west by health warnings on the packet. Unfortunately financial health warnings seem to do little to stop the lemmings losing their life savings in the financial markets.

Perhaps forcing the addition of the following to marketing literature might help:toxic[1]


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Don’t go Down the Rabbit Hole?

“Alice was beginning to get very tired of sitting by her sister on the bank and of having nothing to do…..when suddenly a White Rabbit with pink eyes ran close by her. Alice started to her feet, for it flashed across her mind that she had never before seen a rabbit with either a waistcoat-pocket, or a watch to take out of it, and burning with curiosity, she ran across the field after it, and was just in time to see it pop down a large rabbit-hole under the hedge.
In another moment down went Alice after it, never once considering how in the world she was to get out again.”
Charles Lutwidge 1898, better known by his pen name Lewis Carroll went to Westminster School and Christ Church College Oxford.
And so did I.
When I go back there for dinner in the magnificent “Harry Potter” dining hall I usually make time to stare up at the beautiful “Alice Window”.  What does it mean to “go down the rabbit hole”? According to one source it is to enter into a situation or begin a process or journey that is particularly strange, problematic, difficult, complex, or chaotic, especially one that becomes increasingly so as it develops or unfolds.
That definition is an excellent one.
I simply cannot prevent myself from disappearing down the rabbit hole whenever the opportunity presents itself and nor would I wish to.
One of the great advantages of age (I am 62) is that some of us come to know ourselves. I certainly have. I am not always very pleased with what I have found but at least I have done my best in recent years to lessen my very worst characteristics. I’m not so convinced about the plasticity of the brain but I do my best to act as if it were true.

My interest is in “knowledge”. My particular fascination is in the nature of consciousness and the “meaning” (or otherwise) of reality. It has always been so, although I did not always recognise it.
If it is to be found anywhere the answer lies in science and the philosophy of science.
While the number may not be 42 the “Answer to the Ultimate Question of Life, the Universe, and Everything”, will indeed be calculated by an enormous supercomputer. Except of course “Unfortunately, no one knows what the question is.”
If I had to name a single book I have found most influential in my life it would be Voltaire’s Candide. Followed closely by David Deutsch The Fabric of Reality. I will leave my readers to figure out why or read those books for themselves.
So, let me give a concrete example. I have been trading volatility. I have been using XIV and TMF. It’s fun and the way I trade it is simple. You get a lot of bangs for your buck while the going is good but my suspicion is that the long bond (geared or otherwise) will be a far less useful hedge in the future than it has been in the past if we face a climate of rising interest rates.
I have no spark of originality in my body so it was various discussions on various of the better trading forums which flagged down this particular White Rabbit.
I disappeared down the rabbit hole and am still speaking from an underground labyrinth. The trouble is of course it never really stops. I spent months with Python and Excel creating various VIX trading systems. I spent weeks recreating various volatility Indices and ETFs.
And then I took a dark turn down the options fork somewhere deep, deep down in the rabbit hole.
I bought VIX options data from CBOE. I spent weeks understanding it, cleaning it up and manipulating it into a useable format with Pandas and Python. I spent more weeks designing and testing all manner of options systems on the data. Could I use options to hedge my short volatility position in XIV?
And then the chaos and madness really set in. I decided to try and fabricate “fake” options data from the spot prices of the S&P 500 index. More weeks of intense fun with the wonderful Pandas (thanks Wes McKinney you are one of my heroes). Endless hours of fun playing with Black Scholes, monte carlo, binomial models.
And currently I am wasting my time simulating implied volatility and the volatility smile to add into my fake option data.
But no time is truly wasted unless you really want to make money fast. It has lead me into deep speculation on my favourite topics. As did my endless months experimenting with machine learning.
The small minority of followers who have “followed” this article so far will be wondering where the ramble ends and what is my point.
Well its back to philosophy I fear. And the temple of Appollo at Delphi. Socrates said that the unexamined life is not worth living – a gloss perhaps on “know thyself”.
And here is my punchline:
It’s all very well for a manic old git like me but it is unlikely to make you much money.
The most money I ever made in my vainglorious career came from simplicity and dumbness. Discovering a brain dead area of the market which at the time was a no fail zone and milking it for all it was worth. It was an intellectual desert but it set me up for many years to come and for that I remain grateful.
Looking out at the financial blogosphere I suspect that those who create wealth from it are people who do NOT go down rabbit holes. Or if they do, then people who are sensible (or clever enough) to make the journey pay. And kudos to such people.
Perhaps the biggest problem in the financial blogosphere is that a large percentage of its population is made up of people who would not recognise a rabbit hole if they were to break their leg in one. And such people have no interest in disappearing down it.
There are some very bright people out there who have the people skills to combine their trips down the rabbit hole with energy and salesmanship. They are good communicators as well as clever and knowledgeable. They set up hedge funds and sell the hell out of them. They make billions even if (in many cases) their investors do not.
And then there are the people who are too stupid to get any benefit from going down rabbit holes but have skin like rhinos and a sales ability. The financial blogosphere is full of such types. Knowingly or otherwise they sell snake oil to the gullible or the inexperienced. Sometimes they sell foolish books, sometimes they give pointless seminars (they are “THOUGHT LEADERS”!  They are “EDUCATORS”!) and sometimes they manage money.
And as for me? Well I’m just an aging cynic. I trade a bit, I scribble down a few thoughts. But mostly I disappear down the rabbit hole for months at a time.

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Financial -Hacker – “ersatz” option prices

Financial Hacker


Nope. It doesn’t cut it. You can’t use a single measure of historic volatility for everything from a one month option to an expiry 24 months out. Perhaps the whole scheme is invalid. For instance IV for an SPX two year maturity is currently 15%+ while an option expiring in the next few days is 5% ish.

It may be invalid to use manufactured data at all. Except if you treat it as a sort of Monte Carlo test: this is what may/could have happened / might happen.

Financial Hacker

Anthony, the script is calculating the current price of an option. The current price depends on current volatility. Not on volatility from 24 months ago.

You calculate the value of European options with the Black Scholes formula, and American options, as in the script above, with an approximation method. Both methods normally use 20 days volatility. The volatility sampling method can differ, but the 20 days are pretty common to all options trading software that I know. And you can see from the comparison with real prices above that this period works rather well.


No, you can not calculate the current price of an option on any given day in that way. There is no way to accurately reproduce implied volatility hence price on any given date in the past. And it is the implied volatility we are interested in, not the historic. I totally agree on Black Scholes of course and its uses but it is cart before horse to expect to plug in 20 day volatility as at 3rd January 1985 and expect it to come up with an accurate price as traded at the close on that day for the SPX for any given strike or expiry.

It’s looking at it the wrong way around.

What you can try is to play around with different methods of estimating what the implied vol/ price MAY have been on 3rd Jan 1985 for a given strike and expiry of an SPX option.

For instance you might use 5 day historic volatility for an option expiring in a week and 252 day volatility for an option expiring in a year. Or you might imply volatilities by looking at the term structure of VIX futures contracts from 2004. Or at least use the VIX index itself going back to 1986 as input for 30 day volatility.

Whatever you do you won’t really be producing anything like what was actually traded on the day. Or at least not consistently and accurately over all expiries and strikes.

I believe that the process you describe does have a value but that the outcome of both the prices produced and the back tests resulting therefrom will be more akin to a random monte carlo process than to a back test on actual traded price data.

I believe it is a valuable process but that what is produced is a series of parallel universes: what might have happened to a given strategy over a given period of time using implied volatilities which may or may not have been traded.

Sorry to be long winded and I am an admirer of both your product and your script above. I would not have thought of generating fake option prices had I not seen your excellent article.

But in my opinion at least you need to rethink your input into the BS formula as far as volatility is concerned.


Incidentally please be well aware that I admire your product and your thoughts. Don’t imagine I am being difficult. Equally please don’t imagine I believe I am “right”!

I am just enjoying the journey and the dialogue with you and hoping together we can improve each other’s understanding of the topic.

Mine is limited!


Say the date you are looking at is 7th January 1987. On that day historic SPX volatility calculated over 20 trading days was 15.23. Historic volatility on that day for the past 252 days was 14.65

For 5 days it was 18

Now say I am trying to “calculate” (guess) a price (which might have been traded on 7th January 1987) for an option expiring in 5 days, 20 days and 252 days. Let’s assume ATM.

My suspicion is that it would not be helpful to use 15.23 for all three expiries.

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What volatility to use in “ersatz” option data?

You can’t just calculate a fixed 20 day standard deviation of returns, annualize it and apply it to historic data such as a stock index and expect to calculate realistic fake prices for options.

Because option prices are all about future expected volatility not past historic volatility. To understand the point look at today’s quotes for the SPX for instance. The price of an option expiring this month may imply a very low volatility of 5% (such has been the calm in the US markets) but a two year LEAP is more likely to be priced at an implied volatility of 16% – more in line with the long term S&P volatility over a long period of time.

The same (sort of!)point can be gleaned by looking at the term structure of VIX futures: in normal circumstances it will slope upwards partly because sellers demand a premium dependent on the term they are covering (they will charge more for 12 month’s cover than 30 days) and partly because they may expect volatility to rise or fall over the next few months.

So if you ARE going to use fake option data, treat it as a sort of monte carlo simulation: the outcome of your tests will represent one of many possible outcomes and parallel universes.

This should NOT put people off using reasonably calculated synthetic data ( all back testing is “inaccurate” and un-predictive).

But be aware that however carefully the volatility estimates for the past have been calculated, the implied vol and actual prices of real option prices traded for the relevant time are likely to vary widely from those surmised from a post hoc application of Black Scholes et al.

At some stage I will post on the volatility estimates I have used to produce synthetic option prices.

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Quantopian – Bread today please not jam tomorrow #algotrading

As I suspected a while ago, all is not well with Quantopian. The performance of their fund has disappointed both themselves and presumably their investors. Their CIO departs, they suspend auto trading for participants, there seems to be a drop off in the traffic at their forum.

Let me make myself abundantly clear: the open source movement has its profoundly good points. Wes McKinney and his Pandas add on to Python being my ultra top favourite example.

The team at Quantopian have made some hugely “valuable” software and they have made it available for free along with some extraordinarily useful guidance and educational advice for quant minded investors.

What I would say to Fawce and his team from a personal perspective is that this is not, unfortunately enough.

Note that the revered Wes McKinney does not appear to make any money (directly at least) from Pandas. Note that I have not made a penny or received anything but a misguided sense of satisfaction in many years of writing about finance and systematic trading. I suspect that the vast majority if not all of the many participants on the Quantopian forum have received nothing in material terms for their participation. Although many of them will doubtless have benefitted from the education.

But education does not put food on the table and that is what is missing from this whole internet aged outsourced splurge.

Musicians receive nothing from the outpouring of their talent on youtube, talented people are conned into writing books and giving seminars to make money for the publishers and promoters, advice is sought and not paid for.

In my own case I am fortunately reasonably well off in most people’s terms but that does not mean I enjoy giving away my expertise for vanity alone. Everyone has SOME talent and he is foolish if he gives it away for nothing. Unless for a charitable cause. Certainly not to boost somebody else’s P&L/

So my message to Fawce is as follows: Congratulations. I admire your efforts. But please try and think of some sensible way to make money out of it not only for yourselves but for your participants.

The vague hope of an allocation in the future resulting from some trading competition does not cut it.  Its difficult I know: but if you want our help we are happy to give it but only on the basis of some acceptable way of recompensing us for our efforts.

Bread today please not jam tomorrow.

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Options Data for the S&P 500 #OptionsTrading

CBOE SPX Option Specifications

Subscription to options data costs many hundreds of dollars per stock – with Greeks, data since 2004 from the CBOE for SPX options is not far short of $400. It would be closer to 1,000 if they had data to offer back to 1985.

I am playing with synthetic data based (in the case of SPX at least) on the Black Scholes Merton process.

It all boils down to what volatility one is going to feed into the option pricing formula. Clearly it is NOT possible to faithfully replicate actual traded option prices.  That would be cart before horse.  The best one can do is to make some assumptions as to what the implied volatilities might have been on the given day and treat the whole exercise as a production of random prices which may have some use or significance in the production of back tests for some basic option strategies.

Back testing has little predictive ability anyway, so the use of almost randomly produced estimates of implied volatility/prices may have about as much validity as the use of actual option prices.

Implied volatilities for use in the calculations can be derived in many ways. Ideas include the use of historic volatility, the VIX futures structure (since inception of VIX futures in 2004) and the VIX index. Historic volatility could be differentiated in terms of using (say) 5 day historic volatility on a given day for input into an option expiring in 5 days, and so on out to expiries of two years out.

Rather than assuming such data or back tests using such data have any predictive value, the practitioner is better off assuming that such exercises have an educational function in better understanding option pricing and long term option strategies.

Treat it like a convoluted monte carlo simulation.

AM settlement is assumed on the expiry date.  I have closely followed the CBOE specification for the price series.

Calculation of option premia is made on the basis of a European vanilla option.  Prices at expiry are calculated by reference to the opening price of the underlying.

Data provided consists of:

  • Trade Date
  • Expiry
  • Open – underlying
  • Close – underlying
  • The 3 month TBill rate
  • Volatility of underlying (20 days, annualised)
  • Dividend rate applied
  • Strike
  • Call Price
  • Put Price

Feedback (negative or positive) would be very welcome!


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More on “Outsourcing”

In the “real” world, Hedge Funds pay their staff. In the fake world of “Outsourcing” they don’t. Rather like hiring an indian from Bangladesh living on the floodplains to do your telephone sales – but at least they get paid SOMETHING. I agree that technically Q have come up with some good research and a good back testing engine (if you have the infinite time and patience to look through the more than voluminous source code).

I very much fear that no statistical test and no amount of live trading verifies anything very much. How many fund managers let alone hedge fund managers have we seen come and go after stratospheric periods during which they appeared to be omniscient. JW Henry and Bill Dunn are classic examples. Maybe their time will come again, maybe not. There are periods where a strategy fits the markets and rather more periods where it does not. But this is not a diatribe about the foolhardiness of prediction…so lest I get carried away I’m just saying that people on the end of the outsourcing chain, the mugs hoping for some tiny allocation, are about as likely to achieve their dream as the average lottery ticket punter.

The financial world in particular is overly populated by FWOT: systems, participants, the works. A giant “Bonfire of the Vanities”

My distaste and extreme scepticism result from years of disappointment following contacts on the internet. Magazines who pay nothing for articles they have published, conference and seminar promoters who expect you to perform for nothing when they are charging punters a couple of thousand quid for entry, an endless stream of people who want to talk about ideas or proposals which inevitably lead nowhere. Life is too precious to waste on such nonsense.

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Hedge Fund “Outsourcing” and the something for Nothing mentality.

Is all well with Quantopian? They seem to have gone remarkably quiet since announcing the tie up with Big Steve Cohen earlier in the year.

I dropped in recently and the activity on the forum seems to have declined. The blog by the (CEO?) or whoever seems to have been dropped and they have disappeared from the news.

One problem in my view is that without exception EVERYBODY uses the internet to try and get something for nothing.  And “outsourcing” by hedge funds seems to be the latest example of that. To be fair Quantopian provides an excellent on-line backtesting engine for US stocks which is scott free and includes data. Their technical staff is excellent and their is much to be learnt from analysts such as Thomas Wiecki.

The problem is that it is hard to make any money – either for the punters who use the platform or the punters who provide it. For one thing given the open source environment for software and data most of us can program our own back testing engines and source our own free data. For another we don’t really relish working on systems and publishing them on websites just for the hell of it. It would be nice to actually make some money for a change from a lot of hard work. Probably difficult unless you have thighs to flash like the Kardashians or the bare faced cheek and rhino thick skin of some of the truly awful systems sellers out there on the internet. The systems sellers seem to profit from selling dreams to fools and by getting paid for books, seminars and general buffoonery.

If such people were the magicians they claim to be they would not need to engage in shameless self promotion – they would trade for themselves.

Back to Quantopian and their ilk.  They are an excellent bunch but have lost their way. Finance is not a hobby for people like myself – it is a way of life and has been for almost 35 years.  I have had good years and bad but at my age I would welcome taking less risk – hence I have cut way back on my own trading.

But that does not mean I enjoy giving my expertise away for free – and that is what the internet seems to require. Unless you are a seller of impossible trading dreams with a huge ego and the cynicism and morals of Bernie Madoff.

Guys like Quantopian (and there are quite a few others out there by now) need to find a way to recompense good quality research. At present the “carrot” is that by providing algos and entering into trading competitions you may (eventually….or may not) receive an allocation to trade and profit from that.

Well thanks but that does not pay the rent, nor will it ever. It’s a something for nothing world out there and most of these “outsourcing” hedge funds have teams of in-house quants anyway.  And they have to pay those guys.  Not so the fools who plug away day in day out publishing their research on their own blogs or, worse, on competition websites.

If the outsourcers found a fair way to pay for the outsourced research, matters might take on a more interesting mantle.

Until such time, goodnight sooty – why should we bother?

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I was flattered to be asked by Christopher Parker of Harriman House to contribute a chapter to their Book of Investing Rules.  Other(rather better known!) contributors include Jack Bogle,William Bernstein and Burton Malkiel.

The book will be released at the end of October.

Here is my chapter.

Since I was not paid for writing it, I hope Harriman House will have no objection to my providing it here.

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Vix Calls to Hedge Short Vol Strat?

As a brief addendum if you treat the VIX as a mean reverting series (which it is) you can choose to enter monthly calls (weekly, whatever) only if the VIX is above a certain level (IE above its normal range).

The sample size is likely to be small and the scheme very prone to curve fitting.  But it is worth consideration.

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Call Options for Hedging – FWOT

Like the great herd of sheep like morons you read about in the financial press and blogosphere I am currently short volatility having only discovered the trade last year. As a Johnny Come Lately (as usual) I have spent many weeks looking into protecting my long position in the inverse volatility ETF XIV with various hedging methods.

I have already written a post on hedging it with TMF which has been highly successful so far but will undoubtedly let me down at some crucial point in the future.

I then turned to options and bought VIX data from CBOE.  I have spent weeks cleaning up the messy and badly presented data and then turned to writing a back testing program in Python/Pandas to back test various option strategies.

I had never bothered much with options before partly because I was put off by the ridiculous names people give to their various strategies and partly because the largely useless “greeks” were all greek to me, and in any event have absolutely no predictive value whatsoever.

Here is the punchline: protecting your position with long call options is a FWOT unless you are an expert in market timing and know exactly when to put the hedge on. If you are permanently long puts you will destroy your returns with the huge cost of the option premiums. And if you think you can time markets save yourself the bother and expense of options and simply exit you short volatility position.  

Having disappeared down the options rabbit hole for a couple of months I am now absolutely staggered by the sheer bloody nonsense out there  and the plethora of stupid or dishonest sharks peddling schemes to the hapless fools seeking Eldorado.

It is particularly interesting to see that all the CBOE indices involve selling options not buying them. Option selling is not without its huge perils but compared to option buying it is the holy grail – which is actually damning the practice with faint praise.

As anyone who has bothered to do any back testing with be aware, option selling can be every bit of much as a disaster as option buying.

So why, in the name of god, is there an entire vast industry out there built around option trading? The only answer has to be “because there are a lot of bloody fools who think they have discovered the philosopher’s Stone”.

I have almost come to the end of my option Odyssey but my last vague interest is in back testing The CBOE S&P 500 Range Bound Premium Income Index Series . It looks interesting prima facie but as is usual with any trading scheme scheme it relies on historic data to predict the future (in this case the historical volatility of the S&P 500).

I will report further but suspect that a promising idea will turn out to be an over optimistic chimera.

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CBOE Option Data – Caveat Emptor

I recently bought EOD data stretching back to 2006 on an option series from CBOE. Frankly, the data is a disgrace and I got no reply from my complaint to CBOE.

Problems include strike prices out by up to 3 decimal points in some cases and phantom expiration months which suddenly appear and equally suddenly disappear.

I am having to go through the data line by line to correct the errors. Any attempt to perform systematised analysis on the data I bought was a farce before the tedious hand conducted clean up.

I also have a problem with the expiration dates. There is no trading on the day of expiration – instead the 0’s are shown for each strike. It seems absurd that the exercise-settlement value is not stated and there is no way to calculate or approximate it since the data does not even include the day’s spot opening price for the VIX.

Unless I have badly misinterpreted something (always possible) I would say shame on the CBOE for selling such misleading data.  Its value for my purpose is rendered almost useless.