Geoff Considine

Stress Testing Your Portfolio

Correction:

Ron is correct: Bob's portfolio would have lost 19% of its value even without any withdrawals. Before withdrawals, the stress test formula proposed in this article would suggest a 'worst case' of 8.7% - 3*10.6% = -23%. Had Bob done the stress test ahead of time, he could have tuned down his risk level if this was too severe blow. Bob did not have a very well diversified portfolio (according to QPP) and I am in no way saying that this was a great portfolio choice. My point is that a Monte Carlo model, properly stress tested, would have alerted Bob to the risks in his portfolio.

I emphasize: Milevsky's point (and I agree) is that we can never be sure whether we estimate the probability of extreme events well--but we can stress test to see if the 'worst case' events that we can estimate are survivable.

On a related note: there have been some famous cases in which quant models have predicted that the things that hit their portfolios were 25 standard deviation kinds of events--i.e. effectively impossible. This was true in 08 and also in the case of LTCM. The models were clearly wrong. 3 standard deviation events do happen, and we are also saying that we know that they will probably happen with greater frequency in real life--which is why stress testing to ensure survivability of such events is so important.

Opportunities in Options Markets, Summer 2009

John:

Thanks for the comments. Obviously one can sell puts vs. selling covered calls--one is just the synthetic of the other. The issue comes down to how confident you are in future volatility--the cost of rolling the strategy forward through time.

I agree that Bodie's strategy is far more conservative than what I am proposing.

I have been focusing on selling long-dated options--like what I use in my examples.

Geoff



On Jul 02 02:46 AM ikkyu wrote:

> Greetings Geoff,
>
> Nice to see the evolution of your thoughts about monte-carlo and
> options pricing. I think this is the most interesting stuff you have
> done to date.
>
> Please let me ask a few questions, if you don't mind.
>
> Not sure why underpriced options would suggest buying calls rather
> than buying puts (or more reasonably straddles) in the short run
> (<3 years). Serial correlation can be positive with a negative price
> trend, can it not?
>
> Also, are you talking about buying OTM calls on EBAY? While stock
> markets tend to go produce positive results over long periods, you
> have to have to inherently predict the magnitude of the move when
> buying options.
>
> Which options are you talking about selling? The long dated LEAPs
> or the front month? You would have interest rate risk on the LEAP,
> far lower gamma initially, and wider bid-ask spreads. I usually divide
> the time value by the number of days till expiry to get a better
> idea of the decay per day.
>
> Also, why sell covered calls at all? Naked puts would be the risk
> equivalent and would simplify things. If you get exercised, you could
> then start selling calls on the underlying.
>
> While i like your plan, it is clearly not an equivalent for Bodie's
> conservative methods. Bodie's plan seems like it would work better
> with a call spreads. It would be like your own index annuity. <br/>
>
> Just some thought. Nice piece of work. Seems like you are definitely
> thinking out of the box.
>
> Cheers from Osaka,
> john
>

Opportunities in Options Markets, Summer 2009

This is just using QPP's projected volatilities for each ticker and the rest of the tabel is other data. Or did I miss your question?


On Jul 02 02:54 PM gasem wrote:

> How do you use QPP to generate the above table?
>
> thanks

Bill Gross: Dividend Stocks and Bonds Make Most Sense Now

I agree with Mr. Gross on the dividend-paying stocks. There is a range of evidence to support the idea that dividend paying stocks look good (seekingalpha.com/artic...). I also think that there are ways to play this scenario in a manner that also lets you maintain some upside (seekingalpha.com/artic...) in selected sectors.

Stress Testing Your Portfolio

Actually, my 3SD loss is worse than what happened over the last two years by notable amount. You are missing the subtlety of Milevsky's proposal. We can never know the tru probability of really extreme events all that well--even if the world is Gaussian, we would have estimation error on the mean and SD. Milevsky's is suggesting taking a model's estimate of 'worst case' and making sure that it is survivable--this is very reasonable. You are saying that the test is 'historical maximum drawdowns' which is also reasonable, but will tend to mack really high loss potential. Many firms have not existed long enough to truly test the extremes in real life--thats why we use models in the first place.


On Jun 19 07:23 AM MachineGhost wrote:

> > but I am hoping that the 3SD worst estimate is still a good

Stress Testing Your Portfolio

BlueOkie:

Nothing in QPP or Monte Carlo is inherently backward looking, though plenty of Monte Carlo implementations are just that way. QPP has been tested extensively as a forward looking tool--and its results speak for themselves. Also, nobody rationally suggests that investors will never change pathes--I wrote an article showing how this relates to Monte Carlo and how a combination of MC and the flexibility to adjust your plans dramatically increases your odds of success. BTW, who said anything about living to be 120?

Geoff


On Jun 17 08:59 AM BlueOkie wrote:

> Monte Carlo is an excellent tool. The problem is what you input for
> the variables. Bob is a person and will alter his behavior given
> a changing environment. Monte Carlo works in hindsight and in a class
> room. The probability of event "A" in 2006 may not be equal of "A"
> 's probability in 2007 or even any of the future years. Finally,
> why would you look at the probability of Bob living to 120?

Stress Testing Your Portfolio

I am not accounting for the increase in autocorrelation / cross correlation that occurs in a major meltdown but I am hoping that the 3SD worst estimate is still a good measure. Basically, we are saying that we plan for a really bad (<1/1000) event while ignoring autocorrelation/correl... increases and this is used as a reasonable estimate of the worst case that investors must plan for, given that we know that this will under-estimate the probability of such an event. In light of 2008-2009, this look very reasonable. My estimated worst case 1-year using this simplified approach was worse than 2009-2009 for all the portfolios I have examined.


On Jun 16 05:18 PM gasem wrote:

> In terms of stress testing how do you view changes in a portfolios
> diversification metric and auto-correlation metric
>
> As I watch things evolve I saw diversity nose dive and auto correlation
> explode

Stress Testing Your Portfolio

Guys:

Thanks for all the comments. I am running a bunch more cases right now using this stress test metric. I am looking now at the two year period ending in May 09. This fills out the picture. I will post my next article with more of these results.

Cheers,

Geoff

Stress Testing Your Portfolio

On Jun 12 01:09 PM Analyste de Boston wrote:

>In truth, there were many, many more
> +65yo Buy&amp;Holders with >70% allocation to eqty in 2007.

Yes, but that is precisely the kind of over-aggressive stature that Monte Carlo tools like QPP help to warn against.

Stress Testing Your Portfolio

Hi guys:

I enjoyed the comment stream today, after being away for the weekend. What I find most striking is that this topic has not gotten more attention in the media. There was the really poor WSJ article on Monte Carlo, but you guys are really hashing out the important issues. I agree with the comment on market discipline--the hardest thing for people to do is to stay with a plan--if they have a plan. I am sure that there are lot's of Bob's in the world who sold their equities and purchased an annuity just before the market rallied 35% or so in early 2009. I think that Monte Carlo tools can help investors to be more cognizant of thr risks and thus choose a level of risk that they can live with. Back when QPP was projecting a doubling in volatility over recent years (in 2007), I saw very little commentary on this issue. THAT was the time to prepare. After the crash, there are many people who have been crushed and I am well aware that what Gasem says is true: there were many people aged 60+ with very high allocations to equities--and largely undiversified exposure to equities, too. Monte Carlo is not a crystal ball, but it can provide guidance that helps investors avoid taking too much risk. Also, I am totally sympathetic to the ideas that there are much better portfolios than Bob's--I agree. The specific portfolio is simply a straw man.

Also, Analyst de Boston says that his market timing made his investors 61% in this bear market. First off, I tip my hat :) Second, Monte Carlo does not mean that you do not use tactical asset allocation methods--I have written about this. In the case shown here there is no Tactical component, but this is just one case...

Geoff

E*Trade's Online Advisor Hopes to Lure DIY Investors

Zack:

Nice article. This is a timely piece and I hope to see more discussion of this kind of emerging solution. One thing I am surprised you did not mention: Where do you see FinancialEngines.com in this space? Their goal has always been to provide online portfolio guidance using their tools, and they have been around for quite a while.

Regards,

Geoff

Did Portfolio Planning Tools Fail Investors in 2008?

Bob:

My next article shows how to stress test--step by step--in QPP or in any other Monte Carlo model...

Geoff


On Jun 08 10:23 AM BobLSW wrote:

> Geoff,
>
> Could you give a novice some guidance on how to QPP to stress test?
> So far I've been just using it to generate the projected return/risk
> for my portfolio at the end of each week. I than look at the table
> showing the 80%/50%/20% probablilties. I use the SP # as suggested
> 8%/15%.
>
> Thanks,
> Bob

Did Portfolio Planning Tools Fail Investors in 2008?

Gasem:

I like your examples but I also suggest that you read Milevsky's paper. You raise a number of important issues. First, the cycle in volatility. Volatility was very low, so people took bigger risks--and this led directly to the crash. This process is well documented in Minsky's instability hypothesis. Quantext Portfolio Planner clearly docuemented this risk well before the crash--and I have written many articles on it here at SeekingAlpha.

Second, Monte Carlo models are attempting to capture a series of unknown future factors in terms of cumulative risks. We do not need to know specifically what these are. I disagree that the recent market crash is beyond the realm of statistics to capture (bad cement vs. 100 year flood). We cannot predict what will happen in terms of the extreme events but we can stress test our plans to see if they will hold up in extreme events--thats the point of my article.


On Jun 08 11:05 AM gasem wrote:

> The issue of the past melt down IS UNRELATED to a probabilistic thing.
> The melt down was due to systemic risk. In effect the market was
> rigged. AAA bonds were NOT AAA loans were being made to people who
> HAD NO ABILITY TO EVER PAY THEM BACK. Government policy was such
> that there was a bias to do financially unsound things. Everyone
> knew this was going on EVERYONE. Because there was a huge amount
> of money to be made the bet was "I'll play the game make my huge
> amount of money AND I'll be smart enough to get out before it crashes."
> Virtually no one was smart enough, so the market unwound all at once.
>
>
> In my opinion the thing in the monte carlo engine that should have
> given this away was was the ever declining S&amp;P volatility during
> the period following the burst of the tech bubble. We went through
> recession and we went through 2 wars yet the volatility declined.
> THAT decline was due to the systemic bias that was added by the government
> which gave us the sandbox where the Tech bubble was turned into the
> real estate bubble, and that is now being turned into the currency/credit/govern...
> bailout bubble Another systemic risk, and another reason to NOT invest
> in America
>
> To blame monte carlo for government violation of the rule of randomization
> is to absolutely NOT understand what a monte carlo engine does. The
> example of engineering a bridge for the 100 year flood is the perfect
> example. You can engineer for that probablility, but if you systematically
> undermine the quality of your concrete (as in adding systemic risk)
> your bridge is built on a fraud that is not the fault of the model.
>
>

Did Portfolio Planning Tools Fail Investors in 2008?

Guys:

Great comments all. I would like to see more discussion of the roles and duties of advisors here on SA if that would interest people. This is a major issue and I think that advisors and individual investors would benefit from more dialog. I think that really good advisors help their clients to understand the responsibilities on both sides of desk. I am quite convinced that good advisors add considerable value for many investors. That may or may not include making tactical decisions--depends on the advisor and the client. This debate is very similar to what has gone on in the institutional world for several years.

Some investors want to hand over their money and have no involvement whatsoever. Some investors are proactive. Many of the users of my Monte Carlo platform are individuals and quite a few have introduced their advisors to our tools rather than the other way around.

The models and the use of models is one part of the discussion, but this is a bigger topic obviously.

Regards,

Geoff

Did Portfolio Planning Tools Fail Investors in 2008?

Alan:

Milevsky's proposed SORDEX statistic is a great solution. The more I work with it, the more impressed I am.

G.


On Jun 03 10:17 PM Alan Young wrote:

> The average investor, being told that their portfolio had a 95 or
> 98% chance of sustaining its value throughout their remaining lifespan,
> would be satisfied. There are no 100% guarantees.
>
> But the problem is not the modeling. The problem is that a once-in-a-century
> event is thought of as a remote improbability, because "that hasn't
> happened for many years and everything is different now." Actually,
> an investor with a remaining life expectancy of 30-35 years has about
> a 1/3 chance of encountering a 100-year improbability. That is a
> substantial enough risk that some specialized control device should
> be added to the plan. If only we could know what that would be.