Author Topic: Engineering Targeted Returns and Risk  (Read 8185 times)

MachineGhost

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Engineering Targeted Returns and Risk
« on: March 13, 2013, 12:43:12 AM »
In 1996, Bridgewater Associates established the All Weather principles for asset allocation, which have now been more broadly adopted under the banner “Risk Parity.”  In 2004, Mr. Dalio wrote an article in which he explained these principles. That article is reprinted here, with relevant updates.

http://www.docyoushare.com/file/index.php?f=eil1MHIu
"All generous minds have a horror of what are commonly called 'Facts'. They are the brute beasts of the intellectual domain." -- Thomas Hobbes

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AgAuMoney

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Re: Engineering Targeted Returns and Risk
« Reply #1 on: March 14, 2013, 10:07:26 PM »
1996, didn't the other article in the other thread say they had been discussing it in the 1970's?  Oh well, no matter.

I'm deeply skeptical of attempting to so finely tune future risk and performance based on past risk and performance.

Calling it "engineering" is in vogue, but in reality the only relationship to engineering is math.  Engineering is based on testable, falsifiable and documented principles.  Financial engineering of this sort is based on theory and assumptions resulting in the famous GIGO principle with no way of knowing in advance.

MPT is based on academic theory with innumerable assumptions to try and make it applicable to the real world.

For example, risk.  In MPT risk has meaning.  In the real world future risk is unknowable and past risk is an impossible concept so when trying to apply MPT to the real world they equate risk and beta.  Beta can be calculated from historical data.  But beta isn't risk and equating it invalidates in the real world any plausibility MPT might have in the theoretical.

melveyr

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Re: Engineering Targeted Returns and Risk
« Reply #2 on: March 14, 2013, 10:21:08 PM »
Well, I don't think his strategies are overly engineered really. He really just offers something very similar to the PP, except with different levels of leverage applied so that the investor can take risk commensurate with their risk tolerance.

FWIW I have found that for the PP you can dial in the amount of leverage you take with the PP by adjusting the bond duration (duration is very similar to leverage for bonds): http://gyroscopicinvesting.com/forum/index.php?topic=3613.msg50148#msg50148

I like Dalio and I think studying his fund and strategy has helped me learn more about the PP and macro based investing than any other source (except for this forum and HB himself of course).
« Last Edit: March 14, 2013, 10:25:53 PM by melveyr »
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MachineGhost

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Re: Engineering Targeted Returns and Risk
« Reply #3 on: March 14, 2013, 11:39:59 PM »
Ag, I thiink you're confusing the two definitions of beta.  It means both the traditional correlated volatility to an index that is standard in CAPM as well as the more recent definition for exposure to any asset's risk.  I do not know why they conflated the two definitions in one term.  Typical "ivory tower" academics, probably.

There's nothing engineered about the AWP other than they use leveraging and deleveraging to normalize the risk across all the asset classes relative to each other.  That is the single crucial difference between AWP and PP and it solves a major flaw of the PP being overexposed to gold's beta (in the risk exposure sense) and "tight money".

The problem is I'm not quite convinced us mere mortals have the ability to delevarage gold, stocks and bonds and leverage up cash so all can meet in the sweet spot.  Perhaps melveyr's duration concept is the answer?  But I worry about not having cash as even the AWP has cash.  A middle compromise from the barbell just doesn't seem like it will work.
« Last Edit: March 14, 2013, 11:46:06 PM by MachineGhost »
"All generous minds have a horror of what are commonly called 'Facts'. They are the brute beasts of the intellectual domain." -- Thomas Hobbes

Disclaimer: I am not a broker, dealer, licensed investment advisor or licensed physician. I should not be considered as permitted to render such advice.

melveyr

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Re: Engineering Targeted Returns and Risk
« Reply #4 on: March 14, 2013, 11:56:15 PM »
MG,

I have noticed your posts moving towards more quanty type stuff which I like  :)

You might be interested in an extremely interesting formula which I stumbled upon. Most people assemble portfolios based on "dollar" allocations. However, you can also look at a portfolios "risk allocation." To do this for each asset you look at the weighted beta of each asset in the portfolio. In this context, the individual assets beta is with respect to the total portfolio (normally people calculate beta with respect to the stock market). So for example to find the risk allocation of the PP you would do the following.

Gold Risk: (weight of gold in portfolio) * (cov(gold returns, portfolio returns) / portfolio variance)
Stock Risk: (weight of stocks in portfolio) * (cov(stock returns, portfolio returns) / portfolio variance)
LTT Risk: (weight of LTT in portfolio) * (cov(LTT returns, portfolio returns) / portfolio variance)

A 3 way split between gold, LTT, and stocks has historically actually had unequal risk allocation...

Risk Allocation
Stocks: 30.1%
LTT: 24.8%
Gold: 45%

So in terms of risk allocation, the PP has historically been overweight gold even though the dollar amounts make it appear neutral.

For the 1978-2011 period the following dollar weightings were what provided equal risk contribution between the assets.

Stocks: 34%
LTT: 37%
Gold: 28%

In some sense this is reassuring that it is not that far off from the traditional PP! However, it helps make an argument that the PP is slightly overweight gold if you are aiming for neutrality between the assets.

« Last Edit: March 15, 2013, 12:04:26 AM by melveyr »
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MachineGhost

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Re: Engineering Targeted Returns and Risk
« Reply #5 on: March 15, 2013, 12:16:39 AM »
I have noticed your posts moving towards more quanty type stuff which I like  :)

There's nothing like real money on the line to crystalize and clarify.  Most people want to solve a problem and move on; I want to make sure there isn't going to be another one!  I loathe the strategic PP because the risk is too high; only recently do I "see" the exact specifics.

Anyway, I think that omitting cash for these "risk parity" allocations omits one of the economic environments.  So what is a way to deal with it in lieu of duration?  All I can think of is T-Bill futures.

"All generous minds have a horror of what are commonly called 'Facts'. They are the brute beasts of the intellectual domain." -- Thomas Hobbes

Disclaimer: I am not a broker, dealer, licensed investment advisor or licensed physician. I should not be considered as permitted to render such advice.

melveyr

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Re: Engineering Targeted Returns and Risk
« Reply #6 on: March 15, 2013, 12:21:50 AM »
I have noticed your posts moving towards more quanty type stuff which I like  :)

There's nothing like real money on the line to crystalize and clarify.  Most people want to solve a problem and move on; I want to make sure there isn't going to be another one!  I loathe the strategic PP because the risk is too high; only recently do I "see" the exact specifics.

Anyway, I think that omitting cash for these "risk parity" allocations omits one of the economic environments.  So what is a way to deal with it in lieu of duration?  All I can think of is T-Bill futures.

I think the real issue is that leverage is essentially like being "short cash" because the price of leverage is based off of the short term interest rate. When I am trying to backtest a leveraged strategy I just plug a negative number into cash to make the allocation equal 100%. So there is no way to lever up cash.

If you want to magnify the returns of your portfolio through its use than you just have to pray that any "tight money" recession will be short lived. Even the PP is vulnerable to tight money recessions. Luckily we have easy money with no end sight  ;D
« Last Edit: March 15, 2013, 12:24:21 AM by melveyr »
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AgAuMoney

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Re: Engineering Targeted Returns and Risk
« Reply #7 on: March 15, 2013, 11:51:38 PM »
Ag, I thiink you're confusing the two definitions of beta.  It means both the traditional correlated volatility to an index that is standard in CAPM as well as the more recent definition for exposure to any asset's risk.  I do not know why they conflated the two definitions in one term.  Typical "ivory tower" academics, probably.

Perhaps I am.  But all the papers on MPT I have read covering several decades have all used "risk" as the theoretical term, and when applying MPT principles to the market there is no way to measure risk to come up with a number.  Most of the papers then have explicitly adopted the standard measure of beta as a stand in for that unquantifiable risk in the equations.

If you read this paper on the All Weather approach, it is based on (or developed based on) MPT, and seems to use beta in the exact same way.

AgAuMoney

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Re: Engineering Targeted Returns and Risk
« Reply #8 on: March 15, 2013, 11:54:32 PM »
There's nothing engineered about the AWP other than they use leveraging and deleveraging to normalize the risk across all the asset classes relative to each other....

The problem is I'm not quite convinced us mere mortals have the ability to delevarage gold, stocks and bonds and leverage up cash so all can meet in the sweet spot.

That is exactly the engineering I am skeptical of as well.  With as many assumptions as are necessary to populate the equations, it is impossible to prove they are all valid for the past, much less will hold that validity when needed in the future.  (Look, is that a black swan?!)  Garbage in, garbage out.

AgAuMoney

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Re: Engineering Targeted Returns and Risk
« Reply #9 on: March 15, 2013, 11:55:56 PM »
you can also look at a portfolios "risk allocation." To do this for each asset you look at the weighted beta of each asset in the portfolio. In this context, the individual assets beta is with respect to the total portfolio

See, there again is that beta as a substitute for risk...

AgAuMoney

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Re: Engineering Targeted Returns and Risk
« Reply #10 on: March 16, 2013, 02:00:33 AM »
Dylan Grice, an investment strategist formerly with Societe Generale is now with Edelweiss Holdings.  He writes in a recent Edelweiss Journal:

Quote from: DylanGrice
Of the many elemental flaws in macroeconomic practice is the true observation that the economic variables in which we might be most interested happen to be those which lend themselves least to measurement. Thus, the statistics which we take for granted and band around freely with each other measuring such ostensibly simple concepts as inflation, wealth, capital and debt, in fact involve all sorts of hidden assumptions, short-cuts and qualifications. So many, indeed, as to render reliance on them without respect for their limitations a very dangerous thing to do. As an example, consider the damage caused by banks to themselves and others by mistaking price volatility (measurable) with risk (unmeasurable). Yet faith in false precision seems to us to be one of the many imperfections our species is cursed with.

The previous issue was entitled On measuring the unmeasurable and alluded to the same concept.  It was excerpted from their annual letter to shareholders, and unattributed in the Journal.  I do not believe Dylan wrote it, but perhaps he did.

melveyr

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Re: Engineering Targeted Returns and Risk
« Reply #11 on: March 16, 2013, 03:42:49 PM »
you can also look at a portfolios "risk allocation." To do this for each asset you look at the weighted beta of each asset in the portfolio. In this context, the individual assets beta is with respect to the total portfolio

See, there again is that beta as a substitute for risk...

I agree that beta is a mere proxy for risk. However, I would rather use a proxy than nothing at all! I like using quantitative measures to help verify a theoretical framework (like the PP) or use the quantitative measures to help arrive at new ideas. Whenever I go on a number crunching binge I always learn more about markets.  :D
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AgAuMoney

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Re: Engineering Targeted Returns and Risk
« Reply #12 on: March 16, 2013, 04:22:03 PM »
Using a proxy allows computing results, with implied correctness to those results, when that correctness is entirely dependent on the correctness of the proxy.

I would argue that using an incorrect proxy is worse than nothing at all.

Stefan

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Re: Engineering Targeted Returns and Risk
« Reply #13 on: March 17, 2013, 03:47:24 AM »
I am happy to see renewed interest in AWP. I tried to bring it up in the VP forum last year - but it didn't go anywhere...
AWP is, of course, based on PP, but with a few key improvements. And I think you can only gain, a lot, if you understand these mechanisms and have the skill set to apply them to your portfolio management:

1. The Holy Grail. The idea of having more, uncorrelated ACs is that, the more ACs you add to your portfolio, the less volatile your portfolio. This is what Ray Dalio calls the “Holy Grail” of investing (see his interview in Schwagger’s “Hedge Fund Wizards” for a complete explanation). In RD’s case, he has the ability to use much more uncorrelated ACs than us, the public. But still, because of the ETFs bonanza of these times we can use ACs like emerging  market debt, high yield, TIPs, commodities, all unavailable to us in HBs times. And I tested that they really reduce the  portfolio volatility while improving its returns.

2. Explicit Risk Parity. Allocate ACs so that each contribute equally to portfolio risk. Here is a simple mechanism for this: If all assets are somewhat uncorrelated (based on their different response to growth/inflation shocks), allocating each asset inverse proportional with their volatility would achieve this. This is called “naïve” risk parity, as it is obviously an approximate derivation from the portfolio variance formula, but this is what is mostly used in practice. The idea is, to reallocate (or re-balance in PP parlance) on a periodic basis, but based on volatility and not just equal weights. Try to use volatile ACs, so you do not need leverage.
Now, HBPP achieves this implicitly. The 3 ACs in HBPP all have similar volatility. For instance, this is the reason he uses the long bond instead of the TNote, to match stocks and gold volatility. AWP just makes this allocation mechanism explicit.

3. Targeted Volatility. Basically, you measure the current portfolio volatility, periodically (say, once a month) and adjust the AC weights to reduce the whole portfolio volatility if above target. Or leverage if below target (but you won’t do that in practice). Adjustable target volatility is the system parameter you can dial up/down to the “sleep well at night” value.

4. Another key thing RD does is that he overlays a risk management system on top of all this. For instance, in 2008 he reduced massively the AWP allocations based on what he called his “depression gauge”.  This is on top of the targeted volatility risk management .
RD I think uses fundamental research for his “gauge” but you can achieve similar results using technical indicators, like MG apparently tried to show here.
« Last Edit: March 17, 2013, 04:00:50 AM by Stefan »

MachineGhost

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Re: Engineering Targeted Returns and Risk
« Reply #14 on: March 17, 2013, 06:48:44 AM »
But still, because of the ETFs bonanza of these times we can use ACs like emerging  market debt, high yield, TIPs, commodities, all unavailable to us in HBs times. And I tested that they really reduce the  portfolio volatility while improving its returns.

So this is essentially slicing, dicing and tilting the four assets?

Quote
This is called “naïve” risk parity, as it is obviously an approximate derivation from the portfolio variance formula, but this is what is mostly used in practice. The idea is, to reallocate (or re-balance in PP parlance) on a periodic basis, but based on volatility and not just equal weights. Try to use volatile ACs, so you do not need leverage.

Again, what do you do about cash?  You can't naively risk cash because it will overwhelm the other three assets.  On the other hand, you can't naively risk the other three assets and place the gap into cash either because their percentages are way too small.  If you decide to scale naive risk non-cash upwards proportionally, then you get into issues of how far to go.

Quote
Now, HBPP achieves this implicitly. The 3 ACs in HBPP all have similar volatility. For instance, this is the reason he uses the long bond instead of the TNote, to match stocks and gold volatility. AWP just makes this allocation mechanism explicit.

I would argue the HBPP does it very poorly and inefficiently.  As melveyr quanted earlier, gold's volatility dominates.

My solution posted elsewhere was to give up on tactical allocation and increase cash and reduce the other three assets proportionaly for my targeted risk.  But I still feel like this is putting lipstick on a pig...  perhaps the solution is to preserve the proportions between three risk normalized assets and then increase or decrease cash to get to the targeted volatility?
« Last Edit: March 18, 2013, 12:49:59 AM by MachineGhost »
"All generous minds have a horror of what are commonly called 'Facts'. They are the brute beasts of the intellectual domain." -- Thomas Hobbes

Disclaimer: I am not a broker, dealer, licensed investment advisor or licensed physician. I should not be considered as permitted to render such advice.