In an earlier post, I indicated that I had read the paper referenced below, and I wanted to summarize for you some of the more salient points. I write this post requesting your forgiveness in advance that I'm such a poor conduit for expressing some of the issues in this paper. Despite my inadequacy in purveying the learned information--I'm going to liken this effort to not being able to play the concerto but able to hum (off-key, of course), the tune--I'm nevertheless going to try.
As an individual investor, I find the complexity of the financial markets overwhelming at times. But Albert Einstein found simplicity and elegance in his economic rendering of the theory of relativity to e=mc(2). By that example (and clearly understanding that I'm no Albert Einstein, but rather one who appreciates simplicity), I will see complexity, then, as an obstacle that must be cut through to find the essence--the kernel--that is fully within the grasp of us mere mortals. We'll let the statistical and economic gods wrestle with and collegially debate the more arcane aspects of this learned paper. And, on a strictly selfish basis, I will extract those aspects that I found interesting and worth considering.
But why be interested at all in this paper and its theories and findings? Why should you be interested, wasting your valuable time reading this post? In a word, RISK. Risk v. reward is a time honored means of measuring whether an endeavor will prove fruitful or not. I feel inadequately informed on risk; and maybe you are well-informed. If you are not, then some of these considerations may amplify your awareness of risk. If we do not have a basic understanding of the risks--what those risks are and whether or not the risk profile of the market is rising or falling--then how will we make prudent choices with respect to allocating/protecting our resources?
This paper and my distillation of it is only a slice of overall risk--but I think that it covers one of the greatest risks--an exogenous event that creates a rather serious problem in the markets. Trust me, you will not be able to get out of the market if such an event happens. I couldn't even get current data through Fidelity during the February 28 Shanghai Express that had all the exits blocked.
In the interest of not losing you (or myself) in this exposition, I'm going to break it up into manageable segments. I will create a label for the post "HF and Systemic Risk" so that you can see the series). I'd like to also add that everything expressed herein is 100% attributable to the paper. However, I will have a couple of peanut gallery observations, and I will clearly label them as my own through bracket offsets [.....].
Finally, I would deeply appreciate some feedback as to if you find this exposition of this article helpful at all. Granted, there is a piece of me that is writing to force (and reinforce) my personal distillation of the material, but I would be lying if I stated didn't care if YOU were interested. I'm not looking for any blind encouragement, but rather a sincere judgment on your part as to whether or not this is a good use of your time. You may e-mail me (see profile) or place a comment in the comments section.
First, let me introduce the paper and the authors as well as the abstract. Emphasis added. The link on the header is to the paper.
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As an individual investor, I find the complexity of the financial markets overwhelming at times. But Albert Einstein found simplicity and elegance in his economic rendering of the theory of relativity to e=mc(2). By that example (and clearly understanding that I'm no Albert Einstein, but rather one who appreciates simplicity), I will see complexity, then, as an obstacle that must be cut through to find the essence--the kernel--that is fully within the grasp of us mere mortals. We'll let the statistical and economic gods wrestle with and collegially debate the more arcane aspects of this learned paper. And, on a strictly selfish basis, I will extract those aspects that I found interesting and worth considering.
But why be interested at all in this paper and its theories and findings? Why should you be interested, wasting your valuable time reading this post? In a word, RISK. Risk v. reward is a time honored means of measuring whether an endeavor will prove fruitful or not. I feel inadequately informed on risk; and maybe you are well-informed. If you are not, then some of these considerations may amplify your awareness of risk. If we do not have a basic understanding of the risks--what those risks are and whether or not the risk profile of the market is rising or falling--then how will we make prudent choices with respect to allocating/protecting our resources?
This paper and my distillation of it is only a slice of overall risk--but I think that it covers one of the greatest risks--an exogenous event that creates a rather serious problem in the markets. Trust me, you will not be able to get out of the market if such an event happens. I couldn't even get current data through Fidelity during the February 28 Shanghai Express that had all the exits blocked.
In the interest of not losing you (or myself) in this exposition, I'm going to break it up into manageable segments. I will create a label for the post "HF and Systemic Risk" so that you can see the series). I'd like to also add that everything expressed herein is 100% attributable to the paper. However, I will have a couple of peanut gallery observations, and I will clearly label them as my own through bracket offsets [.....].
Finally, I would deeply appreciate some feedback as to if you find this exposition of this article helpful at all. Granted, there is a piece of me that is writing to force (and reinforce) my personal distillation of the material, but I would be lying if I stated didn't care if YOU were interested. I'm not looking for any blind encouragement, but rather a sincere judgment on your part as to whether or not this is a good use of your time. You may e-mail me (see profile) or place a comment in the comments section.
First, let me introduce the paper and the authors as well as the abstract. Emphasis added. The link on the header is to the paper.
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Systemic Risk and Hedge Funds
Nicholas Chany, Mila Getmanskyz,
Shane M. Haasx, and Andrew W. Loyy
This Draft: August 1, 2005
Abstract
Systemic risk is commonly used to describe the possibility of a series of correlated defaults among financial institutions|typically banks|that occur over a short period of time, often caused by a single major event. However, since the collapse of Long Term Capital Management in 1998, it has become clear that hedge funds are also involved in systemic risk exposures. The hedge-fund industry has a symbiotic relationship with the banking sector, and many banks now operate proprietary trading units that are organized much like hedge funds. As a result, the risk exposures of the hedge-fund industry may have a material impact on the banking sector, resulting in new sources of systemic risks. In this paper, we attempt to quantify the potential impact of hedge funds on systemic risk by developing a number of new risk measures for hedge funds and applying them to individual and aggregate hedge-fund returns data. These measures include: illiquidity risk exposure, nonlinear factor models for hedge-fund and banking-sector indexes, logistic regression analysis of hedge-fund liquidation probabilities, and aggregate measures of volatility and distress based on regime-switching models. Our preliminary findings suggest that the hedge-fund industry may be heading into a challenging period of lower expected returns, and that systemic risk is currently on the rise.
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- number of hedge funds
- characteristics of these hedge funds to include (1) the dynamic investment strategies, (2) opacity; (3) attrition rates/longevity (or lack of it);
- interdependency of financial institutions with hedge funds (from both an investor and creditor stand point);
- correlations/non-correlations the dynamic investment strategies and how outside events can cause these strategies to suddenly correlate resulting in phase locking.
- reliance on linear risk models that do not effectively quantify non-linear risk
I'll spend the next installment providing some color regarding the hedge fund profile.]
3 comments:
Leisa,
I look forward to reading your take on this paper. Just wondering how you ended up selecting this particular study. I always have reservations about mathematical modeling of events which are not purely physical in nature (ie, not reproducible). I don't believe the out-sized performance of most hedge funds is necessarily explained by the assumption of more risk (unless you want to include legal liability and discovery as risks). It's not difficult to retroactively come up with an equation to explain a sequence of events, even if you're trying to "explain" human behavior. It's also a little too slick (it reminds me of John Cage's celebrated but hardly marketable 4'33"). In any case, I admire your efforts in trying to distill what the study has to offer (I scrolled through it and I'm glad it's you and not me!)
2nd_ave
2nd_ave
I'm just sitting down to do my next installment--thank you 2nd_ave for your feedback.
Your observations are good ones.
How did I settle on this study?--the study and I found each other: a fated match.
Regarding outsized performance not being due to outsized risk....I don't think that the authors are stating this, but rather that standard measures of risk do not appropriately measure the inherent risk--and in fact, the risks may be (1) misunderstood, (2)misrepresented and/or (3) unhedged.
I'm uncertain about the "little too slick" comment. A singular takeaway from the paper is the authors' claim (accurate or not I cannot say) that the means available to measure the real risks due to leverage and illiquidity and to include multiple counterparty risk--where the risk exposure is not disclosed or transparent in any way deterring any sort of judgment or analysis of greater than prudent risk exposure--is unsuitable. An unsuitable means of risk measurement MAY lead to an unsuitable means of risk assessment. They authors' are supplying one methodology, but appear to be wholly acknoweledging its shortcomings and calling for greater research.
By its very nature--that being systemic events are few and far between--any sort of statistical analysis of the event itself would be useless. Rather, the authors appear to be focusing on risk contributors--(a) hedge fund proliferation, (b) their use of leverage, (c) illiquidity of certain of the strategies and finally (d) trigger events in the market (think Shangai!, LTCM)that take non-correlated strategies and make them correlated bringing about the "phase-lock" which then causes the meltdown.
Perhaps poorly explained, but I hope that answers a bit of your questions.
Thank you, thank you, thank you, for your feedback.
The paper is appropriately titled to limit its subject to systemic risk, so I guess some of my comments are potshots. It's the non-systemic risks that would require an investigative reporter rather than a mathematician. If there are in fact mathematical models that detail how trigger events can somehow turn non-correlated strategies into correlated events and lead to a meltdown, then it would be a very timely statement.
2nd_ave
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