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Derivative's documentation matters

2018-06-05T09:55:23Z

Hector: Created page with "== Firms Involved == * Codere SA * GSO Capital Partners (Blackstone Group) == Year of the event == 2013 == Description of the case == Codere SA is a Spanish gaming company...."

== Firms Involved ==
* Codere SA
* GSO Capital Partners (Blackstone Group)

== Year of the event ==
2013

== Description of the case ==
Codere SA is a Spanish gaming company. Blackstone's GSO, lead by Akshay Shah<ref>[https://www.ft.com/content/5e23e516-5cdc-11e8-ad91-e01af256df68 "The mystery trader who roiled Wall Street", Financial Times, 2018-06-05]</ref> fund bought CDS on the firm, and then went on to propose cheap financing to Codere, with the condition that they delay the payment of a coupon on existing bonds by a few days, hence briefly defaulting and triggering the CDS which GSO owned<ref>[https://www.bloomberg.com/view/articles/2013-12-05/blackstone-made-money-on-credit-default-swaps-with-this-one-weird-trick "Blackstone made money on CDS with this one weird trick", Matt Levine, Bloomberg, 2013-12-05]</ref>.
This trade was widely criticized as the writers of the CDS found the default to be manufactured and artificial, and that CDS were not meant to be used like this and shouldn't have been triggered. The trade was nonetheless legal and went through, making a handsome payout to GSO.

== Take-aways ==
* Derivative instruments don't behave as we want them to. They behave as described in their documentation: prospectuses and ISDA rules. A deep understanding of these details can provide an edge and yield profit.
* CDS are primarily hedging instruments: using them for other purposes, for example "naked" speculation, requires extra dilligence to ensure that one only gains exposure to the factors or risks desired.

== References ==
<references />

The riskiness of volatility products

2018-02-13T20:32:22Z

Hector:

== Firms Involved ==
* Credit Suisse

== Year of the event ==
January 2018

== Description of the case ==
On Monday 5th of January 2018, the volatility of US equities, as measured by the VIX<ref>[http://www.cboe.com/products/vix-index-volatility/vix-options-and-futures/vix-index CBOE, VIX description page]</ref>, skyrocketed by 116%. This caused some serious issues on instruments designed to allow investors to bet against an increase of volatility. In particular, the VIX, and exchange-traded note (ETN), lost 93% of its value. Credit Suisse consequentially shut down the ETN on the next day<ref>[https://www.credit-suisse.com/corporate/en/articles/media-releases/credit-suisse-announces-event-acceleration-xiv-etn-201802.html Credit Suisse, Press release, ''Credit Suisse AG Announces Event Acceleration of its XIV ETNs'']</ref>, in accordance with the prospectus which allowed the issuer to do so in case of daily variation of more than 20%. This instrument was available to retail investors, even though its structure, covenants and risk profile were highly complex to apprehend.

In addition, huge intraday tracking error made the instrument exceptionally inefficient at replicating such a bet, in particular throughout Monday 5th<ref>[https://www.bloomberg.com/view/articles/2018-02-09/inverse-volatility-products-almost-worked Bloomberg, Matt Levine, ''Inverse Volatility Products Almost Worked'']</ref>. This was caused by the calculation method of the instrument, which relied on the prices of several futures on VIX with various maturities and not on the actual current VIX level<ref>[http://app.velocitysharesetns.com/files/prospectus/CS_VIX_VelocityShares_ETN_Amended_Final_Pricing_Supplement_AR48_long_form_2.PDF Credit Suisse, ''XIV Prospectus'']</ref>.

== Take-aways ==
* Selecting the right instrument to place a bet is key. For that, prospectus need to be read. The working of the instrument used needs to be thoroughly understood.
* In undertaking any kind of bet, beware of the tail risk (black swans).

== References ==
<references />

How to spot Ponzi schemes

2017-09-25T19:31:28Z

Hector:

== Firms Involved ==
* Bernard L. Madoff Investment Securities

== Year of the event ==
2008

== Description of the case ==
Bernard Madoff set up a sort of hedge funds around 1990. His official strategy was a split-strike conversion, which is a combination of a protective put and a covered call. To be more precise, it consists in building a long portfolio, and then sell out-of-the-money calls on an index with which the portfolio is highly correlated, and buying out-of-the-money put options (Strike below the calls'). The fund delivered about 16% annual return with minimal volatility, allowing the feeders such as ''Fairfield Sentry'' to reach Sharpe ratios above 2, unusually high for hedge funds. The fund was basically delivering the S&P500 with half its volatility.

However, the scheme proved to be a fraud in the form of a Ponzi Scheme. A rigorous operational due diligence would have raised the following warnings<ref>[https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1335639 Gregoriou & L'Habitant, "Madoff: A Riot of Red Flags", 2009]</ref> :
* Madoff's service providers (broker-dealer, fund administration, custody, etc.) were related to Madoff, or the services were performed internally.
* Madoff's family members occupied key position throughout the structure: board, executive positions, etc.
* The structure of the fund was complex and obstructed transparency: Madoff's firm was shielded by feeders which portfolios he managed as an advisor.
* The fee structure was highly unusual: Madoff allegedly only applied transactions fees, and no management nor performance fees.
* The auditor was an obscure firm which officially declared not having any audit clients, hence avoiding supervision by the regulatory bodies.

In addition, skeptics also highlighted before Madoff's fall that he could not deliver the performance disclosed without front-running the clients of his broker-dealer firm, the other possibility being that he was heading a Ponzi Scheme <ref>[https://www.sec.gov/news/studies/2009/oig-509/exhibit-0293.pdf Markopolos, "The World's Largest Hedge Fund is a Fraud", 2005.]</ref>

== Take-aways ==
* It is key to perform a rigorous operational due diligence in addition to quantitative analysis in any investment decisions, particularly in hedge funds. Effective frameworks do exist<ref>[https://papers.ssrn.com/sol3/papers.cfm?abstract_id=918461 Brown, Goetzmann, Liang and Schwarz, "Mandatory Disclosure and Operational Risk: Evidence from Hedge Fund Registration", 2006]</ref>.
* One must always remain skeptical and make sure to understand where the performance of any fund manager comes from. It may be selection skill, market timing skill, luck, fraud, or a mix of those.

== References ==
<references />

When learners escape models of their behavior

2017-07-24T15:54:29Z

Hector: Created page with "== Authors of the Article == * Jean Czerlinski Whitmore, ''Software engineer at Google'' == Publication Year == 2017 == Take-aways == * Escape pressures prompt agents to esc..."

== Authors of the Article ==
* Jean Czerlinski Whitmore, ''Software engineer at Google''

== Publication Year ==
2017

== Take-aways ==
* Escape pressures prompt agents to escape models of their behaviors, leaving the models at best useless, at worst counterproductive. Examples of escape from models include:
** The spam industry gamed the spam filters for Viagra, using various tricks such as voluntary spelling mistakes, use of images, etc.
** The pet food industry, which artificially increased the measured protein content of their pet food by using components causing the chemical test to produce higher results with lower protein content.
** The academic world, where there is a high pressure to publish a lot of papers without strong controls on quality.
* Such escape pressures are caused by:
** Visible and clearly specified goals
** High difficulty in achieving goals
** Significant gap in terms of outcome (success vs failure lead to considerably different outcomes)
* Modelers should take into account the existence of escape behaviors, and build their models accordingly:
** Use multiple models, not a single one to avoid model-specific limits and biases
** Use updatable or modular models to be able to adapt to new escape behaviors
** Use explainable models to differentiate between bad luck and model failure when predictions are wrong, and hence determine when to update the model
** Limit available information about your model, and limiting the possibility for others to test the model so they can’t easily understand it and game it.
* Escape pressure is a significant factor in finance. As regulations are announced publicly and are slow to be updated, financiers have room for escape. This may justify the increased complexity of financial regulations trying to capture all observed escape behaviors. Pushing agents to have more “skin in the game” (see Taleb) might be a good way to limit escape behaviors in finance.

== Quotes ==
<blockquote>''"Too much striving for measured goals hurts unmeasured goals."''</blockquote>

<blockquote>''"Every model excludes some aspects of reality—ideally the unimportant aspects. (If it included all of reality, then it would be reality.) But when a model is used to control human behavior, the humans can react by changing what is important and thereby escape the model."''</blockquote>

<blockquote>''"Modelers should study conditions that make escape from their models likely and develop better meta-modeling techniques to deal with escape."''</blockquote>

== References ==
* [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3006395 Whitmore, ''When learners escape models of their behavior'']

The dog and the frisbee

2017-07-20T12:44:45Z

Hector:

== Authors of the Article ==
* Andrew G. Haldane, ''Executive Director, Financial Stability, Bank of England''
* Vasileios Madouros, ''Economist, Bank of England''

== Publication Year ==
2012

== Take-aways ==
* Regulators and risk managers try to build exhaustive models to capture risk. However the complexity of the models actually decreases their efficiency while increasing their costs.
* Complexity hurts models because: gathering information is costly in terms of cash and time; weighting factors is near-impossible (e.g. 1/N is a very efficient portfolio); We only have small samples available, which makes estimates prone to large errors.
* Empirical studies show that simple models routinely outperform complex ones: risk-based capital ratios (using Basel's III rules) have a lower explanatory power for bankruptcy of large banks than their vanilla leverage ratios. SImilarly, estimating volatility with MA (moving average) leads to less violation of VaR than more complex models such as GARCH (Generalized autoregressive conditional heteroscedasticity) or EWMA (exponentially weighted moving average).
* Simpler rules and financial regulations would be more efficient, harder to game and less costly to implement.

== Quotes ==
<blockquote>''"So what is the secret of the dog’s success? The answer, as in many other areas of complex decision making, is simple. Or rather, it is to keep it simple. Studies have shown that the Frisbee‑catching dog follows the simplest of rules of thumb: run at a speed so that the angle of gaze to the Frisbee remains roughly constant."''</blockquote>

<blockquote>''"So what is the secret of the watchdogs’ failure? The answer is simple. Or rather, it is complexity."''</blockquote>

<blockquote>''"When sample sizes are small, simpler models are unambiguously superior. With highly imperfect information, adding model complexity simply increases prediction errors."''</blockquote>

<blockquote>''"Complexity of models or portfolios generates robustness problems when understanding a complex financial system over plausible sample sizes. More than that, simplicity rather than complexity may be better capable of solving these robustness problems."''</blockquote>

== References ==
* [https://www.kansascityfed.org/publicat/sympos/2012/Haldane_final.pdf Haldane, Madouros,''The dog and the Frisbee'']

How short-sellers cleanse financial markets

2017-07-03T22:17:15Z

Hector: Created page with "== Firms Involved == * Let's Gowex * Gotham City Research == Year of the event == 2014 == Description of the case == In July 2014, Gotham City Research published a detailed..."

== Firms Involved ==
* Let's Gowex
* Gotham City Research

== Year of the event ==
2014

== Description of the case ==
In July 2014, Gotham City Research published a detailed report<ref>[https://gothamcityresearch.com/2014/07/01/lets-gowex-la-charada-pescanova-a-pescanovan-charade/ Gotham City Research, ''"Let’s Gowex: La Charada Pescanova"'']</ref> denouncing Gowex as being a fraud, and announcing a price target of "€0.00 per share". Gowex was a Spanish telecommunications and equipment company providing wifi in public places and was boasting 100k hotspots installed mainly in Spain. After meticulous research, Gotham City Research only counted around 5k of them. They built a comprehensive report which exposed Gowex for blatantly overstating their revenues and profits. Just days after the publication of the report, the CEO recognized the fraud, and Gowex was filing for bankruptcy. In less than a week, the billion and a half of market cap of Gowex were reduced to ashes.

== Take-aways ==
* Low audits fees and contracting with an obscure accounting or audit firm can be a sign of fraud. Gowex was identified as a potential target because of its auditors<ref>[http://www.telegraph.co.uk/finance/newsbysector/banksandfinance/10963645/Gotham-City-Research-who-is-Daniel-Yu.html The Telegraph, ''"Gotham City Research: who is Daniel Yu?"'']</ref>.
* Exposing frauds can be a very profitable business for short-sellers

== References ==
<references />

Cloaked Trading

2017-07-03T21:28:49Z

Hector: Created page with "== Authors of the Article == * Lauren Cohen, ''Harvard Business School; National Bureau of Economic Research (NBER)'' * Dong Lou, ''London School of Economics & Political Scie..."

== Authors of the Article ==
* Lauren Cohen, ''Harvard Business School; National Bureau of Economic Research (NBER)''
* Dong Lou, ''London School of Economics & Political Science (LSE)''
* Christopher J. Malloy, ''Harvard Business School; National Bureau of Economic Research (NBER)''

== Publication Year ==
2016

== Take-aways ==
* Fund managers who have to disclose their holdings one a quarterly basis hide some of their positions using window-dressing (ie. Selling right before the quarter-end snapshot, and re-entering in the position afterward).
* The positions hidden earn abnormal returns: +370bps on the next month (annualized 36%).

== Quotes ==
<blockquote>''"Fund managers, knowing that the snapshot of their quarter-end holdings is mandated to be publicly viewable, solve endogenously as to the quantity and scope of information they choose to reveal through the snapshot"''</blockquote>

<blockquote>''"Mandated portfolio requirements and constraints are not without merit or justification, but we must recognize their onerous nature and the distortion these constraints have on observed behaviour."''</blockquote>

== References ==
* [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2901494 Cohen, Lou & Malloy, ''Cloaked Trading'']

Replicating Anomalies

2017-07-03T21:08:46Z

Hector: Created page with "== Authors of the Article == * Kewei Hou, ''Fisher College of Business, The Ohio State University; China Academy of Financial Research (CAFR)'' * Chen Xue, ''Lindner College o..."

== Authors of the Article ==
* Kewei Hou, ''Fisher College of Business, The Ohio State University; China Academy of Financial Research (CAFR)''
* Chen Xue, ''Lindner College of Business, University of Cincinnati''
* Lu Zhang, ''Fisher College of Business, The Ohio State University; NBER''

== Publication Year ==
2017

== Take-aways ==
* Most infringements to market efficiency identified by academic research are actually flukes. The market anomalies comprise variables for: momentum, value versus growth, investment, profitability, intangibles, trading frictions (among which liquidity).
* Most academic papers finding market anomalies abuse of equal weighting, hence overweighting small cap stocks, for which transactions costs are very high (ie. the arbitrages cannot be implemented for these stocks)
* Overall, financial markets appear more efficient than depicted in the academic litterature

== Quotes ==
<blockquote>''"Our results indicate widespread p-hacking in the anomalies literature. Out of 447 anomalies, 286 (64%) are insignificant at the 5% level. Imposing the cutoff t-value of three proposed by Harvey, Liu, and Zhu (2016) raises the number of insignificant anomalies further to 380 (85%)."''</blockquote>

<blockquote>''"The biggest casualty is the liquidity literature. In the trading frictions category that contains mostly liquidity variables, 95 out of 102 variables (93%) are insignificant. (...) The distress anomaly is virtually nonexistent in our replication. (...) Even for significant anomalies, such as price momentum and operating accruals, their magnitudes are often much lower than originally reported."''</blockquote>

<blockquote>''"regressions impose a linear functional form, making them more susceptible to outliers, which most likely are microcaps. Alas, due to high costs in trading these stocks, anomalies in microcaps are more apparent than real. More important, with only 3% of the total market equity, the economic importance of microcaps is small, if not trivial."''</blockquote>

== References ==
* [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2961979 Hou, Xue & Zhang, ''Replicating Anomalies'']

Fake Alpha

2017-07-03T17:12:25Z

Hector:

== Authors of the Article ==
* Marcel Müller, ''Chair of Financial Engineering and Derivatives, Karlsruhe Institute of Technology (KIT)''
* Tobias Rosenberger, ''Chair of Financial Engineering and Derivatives, Karlsruhe Institute of Technology (KIT)''
* Marliese Uhrig-Homburg, ''Chair of Financial Engineering and Derivatives, Karlsruhe Institute of Technology (KIT)''

== Publication Year ==
2017

== Take-aways ==
* Investors misinterpret the skill of active funds managers, and thus tend to accept the negative aggregate returns provided by the active management funds industry
* In particular, investors fail to properly quantify the risks related to factor investing. Therefore they feel that these strategies deliver abnormal or extraordinary returns with respect to their risk profile. Hence they are baited by ''Fake Alpha'' strategies, for which they overpay

== Quotes ==
<blockquote>''"Investors tremendously overinvest into active managed mutual equity funds. (...) We estimate that the US equity active mutual fund industry is too large by about 23% of its actual size. (...) This means that within 2014 $21.9 billion would have been falsely paid by investors of active managed US mutual funds to their managers."''</blockquote>

<blockquote>''"Investors would still provide flows to the funds in the long-run equilibrium even if the managers didn’t have any skill at all, since they confuse skill with risk premia on omitted factors"''</blockquote>

== References ==
* [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2899722 Müller, Rosenberger & Uhrig-Homburg, ''Fake Alpha'']

Do Private Equity Funds Manipulate Reported Returns?

2017-07-03T16:50:15Z

Hector:

== Authors of the Article ==
* Gregory W. Brown, ''University of North Carolina at Chapel Hill, Kenan-Flagler Business School''
* Oleg Gredil, ''Tulane University Freeman School of Business''
* Steven N. Kaplan, ''University of Chicago, Booth School of Business; National Bureau of Economic Research (NBER)''

== Publication Year ==
2016

== Take-aways ==
* Private equity funds managers have an incentive to overstate their performance before raising new funds
* Underperforming fund managers do overstate their performance
* This does not seem to be successful as these managers are less likely than their peers to raise new funds
* In opposite, overperforming fund managers are conservatives as they want to avoid being perceived as exaggerating their performances

== Quotes ==
<blockquote>''"Some GPs of poorly performing funds appear to overstate NAVs around the time they would be attempting to raise a follow-on fund"''</blockquote>

<blockquote>''"We also find evidence of conservatism in valuations among the best performing funds. This is consistent with a concern on the part of GPs about being wrongly labeled as a firm that exaggerates NAVs."''</blockquote>

<blockquote>''"LPs do not assume the interim performance reports are unbiased; they punish GPs for the appearance of overstated performance by not providing capital to subsequent funds"''</blockquote>

== References ==
* [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2271690 Brown, Gredil & Kaplan, ''Do Private Equity Funds Manipulate Reported Returns?'']