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FT: Junk bonds, the darling of the debt markets for two years, are proving remarkably resilient.
Globally, triple C-rated companies, which include names such as J Crew, the clothing chain, and Level 3, the communications group, have sold $9.8bn of debt this year, well above the previous year-to-date record of $5.2bn in 2007.

This reflects demand from the continued inflows into mutual funds investing in high-yield corporate bonds, as well as appetite for risk from hedge fund investors. “In general, there used to be pretty strong resistance to accept new issuance from companies that were rated triple C,” said Martin Fridson, global credit strategist at BNP Paribas Asset Management.
ccc_issuance_ftA handful of bond sales recently included two features considered particularly risky, according to Standard & Poor’s LCD, which tracks the leveraged finance markets. One of those features was so-called PIK toggle, a popular structure before the financial crisis that gives an issuer the option to pay interest with more bonds rather than in cash. Debt was borrowed, too, to pay special dividends to companies’ owners, in a “dividend deal”. Typically, investors will accept these features from companies with ratings on the higher rungs of the junk category, but all four of these deals were rated triple C.

Bonnie Baha, head of global developed credit at DoubleLine, says there are now more riskier companies than in the past. “If you are just looking at spreads, you can say we still have room to run, but what people fail to recognise is that the credit quality of the relevant credit indices is lower now than it was at the previous low points in credit spreads and that alters the logic,” she says. The days of the junk bull run may be numbered.

Story: Junk bonds resilient as US recovery trumps oil, FT

This post explains the Vasicek/Merton single factor model which is part of the Basel framework (IRB approach) and has been used to evaluate CDOs.

Imagine you loan money to a friend who will default with a probability of 1%. When it comes to paying back the loan you will either receive 100% (plus any interest) or 0%. That's pretty risky. So you figure you can improve your situation by making same size loans to n friends. (NB: You will need a license for doing so). In case they all default individually with a probability of p = 1%, the law of large numbers tells you that the more loans you make (increase n), the closer the average default rate (= portfolio default rate) will be to 1%. "The" central limit theorem states that the portfolio default rate will be normally distributed with a mean of 1% and a variance that goes to zero as n increases.

Now here is the result for n = 5000 loans and 100,000 simulations (portfolios):
Unfortunately, this is only true when default solely happens due to idiosyncratic reason such as illness or a divorce, i.e. when the default of one friend is not related to the default of another friend. But in case you make loans to colleagues from work this assumption won't be correct since bankruptcy of the company would turn most of your loans sour at the same time no matter how large (number of obligors) your loan portfolio actually is. In other words: Certain systemic risk can't be diversified away.

Assuming you really have lots of "similar" friends (p = 1%) and they are all pretty evenly distributed across the sectors the economy has to offer one could argue that defaults are actually only a function of this idiosyncratic risk (as before) and a single systemic risk factor reflecting the overall state of the economy. In case the economy does very well, hardly anybody will default (even an expensive divorce is not an issue) and in case the economy enters into a deep recession, the default rate goes north. The sensitivity of each obligor to this systemic factor and the correlation among the obligors is given by √ρ and ρ, respectively.

Result for n = 5000 loans and 100,000 simulations (portfolios):
The average portfolio default rate is not affected by an increase in correlation, but the higher the correlation the more likely extreme portfolio default rates become (good or bad). In case the correlation is one, we are back to a single obligor. Either nobody (0%) or everybody (100%) defaults.

The model (see comment section for details) is a useful starting point but since both systemic and idiosyncratic risk is assumed to be normally distributed and are connected via an uncertain correlation coefficient you could easily be on the wrong end of the trade. NB: That doesn't mean the Basel guys did a bad job. They had two parameters (correlation and systemic shock size) for calibrating the model.


Oliver Wyman:
As the population ages, the demand for financial products will change. Broadly speaking, older consumers are wealthier than younger ones. They have greater balances in savings and investment accounts and are much more likely to live in an un-mortgaged home. As they reach retirement, their demand for “accumulation” products, such as equity mutual funds and amortizing mortgages (designed to accumulate home equity), declines markedly from their peak accumulation years. At this stage of life, their needs shift to “draw-down” products, such as annuities and structured income contracts. [...]

Banks that can develop solutions for these consumers will create massive value for them. Life insurers begin with one advantage over banks. Their traditional business involves expertise in precisely the kinds of products and risks (especially longevity risk) that are required to serve an aging customer base. To succeed in the emerging demographic environment, banks will need to acquire the skills characteristic of life insurers.
The Future of Banking : Six trend that will shape the industry, Oliver Wyman

CDS Curve (white line) vs. Z-Spread (+)
Read: Citi sees free lunch in Greek basis (almost), FT Alphaville

Deutsche Bank Research: Existing evidence related to the impact of HFT on certain market quality and efficiency indicators is inconclusive. Some studies (e.g. Hendershott and Riordan, 2009; Jovanovic and Menkveld, 2010) suggest that HFT using market making and arbitrage strategies has added liquidity to the market, reduced spreads and helped align prices across markets. While there is no proof of a negative liquidity impact in the academic literature, certain issues still remain:
  • HFs are under no affirmative market making obligation, i.e. they are not obliged to provide liquidity by consistently displaying high-quality, two-sided quotes. This may translate into a lack of available liquidity, in particular during volatile market conditions.
  • HFTs contribute little to market depth due to the marginal size of their quotes. This may result in larger orders having to transact with many small orders and may affect overall transaction costs
  • HFT quotes are barely accessible due to the short duration for which the liquidity is available when orders are cancelled within milliseconds.
Another interesting issue is whether HFT contributes to the price formation process on equities markets. In this context, Brogaard (2010) examines a large data set of HFT firms trading on Nasdaq and finds that, firstly, HFTs add substantially to the price formation process as they tend to follow a price reversal strategy (irrespective of whether they are supplying liquidity or demanding it), driven by order imbalances, and so tend to stabilise prices. Secondly, HFTs do not seem to systematically front-run non-HFTs. They provide the best bid and offer quotes for a significant portion of the trading day, but only around a quarter of the book depth (as do non-HFTs) and reduce their supply of liquidity only moderately as volatility increases. Thirdly, HFTs engage in a less diverse variety of strategies than non-HFTs, which may exacerbate market movements if HFTs use similar trading strategies. Fourthly, while in principle high cancellation rates could impact the smoothness of execution in markets where HFTs are present, prevailing narrow spreads seem to suggest that cancelled quotes are quickly replaced by other market participants. Hendershott and Riordan (2009) find that algorithmic traders’ quotes play a larger role in the price formation process than human quotes. Summing up, on the one hand, price discovery benefits from market participants who quickly detect anomalies in market prices and correct them. On the other hand, HFT may distort price formation if it creates an incentive for natural liquidity to shift into dark pools as a way of avoiding transacting with ever-decreasing order sizes. In terms of market volatility, neither Hendershott and Riordan (2009) nor Brogaard (2010) find any evidence for a detrimental impact of either AT [algorithmic trading] or HFT. Economic perspective and potential regulatory aspects.

High-frequency trading? Better than its reputation?, DB Research, Feb 2011

Theory has, at length, become so "scientific" and abstract as to intrigue the mathematicians who have taken delight in developing the concept of a kaleidoscopic and frictionless play of atomistic units in a complex and eternally unfolding equilibrium. The notion of equilibrium suggested equations; equations are prolific parents of their kind; and the game has gone on until the pages of the more esoteric economic journals have become a mass of hieroglyphics intelligible only to those who know the code. All the inconvenient freight of fact has been discarded by the more recondite practitioners until the "science" has come to move in a realm of pure abstraction useful for purposes of cerebration but of steadily declining practical importance.

Much first-rate analytical skill and much scholarly industry has miscarried because the road to academic recognition lay in the refinement of traditional technique, or in assiduous dust-gathering, with little consideration of ultimate purpose. The means have been exalted over the end, and the neophyte, compelled to show his mastery of technique, has quickly learned to love and practice it for its own sake.
This is not to deny the virtue, even the necessity, of abstract speculation or the desirability of the most catholic comprehension of the facts. It is merely to assert that these should be tools rather than ornaments and that we should never cease to ask ourselves what we want and how we propose to get it.

Frank D. Graham, 1942
Social Goals and Economic Institutions, Frank D. Graham, Princeton University Press, 1942, pp. xv-xx
What do Economists Contribute?, Cato Institute, NY University Press, 1999, pp. 27

Financial News: Investment consultants are pushing for a seismic shift from active asset management to passive in a move that could result in savings of more than $50bn a year for pension schemes and other institutional investors and a switch of trillions of dollars in assets.

The advice is based on consultants’ growing belief that some markets, including the US and UK equity markets, have become so efficient that active managers will find it hard to add value.

Tim Hodgson, a senior investment consultant at global consultancy Towers Watson, told Financial News: “We estimate the overall ratio of passive to active, including all invested assets globally, is 10:90. We think it should be 70:30.”

Pension schemes globally controlled more than $26 trillion of assets at the end of last year, according to Towers Watson. A switch of the magnitude proposed would involve almost $16 trillion moving from active to passive mandates. It would also precipitate a fundamental overhaul of the global fund management industry. Full Story