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Quantitative Finance Collector is a blog on Quantitative finance analysis, financial engineering methods in mathematical finance focusing on derivative pricing, quantitative trading and quantitative risk management. Random thoughts on financial markets and personal staff are posted at the sub personal blog.

Nov 13
I have written a working paper on CDS (credit default swap) implied stock volatility and found some interesting results. Post it here just in case someone is interested.

Both CDS and out-of-money put option can protect investors against downside risk, so they are related while not being mutually replaceable. This study provides a straightforward linkage between corporate CDS and equity option by inferring stock volatility from CDS spread and, thus, enables a direct analogy with the implied volatility from option price. I find CDS inferred volatility (CIV) and option implied volatility (OIV) are complementary, both containing some information that is not captured by the other. CIV dominates OIV in forecasting stock future realized volatility. Moreover, a trading strategy based on the CIV-OIV mean reverting spreads generates significant risk-adjusted return. These findings complement existing empirical evidence on cross-market analysis.

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Aug 16
A very nice paper by Knaup and Wagner (2012) published in Management Science. Enjoy it.

We propose a new method for measuring the quality of banks' credit portfolios. This method makes use of information embedded in bank share prices by exploiting differences in their sensitivity to credit default swap spreads of borrowers of varying quality. The method allows us to derive a credit risk indicator (CRI). This indicator represents the perceived share of high-risk exposures in a bank's portfolio and can be used as a risk weight for computing regulatory capital requirements. We estimate CRIs for the 150 largest U.S. bank holding companies. We find that their CRIs are able to forecast bank failures and share price performances during the crisis of 2007–2009, even after controlling for a variety of traditional asset quality and general risk proxies.

Article, Working paper
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Feb 28
Dr. Donald R. van Deventer is the Chairman and Chief Executive Officer of Kamakura Corporation, the world's leading provider of risk management solutions. His primary financial consulting and research interests involve the practical application of leading Kamakura Corporationedge financial theory to solve critical financial risk management problems. He was elected to the 50 member RISK Magazine Hall of Fame in 2002. Dr. Donald R. van Deventer has served on the editorial board of the Journal of Credit Risk since 2005, and has written numerous papers and several books covering a wide range of risk management.  

Tell us a little background info about yourself. Where are you from? What’s your education background?

I grew up in Los Angeles and was a double major at Occidental College in mathematics and economics.  I went to Harvard University and earned my Ph.D. in business economics in 1977.  The business economics program is a joint program of the Department of Economics and the Harvard Business School.

You had worked for a few financial institutions before founding your own company, what are the advantage and disadvantage of working in a risk solution provider over in the risk management group of a big financial firm, especially for a junior?

If one has the chance to work for a very innovative firm like Kamakura, there’s the challenge and the pleasure of making the state of the art better every day.  Within large financial institutions, a junior risk analyst is often trapped using an old fashioned legacy risk system purchased years before from a mediocre vendor.  That’s bad for one’s career for two reasons.  First, you don’t learn state of the art risk management and you run the risk of turning into a risk dinosaur at a young age. Second, if the firm is not using best practice risk management, the odds of failure are high even at a large bank as we’ve seen in the last five years.

A lot of people blame Copula or Black-Scholes formula for the current financial crisis, what’s your opinion on this debate?

My partner Prof. Robert Jarrow has a nice paper on the misuse of financial models and a video on the front page of the Kamakura web site www.kamakuraco.com on exactly this topic.  Black and Scholes certainly shouldn’t be blamed if an analyst uses the Black model (which assumes interest rates are constant) to price interest rate options.  The incorrect usage of financial models is astonishingly widespread.
Jan 26
Time Series Matching with Dynamic Time Warping: a follow-up post for time series matching mentioned in last week.

Risk-Based Dynamic Asset Allocation with Extreme Tails and Correlations: a unique dynamic portfolio construction framework that improves portfolio performance by adjusting asset allocation in accordance with a forecast of market risk.

Problems with Using CDS to Infer Default Probabilities: banking regulations and risk management decisions should not be based on CDS implied default probabilities.

Why Borrowing Rates Should Never Be Tied to Credit Default Swap Spreads: shortfall of doing so.
Jan 6
This week-in-review list is longer than usual since it actually covers over two weeks readings. Back to work from holiday, cheers up.

Quantpedia: The Encyclopedia of Trading Systems - turn academic research into financial profit.

PortfolioProbe: Blog year 2011 in review.

Portfolio optimization using forward-looking information: A minimum-variance strategy based on price information from a cross-section of plain-vanilla options consistently outperforms a wide range of benchmark strategies.

The Most General Methodology to Create a Valid Correlation Matrix for Risk Management and Option Pricing Purposes:  two simple methods to produce a feasible (i.e. real, symmetric, and positivesemidefinite) correlation matrix when the econometric one is either noisy, unavailable, or inappropriate.

Forecasting with Option Implied Information: surveys the methods available for extracting forward-looking information from option prices.

Machine Learning: enroll an online class of machine learning for free.

Collusion and CDS Dealer Volume: roughly 76-82% of all single name credit default swaps are trades between Bill Smith at Goldman Sachs and John Smith at JPMorgan or other dealer firms, should an investor take these traded prices as meaningful information?

The top 7 portfolio optimization problems: an excellent list of top 7 optimization problems we often meet and possible way to solve them.

A youtube video showing how to calculate Value at Risk of put options:
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