Risk Management Quant

Just How Vulnerable Is Asia To The Current US Sub-Prime Crisis?

Fri, 31 Aug 2007 03:59:00 +0000

If you ask Asian banks about their exposure to US Sub-Prime debt, they would probably say that the exposure is pretty small. In fact, Asian central banks also agree with this notion. Unlike some hedge funds with nearly 100% exposure to the sector, the percentage of exposure to US Sub-Prime trough CDO's are not significant enough to dent the bank's earnings and value. Income streams of these banks are diversified enough to absorb the shocks. But that's in the ideal world, where current correlations regimes stay constant.

But we all know that during a crisis situation, correlations can change, and a seemingly isolated case can evolve into a full blown crisis that affects everything. Now we don't know if the banks are thinking about this situation or not. But risk management best practice dictates that they should.

My QA = TA Post Sparked a Debate

Fri, 16 Feb 2007 06:20:00 +0000

I knew this was coming. Posting a link to my previous blog entry in a quants forum sparked a heated debate. See what very intelligent people has to say about the merits of quantitative analysis and technical analysis. Some even pointed out that TA has more realistic models than QA.

Link to the QA vs. TA thread

Tags: quant technical analysis wilmott

Quantitative Analysis = "Highly" Technical Analysis (?)

Wed, 07 Feb 2007 06:34:00 +0000

Branding Quantitative Analysis as "Technical Analysis" will probably bring in some violent reactions from quants. But I just want to point out the similarities that they share. In fact, it can be seen that Quantitative Analysis is a higher form of Technical Analysis.

Technical Analysis is commonly described as Charting. It is the study of charts (graphical representation of past price movements) and finding patterns in them. Investment decisions are then based on these patterns. People say this is superstition as price moves randomly and just forms these patterns by chance. Technical analysis also utilize quantitative techniques via Technical Indicators. Technical Indicators aren't just numbers, they are results of some statistical modelling. Indicators like MACD and Bollinger Bands are actually similar to statistical measures used by quants today (mean and standard deviation respectively). These measures are used for momentum and mean reversion strategies. Technical analysis also looks into other quantifiable variables found in the market like traded volume, open interest, bid ask spreads, etc. Technical analysis gives rise to automatic trading rules which is also done with quantitative analysis.

In the Jan/Feb 2007 Issue of CFA Magazine, there is an article ("Perpetual Motion by Susan Trammell, CFA") about a recent study on trends in quantitative investing. Below are some findings:

Phenomena Being Modeled:

Fund Capacity: 20%
Impact of Trades: 24%
Textual Data: 2%
Higher Moments: 2%
Regime Shifts: 10%
Volatility: 20%
Extreme Events: 10%
Momentum / Reversal: 31%
Trends: 28%

Modeling Methodologies Used:

Shrinkage / Averaging: 9%
Regime Shifting: 4%
Nonlinear: 7%
Contegration: 7%
Cash Flow: 17%
Behavioral: 16%
Momentum / Reversal: 28%
Regression: 36%

As seen in the survey results, trends, momentum, and reversal models are quite popular in quantitative analysis. These are also the same phenomena being modeled by technical analysis but at a less "scientific" degree.

The relationship of Technical and Quantitative analysis can be likened to the relationship between Astrology and Astronomy. One is seen as superstition while the other as a science. Astrology came about due to the lack of sophisticated tools and theories. The same with Technical Analysis -- people relied on charts because it was easier to analyze than numbers. But in the advent of faster and more powerful computers, large amounts of numbers can be analyzed with ease.

To see the survey results, please refer to www.theintertekgroup.com.

Tags: financial engineering investments quant technical analysis

Doomsday!?

Mon, 29 Jan 2007 22:37:00 +0000

We've been hearing about several doomsday scenarios. The most relevant one we're hearing nowadays is Climate Change. But there are also people who speak about Financial Disaster and sites like Financial Armageddon is an example. Their concerns are plausible and worth thinking about.

Tags: books capital markets finance risk management

Losing Money When There is No Volatilty

Mon, 29 Jan 2007 06:40:00 +0000

It is common knowledge that there is more risk when there is more volatility. But it is also possible to lose (a lot of) money in the absence of volatility as well. This case was illustrated in a recent article published by Financial Engineering News. It was reported that Credit Suisse recently lost $120 million in Korean Derivatives -- particularly reverse convertible bonds.

A conventional convertible bond offers lower interest rates but gives the investors an option to call a company's stock. The bondholder is effectively the owner of the option and the issuer is the option writer. A reverse convertible bond gives investors higher interest rates but gives the issuer the right to put shares to the investor. In this case, the bondholder is the seller of the option and the issuer is the option buyer. When volatility increases, option prices increase as well. This added value stems from a higher possibility of going in-the-money. Conversely, a decrease in volatility will lower the option value. So if Credit Suisse was the one who "bought" the stock options via the reverse convertible structure, a decrease in volatility will decrease option value and will result into a mark-to-market loss on their end.

Now as market makers (structurers), shouldn't Credit Suisse be hedging their exposure? The problem with this particular structure is that the option is not based on one stock. It issued reverse convertibles on a number of shares. Hedging proved to be quite difficult and luck was not on their side, as stated in the article:

The problem however came in the hedging. Credit Suisse no longer had a single put option, nor did it have a portfolio of put options, since it could exercise its put into only one share. Instead it had an option on an option, a put option under which it could choose the share on which the option would be exercised. This instrument could be reasonably hedged by an appropriate portfolio of the shares provided volatility remained approximately constant, but it was effectively unhedgeable against a sharp change in volatility. If volatility in Korean shares had increased, there would be no problem; Credit Suisse’s multiple put option would be more valuable. There was, however, no effective way to hedge against a decline in volatility, which is what happened.

The lessons that we can learn here are the following:

1) You can lose when there is less volatility -- particularly in options since volatility is explicitly included in valuation.
2) When building a structure, one should know how to hedge it properly.

Tags: derivatives financial engineering investments valuation volatility structured products options

My Tip for CFA Candidates

Tue, 09 Jan 2007 00:15:00 +0000

This may be old but my quote was publised in the November 06 issue of CFA Advantage.
Hope you find it helpful and inspiring.

Tags: CFA

Making Risk Measures Agree with Accounting 100%

Tue, 26 Dec 2006 02:27:00 +0000

In my consulting experience, there are clients that use risk software to compliment financial reporting (accounting). Instead of being used solely by the risk department, even financial controllers use it. This is due to the current trend of making financial reporting reflective of the firm's economic value based on the risks it is taking (IAS 39 and even Basel II). As a consequence, they expect the results form the risk software to be consistent with accounting results to the last cent. I guess this is the ideal state that everyone wants to achieve but is this really necessary?

Though related, I believe that risk measurement and accounting are serving different purposes. Risk measurement need not be exact because of the uncertainty of risk. Because of the future-centric nature of risk measurement, generalizations and simplifications in the models are made and may not necessarily result into exact market values, etc. In risk measurement, benchmark results are acceptable as long as they are reasonable (where you can see the degree of sensitivity to different types of risks). So what is important in risk measurement is not the valuation of your positions to the exact cent but the model on how this value reacts with different types of risk. Contrary to risk measurement, accounting focuses on past performance. People tend to be very meticulous in this field to the point that they want things to be correct to the last cent. This is because in most organizations, even in today's banks, profit and loss (past performance) is still more important.

Nowadays, with all the innovation in software and the computing power of currently availabe hardware, people tend to assume that risk software can double as accounting software. But in reality, these two fields have different requirements (although they may be similar in some ways). It is true that a software can be made flexible enough to accommodate both requirements. Results may not be exact but good enough. But getting values to agree with the accounting system would result into more computing time due to the increase in inputs, variables, and complexity of models. Is the additional cost justifiable given that additional benefit is only to reconcile a few dollars and cents? Probably not today but probably (and hopefully) in the near future when hardware specs get better while prices get cheaper.

Tags: accounting finance risk measurement software

Model Validation - Not Just for Quants

Tue, 26 Dec 2006 02:10:00 +0000

In an article recently published in the ERisk Monthly Newsletter, it is stated that model validation is not a purely quantitative endeavor. Below is a quote from the article.

Model validation is often thought of as a rather technical and mathematical exercise. However, bank losses from model risk are often caused by poor governance of the wider modeling process, or by a poor understanding of the assumptions and limitations surrounding the model results, rather than by errors in equations.

The growing importance of models in helping executives answer some of banking’s most critical questions – from compliance and capital adequacy to business performance and risk-adjusted compensation – suggests that model validation is too important to be narrowly defined or left to the “quants”.

For both best practice and regulatory compliance reasons, senior bank executives must begin to take a more commanding role in ensuring that model validation is aligned with the overall interests of the bank – and that the bank’s investment in sound risk modeling can be easily communicated and proved to third parties.

Tags: financial engineering derivatives model validation governance audit

Quant Cartoons

Mon, 30 Oct 2006 22:06:00 +0000

This cartoon was sent to me by Financial Engineering News. Enjoy!

FENtoon

Tags: financial engineering derivatives algorithms

Hedge Funds Semantics

Thu, 24 Aug 2006 21:48:00 +0000

Hedge funds are very risky investments. They invest in derivatives, employ unconventional trading strategies, and are usually greatly leveraged... All for the pursuit of extraordinary profits. A lot of hedge funds have come and gone and the survival rate is not encouraging. So why are they called "hedge" funds in the first place?

When we hear the word "hedge" we usually think of protection and safety. In finance, a hedge, usually in the form of derivatives, is used to protect an investment from loss. But it also limits the gains of the position as well. This makes potential earnings predictable and constant. Risk is eliminated since risk is defined as "uncertainty".

But looking at the hedging instrument individually, it is just as exposed to losses as other instruments. Moreover, derivatives are leveraged and losses are potentially greater than conventional assets. The hedge only takes shape if the hedging instrument is taken together with another position, and their reaction to changes in market factors should cancel each other out.

Hedge funds act in the same way. Taken alone, hedge funds are risky investments. But when combined with conventional funds, they can provide diversification benefits and even enhanced returns due unconventional strategies and assets employed. These unconventional strategies and assets result into low correlations with conventional funds.

I guess a lot of people assume that hedge funds are supposed to be safe investments because of the word "hedge". But if these funds are meant to safe in the first place, they should be called "hedged" funds instead.

Tags: finance derivatives hedge funds investments