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
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:
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
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:
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
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
