ETF Central » volatility

C. San-Lin, W.-C. Tsai, Y.-H. Wang, P.-S. P. Weng. The Information Content of the S&P 500 Index and VIX Options on the Dynamics of the S&P 500 Index.

Michael Bommarito — Mon, 22 Nov 2010 02:52:08 +0000

Abstract: Given that both S&P 500 index and VIX options essentially contain information on the future dynamics of the S&P 500 index, in this study, we set out to empirically investigate the informational roles played by these two option markets with regard to the prediction of returns, volatility and density in the S&P 500 index. Our results reveal that the information content implied from these two option markets is not identical. In addition to the information extracted from the S&P 500 index options, all of the predictions for the S&P 500 index are significantly improved by the information recovered from the VIX options. Our findings are robust to various measures of realized volatility and methods of density evaluation.

C. San-Lin, W.-C. Tsai, Y.-H. Wang, P.-S. P. Weng. The Information Content of the S&P 500 Index and VIX Options on the Dynamics of the S&P 500 Index. http://ssrn.com/abstract=1711036.

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Paper: D. J. Fenn, M. A. Porter, S. Williams, M. McDonald, N. F. Johnson, N. S. Jones. Temporal Evolution of Financial Market Correlations.

Michael Bommarito — Tue, 16 Nov 2010 04:44:28 +0000

Here’s a paper out of the CabDyn group at Oxford from D. Fenn and M. Porter. Mason is also one of the leading researchers in network science, and their group has entered into a number of joint Ph.D./post-doctoral hires with the business school there. The result is a large number of interesting papers. This particular paper investigates correlation matrices through RMT, which is exactly what my Quantitative Finance paper and recent working paper address. Though they don’t examine their calculations in an applied context, the results provide additional view into recent correlation dynamics. Abstract and download below:

Abstract: We investigate financial market correlations using random matrix theory and principal component analysis. We use random matrix theory to demonstrate that correlation matrices of asset price changes contain structure that is incompatible with uncorrelated random price changes. We then identify the principal components of these correlation matrices and demonstrate that a small number of components accounts for a large proportion of the variability of the markets that we consider. We then characterize the time-evolving relationships between the different assets by investigating the correlations between the asset price time series and principal components. Using this approach, we uncover notable changes that occurred in financial markets and identify the assets that were significantly affected by these changes. We show in particular that there was an increase in the strength of the relationships between several different markets following the 2007–2008 credit and liquidity crisis.

D. J. Fenn, M. A. Porter, S. Williams, M. McDonald, N. F. Johnson, N. S. Jones. Temporal Evolution of Financial Market Correlations. http://arxiv.org/abs/1011.3225.

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Paper: J. Brogaard. High Frequency Trading and its Impact on Market Quality

Michael Bommarito — Sun, 31 Oct 2010 14:02:35 +0000

I saw that this paper on SSRN, High Frequency Trading and its Impact on Market Quality, was updated a week or so ago (courtesy of Alea) and I thought it would be worth posting. The abstract of the paper below:

This paper examines the impact of high frequency trading (HFT) on the U.S. equities market. I analyze a unique dataset to study the strategies utilized by high frequency traders (HFTs), their profitability, and their relationship with characteristics of the overall market, including liquidity, price discovery, and volatility. The 26 high frequency trading firms in the dataset participate in 73.7\% of all trades. I find the following key results: (1) HFTs tend to follow a price reversal strategy driven by order imbalances, (2) HFTs earn gross trading profits of approximately \$2.8 billion annually, (3) HFTs do not seem to systematically engage in a non-HFTr anticipatory trading strategy, (4) HFTs’ strategies are more correlated with each other than are non-HFTs’, (5) HFTs’ trading level changes only moderately as volatility increases, (6) HFTs add substantially to the price discovery process, (7) HFTs provide the best bid and offer quotes for a significant portion of the trading day and do so strategically so as to avoid informed traders, but provide only one-fourth of the book depth as do non-HFTs, and (8) HFTs may dampen intraday volatility. These findings suggest that HFTs’ activities are not detrimental to non-HFTs and that HFT tends to improve market quality.

J. Brogaard. High Frequency Trading and its Impact on Market Quality. Available at SSRN.

My gut instinct is that there are a few issues with the paper:

As Jonathan acknowledges, he does not address order book dynamics or, more importantly, other identified malicious HFT practices (e.g., stuffing). Since this is a job paper and therefore has to be approachable and “bite-sized,” this in itself is fine. However, the normative claim that “HFTs are not bad” may be too strong in the absence of this analysis.
Without a better idea of where HFTs trade, it is hard to extrapolate from the sample of 120 stocks. The exact selection method is not explicit in the paper, but it seems that the stocks were chosen from the NASDAQ to include a range of market caps. Without a better idea of where HFTs trade, it is quite possible that this selection undersamples the stocks that most HFT transactions occur on. In the absence of industry-wide data, this is a necessary research choice, but its limiting nature on the conclusions should be better stated.
On a somewhat related note, the estimation of profitability and risk-adjusted return is quite daring given the above two constraints.

Despite these few notes, the paper should definitely get Jonathan a great job and I’m interested to see more work on his dataset. He’s also got a great advisor, Thomas Brennan, who I met at the Midwest Law & Economics Conference. Thomas has more industry experience than 90% of all academics and his papers also make for great reads (some on SSRN, most in law reviews or finance journals).

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