Extreme correlation of international equity markets

Testing the hypothesis that international equity market correlation increases in volatile times is a difficult exercise and misleading results have often been reported in the past because of a spurious relationship between correlation and volatility. This paper focuses on extreme correlation, that is to say the correlation between returns in either the negative or positive tail of the multivariate distribution. Using "extreme value theory" to model the multivariate distribution tails, we derive the distribution of extreme correlation for a wide class of return distributions. Using monthly data on the five largest stock markets from 1958 to 1996, we reject the null hypothesis of multivariate normality for the negative tail, but not for the positive tail. We also find that correlation is not related to market volatility per se but to the market trend. Correlation increases in bear markets, but not in bull markets.International equity markets; volatility; correlation and extreme value theory

Margin setting with high-frequency data

Both in practice and in the academic literature, models for setting margin requirements in futures markets classically use daily closing price changes. However, as well documented by research on high-frequency data, financial markets have recently shown high intraday volatility, which could bring more risk than expected. This paper tries to answer two questions relevant for margin committees in practice: is it right to compute margin levels based on closing prices and ignoring intraday dynamics? Is it justified to implement intraday margin calls? The paper focuses on the impact of intraday dynamics of market prices on daily margin levels. Daily margin levels are obtained in two ways: first, by using daily price changes defined with different time-intervals (say from 3 pm to 3 pm on the following trading day instead of traditional closing times); second, by using 5-minute and 1-hour price changes and scaling the results to one day. Our empirical analysis uses the FTSE 100 futures contract traded on LIFFE.

Margin Requirements with Intraday Dynamics

Both in practice and in the academic literature, models for setting margin requirements in futures markets use daily closing price changes. However, financial markets have recently shown high intraday volatility, which could bring more risk than expected. Such a phenomenon is well documented in the literature on high-frequency data and has prompted some exchanges to set intraday margin requirements and ask intraday margin calls. This article proposes to set margin requirements by taking into account the intraday dynamics of market prices. Daily margin levels are obtained in two ways: first, by using daily price changes defined with different time-intervals (say from 3 pm to 3 pm on the following trading day instead of traditional closing times); second, by using 5-minute and 1-hour price changes and scaling the results to one day. An application to the FTSE 100 futures contract traded on LIFFE demonstrates the usefulness of this new approach.ARCH process, clearinghouse, exchange, extreme value theory, futures markets, highfrequency data, intraday dynamics, margin requirements, model risk, risk management, stress testing, value at risk.

Marine radiocarbon reservoir effect of coastal waters off Cape Verde archipelago

Quantification of the marine radiocarbon reservoir effect (Delta R) is essential in order to calibrate conventional C-14 dates from marine shell samples with reliability. Delta R also provides information concerning the intensity of coastal upwelling in marine regions influenced by this phenomenon. C-14 ages of closely associated marine samples (mollusk shells) and terrestrial samples (goat bones) from Sao Vicente Island, Cape Verde Archipelago, permitted the first calculation of the marine C-14 reservoir effect in this region. A Delta R weighted mean value of 70 +/- 70 C-14 yr was obtained. This value is in accordance with the previously published oceanographic conditions of the region indicating the existence of a seasonal active upwelling regime

Implied Correlation from VaR

Value at risk (VaR) is a risk measure that has been widely implemented by financial institutions. This paper measures the correlation among asset price changes implied from VaR calculation. Empirical results using US and UK equity indexes show that implied correlation is not constant but tends to be higher for events in the left tails (crashes) than in the right tails (booms).Implied Correlation, Value at Risk

Multidimensional Scaling on Multiple Input Distance Matrices

Multidimensional Scaling (MDS) is a classic technique that seeks vectorial representations for data points, given the pairwise distances between them. However, in recent years, data are usually collected from diverse sources or have multiple heterogeneous representations. How to do multidimensional scaling on multiple input distance matrices is still unsolved to our best knowledge. In this paper, we first define this new task formally. Then, we propose a new algorithm called Multi-View Multidimensional Scaling (MVMDS) by considering each input distance matrix as one view. Our algorithm is able to learn the weights of views (i.e., distance matrices) automatically by exploring the consensus information and complementary nature of views. Experimental results on synthetic as well as real datasets demonstrate the effectiveness of MVMDS. We hope that our work encourages a wider consideration in many domains where MDS is needed

Correlation Structure of International Equity Markets During Extremely Volatile Periods

Correlation in international equity returns is unstable over time. It has been suggested that the international correlation of large stock returns, especially negative ones, differs from that of usual returns. It is in periods of extreme negative returns that the benefits of international risk diversification are most desired and that the question of international correlation is most relevant to risk-averse agents. If return distributions are not multivariate normal, the usual standard deviation and correlation of returns do not provide sufficient information. Additional information can be gained by focusing directly on the properties of extreme returns. While the interest in stock market crashes and booms is large, no study has specifically focused on the correlation between large price movements. A major econometric issue is to specify the multivariate distribution of extreme returns implied by a given distribution of returns. In this paper, we work directly on large returns and study the dependence structure of international equity markets during extremely volatile periods. We use the results of extreme value theory to model the multivariate distribution of large returns, using monthly data from January 1959 to December 1996 for the five largest stock markets. We find that the correlation of large positive returns are not inconsistent with the assumption of multivariate normality. However, the correlation of large negative returns is much greater than expected, suggesting that the benefits of international risk reduction in extremely volatile periods have been overstated.international equity market; volatility; correlation; extreme value theory

GIFT: A Real-time and Scalable 3D Shape Search Engine

Projective analysis is an important solution for 3D shape retrieval, since human visual perceptions of 3D shapes rely on various 2D observations from different view points. Although multiple informative and discriminative views are utilized, most projection-based retrieval systems suffer from heavy computational cost, thus cannot satisfy the basic requirement of scalability for search engines. In this paper, we present a real-time 3D shape search engine based on the projective images of 3D shapes. The real-time property of our search engine results from the following aspects: (1) efficient projection and view feature extraction using GPU acceleration; (2) the first inverted file, referred as F-IF, is utilized to speed up the procedure of multi-view matching; (3) the second inverted file (S-IF), which captures a local distribution of 3D shapes in the feature manifold, is adopted for efficient context-based re-ranking. As a result, for each query the retrieval task can be finished within one second despite the necessary cost of IO overhead. We name the proposed 3D shape search engine, which combines GPU acceleration and Inverted File Twice, as GIFT. Besides its high efficiency, GIFT also outperforms the state-of-the-art methods significantly in retrieval accuracy on various shape benchmarks and competitions.Comment: accepted by CVPR16, achieved the first place in Shrec2016 competition: Large-Scale 3D Shape Retrieval under the perturbed cas