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Article
Publication date: 4 October 2011

Khaldoun Khashanah and Linyan Miao

This paper empirically investigates the structural evolution of the US financial systems. It particularly aims to explore if the structure of the financial systems changes…

Abstract

Purpose

This paper empirically investigates the structural evolution of the US financial systems. It particularly aims to explore if the structure of the financial systems changes when the economy enters a recession.

Design/methodology/approach

The empirical analysis is conducted through the statistical approach of principal components analysis (PCA) and the graph theoretic approach of minimum spanning trees (MSTs).

Findings

The PCA results suggest that the VIX was the dominant factor influencing the financial system prior to the recession; however, the monetary policy represented by the three‐month T‐bill yield became the leading factor in the system during the recession. By analyzing the MSTs, we find evidence that the structure of the financial system during the economic recession is substantially different from that during the period of economic expansion. Moreover, we discover that the financial markets are more integrated during the economic recession. The much stronger integration of the financial system was found to start right before the advent of the recession.

Practical implications

Research findings will help individuals, institutions, regulators, central bankers better understand the market structure under the economic turmoil, so more efficient strategies can be used to minimize the systemic risk.

Originality/value

This study compares the structure of the US financial markets in economic expansion and contraction periods. The structural dynamics of the financial system are explored, focusing on the recent economic recession triggered by the US subprime mortgage crisis. We introduce a new systemic risk measure.

Details

Studies in Economics and Finance, vol. 28 no. 4
Type: Research Article
ISSN: 1086-7376

Keywords

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Article
Publication date: 1 March 2006

Fotios C. Harmantzis, Linyan Miao and Yifan Chien

This paper aims to test empirically the performance of different models in measuring VaR and ES in the presence of heavy tails in returns using historical data.

Abstract

Purpose

This paper aims to test empirically the performance of different models in measuring VaR and ES in the presence of heavy tails in returns using historical data.

Design/methodology/approach

Daily returns of popular indices (S&P500, DAX, CAC, Nikkei, TSE, and FTSE) and currencies (US dollar vs Euro, Yen, Pound, and Canadian dollar) for over ten years are modeled with empirical (or historical), Gaussian, Generalized Pareto (peak over threshold (POT) technique of extreme value theory (EVT)) and Stable Paretian distribution (both symmetric and non‐symmetric). Experimentation on different factors that affect modeling, e.g. rolling window size and confidence level, has been conducted.

Findings

In estimating VaR, the results show that models that capture rare events can predict risk more accurately than non‐fat‐tailed models. For ES estimation, the historical model (as expected) and POT method are proved to give more accurate estimations. Gaussian model underestimates ES, while Stable Paretian framework overestimates ES.

Practical implications

Research findings are useful to investors and the way they perceive market risk, risk managers and the way they measure risk and calibrate their models, e.g. shortcomings of VaR, and regulators in central banks.

Originality/value

A comparative, thorough empirical study on a number of financial time series (currencies, indices) that aims to reveal the pros and cons of Gaussian versus fat‐tailed models and Stable Paretian versus EVT, in estimating two popular risk measures (VaR and ES), in the presence of extreme events. The effects of model assumptions on different parameters have also been studied in the paper.

Details

The Journal of Risk Finance, vol. 7 no. 2
Type: Research Article
ISSN: 1526-5943

Keywords

Content available
Article
Publication date: 1 March 2013

Abstract

Details

Studies in Economics and Finance, vol. 30 no. 1
Type: Research Article
ISSN: 1086-7376

Keywords

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