nep-fmk New Economics Papers
on Financial Markets
Issue of 2013‒08‒10
five papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Fractality of profit landscapes and validation of time series models for stock prices By Il Gu Yi; Gabjin Oh; Beom Jun Kim
  2. Random matrix approach to dynamic evolution of cross-correlations in the Chinese stock market By Fei Ren; Wei-Xing Zhou
  3. A general Multidimensional Monte Carlo Approach for Dynamic Hedging under stochastic volatility By Dorival Le\~ao; Alberto Ohashi; Vinicius Siqueira
  4. Asset Allocation under the Basel Accord Risk Measures By Zaiwen Wen; Xianhua Peng; Xin Liu; Xiaoling Sun; Xiaodi Bai
  5. Sovereign bond market reactions to fiscal rules and no-bailout clauses – The Swiss experience By Lars P. Feld; Alexander Kalb; Marc-Daniel Moessinger; Steffen Osterloh

  1. By: Il Gu Yi; Gabjin Oh; Beom Jun Kim
    Abstract: We apply a simple trading strategy for various time series of real and artificial stock prices to understand the origin of fractality observed in the resulting profit landscapes. The strategy contains only two parameters $p$ and $q$, and the sell (buy) decision is made when the log return is larger (smaller) than $p$ ($-q$). We discretize the unit square $(p, q) \in [0, 1] \times [0, 1]$ into the $N \times N$ square grid and the profit $\Pi (p, q)$ is calculated at the center of each cell. We confirm the previous finding that local maxima in profit landscapes are scattered in a fractal-like fashion: The number M of local maxima follows the power-law form $M \sim N^{a}$, but the scaling exponent $a$ is found to differ for different time series. From comparisons of real and artificial stock prices, we find that the fat-tailed return distribution is closely related to the exponent $a \approx 1.6$ observed for real stock markets. We suggest that the fractality of profit landscape characterized by $a \approx 1.6$ can be a useful measure to validate time series model for stock prices.
    Date: 2013–08
  2. By: Fei Ren; Wei-Xing Zhou
    Abstract: We study the dynamic evolution of cross-correlations in the Chinese stock market mainly based on the random matrix theory (RMT). The correlation matrices constructed from the return series of 367 A-share stocks traded on the Shanghai Stock Exchange from January 4, 1999 to December 30, 2011 are calculated over a rolling window with a size of 400 days. As a consequence, a thorough study of the variation of the interconnection among stocks and its underlying information in different time periods is conducted. The evolutions of the statistical properties of the correlation coefficients, eigenvalues, and eigenvectors of the correlation matrices are carefully analyzed. We find that the stock correlations are significantly increased in the periods of two market crashes in 2001 and 2008, and the systemic risk is higher in the volatile periods than calm periods. By investigating the significant contributors of the large eigenvectors in different rolling windows, we observe a dynamic evolution behavior in business sectors such as IT, electronics, and real estate, which are those industries leading the rise (drop) before (after) the crash.
    Date: 2013–08
  3. By: Dorival Le\~ao; Alberto Ohashi; Vinicius Siqueira
    Abstract: In this work, we introduce a Monte Carlo method for the dynamic hedging of general European-type contingent claims in a multidimensional Brownian arbitrage-free market. Based on bounded variation martingale approximations for Galtchouk-Kunita-Watanabe decompositions, we propose a feasible and constructive methodology which allows us to compute pure hedging strategies w.r.t arbitrary square-integrable claims in incomplete markets. In particular, the methodology can be applied to quadratic hedging-type strategies for fully path-dependent options with stochastic volatility and discontinuous payoffs. We illustrate the method with numerical examples based on generalized Follmer-Schweizer decompositions, locally-risk minimizing and mean-variance hedging strategies for vanilla and path-dependent options written on local volatility and stochastic volatility models.
    Date: 2013–08
  4. By: Zaiwen Wen; Xianhua Peng; Xin Liu; Xiaoling Sun; Xiaodi Bai
    Abstract: Financial institutions are currently required to meet more stringent capital requirements than they were before the recent financial crisis; in particular, the capital requirement for a large bank's trading book under the Basel 2.5 Accord more than doubles that under the Basel II Accord. The significant increase in capital requirements renders it necessary for banks to take into account the constraint of capital requirement when they make asset allocation decisions. In this paper, we propose a new asset allocation model that incorporates the regulatory capital requirements under both the Basel 2.5 Accord, which is currently in effect, and the Basel III Accord, which was recently proposed and is currently under discussion. We propose an unified algorithm based on the alternating direction augmented Lagrangian method to solve the model; we also establish the first-order optimality of the limit points of the sequence generated by the algorithm under some mild conditions. The algorithm is simple and easy to implement; each step of the algorithm consists of solving convex quadratic programming or one-dimensional subproblems. Numerical experiments on simulated and real market data show that the algorithm compares favorably with other existing methods, especially in cases in which the model is non-convex.
    Date: 2013–08
  5. By: Lars P. Feld (Walter Eucken Institut & University of Freiburg); Alexander Kalb (Bayern LB); Marc-Daniel Moessinger (ZEW (Centre for European Economic Research)); Steffen Osterloh (German Council of Economic Experst)
    Abstract: We investigate the political determinants of risk premiums which sub-national governments in Switzerland have to pay for their sovereign bond emissions. For this purpose we analyse financial market data from 288 tradable cantonal bonds in the period from 1981 to 2007. Our main focus is on two different institutional factors. First, many of the Swiss cantons have adopted strong fiscal rules. We find evidence that both the presence and the strength of these fiscal rules contribute significantly to lower cantonal bond spreads. Second, we study the impact of a credible no-bailout regime on the risk premia of potential guarantors. We make use of the Leukerbad court decision in July 2003 which relieved the cantons from backing municipalities in financial distress, thus leading to a fully credible no-bailout regime. Our results show that this break lead to a reduction of cantonal risk premia by about 25 basis points. Moreover, it cut the link between cantonal risk premia and the financial situation of the municipalities in its canton which existed before. This demonstrates that a not fully credible no-bailout commitment can entail high costs for the potential guarantor.
    Keywords: Sub-national government bonds, fiscal rules, no-bailout clause, sovereign risk premium
    JEL: E62 G12 H63 H74
    Date: 2013

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