Persistence characteristics of Latin American financial markets

The financial rates of return from Latin American stock and currency markets are found to be non-normal, non-stationary, non-ergodic, and long-term dependent, i.e., they have long memory. The degree of long-term dependence is measured by monofractal (global) Hurst exponents from wavelet multiresolution analysis (MRA). Scalograms and scalegrams provide the respective visualizations of these wavelet coefficients and the power spectrum of the rates of return. The slope of the power spectrum identifies the Hurst exponent and thereby the degree of time-scaling dependence that cannot be determined by Box–Jenkins type, stationarity-based, time series analysis. Our long-term dependence and time–frequency scaling results are consistent with similar empirical findings from American, European, and Asian financial markets. They extend the domain of the empirical investigation of the dynamics and risk characteristics of the global financial markets and refute the hypothesis of perfectly efficient financial markets.     

Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development

The scaling properties encompass in a simple analysis many of the volatility characteristics of financial markets. That is why we use them to probe the different degree of markets development. We empirically study the scaling properties of daily Foreign Exchange rates, Stock Market indices and fixed income instruments by using the generalized Hurst approach. We show that the scaling exponents are associated with characteristics of the specific markets and can be used to differentiate markets in their stage of development. The robustness of the results is tested by both Monte Carlo studies and a computation of the scaling in the frequency domain.     

Statistical tests of distributional scaling properties for financial return series

Existing empirical evidence of distributional scaling in financial returns has helped motivate the use of multifractal processes for modelling return processes. However, this evidence has relied on informal tests that may be unable to reliably distinguish multifractal processes from other related classes. The current paper develops a formal statistical testing procedure for determining which class of fractal process is most consistent with the distributional scaling properties in a given sample of data. Our testing methodology consists of a set of test statistics, together with a model-based bootstrap resampling scheme to obtain sample p-values. We demonstrate in Monte Carlo exercises that the proposed testing methodology performs well in a wide range of testing environments relevant for financial applications. Finally, the methodology is applied to study the scaling properties of a data-set of intraday equity index and exchange rate returns. The empirical results suggest that the scaling properties of these return series may be inconsistent with purely multifractal processes.     

基于MF-DCCA方法的证券市场间交叉相关性研究

运用多重分形去趋势波动交叉相关分析法(MF-DCCA),考量上海证券市场和香港证券市场之间的交叉相关关系。实证表明：上海证券市场和香港证券市场之间存在交叉相关性,且呈现出多重分形特征;当证券市场出现较大的波动时,上海证券市场和香港证券市场的交叉标度指数要大于其平均标度指数,即两个证券市场之间的交叉相关性要大于其自相关性。     

Wavelet multiresolution analysis of high-frequency Asian FX rates, Summer 1997

Foreign exchange (FX) pricing processes are nonstationary: Their frequency characteristics are time dependent. Most do not conform to Geometric Brownian Motion (GBM), because they exhibit a scaling law with Hurst exponents between zero and 0.5 and fractal dimensions between 1.5 and 2. Wavelet multiresolution analysis (MRA), with Haar wavelets, is used to analyze these time and scale dependencies (self-similarity) of intraday Asian currency spot exchange rates. We use the ask and bid quotes of the currencies of eight Asian countries (Japan, Hong Kong, Indonesia, Malaysia, Philippines, Singapore, Taiwan, and Thailand) and, for comparison, of Germany for the crisis period May 1, 1998-August 31, 1997, provided by Telerate (U.S. dollar is the numéraire). Their time-scale-dependent spectra, which are localized in time, are observed in wavelet scalograms. The FX increments are characterized by the irregularity of their singularities. Their degrees of irregularity are measured by homogeneous Hurst exponents. These critical exponents are used to identify the global fractal dimension, relative stability, and long-term dependence, or long-term memory, of each Asian FX series. The invariance of each identified Hurst exponent is tested by comparing it at varying time and scale (frequency) resolutions. It appears that almost all investigated FX markets show antipersistent pricing behavior. The anchor currencies of the D-mark and Japanese Yen (JPY) are ultraefficient in the sense of being most antipersistent or “fast mean-reversing.” This is a surprising result because most financial analyst either assume neutral or persistent behavior in the financial markets, based on earlier research by Granger in the 1960s. This is a pedagogical paper explaining the most rational methodology for the identification of long-term memory in financial time series.     

Turbulence in financial markets: the surprising explanatory power of simple cascade models

Price changes in financial markets have been found to share many of the features characterizing turbulent flows. In particular, a number of recent contributions have highlighted that time series from both stock and foreign exchange markets possess multifractal statistics, i.e. the scaling behaviour of absolute moments is described by a convex function. These findings have stimulated the application of certain cascade models from statistical physics to financial data. Extant work in this area has so far been confined to parameter estimation and visual comparison of empirical and theoretical scaling properties. The lack of rigorous statistical measures of goodness of fit in the literature on turbulence has, however, impeded a comparison of these new models with standard approaches in empirical finance. Here we try to fill this gap and provide a first assessment of two elementary cascade models based on elementary goodness-of-fit criteria. As it turns out, these relatively simple one-parameter models are not only capable of accommodating the multiscaling behaviour of price changes, but also provide a perplexingly good fit of the unconditional distribution of the data. In a double-blind test, we would, in fact, be unable to reject identity of the data-generating processes underlying empirical records and simulated data from stochastic cascades.     

Fluctuation dynamics in US interest rates and the role of monetary policy

This paper presents empirical evidence suggesting that the degree of long-range dependence in interest rates depends on the conduct of monetary policy. We study the term structure of interest rates for the US and find evidence that global Hurst exponents change dramatically according to Chairman Tenure in the Federal Reserve Board and also with changes in the conduct of monetary policy. In the period from 1960s until the monetarist experiment in the beginning of the 1980s interest rates had a significant long-range dependence behavior. However, in the recent period, in the second part of the Volcker tenure and in the Greenspan tenure, interest rates do not present long-range dependence behavior. These empirical findings cast some light on the origins of long-range dependence behavior in financial assets.     

Paramater estimation bias and volatility scaling in Black-Scholes option prices

When asset returns conform to a Gaussian distribution, the moments of the distribution over long return intervals may be estimated by scaling the moments of shorter return intervals. While it is well known that asset returns are not normally distributed, a key empirical question concerns the effect that scaling the volatility of dependent processes will have on the pricing of related financial assets. This study investigates the return properties of the most important currencies traded in spot markets against the U.S. dollar: the Japanese yen, the British pound, and the Swiss franc during the period November 1983 to April 2004. The novelty of this paper is that the volatility properties of the series are tested utilising statistical procedures developed from fractal geometry, with the economic impact determined within an option-pricing framework.     

Household insolvency: A review of household debt repayment,delinquency, and bankruptcy

This review paper explores the issues related to the meaning and measurement of insolvency within the domain of household finances. Conceptual and empirical evidence to explain the onset of insolvency is reviewed. Predictive models and financial ratios are presented as techniques for identifying insolvent households. Implications for monitoring of solvency by households and responses to insolvency are presented.     

How trading activity scales with company size in the FTSE 100

This paper investigates the scaling dependencies between measures of ‘activity’ and of ‘size’ for companies included in the FTSE 100. The ‘size’ of companies is measured by the total market capitalization. The ‘activity’ is measured with several quantities related to trades (transaction value per trade, transaction value per hour, tick rate), to the order queue (total number of orders, total value), and to the price dynamic (spread, volatility). The outcome is that systematic scaling relations are observed: (1) the value exchanged by hour and value in the order queue have exponents of less than 1, respectively 0.90 and 0.75; (2) the tick rate and the value per transaction scale with the exponents 0.39 and 0.44; (3) the annualized volatility is independent of the size, and the tick-by-tick volatility decreases with the market capitalization with an exponent of ?0.23; (4) the spread increases with the volatility with an exponent of 0.94. A theoretical random walk argument is given that relates the volatility exponents to the exponents in points 1 and 2.     

公允价值会计:理论分析与经验证据

公允价值会计一直是会计准则制定者与银行界及其监管机构之间争论的焦点.围绕着公允价值会计的争论全面而系统地综述了国外关于公允价值会计对银行业及监管影响的相关研究成果.从历史成本向公允价值转变确实会对银行业及其监管、乃至整个金融体系产生重大影响,在决定是否采用公允价值作为财务报表的主要计量手段之前,需要对公允价值所产生的影响做出不断深入的研究.     

The impact of the 2008 and 2010 financial crises on the Hurst exponents of international stock markets: Implications for efficiency and contagion

This study analyzes how the 2008 and 2010 financial crises, which began in the US and Greece respectively, affected the Hurst exponents of index returns of the stock markets of Belgium, France, Greece, Japan, the Netherlands, Portugal, the UK and US. We perform two innovative statistical tests for this purpose. The first assesses whether the returns exhibit a long memory in the pre-crisis and crisis periods and determines the extent to which the Hurst exponents, calculated with the multifractal detrended moving average technique (MFDMA), differ from the tranquil to the crisis periods. The second test uses copula models to assess whether the correlation between the local Hurst exponents of the markets where the crises originated and those of the other markets increased due to the crises. The results of the first test suggest that although most of the returns exhibit a long memory in the 2008 crisis period, this is not the case in either the pre-crisis or the 2010 crisis periods. These findings shed light on the dynamics of market efficiency. The results of the second test show a significant increase in correlation between the local Hurst exponents of several markets, suggesting the existence of financial contagion. We observed that the 2008 crisis had a greater impact on the memory properties of stock returns than the 2010 financial crisis.     

Forecasting market risk using ultra-high-frequency data and scaling laws

This paper develops a new multiple time scale-based empirical framework for market risk estimates and forecasts. Ultra-high frequency data are used in the empirical analysis to estimate the parameters of empirical scaling laws which gives a better understanding of the dynamic nature of the market. A comparison of the new approach with the popular Value-at-Risk and expected tail loss measures with respect to their risk forecasts during the crisis period in 2008 is presented. The empirical results show the outperformance of the new scaling law method which turns out to be more accurate and flexible due to the scale invariance. The scaling law method promotes the use of massive real data in developing risk measurement and forecasting models.     

Persistence characteristics of the Chinese stock markets

Using advanced signal processing, this paper identifies the lack of ergodicity, stationarity, independence and the degree of persistence of the Shanghai (SHI) stock market and Shenzhen A shares (SZI) and B shares (SZBI), before and after the various deregulations and reregulations. Their lack of stationarity and ergodicity are ascribed to (1) the initial interventions in these stock markets by the Chinese government by imposing various daily price change limits, and (2) the changing trading styles, after the Chinese government left these equity markets to develop by themselves. The SHI, SZI, and SZBI are moderately persistent with Hurst exponents slightly greater than the Fickian 0.5 of the Geometric Brownian Motion. These stock markets were considerably more persistent before the deregulations, but they now behave more like Geometric Brownian Motions, i.e., efficiently. Thus, the Chinese stock markets are gradually and properly being integrated into one Chinese stock market. Our results are consistent with similar empirical findings from Latin American, European, and other Asian emerging financial markets.     

Market risk model selection and medium-term risk with limited data: Application to ocean tanker freight markets

The estimation of medium-term market risk dictated by limited data availability, is a challenging issue of concern amongst academics and practitioners. This paper addresses the issue by exploiting the concepts of volatility and quantile scaling in order to determine the best method for extrapolating medium-term risk forecasts from high frequency data. Additionally, market risk model selection is investigated for a new dataset on ocean tanker freight rates, which refer to the income of the capital good — tanker vessels. Certain idiosyncrasies inherent in the very competitive shipping freight rate markets, such as excessive volatility, cyclicality of returns and the medium-term investment horizons – found in few other markets – make these issues challenging. Findings indicate that medium-term risk exposures can be estimated accurately by using an empirical scaling law which outperforms the conventional scaling laws of the square and tail index root of time. Regarding the market risk model selection for short-term investment horizons, findings contradict most studies on conventional financial assets: interestingly, freight rate market risk quantification favors simpler specifications, such as the GARCH and the historical simulation models.     

Econophysics review: II. Agent-based models

This article is the second part of a review of recent empirical and theoretical developments usually grouped under the heading Econophysics. In the first part, we reviewed the statistical properties of financial time series, the statistics exhibited in order books and discussed some studies of correlations of asset prices and returns. This second part deals with models in Econophysics from the point of view of agent-based modeling. Of the large number of multi-agent-based models, we have identified three representative areas. First, using previous work originally presented in the fields of behavioral finance and market microstructure theory, econophysicists have developed agent-based models of order-driven markets that we discuss extensively here. Second, kinetic theory models designed to explain certain empirical facts concerning wealth distribution are reviewed. Third, we briefly summarize game theory models by reviewing the now classic minority game and related problems.     

Decomposing the effects of financial liberalization: Crises vs. growth

We present a new empirical decomposition of the effects of financial liberalization on economic growth and on the incidence of crises. Our empirical estimates show that the direct effect of financial liberalization on growth by far outweighs the indirect effect via a higher propensity to crisis. We also discuss several models of financial liberalization and growth whose predictions are consistent with our empirical findings.     

Multiscaling and rough volatility: An empirical investigation

Pricing derivatives goes back to the acclaimed Black and Scholes model. However, such a modelling approach is known not to be able to reproduce some of the financial stylised facts, including the dynamics of volatility. In the mathematical finance community, it has therefore emerged a new paradigm, named rough volatility modelling, that represents the volatility dynamics of financial assets as a fractional Brownian motion with Hurst exponent very small, which indeed produces rough paths. At the same time, prices’ time series have been shown to be multiscaling, characterised by different Hurst scaling exponents. This paper assesses the interplay, if present, between price multiscaling and volatility roughness, defined as the (low) Hurst exponent of the volatility process. In particular, we perform extensive simulation experiments by using one of the leading rough volatility models present in the literature, the rough Bergomi model. A real data analysis is also conducted to test if the rough volatility model reproduces the same relationship. We find that the model can reproduce multiscaling features of the prices’ time series when a low value of the Hurst exponent is used, but it fails to reproduce what the real data says. Indeed, we find that the dependency between prices’ multiscaling and the Hurst exponent of the volatility process is diametrically opposite to what we find in real data, namely a negative interplay between the two.     

Does financial market liberalization increase the degree of market efficiency? The case of the Athens stock exchange

In this paper we assess if the financial market liberalization introduced in the beginning of the 1990s in Greece has changed the degree of market development (efficiency) by studying time-varying global Hurst exponents. Our results suggest that changes in financial market liberalization have important positive implications on the degree of development of stock markets. These results have important policy implications for the development of stock markets around the world.