Anomalous volatility scaling in high frequency financial data

Volatility of intra-day stock market indices computed at various time horizons exhibits a scaling behaviour that differs from what would be expected from fractional Brownian motion (fBm). We investigate this anomalous scaling by using empirical mode decomposition (EMD), a method which separates time series into a set of cyclical components at different time-scales. By applying the EMD to fBm, we retrieve a scaling law that relates the variance of the components to a power law of the oscillating period. In contrast, when analysing 22 different stock market indices, we observe deviations from the fBm and Brownian motion scaling behaviour. We discuss and quantify these deviations, associating them to the characteristics of financial markets, with larger deviations corresponding to less developed markets.Comment: 25 pages, 11 figure, 5 table

Anomalous volatility scaling in high frequency financial data

Volatility of intra-day stock market indices computed at various time horizons exhibits a scaling behaviour that differs from what would be expected from fractional Brownian motion (fBm). We investigate this anomalous scaling by using empirical mode decomposition (EMD), a method which separates time series into a set of cyclical components at different time-scales. By applying the EMD to fBm, we retrieve a scaling law that relates the variance of the components to a power law of the oscillating period. In contrast, when analysing 22 different stock market indices, we observe deviations from the fBm and Brownian motion scaling behaviour. We discuss and quantify these deviations, associating them to the characteristics of financial markets, with larger deviations corresponding to less developed markets

Market efficiency, nonlinearity and technical analysis in the global market

In this thesis we investigate market efficiency from a different perspective. Instead of traditional approach to one market in specific, this time around we study market efficiency from a global perspective. See the global market indices as one single market. We used both nonlinear methods and technical analysis in order to accomplish our purpose. We used BDS to test for nonlinearity in the return series, as expected the results conformed with the general view, which is market returns exhibit nonlinear dependence. We trace the cause of the dependence as a result of the ARCH type process. We also used technical trading strategy to test whether profit can be made through trading in stock indices around the world. We investigate the simple moving averages, weighted moving averages and exponential moving averages with different allocation of resources, we found all techniques to be profitable when 1% and 2% commission are considered. For the 50 day simple moving average, the average daily return is 0,0009%, compared with the - 0,669% of the buy and hold strategy. These results were also confirmed using bootstrap methodology in which we considered the random walk model as return generating process. These rules are profitable after accounting for commission fees.Nesta dissertação analisou-se a eficiência dos mercados numa perspectiva diferente. Em vez da abordagem tradicional a um mercado específico, estudou-se a eficiência de uma forma global. Considerou-se que os índices globais dos mercados formavam um mercado único integrado. Utilizaram-se simultaneamente métodos não lineares e a análise técnica para testar a eficiência do mercado global. Utilizou-se a BDS para testar a não linearidade na série de rendibilidades dos índices, tal como esperado, os resultados confirmaram os estudos anteriores, ou seja, os mercados têm uma dependência não linear. Esta dependência resultará de um processo de tipo ARCH. Utilizaram-se regras de “trading” baseadas na análise técnica para testar se é possível obter uma rendibilidade anómala com os referidos índices de acções. Consideraram-se médias móveis simples, ponderadas e exponenciais, ensaiando várias afectações diferentes de recursos (ponderação igual e proporcional), detectou-se que todas as estratégias eram rentáveis mesmo depois de considerar comissões de 1% e até de 2%. Para a média móvel simples de 50 dias, a rendibilidade media diária é de 0,0009%, comparável com -0,669% para a estratégia “buy and hold”. Estes resultados também foram confirmados através da metodologia de “bootstrap”, em que se considerou o modelo “random walk” como um processo gerador das rendibilidades. Estas estratégias são rentáveis mesmo depois de consideradas as comissões

Quantifying the effects of new derivative introduction on exchange volatility, efficiency and liquidity

This thesis investigates the effects of the introduction of new financial derivative products on exchange volatility, efficiency and liquidity. The derivatives under primary investigation are Exchange Traded Funds (ETFs) and Contracts for Difference (CFDs). These products offer a cheap, tax-efficient and speedy method for increasing or decreasing market exposure to price changes in the related primary asset. By facilitating faster and shorter-term trading, these products may increase market liquidity and/or increase market volatility for the related primary asset. The thesis builds a cross-country database of new-derivative-markets opening dates, and investigates the key features of prices and returns for related primary assets before and after the opening of these derivative markets. The database covers 16 countries in the CFD investigation, 21 commodity markets in the ETF investigation, and related data as available (daily closing prices, trading volumes, bid-ask quotes) in each of them. The key price and return features investigated include bid-ask spreads, trading volumes (both of derivatives and related primary assets), and daily return autocorrelation, variance, skewness and kurtosis. This thesis also considers a separate, but related, research problem. It extends and empirically applies a liquidity-indicator model for the Eurozone created by the Bank of England (BOE) and developed further by the European Central Bank (ECB) by including commodity liquidity, and uses this extended model to investigate shifting investor behaviour based on changing market dynamics. Similar to the investigation of the CDF and EFT markets, this investigation is concerned with market stability and liquidity in a changed environment (in this case, the key change is the introduction of the euro currency). Chapter one contains an introduction to the main hypotheses regarding the effects of the introduction of new derivatives on securities markets, and the empirical methods used to test these hypotheses. This chapter also describes the two investment products which are the main focus, CFDs and ETFs, and their particular potential impacts on market-specific characteristics such as volatility, efficiency and liquidity. Chapter two empirically investigates the impact of CFDs on market liquidity and volatility. CFDs have existed for less than twenty years and the CFD market grew rapidly prior to the recent international financial crisis. This chapter empirically examines the roles that CFDs have played, either as an accelerant for mispricing in international equity markets away from fundamental values, or as a source of increased market efficiency through the addition of new liquidity. This chapter uses GARCH and EGARCH models to test for the impact of CFDs on the return volatility and autocorrelation of the underlying security. In the case of Australia, the analysis is applied to individual securities. In the other 15 countries investigated in this chapter, the analysis is applied at the level of the market index. The chapter also investigates whether the stylised characteristics of CFDs are more or less pronounced in low liquidity exchanges. This chapter finds that CFDs appear to have influenced asset-specific variance and return autocorrelation. Some tentative explanations for these findings are offered. The presence of bid and ask-price ‘overhangs’ associated with CFD trading cannot be rejected and may be associated with observed volatility reductions in some jurisdictions. Following the analysis based on CFDs in chapter two, ETFs are the primary focus of chapter three. ETFs have existed since the late 1980s, but were first traded on commodity markets in the early 2000s. Their inception has been linked by some market analysts with the large growth in commodity market volatility seen in recent years. This chapter directly tests this link. The chapter also investigates whether the stylised characteristics of ETFs are more or less pronounced in larger commodity markets than in smaller markets. The results indicate that larger ETFs in terms of their assets under management at their dates of inception, are associated with higher volatility. Smaller commodity markets are found to have increased efficiency after the introduction of ETFs, indicating that there are some benefits from new ETF investment in markets below $4 to$5 billion in size, but the associated caveat is that of increased volatility, indicative of potential pitfalls in the ETF portfolio rebalancing process. It appears that ETFs have made commodity markets more efficient through a new influx of trading counterparties, but they appear to be associated with a cost. The need for regulation of investment size and market ownership limits therefore cannot be rejected. Chapters two and three look at two particular new instruments and their effects on liquidity and volatility. Another major innovation in market structure was the advent of the euro currency in January 1999. The power and presence of a financially-combined Europe attracted new international investment, therefore influencing liquidity. The combination of this influx of investors and new products (including CFDs and ETFs) can potentially have wide market impacts. Understanding the structural changes of liquidity in Europe in recent years is important for macroprudential risk assessment, as sudden changes in conditions may be indicative of current stress and a signal of future stress. Chapter four presents a Europeanspecific liquidity measure used by several central banks, and provides some new modifications to this measure. The measure is constructed by combining several facets of liquidity and depth measurement across several asset markets. It attempts to incorporate aspects such as market tightness, depth and resiliency. The flows and the direction of causality can also be inferred using vector autoregression, Granger causality techniques and impulse response functions. The measure uses a combination of liquidity determinants including the bid-ask spread, the return to volume ratio and numerous measures of liquidity premia. In the chapter, the modified liquidity measure is applied empirically to European-area data

Quantifying the effects of new derivative introduction on exchange volatility, efficiency and liquidity

This thesis investigates the effects of the introduction of new financial derivative products on exchange volatility, efficiency and liquidity. The derivatives under primary investigation are Exchange Traded Funds (ETFs) and Contracts for Difference (CFDs). These products offer a cheap, tax-efficient and speedy method for increasing or decreasing market exposure to price changes in the related primary asset. By facilitating faster and shorter-term trading, these products may increase market liquidity and/or increase market volatility for the related primary asset. The thesis builds a cross-country database of new-derivative-markets opening dates, and investigates the key features of prices and returns for related primary assets before and after the opening of these derivative markets. The database covers 16 countries in the CFD investigation, 21 commodity markets in the ETF investigation, and related data as available (daily closing prices, trading volumes, bid-ask quotes) in each of them. The key price and return features investigated include bid-ask spreads, trading volumes (both of derivatives and related primary assets), and daily return autocorrelation, variance, skewness and kurtosis. This thesis also considers a separate, but related, research problem. It extends and empirically applies a liquidity-indicator model for the Eurozone created by the Bank of England (BOE) and developed further by the European Central Bank (ECB) by including commodity liquidity, and uses this extended model to investigate shifting investor behaviour based on changing market dynamics. Similar to the investigation of the CDF and EFT markets, this investigation is concerned with market stability and liquidity in a changed environment (in this case, the key change is the introduction of the euro currency). Chapter one contains an introduction to the main hypotheses regarding the effects of the introduction of new derivatives on securities markets, and the empirical methods used to test these hypotheses. This chapter also describes the two investment products which are the main focus, CFDs and ETFs, and their particular potential impacts on market-specific characteristics such as volatility, efficiency and liquidity. Chapter two empirically investigates the impact of CFDs on market liquidity and volatility. CFDs have existed for less than twenty years and the CFD market grew rapidly prior to the recent international financial crisis. This chapter empirically examines the roles that CFDs have played, either as an accelerant for mispricing in international equity markets away from fundamental values, or as a source of increased market efficiency through the addition of new liquidity. This chapter uses GARCH and EGARCH models to test for the impact of CFDs on the return volatility and autocorrelation of the underlying security. In the case of Australia, the analysis is applied to individual securities. In the other 15 countries investigated in this chapter, the analysis is applied at the level of the market index. The chapter also investigates whether the stylised characteristics of CFDs are more or less pronounced in low liquidity exchanges. This chapter finds that CFDs appear to have influenced asset-specific variance and return autocorrelation. Some tentative explanations for these findings are offered. The presence of bid and ask-price ‘overhangs’ associated with CFD trading cannot be rejected and may be associated with observed volatility reductions in some jurisdictions. Following the analysis based on CFDs in chapter two, ETFs are the primary focus of chapter three. ETFs have existed since the late 1980s, but were first traded on commodity markets in the early 2000s. Their inception has been linked by some market analysts with the large growth in commodity market volatility seen in recent years. This chapter directly tests this link. The chapter also investigates whether the stylised characteristics of ETFs are more or less pronounced in larger commodity markets than in smaller markets. The results indicate that larger ETFs in terms of their assets under management at their dates of inception, are associated with higher volatility. Smaller commodity markets are found to have increased efficiency after the introduction of ETFs, indicating that there are some benefits from new ETF investment in markets below $4 to$5 billion in size, but the associated caveat is that of increased volatility, indicative of potential pitfalls in the ETF portfolio rebalancing process. It appears that ETFs have made commodity markets more efficient through a new influx of trading counterparties, but they appear to be associated with a cost. The need for regulation of investment size and market ownership limits therefore cannot be rejected. Chapters two and three look at two particular new instruments and their effects on liquidity and volatility. Another major innovation in market structure was the advent of the euro currency in January 1999. The power and presence of a financially-combined Europe attracted new international investment, therefore influencing liquidity. The combination of this influx of investors and new products (including CFDs and ETFs) can potentially have wide market impacts. Understanding the structural changes of liquidity in Europe in recent years is important for macroprudential risk assessment, as sudden changes in conditions may be indicative of current stress and a signal of future stress. Chapter four presents a Europeanspecific liquidity measure used by several central banks, and provides some new modifications to this measure. The measure is constructed by combining several facets of liquidity and depth measurement across several asset markets. It attempts to incorporate aspects such as market tightness, depth and resiliency. The flows and the direction of causality can also be inferred using vector autoregression, Granger causality techniques and impulse response functions. The measure uses a combination of liquidity determinants including the bid-ask spread, the return to volume ratio and numerous measures of liquidity premia. In the chapter, the modified liquidity measure is applied empirically to European-area data

Behavior of Financial Markets Efficiency During the Financial Market Crisis: 2007-2009

This paper examines the behavior of financial markets efficiency during the recent financial market crisis. Using the Hurst exponent as a criterion of market efficiency we show that level of market efficiency is different for pre-crisis and crisis periods. We also classify financial markets of different countries by the level of their efficiency and reaffirm that financial markets of developed countries are more efficient than the developing ones. Based on Ukrainian financial market analysis we show the reasons of inefficiency of financial markets and provide some recommendations on their solution and thus improving the efficiency

Temporal Evolution of Financial Market Correlations

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.Comment: 15 pages, 10 figures, 1 table. Accepted for publication in Phys. Rev. E. v2 includes additional section