Essays on heterogeneous news flow on volatility

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Estimating Dependences and Risk between Gold Prices and S&P500: New Evidences from ARCH,GARCH, Copula and ES-VaR models

This thesis examines the correlations and linkages between the stock and commodity in order to quantify the risk present for investors in financial market (stock and commodity) using the Value at Risk measure. The risk assessed in this thesis is losses on investments in stock (S&P500) and commodity (gold prices). The structure of this thesis is based on three empirical chapters. We emphasise the focus by acknowledging the risk factor which is the non-stop fluctuation in the prices of commodity and stock prices. The thesis starts by measuring volatility, then dependence which is the correlation and lastly measure the expected shortfalls and Value at risk (VaR). The research focuses on mitigating the risk using VaR measures and assessing the use of the volatility measures such as ARCH and GARCH and basic VaR calculations, we also measured the correlation using the Copula method. Since, the measures of volatility methods have limitations that they can measure single security at a time, the second empirical chapter measures the interdependence of stock and commodity (S&P500 and Gold Price Index) by investigating the risk transmission involved in investing in any of them and whether the ups and downs in the prices of one effect the prices of the other using the Time Varying copula method. Lastly, the third empirical chapter which is the last chapter, investigates the expected shortfalls and Value at Risk (VaR) between the S&P500 and Gold prices Index using the ES-VaR method proposed by Patton, Ziegel and Chen (2018). Volatility is considered to be the most popular and traditional measure of risk. For which we have used ARCH and GARCH model in our first empirical chapter. However, the problem with volatility is that it does not take into account the direction of an investments’ movement: volatility of stocks is that they suddenly jump higher and investors are not distressed with gains. When we talk about investors for them the risk is about the odds of losing money, after my research and findings VaR is based on the common-sense fact. Hence, investors care about the odds of big losses, VaR answers the question, what is my worst-case scenario? Or simply how much I could lose in a really bad month? The results of the thesis demonstrated that measuring volatility (ARCH GARCH) alone was not sufficient in measuring the risk involved in an investment therefore methodologies such as correlation and VAR demonstrates better results. In terms of measuring the interdependence, the Time Varying Copula is used since the dynamic structure of the de- pendence between the data can be modelled by allowing either the copula function or the dependence parameter to be time varying. Lastly, hybrid model further demonstrates the average return on a risky asset for which Expected Shortfall (ES) along with some quantile dependence and VaR (Value at risk) is utilised. Basel III Accord which is applied in coming years till 2019 focuses more on ES unlike VaR, hence there is little existing work on modelling ES. The thesis focused on the results from the model of Patton, Ziegel and Chen (2018) which is based on the statistical decision theory. Patton, Ziegel and Chen (2018), overcame the problem of elicitability for ES by using ES and VaR jointly and propose the new dynamic model of risk measure. This research adds to the contribution of knowledge that measuring risk by using volatility is not enough for measuring risk, interdependence helps in measuring the dependency of one variable over the other and estimations and inference methods proposed by Patton, Ziegel and Chen (2018) using simulations proposed in ES-VaR model further concludes that ARCH and GARCH or other rolling window models are not enough for determining the risk forecasts. The results suggest, in first empirical chapter we see volatility between Gold prices and S&P500. The second empirical chapter results suggest conditional dependence of the two indexes is strongly time varying. The correlation between the stock is high before 2008. The results further displayed slight stronger bivariate upper tail, which signifies that the conditional dependence of the indexes is influence by positive shocks. The last empirical chapter findings proposed that measuring forecasts using ES-Var model proposed by Patton, Ziegel and Chen (2018) does outer perform forecasts based on univariate GARCH model. Investors want to 10 protect themselves from high losses and ES-VaR model discussed in last chapter would certainly help them to manage their funds properly

statistical methods on risk management of extreme events

The goal of the dissertation is the investigation of financial risk analysis methodologies, using the schemes for extreme value modeling as well as techniques from copula modeling. Extreme value theory is concerned with probabilistic and statistical questions re- lated to unusual behavior or rare events. The subject has a rich mathematical theory and also a long tradition of applications in a variety of areas. We are interested in its application in risk management, with a focus on estimating and forcasting the Value-at-Risk of financial time series data. Extremal data are inherently scarce, thus making inference challenging. In order to obtain good estimates for risk measures, we develop a two-stage approach: (1) fitting the GARCH-type models at the first stage to describe the volatility clustering and other stylized facts of financial time series; (2) using the extreme value theory based models to fit to the tails of the residuals. Additionally, the performance measures provide information in terms of the comparison of the two-stage semi-parametric approach with the parametric methodologies, through robust backtesting. Copula is a particular branch of probability theory, with which, given sufficient data, we can separate the marginal behavior of individual risks and their dependence structure from a multivariate random variable. Linear correlation is widely used to model dependence but has limitations as a measure of association and thus we opt to use copulas to analyze the dependence structure and build models for our different problems arising in risk management. For this part of the dissertation, we take a look at different copula families, highlight for some when they are most appropriate to use for a particular application, discuss some of their drawbacks as diverse scenarios occur in different risk management models, and explore the possibility of developing the copula modeling to reflect the complicated dependence structure of portfolios

Studies on African equity markets and global shocks : co-movement, contagion, and diversification

A Doctoral thesis submitted in fulfilment of the requirements for the award of Doctor of Philosophy degree in the field of Finance The Graduate school of Business Administration, University of the Witwatersrand, October 2016The global financial system has experienced turmoil in the past three decades, at the least. Although the shocks originate abroad, they possess some rippling effects on African economies. The essence of market integration and cross-border listings of stocks has fueled the need for African markets to be well integrated with the global economy. Despite this need, available empirical literature exploring the integration of African markets regionally, and with the rest of the world appear unclear. Moreover, the possibility of global shocks transmitting to Africa via its emerging equity markets remains underexplored. At the same time, such knowledge is critical for not only understanding the functioning of equity markets in particular, but also important for regulating the financial system in general. This thesis addresses these gaps inherent in extant literature and proffer empirical and theoretical solutions by exploring the nexus between African stock markets and global shocks. The emphasis is on contagion, co-movement, and diversification. The thesis is organized into four empirical essays, each deeply touching on specific theme (s) that form the core of the problems or research questions under investigation while employing advanced econometric techniques that underpin the modeling of asset returns. The first essay examines the capacity of African equity markets to act as ‗hubs‘ for portfolio investors during tranquil and turbulent conditions of global equity and commodity markets. The findings posit that African stock markets provide decorrelation from commodity and global equity markets during extreme market conditions. To the extent that the results reveal the strength of African stocks in cushioning international portfolio investors in a mean-variance stand-point during market crashes, the essay helps to decay doubts in the minds of investors on the perceived lack of capacity of the continent‘s stocks to yield higher expected risk-return trade-offs during global market sell-offs. The implication of the study is that given the recent history of commodities and global stocks, fund managers around the world seeking viable alternatives to compensate for losses from commodity shocks through uncorrelated markets may consider the equity markets in Africa, albeit on account of volatility persistence, present and past market conditions, markets stability, as well as size and liquidity issues. The second essay examines regional and global co-movement of African stock markets using the three-dimensional continuous Morlet wavelet transform methodology. The essay establishes evidence of stronger co-movements broadly narrowed to short-run fluctuations. The co-movements are time-varying and commonly non-homogeneous – with phase difference arrow vectors implying lead-lag African Equity Markets and Global Shocks 2016 © Gideon Boako Page iii relationships. The presence of lead-lag effects and stronger co-movements at short-run fluctuations may induce arbitrage and diversification opportunities to both local and international investors with long-term investment horizons. The findings also reveal that some African equity markets are, to a degree, segmented from volatilities of the dollar and euro exchange rates. The third essay sheds light on whether African equity markets decoupled from, and / or converged with regional and global markets from 2003 to 2014, and analyzes the implications of that for shocks spillovers. Although there is no evidence of African markets convergence either regionally or globally, shock propagation exists in a time-varying setting. Regional markets in Africa are not just ‗shock absorbers‘ but also ‗shock transmitters‘. In the last essay, the dependence structure and (extreme) downside developed equity markets and currency price risk spillover effects to African stock markets using value-at-risk (VaR) and conditional value-at-risk (CoVaR) based on stochastic copulas is modeled. The study finds evidence of non-homogenous weak negative dependence between stocks and the USD and EUR exchange rates. Except for Egypt, there is evidence of positive significant dependencies between all African markets and their developed counterparts. Although, evidence of both uni-directional and bidirectional causality, as well as upper and lower tail dependencies are found across the stocks and currency markets, only some minuscule evidence of downside spillover effects was recorded, albeit episodic. It is observed that propagation of shocks from the GFC had a second round effect in African stock markets. Thus, the impact of the GFC to African economies was not through the credit crunches and liquidity freezes in Phase I of the crisis, but rather through the global recession that followed into the second phase. The findings are consistent with the view that global shocks propagation to developing markets may stagger during crisis and intensify post-crisis. A practical implication from the results is that given the relatively scarce resources and levels of technological know-how available to African governments, efforts to wean the continent‟s equity markets from adverse effects of global market crashes should be geared towards plans and programmes to mitigate the shocks not at the early stages but latter stages, where the effects to Africa could be prominently felt. Three key arguments are deduced from all the essays. First, although financial market underdevelopment seems prima-facie, to help countries isolate themselves against immediate contagion, it also reduces the ability of the real economy to cushion the impact of the crisis. African Equity Markets and Global Shocks 2016 © Gideon Boako Page iv Therefore, the argument of the thesis is that despite the common fear that a highly integrated and developed market may present fertile grounds for shock spillover, Africa must continue to pursue programmes aimed at enhancing inter and intra-regional integration. However, the degree and extent of both inter- and intra-regional integration ought to be pegged at certain optimal levels in order to reap benefits from scale economies. Such endeavours at integration will not only help in risk diversification but also help smooth the impact of shocks. The second argument is that, the proposition of the ―decoupling theory‖ i.e. returns of African equity markets and global stocks are not jointly normal during crisis periods may not be entirely tenable, empirically. Thirdly, the thesis argues that the “shift-contagion” theory may not reflect the reality for Africa, particularly during initial stages of crisis. Instead, the thesis suggests an extension and argues for a “delayed-shift contagion” theory. Keywords: Decoupling, shift-contagion, spillover effects, CoVaR, exchange rates, commodities. JEL Classification: C40, C58, F31, F36, G10, G11, G15,GR201

Modelling cross-market linkages between global markets and China’s A-, B- and H-shares

One of the biggest challenges in quantifying joint risk and forming effective policies in financial management and investment strategies is to fully understand the characteristics of market associations in low and high volatility periods. Market interdependence, therefore, is a hot topic that has received interest from academics and industry experts, especially since the Asian Financial Crisis in 1997. China, being the world’s second-largest economy, has been the centre of many studies investigating stock market dependencies. While China has three major share types, namely A-, B- and H-shares, with different market players, market characteristics and operating efficiency, the number of studies on each of these share types remains conservative in comparison to the vast literature on the financial modelling of market interdependencies. Given the need for a more comprehensive understanding of the influence between these share types and other global markets, especially during market turbulences, this thesis examines the cross-market linkages between A-, B- and H-shares in China and several major emerging and advanced markets from 2002 to 2017, which is divided into two non-crisis periods and two crisis periods. This thesis assesses market integration among 17 markets, including asymmetries and leverage effect in the marginal distributions, volatility spillover and tail dependence. The thesis aims to: 1) investigate the univariate asymmetries and leverage effect in the distributional volatility of each time series and to detect volatility spillover between China and other studied markets; 2) assess the dynamic multivariate dependence between China and other studied markets; 3) evaluate the bivariate dependence structure for each of China’s markets and other studied markets using seven different copula functions; and 4) study the multivariate joint tail dependence structure of all studied markets using vine copulas. There are various findings from the thesis. Many advanced and emerging markets experienced leverage effect and asymmetries in volatility. China’s markets were much more prone to local shocks than external shocks and in many cases, there is evidence that China’s markets diverged from the global trends especially during the crisis periods. Besides, segmentation between China’s markets and the United States is clearly evident. In addition, regional dependence is stronger than intra-regional dependence. The thesis also found the existence of contagion effect between each of China’s markets and various markets in the sample in the Global Financial Crisis. Finally, heterogeneity was found for A-, B- and H-shares in various aspects, from distributional asymmetries to joint behaviour in both crisis and non-crisis periods. A novel aspect of this thesis is that it closes the gap in the literature of market linkages for A-, B- and H-shares with other global markets by assessing volatility spillover, time-varying co-movement, and tail dependence among the studied markets. This thesis provides various implications in both theoretical and empirical contexts in many areas including measuring joint risk at the tails, constructing an optimal portfolio, hedging, and managing financial exposures and contagious volatility from other markets. The thesis provides some recommendations and suggestions regarding the policies implemented in China

Survey of quantitative investment strategies in the Russian stock market : Special interest in tactical asset allocation

Russia’s financial markets have been an uncharted area when it comes to exploring the performance of investment strategies based on modern portfolio theory. In this thesis, we focus on the country’s stock market and study whether profitable investments can be made while at the same time taking uncertainties, risks, and dependencies into account. We also pay particular interest in tactical asset allocation. The benefit of this approach is that we can utilize time series forecasting methods to produce trading signals in addition to optimization methods. We use two datasets in our empirical applications. The first one consists of nine sectoral indices covering the period from 2008 to 2017, and the other includes altogether 42 stocks listed on the Moscow Exchange covering the years 2011 – 2017. The strategies considered have been divided into five sections. In the first part, we study classical and robust mean-risk portfolios and the modeling of transaction costs. We find that the expected return should be maximized per unit expected shortfall while simultaneously requiring that each asset contributes equally to the portfolio’s tail risk. Secondly, we show that using robust covariance estimators can improve the risk-adjusted returns of minimum variance portfolios. Thirdly, we note that robust optimization techniques are best suited for conservative investors due to the low volatility allocations they produce. In the second part, we employ statistical factor models to estimate higher-order comoments and demonstrate the benefit of the proposed method in constructing risk-optimal and expected utility-maximizing portfolios. In the third part, we utilize the Almgren–Chriss framework and sort the expected returns according to the assumed momentum anomaly. We discover that this method produces stable allocations performing exceptionally well in the market upturn. In the fourth part, we show that forecasts produced by VECM and GARCH models can be used profitably in optimizations based on the Black–Litterman, copula opinion pooling, and entropy pooling models. In the final part, we develop a wealth protection strategy capable of timing market changes thanks to the return predictions based on an ARIMA model. Therefore, it can be stated that it has been possible to make safe and profitable investments in the Russian stock market even when reasonable transaction costs have been taken into account. We also argue that market inefficiencies could have been exploited by structuring statistical arbitrage and other tactical asset allocation-related strategies.Venäjän rahoitusmarkkinat ovat olleet kartoittamatonta aluetta tutkittaessa moderniin portfolioteoriaan pohjautuvien sijoitusstrategioiden käyttäytymistä. Tässä tutkielmassa keskitymme maan osakemarkkinoihin ja tarkastelemme, voidaanko taloudellisesti kannattavia sijoituksia tehdä otettaessa samalla huomioon epävarmuudet, riskit ja riippuvuudet. Kiinnitämme erityistä huomiota myös taktiseen varojen kohdentamiseen. Tämän lähestymistavan etuna on, että optimointimenetelmien lisäksi voimme hyödyntää aikasarjaennustamisen menetelmiä kaupankäyntisignaalien tuottamiseksi. Empiirisissä sovelluksissa käytämme kahta data-aineistoa. Ensimmäinen koostuu yhdeksästä teollisuusindeksistä kattaen ajanjakson 2008–2017, ja toinen sisältää 42 Moskovan pörssiin listattua osaketta kattaen vuodet 2011–2017. Tarkasteltavat strategiat on puolestaan jaoteltu viiteen osioon. Ensimmäisessä osassa tarkastelemme klassisia ja robusteja riski-tuotto -portfolioita sekä kaupankäyntikustannusten mallintamista. Havaitsemme, että odotettua tuottoa on syytä maksimoida suhteessa odotettuun vajeeseen edellyttäen samalla, että jokainen osake lisää sijoitussalkun häntäriskiä yhtä suurella osuudella. Toiseksi osoitamme, että minimivarianssiportfolioiden riskikorjattuja tuottoja voidaan parantaa robusteilla kovarianssiestimaattoreilla. Kolmanneksi toteamme robustien optimointitekniikoiden soveltuvan parhaiten konservatiivisille sijoittajille niiden tuottamien matalan volatiliteetin allokaatioiden ansiosta. Toisessa osassa hyödynnämme tilastollisia faktorimalleja korkeampien yhteismomenttien estimoinnissa ja havainnollistamme ehdotetun metodin hyödyllisyyttä riskioptimaalisten sekä odotettua hyötyä maksimoivien salkkujen rakentamisessa. Kolmannessa osassa käytämme Almgren–Chrissin viitekehystä ja asetamme odotetut tuotot suuruusjärjestykseen oletetun momentum-anomalian mukaisesti. Havaitsemme, että menetelmä tuottaa vakaita allokaatioita menestyen erityisen hyvin noususuhdanteessa. Neljännessä osassa osoitamme, että VECM- että GARCH-mallien tuottamia ennusteita voidaan hyödyntää kannattavasti niin Black–Littermanin malliin kuin kopulanäkemysten ja entropian poolaukseenkin perustuvissa optimoinneissa. Viimeisessä osassa laadimme varallisuuden suojausstrategian, joka kykenee ajoittamaan markkinoiden muutoksia ARIMA-malliin perustuvien tuottoennusteiden ansiosta. Voidaan siis todeta, että Venäjän osakemarkkinoilla on ollut mahdollista tehdä turvallisia ja tuottavia sijoituksia myös silloin kun kohtuulliset kaupankäyntikustannukset on huomioitu. Toiseksi väitämme, että markkinoiden tehottomuutta on voitu hyödyntää suunnittelemalla tilastolliseen arbitraasiin ja muihin taktiseen varojen allokointiin pohjautuvia strategioita

Bayesian Networks for Asset Management and Financial Risk

This thesis explores the use of Bayesian networks to develop “views” for a Black-Litterman asset allocation model, and determines whether they can help in the creation of better investment portfolios. Views represent an investor’s expectations of the future performance of a company’s shares: an estimate of expected return, and a measure of the uncertainty of this estimate. This thesis aims to automate the creation of views and to pioneer intelligent portfolio construction as part of an algorithmic asset management process

Sectoral dynamics of financial co-integration between BRICS and developed stock markets

This study examines the sectoral dynamics of co-integration between the BRICS (Brazil, Russia, India China and South Africa) and developed stock markets, represented by Germany, Japan, the UK and the US, during the four phases of the Global Financial Crisis (GFC), the three phases of the European Sovereign Debt Crisis (ESDC) and the UK Brexit crisis. The sample includes daily sectoral equity indices over the period January 2006 to December 2017. The study applies the ADCC GJRGARCH model to estimate the time-varying correlations across the nine countries within each sector and across sectors within each country, and assesses the conditional correlation dynamics during each of the phases of the three crisis periods. The results support the existence of financial co-integration across sectors and among all the nine countries during the GFC and ESDC. Only developed countries exhibit co-integration during the UK Brexit crisis. While some sectors were less affected during some of the crisis periods, on average, financials were the most affected during the GFC, ESDC and UK Brexit crisis. Further analysis on a crisis phase level reveals that most country pairs and sector pairs exhibit significant increases in conditional correlations in phase two of the GFC and ESDC, limiting the effectiveness of international diversification during this period. The results provide useful insights for policy makers and investors

Quantitative Methods for Economics and Finance

This book is a collection of papers for the Special Issue “Quantitative Methods for Economics and Finance” of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice

Extreme value theory for finance: a survey

Extreme value theory is concerned with the study of the asymptotical distribution of extreme events, that is to say events which are rare in frequency and huge with respect to the majority of observations. Statistical methods derived from this theory have been increasingly employed in finance, especially in the context of risk measurement. The aim of the present study is twofold. The first part delivers a critical review of the theoretical underpinnings of extreme value theory. The second part provides a survey of some major applications of extreme value theory to finance, namely its use to test different distributional assumptions for the data, Value-at-Risk and Expected Shortfall calculations, asset allocation under safety-first type constraints and the study of contagion and dependence across markets under stress conditions.extreme value theory, risk management, fat-tailed distributions, Value-at-Risk, systemic risk, asset allocation