Measuring market risk using extreme value theory

The adoption of Basel II standards by the Bangko Sentral ng Pilipinas initiates financial institutions to develop value-at-risk (VaR) models to measure market risk. In this paper, two VaR models are considered using the peaks-over-threshold (POT) approach of the extreme value theory: (1) static EVT model which is the straightforward application of POT to the bond benchmark rates; and (2) dynamic EVT model which applies POT to the residuals of the fitted AR-GARCH model. The results are compared with traditional VaR methods such as RiskMetrics and AR-GARCH-type models. The relative size, accuracy and efficiency of the models are assessed using mean relative bias, backtesting, likelihood ratio tests, loss function, mean relative scaled bias and computation of market risk charge. Findings show that the dynamic EVT model can capture market risk conservatively, accurately and efficiently. It is also practical to use because it has the potential to lower a bank’s capital requirements. Comparing the two EVT models, the dynamic model is better than static as the former can address some issues in risk measurement and effectively capture market risks.extreme value theory, peaks-over-threshold, value-at-risk, market risk, risk management

A Range-Based GARCH Model for Forecasting Volatility

A new variant of the ARCH class of models for forecasting the conditional variance, to be called the Generalized AutoRegressive Conditional Heteroskedasticity Parkinson Range (GARCH-PARK-R) Model, is proposed. The GARCH-PARK-R model, utilizing the extreme values, is a good alternative to the Realized Volatility that requires a large amount of intra-daily data, which remain relatively costly and are not readily available. The estimates of the GARCH-PARK-R model are derived using the Quasi-Maximum Likelihood Estimation (QMLE). The results suggest that the GARCH-PARK-R model is a good middle ground between intra-daily models, such as the Realized Volatility and inter-daily models, such as the ARCH class. The forecasting performance of the models is evaluated using the daily Philippine Peso-U.S. Dollar exchange rate from January 1997 to December 2003.Volatility, Parkinson Range, GARCH-PARK-R, QMLE

Deubiquitinating Proteases in Plasmodium falciparum

Plasmodium falciparum is the blood-borne parasite responsible for the deadliest form of human malaria, a disease that kills up to two million people each year (1). Lack of effective vaccines and continued emergence of resistant strains demands the development of novel therapeutics for this continued global health problem (2, 3). In an effort to discover new drugs, we are investigating parasite expressed proteases of the ubiquitin-proteasome system as potential targets of therapeutic intervention. The ubiquitin-proteasome system regulates protein levels in all eukaryotic cells by covalent modification of protein substrates by ubiquitin and their subsequent direction to the proteasome for degradation (6). DUBs are proteases responsible for hydrolyzing the protein-ubiquitin bond; thus participating in multiple ubiquitin-related processes such as ubiquitin recycling and ubiquitin processing. Due to the increasing promise of proteases as drug targets for a variety of diseases and the importance of the ubiquitin-proteasome pathway in eukaryotes, we are interested in P. falciparum deubiquitinating proteases (PfDUBs) as putative drug targets (9). Seventeen DUBs have recently been identified in the P. falciparum genome (11). Using BLASTP homology searching, we have determined that the DUBs USP14, UCH-L5, and POH1 appear to be conserved in P. falciparum. These three DUBs are known to associate with the proteasome in mammalian cells and we hypothesize that in P. falciparum, they serve a role in ubiquitin recycling through the removal of ubiquitin from protein substrates prior to entering the proteasome for degradation (21, 22, 24). Since the presence of monomeric ubiquitin is necessary for the initial conjugation of ubiquitin to substrates, disruption of ubiquitin recycling may deplete the necessary pools of monomeric ubiquitin. To validate the essentiality of these three PfDUBs, we have used molecular genetic techniques to insert onto the end of their coding regions a sequence encoding a gene that allows us to attenuate the expression of the resulting fusion protein. Regardless of protein attenuation, we show that parasite death occurs in minimal media as a result of the C-terminal modification of either PfUSP14 or PfPOH1. Contrary to our model, attenuation of these PfDUBs did not appreciably deplete monomeric ubiquitin; however the parasites do appear to show a possible stress-related response. In addition to our essentiality studies, we have biochemically characterized PfUCH-L5 by tagging it with a hemagglutinin (HA) epitope tag. We have immunoprecipitated PfUCH-L5-HA, assayed for deubiquitinating activity, and assessed its biochemical properties.A three-year embargo was granted for this item

Time-varying conditional Johnson SU density in value-at-risk (VaR) methodology

Stylized facts on financial time series data are the volatility of returns that follow non-normal conditions such as leverage effects and heavier tails leading returns to have heavier magnitudes of extreme losses. Value-at-risk is a standard method of forecasting possible future losses in investments. A procedure of estimating value-at-risk using time-varying conditional Johnson SU¬ distribution is introduced and assessed with econometric models. The Johnson distribution offers the ability to model higher parameters with time-varying structure using maximum likelihood estimation techniques. Two procedures of modeling with the Johnson distribution are introduced: joint estimation of the volatility and two-step procedure where estimation of the volatility is separate from the estimation of higher parameters. The procedures were demonstrated on Philippine-foreign exchange rates and the Philippine stock exchange index. They were assessed with forecast evaluation measures with comparison to different value-at-risk methodologies. The research opens up modeling procedures where manipulation of higher parameters can be integrated in the value-at-risk methodology.Time Varying Parameters; GARCH models; Nonnormal distributions; Risk Management

Measuring the Common Component of Stock Market Fluctuations in the Asia-Pacific Region

This paper fits Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) models to the daily closing stock market indices of Australia, China, Hong Kong, Indonesia, Japan, Korea, Malaysia, Philippines, Singapore, and Taiwan to compute for time-varying weights associated with the volatilities of individual indices. These weights and the returns of the various indices were then used to determine the common component of stock market returns. Our results suggest that a common component of the Asia-Pacific stock market returns exists, which significantly explains the individual country’s stock market returns. We also find that stock markets of Korea and Hong Kong are the two most sensitive to changes in the common component stock returns, while China’s stock market is the least sensitive.Common Component, Volatility, GARCH model

Estimating Inflation-at-Risk (IaR) using Extreme Value Theory (EVT)

The Bangko Sentral ng Pilipinas (BSP) has the primary responsibility of maintaining stable prices conducive to a balanced and sustainable economic growth. The year 2008 posed a challenge to the BSP’s monetary policy making as inflation hit an official 17-year high of 12.5 percent in August after 10 months of continuous acceleration. The alarming double-digit inflation rate was attributed to rising fuel and food prices, particularly the price of rice. A high inflation rate has impact on poverty since inflation affects the poor more than the rich. From a macroeconomic perspective, high level of inflation is not conducive to economic growth. This paper proposes a method of estimating Inflation-at-Risk (IaR) similar to the Value-at-Risk (VaR) used to estimate risk in the financial market. The IaR represents the maximum inflation over a target horizon for a given low pre-specified probability. It can serve as an early warning system that can be used by the BSP to identify whether the level of inflation is extreme enough to be considered an imminent threat to its inflation objective. The extreme value theory (EVT), which deals with the frequency and magnitude of very low probability events, is used as the basis for building a model in estimating the IaR. The estimates of the IaR using the peaks-over-threshold (POT) model suggest that the while the inflation rate experienced in 2008 can not be considered as an extreme value, it was very near the estimated 90 percent IaR.Inflation-at-Risk (IaR), Extreme Value Theory (EVT), Peaks-over-Threshold (POT)

Robust Determinants of Income Growth in the Philippines

This paper studies the relationship between population dynamics and income growth in the Philippines using data from 74 provinces for the period 1985-2003. Simulation techniques were used to quantify the effect of population dynamics on the differences in income of the provinces. It also examines the robustness of the explanatory variables to determine "deep" determinants of income growth. The study shows that population variable is robustly related with growth and while it is not the sole culprit for the dismal growth performance over the years, it shows that the opportunities associated with the demographic transition are real and can provide the stimulus needed by the country.economic growth, population, population growth, demographic transition

Robust Determinants of Income Growth in the Philippines

This paper studies the relationship between population dynamics and income growth in the Philippines using data from 74 provinces for the period 1985-2003. Simulation techniques were used to quantify the effect of population dynamics on the differences in income of the provinces. It also examines the robustness of the explanatory variables to determine "deep" determinants of income growth. The study shows that population variable is robustly related with growth and while it is not the sole culprit for the dismal growth performance over the years, it shows that the opportunities associated with the demographic transition are real and can provide the stimulus needed by the country.economic growth, population, population growth, demographic transition

Population Dynamics and Household Saving: Evidence from the Philippines

The economic growth implications due to changes in the nation’s age structure have been substantial. In the course of the demographic transition, countries experience an increasing share of the working age population relative to the total population and this creates favorable effects on economic growth. The changing age structure also influences household saving rate. This paper looks at the role of the slow demographic transition in the Philippines to its aggregate household saving rate using panel data from the Family Income and Expenditure Survey (1985 to 2003). It is known for a fact that household saving rate in the Philippines is one of the lowest in East Asia. The econometric model is based on the augmented life cycle model and the results suggest that the country’s population dynamics plays an important role in its household saving rate. The Philippines rapid population growth creates a big bulge in the lower portion of the age pyramid that resulted in a higher percentage of young dependents. This suggests that the country is paying a high price for its high population growth resulting to low saving rate and consequently, low economic growth. The results also show that remittance from migrant workers is a major source of aggregate household saving.Demographic Transition, Saving Rate

Robustness Procedures in Economic Growth Regression Models

A central question for empirical economics, particularly economic growth, is which explanatory variables to include and exclude in the regressions. This paper aims to identify variables strongly correlated with provincial income growth in the Philippines by applying robustness procedures in determining which variables are strongly correlated with income growth. The extreme bound analysis (EBA) and Bayesian Averaging of Classical Estimates (BACE) were applied to fifteen determinants of income growth from a data set consisting of 74 Philippine provinces for the period 1985 to 2003 to test which among the explanatory variables are strongly correlated to growth. The tests show that among the fifteen variables, five variables stand out as being robust. The log of initial income, the ARMM indicator, the expenditure GINI and its square and the proportion of young dependents are all considered as strongly correlated to growth.Robust, Extreme Bound Analysis (EBA), Bayesian Averaging of Classical Estimates (BACE)