Essays on Vietnam’s Financial Reforms: Foreign Exchange Statistics and Evidence of Long-Run Equilibrium

In this paper, we examine exchange rates in Vietnam’s transitional economy. Evidence of long-run equilibrium are established in most cases through a single co-integrating vector among endogenous variables that determine the real exchange rates. This supports relative PPP in which ECT of the system can be combined linearly into a stationary process, reducing deviation from PPP in the long run. Restricted coefficient vectors ß’ = (1, 1, -1) for real exchange rates of currencies in question are not rejected. This empirics of relative PPP adds to found evidences by many researchers, including Flre et al. (1999), Lee (1999), Johnson (1990), Culver and Papell (1999), Cuddington and Liang (2001). Instead of testing for different time series on a common base currency, we use different base currencies (USD, GBP, JPY and EUR). By doing so we want to know the whether theory may posit significant differences against one currency? We have found consensus, given inevitable technical differences, even with smallerdata sample for EUR. Speeds of convergence to PPP and adjustment are faster compared to results from other researches for developed economies, using both observed and bootstrapped HL measures. Perhaps, a better explanation is the adjustment from hyperinflation period, after which the theory indicates that adjusting process actually accelerates. We observe that deviation appears to have been large in early stages of the reform, mostly overvaluation. Over time, its correction took place leading significant deviations to gradually disappear.

Characterization of the morphonuclear features and DNA ploidy of typical and atypical carcinoids and small cell carcinomas of the lung

The authors analyzed several cytomorphonuclear parameters related to chromatin distribution and DNA ploidy in typical and atypical carcinoids and in small cell lung cancers. Nuclear measurements and analysis were performed with a SAMBA 200 (TITN, Grenoble, France) cell image processor with software allowing the discrimination of parameters computed on cytospin preparations of Feulgen-stained nuclei extracted from deparaffinized tumor tissues. The authors' results indicate a significant increase in DNA content--assessed by integrated optical density (IOD)--from typical carcinoids to small cell lung carcinomas, with atypical carcinoids showing an intermediate value. Parameters related to hyperchromatism (short and long run length and variance of optical density) also characterize the atypical carcinoids as being intermediate between typical carcinoids and small cell lung cancers. The systematic measurement of these cytomorphonuclear parameters seems to define an objective, reproducible "scale" of differentiation that helps to define the atypical carcinoid and may be of value in establishing cytologic criteria for differential diagnosis.

Cross-sectional study of 168 patients with hepatorenal tyrosinaemia and implications for clinical practice

Background: Hepatorenal tyrosinaemia (Tyr 1) is a rare inborn error of tyrosine metabolism. Without treatment, patients are at high risk of developing acute liver failure, renal dysfunction and in the long run hepatocellular carcinoma. The aim of our study was to collect cross-sectional data. Methods. Via questionnaires we collected retrospective data of 168 patients with Tyr 1 from 21 centres (Europe, Turkey and Israel) about diagnosis, treatment, monitoring and outcome. In a subsequent consensus workshop, we discussed data and clinical implications. Results: Early treatment by NTBC accompanied by diet is essential to prevent serious complications such as liver failure, hepatocellular carcinoma and renal disease. As patients may remain initially asymptomatic or develop uncharacteristic clinical symptoms in the first months of life newborn mass screening using succinylacetone (SA) as a screening parameter in dried blood is mandatory for early diagnosis. NTBC-treatment has to be combined with natural protein restriction supplemented with essential amino acids. NTBC dosage should be reduced to the minimal dose allowing metabolic control, once daily dosing may be an option in older children and adults in order to increase compliance. Metabolic control is judged by SA (below detection limit) in dried blood or urine, plasma tyrosine (<400 μM) and NTBC-levels in the therapeutic range (20-40 μM). Side effects of NTBC are mild and often transient. Indications for liver transplantation are hepatocellular carcinoma or failure to respond to NTBC. Follow-up procedures should include liver and kidney function tests, tumor markers and imaging, ophthalmological examination, blood count, psychomotor and intelligence testing as well as therapeutic monitoring (SA, tyrosine, NTBC in blood). Conclusion: Based on the data from 21 centres treating 168 patients we were able to characterize current practice and clinical experience in Tyr 1. This information could form the basis for clinical practice recommendations, however further prospective data are required to underpin some of the recommendations.

Measuring, Modeling, and Forecasting Volatility and Correlations from High-Frequency Data

This dissertation contains four essays that all share a common purpose: developing new methodologies to exploit the potential of high-frequency data for the measurement, modeling and forecasting of financial assets volatility and correlations. The first two chapters provide useful tools for univariate applications while the last two chapters develop multivariate methodologies. In chapter 1, we introduce a new class of univariate volatility models named FloGARCH models. FloGARCH models provide a parsimonious joint model for low frequency returns and realized measures, and are sufficiently flexible to capture long memory as well as asymmetries related to leverage effects. We analyze the performances of the models in a realistic numerical study and on the basis of a data set composed of 65 equities. Using more than 10 years of high-frequency transactions, we document significant statistical gains related to the FloGARCH models in terms of in-sample fit, out-of-sample fit and forecasting accuracy compared to classical and Realized GARCH models. In chapter 2, using 12 years of high-frequency transactions for 55 U.S. stocks, we argue that combining low-frequency exogenous economic indicators with high-frequency financial data improves the ability of conditionally heteroskedastic models to forecast the volatility of returns, their full multi-step ahead conditional distribution and the multi-period Value-at-Risk. Using a refined version of the Realized LGARCH model allowing for time-varying intercept and implemented with realized kernels, we document that nominal corporate profits and term spreads have strong long-run predictive ability and generate accurate risk measures forecasts over long-horizon. The results are based on several loss functions and tests, including the Model Confidence Set. Chapter 3 is a joint work with David Veredas. We study the class of disentangled realized estimators for the integrated covariance matrix of Brownian semimartingales with finite activity jumps. These estimators separate correlations and volatilities. We analyze different combinations of quantile- and median-based realized volatilities, and four estimators of realized correlations with three synchronization schemes. Their finite sample properties are studied under four data generating processes, in presence, or not, of microstructure noise, and under synchronous and asynchronous trading. The main finding is that the pre-averaged version of disentangled estimators based on Gaussian ranks (for the correlations) and median deviations (for the volatilities) provide a precise, computationally efficient, and easy alternative to measure integrated covariances on the basis of noisy and asynchronous prices. Along these lines, a minimum variance portfolio application shows the superiority of this disentangled realized estimator in terms of numerous performance metrics. Chapter 4 is co-authored with Niels S. Hansen, Asger Lunde and Kasper V. Olesen, all affiliated with CREATES at Aarhus University. We propose to use the Realized Beta GARCH model to exploit the potential of high-frequency data in commodity markets. The model produces high quality forecasts of pairwise correlations between commodities which can be used to construct a composite covariance matrix. We evaluate the quality of this matrix in a portfolio context and compare it to models used in the industry. We demonstrate significant economic gains in a realistic setting including short selling constraints and transaction costs.