Three essays on the interest rate forward-futures differential 1. Empirical investigation of the size and the nature of the Eurodollar futures-foward differential 2. Decomposition of the interest rate forward-futures price differential 3. How much premium is there for interest rate futures?

This dissertation analyzes a series of issues that surround both the theoretical modeling and the empirical estimation of the forward-futures differential, commonly known as the convexity adjustment. Opposite to theoretical implication, I find that the magnitude of the forward-futures rate differential is much smaller than what was expected, and that its sign is negative on many occasions. Neither asynchronicity bias, nor the unconventional feature of the Eurodollar futures pricing can explain the observed phenomena. The term structure interpolation error and the two business day lag between the fixing (settlement) date and the transaction (value) date to which the implied forward rates and prices are applied cannot be attributed to the observed abnormality either. I further show that the difference between the implied forward price obtained from the spot rate term structure and the original Eurodollar futures price at any point of time before maturity is composed of two parts: the element due to marking-to-market and the element arisen from the unconventional settlement of the Eurocurrency futures. It is also demonstrated that the discrepancy between the forward price and the futures price arisen from the unconventional settlement of the Eurocurrency futures can be hedged using a specific basket of caplets. This paper also performs the analysis for the three most traded interest rate futures contracts in Europe: EURIBOR futures, short sterling futures and Euroswiss franc futures. I show that the futures premium is barely detectible for the contracts with maturities below one year. The futures premium for maturities above twelve months varies across the models and is a subject to model assumptions regarding the volatility input and its evolution. Finally, I show that in the presence of the limits to arbitrage the rate on a forward rate agreement (FRA) contract and the respective implied forward rate derived from the spot yield curve would differ and their difference increases with the maturity. This finding allows to challenge the results in recently published works that argue that the convexity adjustment is not priced in by the FRA market makers

An Econometric Macroeconomic Model for Analysis and Forecasting of Key Indicators of the Belarusian Economy

Results of econometric modeling of the Belarusian economy are presented in the article. The methodology of building macromodel for analysis and forecasting of main indicators is described. Estimations of the effects of a rise in oil and gas prices on the key economic indicators are given. The consequences of different scenarios of development of Belarusian economy in 2008 are obtained by simulationeconometric modeling; macromodel; oil and gas prices

Forecasting movements of health-care stock prices based on different categories of news articles using multiple kernel learning

—The market state changes when a new piece of information arrives. It affects decisions made by investors and is considered to be an important data source that can be used for financial forecasting. Recently information derived from news articles has become a part of financial predictive systems. The usage of news articles and their forecasting potential have been extensively researched. However, so far no attempts have been made to utilise different categories of news articles simultaneously. This paper studies how the concurrent, and appropriately weighted, usage of news articles, having different degrees of relevance to the target stock, can improve the performance of financial forecasting and support the decision-making process of investors and traders. Stock price movements are predicted using the multiple kernel learning technique which integrates information extracted from multiple news categories while separate kernels are utilised to analyse each category. News articles are partitioned according to their relevance to the target stock, its sub industry, industry, group industry and sector. The experiments are run on stocks from the Health Care sector and show that increasing the number of relevant news categories used as data sources for financial forecasting improves the performance of the predictive system in comparison with approaches based on a lower number of categories

Role of matrix metalloproteinase polymorphisms in systemic chronic inflammatory diseases and chronic periodontitis

Сучасні наукові відомості підтверджують найчастіше поєднання і взаємозв’язок хронічних запальних хвороб пародонту і таких як цукровий діабет (ЦД), серцево-судинні захворювання (ССЗ), ревматоїдний артрит (РА). Основним патогенетичним напрямком участі матриксних металопротеїназ (ММП) у запаленні вважається міграція лейкоцитів, яка пов’язана з подоланням тканинних бар’єрів та тканинною деструкцією. Поліморфізми ММП можуть брати участь у спільному патогенезі деяких системних запальних захворювань і прогресуючих стоматологічних. В огляді літератури визначено спільні поліморфізми генів ММП при ЦД, ССЗ, РА та хронічному пародонтиті. Встановлено, що найбільш клінічно значущими є поліморфізми: 5А(-1612)6А гену ММП-3, С(-799)Т гену ММП-8 та С(-1562)T ММП-9. Поширеність та значення поліморфізмів ММП серед української популяції належить вивчити для визначення переліку генів для типування з метою прогнозу та вибору засобів лікування хронічного пародонтиту; Современные научные исследования подтверждают закономерное сочетание и взаимосвязь хронических воспалительных заболеваний пародонта и сахарного диабета (СД), сердечно-сосудистых заболеваний (ССЗ), ревматоидного артрита (РА). Основной патогенетической ролью матриксных металлопротеиназ (ММП) при воспалении считается миграция лейкоцитов, связанная с преодолением тканевых барьеров и тканевой деструкцией. Полиморфизмы ММП могут участвовать в едином патогенезе некоторых системных воспалительных заболеваний и прогрессирующих стоматологических. В обзоре определены общие полиморфизмы генов ММП при СД, ССЗ, РА и хроническом пародонтите. Установлено, что наиболее клинически значимыми являются полиморфизмы: 5А(-1612)6А гена ММП-3, С(-799)Т гена ММП-8 и С(-1562)T ММП-9. Распространенность и значение полиморфизмов ММП среди украинской популяции необходимо исследовать для определения перечня генов для типирования с целью прогноза и выбора средств лечения хронического пародонтита; The current evidence links periodontal diseases to diabetes mellitus, cardiovascular disease (CVD), rheumatoid arthritis (RA). The main pathogenetic role of matrix metalloproteinases (MMPs) in inflammation is mediation of leukocyte migration, which is associated with overcoming tissue barriers and relate destruction. MMPs polymorphisms may participate in the pathogenesis of some common systemic inflammatory diseases and chronic periodontitis. The review identified common MMPs polymorphisms in diabetes, CVD, RA and chronic periodontitis and allowed to detect that the most clinically significant polymorphisms such as MMP-3 5A(-1612)6A, MMP-8 C(-799)T and MMP-9 C(-1562)T. The prevalence and significance of MMP polymorphisms in the Ukrainian population have to be explore to determine list of genotyping for prognosis and choice of chronic periodontitis treatment

Forecasting price movements using technical indicators: investigating the impact of varying input window length

The creation of a predictive system that correctly forecasts future changes of a stock price is crucial for investment management and algorithmic trading. The use of technical analysis for financial forecasting has been successfully employed by many researchers. Input window length is a time frame parameter required to be set when calculating many technical indicators. This study explores how the performance of the predictive system depends on a combination of a forecast horizon and an input window length for forecasting variable horizons. Technical indicators are used as input features for machine learning algorithms to forecast future directions of stock price movements. The dataset consists of ten years daily price time series for fifty stocks. The highest prediction performance is observed when the input window length is approximately equal to the forecast horizon. This novel pattern is studied using multiple performance metrics: prediction accuracy, winning rate, return per trade and Sharpe ratio

The trend is our friend: Risk parity, momentum and trend following in global asset allocation

We examine applying a trend following methodology to global asset allocation between equities, bonds, commodities and real estate. This strategy offers substantial improvement in risk-adjusted performance compared to buy-and-hold portfolios and a superior method of asset allocation than risk parity. We believe the discipline of trend following overcomes many of the behavioural biases investors succumb to, such as regret and herding, and offers a solution to the inappropriate sequence of returns which can be problematic for decumulation portfolios. The other side of behavioural biases is that they may be exploited by investors: an example is momentum investing where herding leads to continuation of returns and has been identified across many assets. Momentum and trend following differ as the former is a relative concept and the latter absolute. Combining both can achieve the higher return levels associated with momentum portfolios with much reduced volatility and drawdowns due to trend following. Measures based on utility of a representative investor reinforce the superiority of combining trend following with momentum strategies. These techniques help address the sequencing of returns issue which can be a serious issue for financial planning

Technical trading and cryptocurrencies

This paper carries out a comprehensive examination of technical trading rules in cryptocurrency markets, using data from two Bitcoin markets and three other popular cryptocurrencies. We employ almost 15,000 technical trading rules from the main five classes of technical trading rules and find significant predictability and profitability for each class of technical trading rule in each cryptocurrency. We find that the breakeven transaction costs are substantially higher than those typically found in cryptocurrency markets. To safeguard against data-snooping, we implement a number of multiple hypothesis procedures which confirms our findings that technical trading rules do offer significant predictive power and profitability to investors. We also show that the technical trading rules offer substantially higher risk-adjusted returns than the simple buy-and-hold strategy, showing protection against lengthy and severe drawdowns associated with cryptocurrency markets. However there is no predictability for Bitcoin in the out-of-sample period, although predictability remains in other cryptocurrency markets