Lukasz T. Gatarek

Information Flows around the Globe: Predicting Opening Gaps from Overnight Foreign Stock Price Patterns

In a closed circuit moving blade cooled turbine, holes in the radial direction formed in the outer periphery of a second stage wheel are led to cooling air supply holes to second stage moving blades and to prevent the cooling air from leaking into the junction, the holes in the radial direction and the cooling air supply holes are interconnected and the supply members covering the junction are fit into them. The cooling air after cooling the second stage moving blades is introduced into the collection holes formed in the outer periphery of the spacer via the cooling air collection holes and to prevent the cooling air from leaking into the boundary, the cooling air collection holes and collection holes are interconnected and the collection members covering the boundary are fit into them. To make the sum of minimum sectional areas of the respective paths of the second stage moving blades smaller than the sum of minimum sectional areas of the respective paths of the first stage moving blades, a minimum sectional member is incorporated into the supply member.

Return and Risk of Pairs Trading Using a Simulation-Based Bayesian Procedure for Predicting Stable Ratios of Stock Prices

We investigate the direct connection between the uncertainty related to estimated stable ratios of stock prices and risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one. A simulation-based Bayesian procedure is introduced for predicting stable stock price ratios, defined in a cointegration model. Using this class of models and the proposed inferential technique, we are able to connect estimation and model uncertainty with risk and return of stock trading. In terms of methodology, we show the effect that using an encompassing prior, which is shown to be equivalent to a Jeffreys’ prior, has under an orthogonal normalization for the selection of pairs of cointegrated stock prices and further, its effect for the estimation and prediction of the spread between cointegrated stock prices. We distinguish between models with a normal and Student t distribution since the latter typically provides a better description of daily changes of prices on financial markets. As an empirical application, stocks are used that are ingredients of the Dow Jones Composite Average index. The results show that normalization has little effect on the selection of pairs of cointegrated stocks on the basis of Bayes factors. However, the results stress the importance of the orthogonal normalization for the estimation and prediction of the spread — the deviation from the equilibrium relationship — which leads to better results in terms of profit per capital engagement and risk than using a standard linear normalization.

The relation between sovereign credit default swap premium and banking sector risk in Poland

We investigate causality between returns on sovereign CDSs and bank equities for Poland between 2004 and 2014 to provide evidence on contagion between sovereign and banking sector risk pricing. We find some evidence of contagion from Polish sovereign CDS returns to bank equity returns during the crisis period. We benchmark the results for Poland against a sample ofWestern European countries. We document strong negative correlation between sovereign CDS and bank equity returns for individual countries as well as strong commonality of both sovereign and banking sector risks across different countries. We do not however find a clear pattern of contagion between these two markets across European countries. To further investigate drivers of CDS and bank equity returns, we conduct principal component analysis and we find that first three principal components explain as much as 97% of variation with the third principal component mostly associated with Polandspecific risk.

Optimal Hedging with the Cointegrated Vector Autoregressive Model

We derive the optimal hedging ratios for a portfolio of assets driven by a Cointegrated Vector Autoregressive model (CVAR) with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that allows for the hedges to be cointegrated with the hedged asset and among themselves. We find that the minimum variance hedge for assets driven by the CVAR, depends strongly on the portfolio holding period. The hedge is defined as a function of correlation and cointegration parameters. For short holding periods the correlation impact is predominant. For long horizons, the hedge ratio should overweight the cointegration parameters rather then short-run correlation information. In the infinite horizon, the hedge ratios shall be equal to the cointegrating vector. The hedge ratios for any intermediate portfolio holding period should be based on the weighted average of correlation and cointegration parameters. The results are general and can be applied for any portfolio of assets that can be modeled by the CVAR of any rank and order.