This paper deals with the impact of macroeconomic fundamentals on Lithuanian government securities' prices using quarterly data for the period 2000-2013, applying five major macroeconomic variables: gross domestic product, consumer prices, interest rates, money supply, and foreign direct investment. The two main goals of the paper are: 1) to identify macroeconomic variables which are the main driving forces behind debt security prices and 2) due to the lack of sufficient data on the Lithuanian government security index, to create and calculate a similar index from the primary and secondary market sovereign security prices. The research has been conducted using the methods of descriptive statistics, the vector autoregression model, the impulse response function, and the forecast error variance decomposition. The paper finds that, when consumer prices or interest rate rise up, sovereign security prices decline significantly and, on the other hand, money supply is the only factor that significantly and directly influences the government security prices. However, the effects of the gross domestic product and foreign direct investment were found to be statistically insignificant. Finally, the government security index is inert and rarely changes its long-term trend. These conclusions provide related persons with rich information in establishing the investment strategy or fiscal / monetary policy.

Abstract. The central bank community has been split into those who started to employ negative interest rates (NIR) and those who do not intend to do so

The purpose of this paper is to determine the factors that shape the liquidity levels of euro area sovereign bonds. The values of liquidity measure and explanatory variables were calculated from the limitorder book dataset for almost five hundred bonds from six largest euro area sovereign bond markets. The created variables were used in a cross-sectional regression model. The results revealed that characteristics of sovereign bonds are indeed highly linked with bond liquidity levels, and these effects become even stronger during the regimes of lower market liquidity. Contrary to the statements of market participants and findings of many other studies, the magnitude of trading automation and obligatory requirements imposed on dealers were found to be negatively linked with the liquidity level of sovereign bonds.

The purpose of this paper is to determine the long-run causal impact of various economic factors on Lithuanian stock, government securities and real estate prices, and to assess how accurately future asset returns can be forecasted based solely on economic information. Five macroeconomic indicators, namely, gross domestic product (GDP), foreign direct investment (FDI), consumer price index (CPI), money supply (MS) and Vilnius interbank offered rate (VILIBOR), were included in the model. The results of the created autoregressive distributed lag model (ARDL) revealed that a long-run causal relationship between Lithuanian assets and macroeconomic variables exists and that changing values of these indicators explain about half of the variability of assets’ returns. The results of ARDL model forecast showed that the most precise predictions are obtainable in real estate market, while forecasted returns of stock and government securities are not so accurate, especially the further forecast horizon. The possibility to understand driving factors behind changes of asset prices and to predict future return is of a particular importance not only for investors and businessmen, but also for the policy makers who are responsible for making substantiated decisions regarding monetary, macroprudential and fiscal policies they conduct.

The purpose of this paper is to determine the liquidity spillover effects of trades executed in European sovereign bond markets and to assess the driving factors behind the magnitude of the spill-overs between different markets. The one minute-frequency limit order-book dataset is constructed from mid-2011 until end-2017 for sovereign bonds from the six largest euro area countries. It is used for the event study and panel regression model. The event study results revealed that liquidity spill-over effects of trades exist and vary highly across different order types, direction and size of the trade, the maturity of traded bonds, and various markets. The panel regression model showed that less liquid bonds and bonds whose issuer is closer by distance to the country of the traded bond have more substantial spillover effects and, at the same time, are also more affected by trades executed in another market. These results should be of interest to bond market participants who want to limit the exposure to the liquidity spillover risk in bond markets.