Determinants of European stock market integration

We analyse the determinants of stock market integration among EU member states for the period 1999–2007. First, we apply bivariate DCC-MGARCH models to extract dynamic conditional correlations between European stock markets, which are then explained by interest rate spreads, exchange rate risk, market capitalisation, and business cycle synchronisation in a pooled OLS model. By grouping the countries into euro area countries, “old” EU member states outside the euro area, and new EU member states, we also evaluate the impact of euro introduction and the European unification process on stock market integration. We find a significant trend toward more stock market integration, which is enhanced by the size of relative and absolute market capitalisation and hindered by foreign exchange risk between old member states and the euro area. Interest rate spreads and business cycle synchronisation are also significant factors in explaining equity market integration.     

Is Bitcoin a better hedging and safe-haven investment than traditional assets against currencies? Evidence from the time-frequency domain approach

Many studies have discussed hedges and safe havens against stocks, but few studies focus on the hedging/safe-haven performance of assets against the currency market over different time horizons. This paper studies the connectedness, hedging and safe-haven properties of Bitcoin/gold/crude oil/commodities against six currencies across multiple investment horizons, placing a particular focus on the performance of these assets during the recent COVID-19 outbreak. Our findings suggest that the overall dependence between assets and the currency market is the strongest in the short term, and Bitcoin is the least dependent across all investment horizons. The dynamic relationships between the four assets and the currency market vary with timescales. Bitcoin offers better hedging capability in the long term and commodities emerge as the most favorable option for the optimal portfolio of currency over all time horizons. Further analysis shows that assets are better at helping investments reduce risk in the initial stages of the pandemic, and gold is an effective and robust safe haven for currencies.     

Hoarding international reserves versus a Pigovian tax-cum-subsidy scheme: Reflections on the deleveraging crisis of 2008-2009, and a cost benefit analysis

We outline the case for supporting self-insurance by imposing a tax on external borrowing in a model of an emerging market. Entrepreneurs finance tangible investments via bank intermediation of foreign borrowing, exposing the economy to negative fire-sale externalities at times of deleveraging; a risk that increases with the ratio of aggregate external borrowing to international reserves. Price taking economic agents ignore their marginal impact on the expected cost of a deleveraging crisis. The optimal borrowing tax reduces the distorted activity, external borrowing, and induces borrowers to co-finance the precautionary hoarding of international reserves.     

The risk spillover between China’s economic policy uncertainty and commodity markets: Evidence from frequency spillover and quantile connectedness approaches

Based on the frequency spillover method extended by Baruník and Křehlík (2018), we explore the risk spillover relationship between China’s economic policy uncertainty (CNEPU) and commodity futures in different frequency domains with daily settlement price data of 14 commodity futures in China. The results show that the risk spillover relationship between CNEPU and the commodity market mainly occurs in the short term. Quantile connectedness results show that economic policy uncertainty, which mainly plays the role of risk transmitter, is more closely related to the commodity market during the market boom and recession. Soybeans, soybean meal, and corn have shown high investment value in the process of market recovery, which is exposed to less risk spillover from policy uncertainty. Finally, the economic crisis with different characteristics will have specific impacts on asymmetric risk spillovers based on certain impact mechanisms.     

How Do Alphas and Betas Move? Uncertainty,Learning and Time Variation in Risk Loadings*

I employ a parsimonious model with learning, but without conditioning information, to extract time‐varying measures of market‐risk sensitivities, pricing errors and pricing uncertainty. The evolution of these quantities has interesting implications for macroeconomic dynamics. Parameters estimated for US equity portfolios display significant low‐frequency fluctuations, along patterns that change across size and book‐to‐market stocks. Time‐varying betas display superior predictive accuracy for returns against constant and rolling‐window OLS estimates. As to the relationship of betas with business‐cycle variables, value stocks’ betas move pro‐cyclically, unlike those of growth stocks. Investment growth, rather than consumption, predicts the betas of value and small‐firm portfolios.     

Examining macroeconomic models through the lens of asset pricing

We develop new methods for representing the asset-pricing implications of stochastic general equilibrium models. We provide asset-pricing counterparts to impulse response functions and the resulting dynamic value decompositions (DVDs). These methods quantify the exposures of macroeconomic cash flows to shocks over alternative investment horizons and the corresponding prices or investors’ compensations. We extend the continuous-time methods developed in Hansen and Scheinkman (2012) and Borovi?ka et al. (2011) by constructing discrete-time, state-dependent, shock-exposure and shock-price elasticities as functions of the investment horizon. Our methods are applicable to economic models that are nonlinear, including models with stochastic volatility.     

The method of simulated quantiles

We introduce the Method of Simulated Quantiles, or MSQ, an indirect inference method based on quantile matching that is useful for situations where the density function does not have a closed form and/or moments do not exist. Functions of theoretical quantiles, which depend on the parameters of the assumed probability law, are matched with the sample counterparts, which depend on the observations. Since the theoretical quantiles may not be available analytically, the optimization is based on simulations. We illustrate the method with the estimation of α$\alpha$-stable distributions. A thorough Monte Carlo study and an illustration to 22 financial indexes show the usefulness of MSQ.     

Relating Macro-economic Efficiency to Financial Efficiency: A Comparison of Fifteen OECD Countries Over an Eighteen Year Period

This paper examines the role of the banking sector in the overall economic activity and its contribution to the convergence/divergence in fifteen OECD countries over the time period of 1980–1997. We resort to a non-parametric technique (DEA) and estimate a world wide macro-economic as well as a worldwide banking frontier. We find a very similar pattern in the evolution of banking and macro-economic efficiency. We further study the evolution of the macro-economic and banking productivity and discover, in both cases, convergence over time. Our first finding is that the performance of the banking sector helps to explain the overall economic performance. Our second finding is that the financial orientation of each country constitutes a relevant feature for the last mentioned explanation.