Threshold effect of economic openness on bank risk-taking: Evidence from emerging markets

This paper investigates the non-linear effects of two aspects of economic openness, namely, trade openness and financial openness, on banking system stability. We use a panel of 42 emerging markets from 2000 to 2014 to test whether bank risk-taking behaviour varies with the level of openness. We find that a higher degree of trade openness promotes bank stability linearly. Conversely, the non-linear effect of financial openness on bank risk-taking is evident. When the financial system is not sufficiently open, the impact of financial openness on bank stability is insignificant. However, as the domestic financial market becomes more open, financial openness can help discipline the behaviour of banks, making them more stable. We also find evidence that these effects are transmitted through the market discipline channel. Our findings highlight the importance of strengthening the domestic regulatory framework and transparency as the economy becomes more integrated.     

Valuation of VIX and target volatility options with affine GARCH models

In this paper we propose semiclosed-form solutions, subject to an inversion of the Fourier transform, for the price of VIX options and target volatility options under affine GARCH models based on Gaussian and Inverse Gaussian distributions. We illustrate the advantage of the proposed analytic expressions by comparing them with those obtained from benchmark Monte–Carlo simulations. The empirical performance of the two affine GARCH models is tested using different calibration exercises based on historical returns and market quotes on VIX and SPX options.     

Modelling with flexibility through the business cycle: using a panel smooth transition model to test for the lipstick effect

ABSTRACT

Consumer spending typically declines during periods of economic distress, but observers have noted that lipstick purchases appear to increase during recessions, which is often referred to as the lipstick effect. However, the existence of such effect has remained empirically unconfirmed. Using weekly retail scanner data on lipstick sales from 2006 to 2016 in the United States, we applied a Panel Smooth Transition Regression (PSTR) demand model to test the relationship between economic distress and lipstick sales. This flexible demand specification allows regression coefficients to vary as a function of an exogenous macroeconomic variables and fluctuate asymmetrically, non-linearly, and time-varyingly across an unlimited number of regimes. Empirical results show the income elasticity of demand for lipstick decreased rapidly from 0.31 to 0.05 during the 2007–2009 recession, then slowly rebounded to 0.31 by the second quarter of 2014, thus first empirically confirming the existence of the lipstick effect.     

Policy uncertainty and overseas property purchases: Evidence from China

A political leadership transition occurs in China every five years. This shift in leadership is accompanied by tremendous uncertainty within Chinese society, particularly for the nation's wealthy people. Examining private residential property transaction data in Singapore, this paper reveals that the number of transactions by Chinese mainland buyers increases by half during political transitions that occurred between 1998 and 2013, in comparison to buyers from Malaysia, the US, and Hong Kong.     

How to measure competition in an economy in transition

This paper attempts to find a robust method of measuring competition when firms' operational activities are subject to frictions. The first part theoretically tests the indicative quality of two competition measures, the price‐cost margin (PCM) and the profit elasticity, in a model of monopolistic competition. The second part studies the empirical performance of the indices for a panel of Ukrainian manufacturing firms. This study offers a new approach to measuring profit elasticity that relies on structural estimation of a production function. The estimation methodology retrieves a productivity index that is adjusted to imperfect competition. The proposed method of measuring profit elasticity is found to be robust to frictions, but the PCM and traditional profit elasticity are biased, especially when the intensity of competition is low. Empirical findings show that competition exhibits a significantly positive correlation with aggregate productivity performance, while its impact on firm productivity is nonlinear.     

Nonlinear causality testing with stepwise multivariate filtering: Evidence from stock and currency markets

We examine the spillovers of the US subprime crisis to Asian and European economies and in particular to what extent currency and stock markets have been affected by the crisis. Linear and nonlinear dependencies are detected after pairwise and system-wise causality analysis. A new stepwise multivariate filtering approach is implemented after controlling for conditional heteroskedasticity in the raw data and in VAR/VECM residuals using multivariate GARCH models. Significant nonlinear causal linkages persisted even after the application of GARCH-BEKK, CCC-GARCH and DCC-GARCH modelling. This indicates that volatility effects might partly induce nonlinear causality. Perhaps new short-term asset-pricing models could be developed to explain this stylized fact. These results might also have important implications for hedging, trading strategies and financial market regulation.     

Trends in stock-bond correlations

Previous studies document the existence of long-run trends in comovements in the stock and bond markets. Following these findings, this article examines possible trends in stock-bond return correlations. To this end, we introduce a trend component into a smooth transition regression (STR) model including the multiple transition variables of Aslanidis and Christiansen (2012). The results indicate the existence of significant decreasing trends in stock-bond correlations for many advanced safer countries. In addition, although stock market volatility continues to be an important factor in stock-bond correlations, the short rate and yield spread become only marginally significant once we introduce the trend component. Our out-of-sample analysis also demonstrates that the STR model, including the volatility index and time trend as the transition variables, dominates other models. Furthermore, we find a significant increase in stock-bond correlations for riskier euro countries around the beginning of the euro crisis. Our findings of decreasing and increasing trends in stock-bond correlations can be considered a consequence of the decreasing effects of diversification and more intensive flight-to-quality behaviour that have taken place in recent years and after the euro crisis.     

The information content of implied volatility in developed versus developing FX markets

This article predicts the daily movement of monthly foreign exchange (FX) rate volatility using a linear combination of a time-series model and implied volatilities from options. The focus is on analysing the FX volatilities in three developing economies (the Brazilian real (BRL), the Indian rupee (INR) and the Russian ruble (RUB)) against the US dollar (USD). The empirical exercise utilizes two time-series models, mixed data sampling (MIDAS) and GARCH. The analysis indicates that for both developed and developing economies the predictive power of MIDAS and that of GARCH is comparable. Further on in this article, we will ascertain whether the relationship between realized and implied volatility is fundamentally different in the case of developing economies from that among developed economies. Thus, we compare the pairs USD/BRL, USD/INR and USD/RUB against EURO/USD and USD/Japanese yen to determine the information content and predictive power of implied volatilities. Plots of the MIDAS coefficients show that the volatility is more persistent in developing economies than in developed economies.     

Reserves and cash flows under stochastic retirement

Uncertain time of retirement and uncertain structure of retirement benefits are risk factors for life insurance companies. Nevertheless, classical life insurance models assume these are deterministic. In this paper, we include the risk from stochastic time of retirement and stochastic benefit structure in a classical finite-state Markov model for a life insurance contract. We include discontinuities in the distribution of the retirement time. First, we derive formulas for appropriate scaling of the benefits according to the time of retirement and discuss the link between the scaling and the guarantees provided. Stochastic retirement creates a need to rethink the construction of disability products for high ages and ways to handle this are discussed. We show how to calculate market reserves and how to use modified transition probabilities to calculate expected cash flows without significantly more complexity than in the traditional model. At last, we demonstrate the impact of stochastic retirement on market reserves and expected cash flow in numerical examples.     

A nesting framework for Markov-switching GARCH modelling with an application to the German stock market

In this paper, we establish a generalized two-regime Markov-switching GARCH model which enables us to specify complex (symmetric and asymmetric) GARCH equations that may differ considerably in their functional forms across the two Markov regimes. We show how previously proposed collapsing procedures for the Markov-switching GARCH model can be extended to estimate our general specification by means of classical maximum-likelihood methods. We estimate several variants of the generalized Markov-switching GARCH model using daily excess returns of the German stock market index DAX sampled during the last decade. Our empirical study has two major findings. First, our generalized model outperforms all nested specifications in terms of (a) statistical fit (when model selection is based on likelihood ratio tests) and (b) out-of-sample volatility forecasting performance. Second, we find significant Markov-switching structures in German stock market data, with substantially differing volatility equations across the regimes.