Financial System and Housing Price

The 2007/2008 US financial crisis is related to the securitization of mortgage loans and the housing-price boom and bust. In this article, we test the hypothesis that housing-price change is related to the development of the financial system. Using panel data for 23 countries from 1988 to 2012, we have found that the housing-price growth rate increases as the financial system moves a bank orientation to a market orientation. The policy implication is that the government should beware sudden increases in the capital market relative to the banking sector. Especially, more sophisticated financial supervision with respect to housing-price movement is required when a bank-based financial system progresses quickly to a market-oriented financial system.     

A Multiple and Partial Wavelet Analysis of the Oil Price,Inflation, Exchange Rate,and Economic Growth Nexus in Saudi Arabia

This article provides a fresh insight into the dynamic nexus between oil prices, the Saudi/US dollar exchange rate, inflation, and output growth rate in Saudi Arabia’ economy, using novel Morlet’ wavelet methods. Specifically, it implements various tools of methodology: the continuous wavelet power spectrum, the cross-wavelet power spectrum, the wavelet coherency, the multiple and the partial wavelet coherence to the annual sample period 1969–2014. Our results unveil that the relationships among the variables evolve through time and frequency. From the time-domain view, we show strong but non-homogenous linkages between the four variables. From the frequency-domain view, we uncover significant wavelet coherences and strong lead-lag relationships. From an economic view, the wavelet analysis shows that Saudi economy is still exposed to several global risk factors, which are mainly related to the oil market volatility, and the pegging of the local currency to the US dollar. Such risk factors strongly and negatively affect the real economic growth, exert more pressure on inflation, and substantially limit the freedom to pursue an independent monetary policy.     

The Effects of Oil Price on the Korean Economy: A Global VAR Approach

This article empirically explores the effects of oil price on the Korean economy using a Global VAR model. First, we evaluate the average connectedness of oil price with the Korean domestic variables over the precrisis period. We then investigate the time-varying contribution of oil price to the Korean financial and real sectors during and after the global financial crisis through recursive estimation. It is found that the contribution of oil price becomes very large in the case of real exports, equity prices, and real output, but plays a much less prevalent role in the remaining cases. In the meantime, the time-varying contribution of oil price to the Korean economy has not changed during and after the global financial crisis. Interestingly, we find that the Korean economy is affected mostly by overseas financial conditions in the short-term but it becomes more susceptible to oil price fluctuations in the long run, suggesting that Korea’s reliance on energy imports leaves the economy exposed to volatility in energy prices.     

On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks

Daily and weekly seasonalities are always taken into account in day-ahead electricity price forecasting, but the long-term seasonal component has long been believed to add unnecessary complexity, and hence, most studies have ignored it. The recent introduction of the Seasonal Component AutoRegressive (SCAR) modeling framework has changed this viewpoint. However, this framework is based on linear models estimated using ordinary least squares. This paper shows that considering non-linear autoregressive (NARX) neural network-type models with the same inputs as the corresponding SCAR-type models can lead to yet better performances. While individual Seasonal Component Artificial Neural Network (SCANN) models are generally worse than the corresponding SCAR-type structures, we provide empirical evidence that committee machines of SCANN networks can outperform the latter significantly.     

A novel cluster HAR-type model for forecasting realized volatility

This paper proposes a cluster HAR-type model that adopts the hierarchical clustering technique to form the cascade of heterogeneous volatility components. In contrast to the conventional HAR-type models, the proposed cluster models are based on the relevant lagged volatilities selected by the cluster group Lasso. Our simulation evidence suggests that the cluster group Lasso dominates other alternatives in terms of variable screening and that the cluster HAR serves as the top performer in forecasting the future realized volatility. The forecasting superiority of the cluster models are also demonstrated in an empirical application where the highest forecasting accuracy tends to be achieved by separating the jumps from the continuous sample path volatility process.     

The effect of permanent product discounts and order coupons on purchase incidence,purchase quantity,and spending

This paper examines the influence of a permanent discount strategy on customer purchase behavior, i.e., purchase incidence in each week, purchase quantity (in units), and total order spending (in CNY). Permanent discounts are defined as discounts continuously provided by retailers. We identify two types of permanent discounts, namely, product-specific price discounts (PD) and order coupons (OD, which can be redeemed for a total order). We collect transactional data from a Chinese online retailer and empirically examine the effects of the two types of permanent discounts and customers’ expectations of PD and OD. We find nonlinear relationships between permanent discounts and customer purchase behavior. PDs negatively influence spending when they are lower than 19% but show a positive effect beyond this threshold, hence depicting a U-shaped relationship. They also affect purchase quantity positively but at a decreasing rate. Customer expectations of PD influence purchase incidence, spending, and purchase quantity following a U-shaped patter with a positive influence appearing when PD expectations are high than 31%, 27%, and 18% respectively. On the other hand, ODs influence spending and purchase quantity positively at an increasing rate. Customer expectations of OD influence purchase incidence, spending, and purchase quantity following a U-shaped relationship where the positive influence on purchase incidence shows beyond OD expectations of 426 CNY, and the positive effect appearing on spending and purchase quantity when these expectations are higher than 34 CNY. We also find that customer expectations of discounts interact with current discount levels in their influence on spending. Combining these results and considering that order coupons negatively affect the profit margin of the total basket, we suggest that retailers should offer order coupons with relatively low value but product-specific price discounts with high discount depth.     

Intraday bidirectional volatility spillover across international stock markets: does the global financial crisis matter?

This article studies volatility spillover between the US and the three largest European stock markets (Frankfurt, London and Paris) around the time of the recent Subprime crisis. In order to investigate the impact of the latter, we break our sample down into two sub-periods: a pre-crisis period and a post-crisis period, using a structural break test that has the advantage of endogenously testing for further breaks in the data. Unlike previous studies that have frequently investigated this issue using low frequency data, our article makes use of intraday data. Accordingly, using Threshold generalized autoregressive conditional heteroscedasticity (GARCH) model estimations, we find weak evidence of volatility transmission between the two regions before the Subprime crisis. However, during the post-crisis period, we record returns and volatility spillover from US to European markets and vice versa at different times of the trading day, indicating that the two regions became more dependent during the recent Subprime crisis, a finding that supports the contagion hypothesis between the US and European stock markets.     

Price Discrimination with Private and Imperfect Information

In this paper, I investigate the competitive and welfare effects of the improvements in information accuracy in markets where firms can price discriminate after observing a private and noisy signal about a consumer's brand preference. I show that when firms believe that consumers have a brand preference for them, then they charge more to these consumers, and this price has an inverse U‐shaped relationship with the signal's accuracy. In contrast, the price charged after a disloyal signal has been observed falls as the signal's accuracy rises. While industry profit and overall welfare fall monotonically when price discrimination is based on increasingly more accurate information, the reverse happens to consumer surplus.     

Oil price shocks and American depositary receipt stock returns

In this paper we examine the impact of oil price shocks on twelve countries American Depositary Receipt (ADR) returns using monthly data from 1999.01 to 2014.12. The results show that oil price shocks have a positive and statistically significant impact on ADR return in all twelve countries. These results are robust to the inclusion of other explanatory variables such as oil price volatility and the spillover of the United States stock market. Further analysis shows that this effect is stronger in the post financial crisis time period compared to the pre-financial crisis time period.