Analysis of Bitcoin prices using market and sentiment variables

This paper proposes an empirical model for analysing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010–17 and 2010–19. Price discovery is achieved through the Gonzalo–Granger permanent‐transitory decomposition. The pricing factors are endogenous linear combinations of the S&P 500 index, gold price, a Google search variable associated to Bitcoin and a fear index proxied by the FED Financial Stress Index. Our empirical analysis shows that during the first period, a linear combination of four pricing factors describes the efficient Bitcoin price. The S&P 500 index and Google searches have a positive effect whereas gold prices and the fear index have a negative effect. In contrast, during the second period, the efficient price behaves idiosyncratically and can be only rationalised by individuals' search for information on the cryptocurrency. These findings provide empirical evidence on the presence of a correction in Bitcoin prices during the period 2018–19 uncorrelated to market fundamentals. We also show that standard empirical asset pricing models perform poorly for explaining Bitcoin prices.     

Many a little makes a mickle: Why do consumers negatively react to sequential price disclosure?

Drip pricing (DP) is distinct from partitioned pricing as it sequentially discloses surcharges to consumers. Critics see DP as a deceptive pricing tactic because it obscures the final price of an offer. We examine the effects of the timing of the final price disclosure and the number of sequentially presented surcharges on consumers' attention to the final price and, ultimately, perceived price fairness. In an eye‐tracking study with 225 participants, we find that the sequential (vs. up‐front) disclosure of the final price lowers perceived price fairness by increasing consumers' attention to the final price, in particular, when the number of surcharges is high. In addition, the sequential disclosure of the final price lowers perceived price fairness because of higher perceived price complexity and lower pricing transparency perceptions. The findings suggest that firms need to be aware of both attentional and cognitive effects of the final price disclosure when designing DP.     

What determines the long-term correlation between oil prices and exchange rates?

In this study, we obtain the long-term correlation between oil prices and exchange rates by employing the dynamic conditional correlation-mixed data sampling (DCC-MIDAS) model. We then identify the factors that influence the long-term correlation using panel data analysis. We find that the long-run correlations between oil prices and exchange rates are negative for all oil-exchange rate markets except Japan. We also find that both inflation and term spread have negative effects, while the risk-free interest rate has a positive effect on the long-term correlation between oil prices and exchange rates. Importantly, the empirical results show that an increase in inflation will significantly damage the real value of the currency itself.     

中国国有企业改革：经验、困境与出路*

作为国有企业产权改革主要模式，“混合所有制”改革是否有助于确保国有资产保值增值，是否有助于推动中国经济可持续发展等问题仍存在探讨空间。本文基于对于改革开放以来中国国有企业改革的成就和教训的考察，指出“混合所有制”可以作为竞争性部门国有企业改革的一个过渡形式；对于垄断央企的改革应该充分借鉴国际上自然垄断行业的改革经验，打破行政垄断，推动竞争性框架建立，并切实实现从“管企业”逐步调整为“管资本”，通过改革实现国有资产的保值增值，并为经济创造新的增长点。     

Cost Analysis of Calcium in Store Brand versus National Brand Grocery Products

Objective: This study was to determine if calcium fortification yields a higher price per serving in grocery store products. Researchers compared store brand to national brand grocery products in relation to cost in order to examine if calcium values were similar between store brand and national brand products. Methods: A total of 112 store brand and 211 national brand grocery products were collected from three low (national chain store), middle and high priced (Virginia and North Carolina regional store) grocery venues. Products were compared using price and calcium percentage per serving. ANOVA was used to determine between store brand and national brand for price per serving and calcium content, and between grocery venues. Results: National brand fortified products had a significantly lower mean price per serving when compared to national brand non-fortified products (p = 0.0002). There was no statistical difference between store brand fortified and non-fortified products (p = 0.9256). Low priced store brand products had the lowest mean price per serving ($0.34 ±0.24). Conclusions: This study found store brand products have similar calcium content as national brand products. Product cost was lower at low priced store compared to middle and high priced stores.     

How Fast are Semiconductor Prices Falling?

The Producer Price Index (PPI) for the U.S. suggests that semiconductor prices have barely been falling in recent years, a dramatic contrast to the rapid declines reported from the mid‐1980s to the early 2000s. This slowdown in the rate of decline is puzzling in light of evidence that the performance of microprocessor units (MPUs) has continued to improve at a rapid pace. Over the course of the 2000s, the MPU prices posted by Intel, the dominant producer of MPUs, became much stickier over the chips' life cycle. As a result of this change, we argue that the matched‐model methodology used in the PPI for MPUs likely started to be biased after the early 2000s and that hedonic indexes can provide a more accurate measure of price change since then. MPU prices fell rapidly through 2004 on every price measure we present, with the PPI declining at an even quicker pace than the hedonic indexes. However, from 2004 to 2009, our preferred hedonic index fell faster than the PPI, and from 2009 to 2013 the gap widened further, with our preferred index falling at an average annual rate of 42 percent, while the PPI declined at only a 6 percent rate. Given that MPUs currently represent about half of U.S. shipments of semiconductors, this difference has important implications for gauging the rate of innovation in the semiconductor sector.     

Forecasting using heterogeneous panels with cross-sectional dependence

In this paper, we focus on forecasting methods that use heterogeneous panels in the presence of cross-sectional dependence in terms of both spatial error dependence and common factors. We propose two main approaches to estimating the factor structure: a residuals-based approach, and an approach that uses a panel of auxiliary variables to extract the factors. Small sample properties of the proposed methods are investigated through Monte Carlo simulations and applied to predict house price inflation in OECD countries.     

The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning

Whether investor sentiment affects stock prices is an issue of long-standing interest for economists. We conduct a comprehensive study of the predictability of investor sentiment, which is measured directly by extracting expectations from online user-generated content (UGC) on the stock message board of Eastmoney.com in the Chinese stock market. We consider the influential factors in prediction, including the selections of different text classification algorithms, price forecasting models, time horizons, and information update schemes. Using comparisons of the long short-term memory (LSTM) model, logistic regression, support vector machine, and Naïve Bayes model, the results show that daily investor sentiment contains predictive information only for open prices, while the hourly sentiment has two hours of leading predictability for closing prices. Investors do update their expectations during trading hours. Moreover, our results reveal that advanced models, such as LSTM, can provide more predictive power with investor sentiment only if the inputs of a model contain predictive information.     

Fiscal and monetary interdependence

Where classical economics integrates the quantity theory of money with the concept of Ricardian equivalence, the tendency of recent macroeconomic presentations is to focus either upon money and inflation or upon taxation and debt. That neglect of classical monetary–fiscal integration is surprising, given an initiative by the International Monetary Fund that set credit, money, and fiscal policy within a single structure. This article places those ‘credit counterparts of broad money’ in the context of the Great Depression and the recent global financial crisis. The upshot is a set of conclusions: that, to counter the prospect of deflation, quantitative easing is a weak policy response; that fiscal deficits are better; and that cuts in taxation are preferable to increased government spending.     

Credit risk pricing and the rationality of lending decision-making within dual banking systems: A parametric approach

The reduction of non-performing loans, and making correct provisions for them, plays a primary role in the management and minimization of banking credit risk. However, these actions depend primarily upon the cost at which banks may dispose of these bad loans. Hence, this study aims to perceive the price of banks’ credit risk via estimating the shadow price of non-performing loans. We assess and compare the perceived price of the credit risk of Islamic and conventional banks operating in 9 countries from the Middle East and Asia, using a quadratic directional distance function. Following this, we evaluate the impact of different settings of directional vectors on shadow prices by conducting a risk-sensitivity analysis. Applying bootstrap regression, the factors affecting NPLs’ prices are further investigated. The paper concludes that the estimation of the shadow prices of bad loans can provide important elements in favor of credit risk management and, therefore, credit risk mitigation.