Diversification and risk-adjusted performance: A quantile regression approach

The effect of diversification on firm performance has been debated. We reexamine the effect using a sample of 44,248 observations of non-financial US firms for the 1997–2009 period employing the quantile regression approach. Our empirical results show that the effect of diversification on firm performance is not homogeneous across various quantile levels: the diversification discount (premium) shows up in firms with high (low) RoE quantiles. Further, we find that diversification affects firm risk as well. Therefore, we consider a risk-adjusted performance measure and find that both diversification discount and premium disappear, which is consistent with the risk-return trade-off principle.     

Financialization and de-financialization of commodity futures: A quantile regression approach

This study employs a quantile regression approach to examine the financialization of commodity futures. We confirm a strong degree of dependence in energy commodities from 2004 to 2013, with moderate effects in metals and lesser magnitudes in agriculture. Our findings show a strengthening in the financialization of energy commodities during the 2008–2009 global financial crisis, while there were weaker effects in agriculture and a decoupling or de-financialization in metal markets. The findings reveal the de-financialization of metals and agricultural markets from 2014 to 2017, after the 2013 closure of commodity trading units on Wall Street. Overall, our findings cast doubt on the diversification benefits of energy-dominated commodity indices after 2013. We argue the impact of financialization on commodity futures markets is more permanent than previously thought.     

The structure and degree of dependence: A quantile regression approach

The copula function defines the degree of dependence and the structure of dependence. This paper proposes an alternative framework to decompose the dependence using quantile regression. We demonstrate that the methodology provides a detailed picture of dependence including asymmetric and non-linear relationships. In addition, changes in the degree or structure of dependence can be modeled and tested for each quantile of the distribution. The empirical part applies the framework to three different sets of financial time-series and demonstrates substantial differences in dependence patterns among asset classes and through time. The analysis of 54 global equity markets shows that detailed information about the structure of dependence is crucial to adequately assess the benefits of diversification in normal times and crisis times.     

Demand for international reserves in developing nations: A quantile regression approach

I estimate the determinants of the demand for international reserves using quantile regressions. Employing a dataset of 108 developing nations over the period of 1980-2007, I find considerable differences at different points of the conditional distribution of reserves. The estimates of elasticities that were found to be insignificant in ordinary least squares regressions become statistically significant at various quantiles of the distribution. Furthermore, majority of the explanatory variables have lower coefficients for the nations that are located on the right tail of the conditional reserve distribution. This finding shows that the level of reserves is as important as the other determinants of the demand for reserves.     

Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach

We construct the complete network of tail risk spillovers among major cryptocurrencies using the Least Absolute Shrinkage and Selection Operator (LASSO) quantile regression. We capture important features of the network, including major risk-driving and major risk-receiving currencies, and the evolution of the tail dependence among the currencies over time. Importantly, we reveal a striking finding that the right tail dependence among the cryptocurrencies is significantly stronger than the left tail counterpart. This unique characteristic may have contributed to the rise in popularity of cryptocurrencies over the last few years. Our portfolio analysis reveals that diversification in cryptocurrency investment can be accomplished simply by employing the naïve equal-weighted scheme even when transaction costs are taken into account.     

Does investor sentiment predict bitcoin return and volatility? A quantile regression approach

The study investigates hypotheses relating to the effect of investor sentiment on predicting bitcoin returns and volatility. Using moments quantile regression, we present robust empirical evidence for the period 2017–2021. Our findings demonstrate that investor interest and emotions are significant predictors of bitcoin returns and volatility, while VIX and Bitcointalk.org forum are the most suitable predictors for representing investor emotions and interest, respectively. The findings also indicate a nonlinear relationship between investor sentiment and bitcoin returns and volatility, with predictable power changing based on the market conditions. Thus, the study enriches existing literature by providing empirical evidence to affirm the viability of behavioral finance theories in the bitcoin market and complements investors with more information to seek profits in different market conditions.     

The relationship between stock price index and exchange rate in Asian markets: A quantile regression approach

This paper uses the data of six Asian countries to estimate the relationship between stock price index and exchange rate. According to the portfolio balance effect, these two variables should be negatively related. However, since the evidence from traditional ordinary least squares estimation is not favorable, the quantile regression model is adopted to observe the various relationships between stock and foreign exchange markets. The results show an interesting pattern in the relation of these two markets in Asia, which indicates that the negative relation between stock and foreign exchange markets is more obvious when exchange rates are extremely high or low.     

Equilibrium model with default and dynamic insider information

We consider an equilibrium model à la Kyle–Back for a defaultable claim issued by a given firm. In such a market the insider observes continuously in time the value of the firm, which is unobservable by the market makers. Using the construction in Campi et al. (http://hal.archives-ouvertes.fr/hal-00534273/en/, 2011) of a dynamic three-dimensional Bessel bridge, we provide the equilibrium price and the insider’s optimal strategy. As in Campi and Çetin (Finance Stoch. 11:591–602, 2007), the information released by the insider while trading optimally makes the default time predictable in the market’s view at the equilibrium. We conclude the paper by comparing the insider’s expected profits in the static and dynamic private information case. We also compute explicitly the value of the insider’s information in the special cases of a defaultable stock and a bond.     

Testing the inflation rates in MENA countries: Evidence from quantile regression approach and seasonal unit root test

We investigate the dynamic behavior and seasonal property (with regime shift) of inflation in the Middle East and North Africa (MENA) countries. Our investigation uses the quantile regression approach developed by Koenker and Xiao (2004) and the newly developed seasonal unit root test of Narayan and Popp (2011) respectively. Our empirical results show that the inflation rates are not mean-reverting, and they show the asymmetries in their dynamic adjustment. Further, we find a seasonal unit root does not exist in the inflation rate for any country in this study. This finding implies that shocks do not have lasting effects on the inflation rate.     

On the volatility spillover between lslamic and conventional stock markets: A quantile regression analysis

This paper aims at analyzing the degree and structure of interdependencies in terms of volatility (transmission, contagion) between Islamic and conventional stock markets on calm periods and at times of financial fragility and crisis. We focused on the recent financial instability periods and used the Quantile Regression-based GARCH model. Main results lead to very interesting conclusions. First, it has been found that Islamic stock markets are not totally immune to the global financial crisis. Second, a very strong interdependence is sensed from the conventional to the Islamic stock markets, especially, from the conventional developed markets to the Islamic Emerging and Arab markets and to the Islamic developed markets. Finally, it has been proved that the interdependencies from conventional to Islamic markets are propagated between Islamic markets. Our findings suggest that the Islamic finance industry does not seem able to provide cushion against economic and financial shocks that affect conventional markets.     

Monetary environments and stock returns: International evidence based on the quantile regression technique

This paper investigates the impact of the local and the US monetary policy environments on stock returns at the different locations on the return distributions. Using data for stock returns and interest rates of 30 countries, the quantile regression technique is employed to estimate the sensitivity of the returns to monetary policy at the different points on the return distributions. The results suggest that higher returns are associated with expansionary monetary policy. Furthermore, some of the stock markets in the sample are found to react to the local, but not the US monetary environments at the lower quantiles while the response at the higher quantiles appears to be sensitive to the US, but not the local monetary conditions. These findings are further supported by the slope equality tests, discussed in Koenker & Bassett (1982), and the analysis of weighted absolute residuals (ANOWAR), proposed by Chen, Ying, Zhang, & Zhao (2008).     

The dynamic effects of monetary policy: A structural factor model approach

A structural factor model for 112 US monthly macroeconomic series is used to study the effects of monetary policy. Monetary policy shocks are identified using a standard recursive scheme, in which the impact effects on both industrial production and prices are zero. The main findings are the following. First, the maximal effect on bilateral real exchange rates is observed on impact, so that the “delayed overshooting” puzzle disappears. Second, after a contractionary shock prices fall at all horizons, so that the price puzzle is not there. Finally, monetary policy has a sizable effect on both real and nominal variables.     

A dynamic model of entrepreneurship with borrowing constraints: theory and evidence

Does wealth beget wealth and entrepreneurship, or is entrepreneurship mainly determined by an individual’s ability? A large literature studies the relationship between wealth and entry to entrepreneurship to inform this question. This paper shows that in a dynamic model, the existence of financial constraints to the creation of businesses implies a non-monotonic relationship between wealth and entry into entrepreneurship: the probability of becoming an entrepreneur as a function of wealth is increasing for low wealth levels—as predicted by standard static models—but it is decreasing for higher wealth levels. U.S. data are used to study the qualitative and quantitative predictions of the dynamic model. The welfare costs of borrowing constraints are found to be significant, around 6% of lifetime consumption, and are mainly due to undercapitalized entrepreneurs (intensive margin), rather than to able people not starting businesses (extensive margin).     

Optimization of a firm's capital structure: A quantitative approach based on a probabilistic prognosis of risk and time of bankruptcy

This article develops a new probabilistic approach to the problem of optimization of a firm's capital structure. The main idea of the approach is straightforward. As a possible firm's bankruptcy is the principal factor restricting the amount of borrowed capital, we assess the probabilities of bankruptcy at various time horizons in the future dependent on the proportion of debt capital and other indices of a firm's current financial position and then calculate how these probabilities influence the firm's value.We identify a set of factors determining conditions of existence and the value of the optimal debt/equity ratio. These include the characteristics of a firm's debt (proportion of short-term component of the debt, cost of service, and maturity horizons of long-term component), characteristics of a firm's ability to pay the debt, and some macroeconomic factors.We represent dependencies of optimal debt/equity ratio and gains in a firm's value on the main influencing factors.The approach is based on real data of real firms and does not use superfluously formalized models. We believe it can be used in practical capital structure decisions although specific calculations must be fulfilled for each firm that needs such decision.     

Integrating XBRL data with textual information in Chinese: A semantic web approach

Due to formatting differences, the difficulties of processing the textual disclosures and integrating them with quantitative financial data are well documented in the literature. Using a design science methodology, this paper describes a method that automatically extracts relevant textual data from annual reports published in Chinese. These extracted words are then mapped to a knowledge framework we proposed. This paper shows that it is technologically feasible to reorganize the MD&A contents into any given knowledge structure to improve the search capability, readability, and cohesiveness of the MD&A contents. Finally, we demonstrate a prototype system that uses semantic web technology to achieve information integration that presents XBRL formatted accounting data with relevant textual disclosures together to assist user decision making.     

A New Zealand failure prediction model: Development and international implications

In this study we develop a failure prediction model for New Zealand listed companies and theorise on the usefulness and international implications of the results. In developing the model, we obtained data from 60 failing and 60 matched non failing New Zealand listed companies, providing an unusually rich database for model development. Binary logistic regression (logit) was applied on 21 potentially significant variables. The predictive strength was tested using holdout tests, with support from applications to more recent company data. Multicollinearity was minimised through a theoretically informed selection of variables, the Pearson correlation and stepwise regression. The resulting model is significant to 91.7% overall, which tested well for prediction and non-multicollinearity, and reveals a unique combination of variables. We conclude by considering the research implications of small-market model development, and the benefits of local, contextually-based models as evidenced by the results of this study.     

Financial distress and the Malaysian dual baking system: A dynamic slacks approach

This paper presents an efficiency assessment of the Malaysian dual banking system using the Dynamic Slacks Based Model (DSBM) in order to assess the evolution of Malaysian Banks’ potential input–saving/output–increase from 2009 to 2013. More precisely, DSBM is used first in a two-stage approach to assess the relative efficiency of Malaysian Islamic and conventional banks by emulating the CAMEL rating systems. Then, in the second stage, Monte Carlo Markov Chain (MCMC) methods applied to generalized linear mixed models (GLMM) are combined with DSBM results as part of an attempt to produce a model for banking performance assessment with effective predictive ability. Results indicate higher inefficiency levels and slacks in Islamic banks when compared to conventional ones. Furthermore, when the scope of analysis is the group of Malaysian Islamic banks, the efficiency levels of foreign banks are lower compared to their national counterparts, suggesting regulatory and cultural barriers. Policy implications are derived.     

A model of returns for the post-credit-crunch reality: hybrid Brownian motion with price feedback

Recent market events have reinvigorated the search for realistic return models that capture greater likelihoods of extreme movements. In this paper we model the medium-term log-return dynamics in a market with both fundamental and technical traders. This is based on a trade arrival model with variable size orders and a general arrival-time distribution. With simplifications we are led in the jump-free case to a local volatility model defined by a hybrid SDE mixing both arithmetic and geometric or CIR Brownian motions, whose solution in the geometric case is given by a class of integrals of exponentials of one Brownian motion against another, in forms considered by Yor and collaborators. The reduction of the hybrid SDE to a single Brownian motion leads to an SDE of the form considered by Nagahara, which is a type of ‘Pearson diffusion’, or, equivalently, a hyperbolic OU SDE. Various dynamics and equilibria are possible depending on the balance of trades. Under mean-reverting circumstances we arrive naturally at an equilibrium fat-tailed return distribution with a Student or Pearson Type~IV form. Under less-restrictive assumptions, richer dynamics are possible, including time-dependent Johnson-SU distributions and bimodal structures. The phenomenon of variance explosion is identified that gives rise to much larger price movements that might have a priori been expected, so that ‘25σ’ events are significantly more probable. We exhibit simple example solutions of the Fokker–Planck equation that shows how such variance explosion can hide beneath a standard Gaussian facade. These are elementary members of an extended class of distributions with a rich and varied structure, capable of describing a wide range of market behaviors. Several approaches to the density function are possible, and an example of the computation of a hyperbolic VaR is given. The model also suggests generalizations of the Bougerol identity. We touch briefly on the extent to which such a model is consistent with the dynamics of a ‘flash-crash’ event, and briefly explore the statistical evidence for our model.