Showing papers in "Studies in Economics and Finance in 2019"

Financial technology: a review of extant literature

Abstract: This paper aims to undertake a thematic review of academic papers on financial technology (FinTech) to identify three broad categories for the purpose of classifying extant literature. The paper summarizes the research and findings in this emerging field. Thereafter, it identifies the gaps and provides directions for further research. Simultaneously, the paper collates technical terms related to FinTech that appear repeatedly in each category and explains them. Finally, the study highlights the lessons that growing FinTech firms and their regulators can learn from the experiences of their counterparts across the globe.,A systematic review of literature consisting of 130 studies (social science research network [SSRN]-29 papers, Scopus-81, other sources-20) on FinTech is carried out in this thematic paper.,This thematic paper divides FinTech into three themes, i.e. financial industry, innovation/technology and law/regulation. The paper suggests that a thorough impact of FinTech on various stakeholders can be understood using three dimensions, namely, consumers, market players and regulatory front. It is noted that FinTech is in its nascent phase and is undergoing continuous development and implementation through product and process innovation, disruption and transformation.,The paper reports that FinTech promises huge potential for further study by various stakeholders in the FinTech industry – from academia to practitioners to regulators.,The paper summarizes lessons that could be of significance for FinTech users, producers, entrepreneurs, investors, policy designers and regulators.,The paper is believed to add value to the understanding of FinTech in light of the emerging threats and opportunities for its various stakeholders.

Corporate social responsibility and bankruptcy

Abstract: This paper aims to examine corporate social responsibility (CSR) and corporate bankruptcy. Specifically, the authors ask the following research questions: Does CSR play a role in determining the likelihood of bankruptcy? Does CSR explain the difference in the probability of that firm eventually reorganizing and emerging from bankruptcy?,The authors address these questions by testing three CSR theories using a sample of 78 firms that filed for Chapter 11 bankruptcy during the period 2007 to 2014 along with a matched sample of firms that did not.,Overall, the findings indicate that stronger CSR firms are less likely to become bankrupt relative to weaker CSR firms, all else being equal. This result is in line with the stakeholder theory of CSR. However, results do not support the conjecture that CSR matters when it comes to bankruptcy emergence. While CSR seems to influence whether a company experiences bankruptcy in the first place, having strong CSR does not seem to help a firm once it has filed for Chapter 11.,This paper extends the existing CSR literature but looks at CSR not from the angel of financial “success” but rather from financial “failure”.,The results could potentially help academics and practitioners alike in seeking understanding and reason behind CSR involvement and bankruptcy avoidance and success.,This is the first paper to test whether CSR plays a role in bankruptcy. The authors use a recent sample of firms with CSR scores that experienced a bankruptcy and a matched sample of CSR-scored firms that did not experience bankruptcy.

Constructing cointegrated cryptocurrency portfolios for statistical arbitrage

Abstract: This paper aims to present a methodology for constructing cointegrated portfolios consisting of different cryptocurrencies and examines the performance of a number of trading strategies for the cryptocurrency portfolios.,The authors apply a series of statistical methods, including the Johansen test and Engle–Granger test, to derive a linear combination of cryptocurrencies that form a mean-reverting portfolio. Trading systems are designed and different trading strategies with stop-loss constraints are tested and compared according to a set of performance metrics.,The paper finds cointegrated portfolios involving four cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Bitcoin Cash (BCH) and Litecoin (LTC), and the corresponding trading strategies are shown to be profitable under different configurations.,The main contributions of the study are the use of multiple altcoins in addition to bitcoin to construct a cointegrated portfolio, and the detailed comparison of the performance of different trading strategies with and without stop-loss constraints.

Bitcoin, Litecoin, and the Euro: an annualized volatility analysis

Abstract: This paper aims to empirically investigate the volatility of Bitcoin, Litecoin and the Euro.,The authors use quantitative methodologies to assess the annualized volatility of two cryptocurrencies and one international fiat currency. The exchange rate of the currencies is monitored on a daily basis using 1,460 observations from January 1, 2014 to December 31, 2017. The models used include the augmented Dickey–Fuller test, Akaike Information Criteria, autocorrelation function and exchange rate changes determining which currency is the most volatile.,The findings indicate, based on the statistical measures used, including the standard deviation of selected currencies and annualized volatility, that Litecoin is more volatile than Bitcoin and the Euro and that Bitcoin is more volatile than the Euro. This furthers previous research on cryptocurrency volatility.,The paper provides compelling evidence about the volatility of Litecoin and Bitcoin. The volatility of cryptocurrencies is furthered with data that are more current. The findings are important for investors, financial markets and central banks.

Dynamic linkages among cryptocurrencies, exchange rates and global equity markets

Abstract: The purpose of this paper is to investigate the short- and long-run dynamic linkages between selected cryptocurrencies, several major world currencies and major equity indices. The results show that despite sharing some common characteristics, the cryptocurrencies do not reveal any short- and long-term stochastic trends with exchange rates and/or equity returns. The dynamics of each cryptocurrency with the Chinese Yuan appears to be more turbulent than that with the other exchange rates. Each cryptocurrency appears to follow its own trend in the global financial market and is independent of the exchange rates or the global stock markets, thus making them suitable for inclusion in global investment portfolios.,The cryptocurrencies examined are Bitcoin, Dash, Ethereum, Monero, Stellar and XRP. In addition, data were collected on major exchange rates with respect to the US dollar, namely, the euro, British pound, Japanese yen and Chinese Yuan. Finally, the following major stock market indices were selected: SP500, DAX, DJIA, CAC, FTSE, NIKKEI, Hang Seng and Shanghai. The study applied vector autoregressive (VAR) model and Engle’s (2002) dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (DCC-GARCH) specification.,First, it was found that cryptocurrencies do not interact with each other because their correlations are weak and do not share a common long-run path; thus they are not cointegrated. Second, impulse response analysis from the VAR models indicate different reactions of each cryptocurrency to both exchange rate and equity shocks and that cryptocurrencies appear to be isolated from market-driven shocks. Third, the ups and downs in the cryptocurrencies’ dynamic conditional correlations (from the DCC-GARCH models) indicate that all cryptocurrencies were susceptible to speculative attacks and market events.,This paper examines the dynamic linkages among the most important cryptocurrencies with major exchange rates and equity markets and, to the best of the authors’ knowledge, is the first paper to do so. Thus, interested market agents would gain valuable insights as to whether this new form of asset might be used for conducting monetary policies and portfolio construction on a global setting.,The paper contributes to the scant literature on the dynamic linkages among major cryptocurrencies and global financial assets. In general, given the differential relationships of each crypto with the equity markets, one could infer that they represent a decent short-run investment vehicle within a well-diversified, global asset portfolio (as they may increase the returns and reduce the overall risk of the portfolio).

Liquidity of financial markets: a review

Abstract: The purpose of this study is to systematically review and analyze the literature in the area of liquidity of financial markets. The study summarizes the key findings and approaches and highlights the research gaps in the extant literature.,A variety of reputed databases are utilized to select 100 research papers, from a large pool of nearly 3,000 research papers spanning between 1972 and 2018 using systematic literature review methodology. The selected research papers are organized to provide an in-depth analysis and an account of the ongoing research in the area of liquidity. The study uses bibliometric network visualization and word-cloud analyses to compile and analyze the literature.,The study summarizes the recent approaches in the liquidity research on aspects such as methodologies followed, variables applied, sub-areas covered, and the types of economies and markets covered. The article shows that the literature on liquidity in the emerging markets (e.g. China and India) is deficient. Overall, the following research areas related to liquidity need further exploration in the context of emerging markets: liquidity beyond the best bid-ask quotes, intraday return predictability using microstructure variables (e.g. order imbalances), impact of algorithmic-trading and volatility of liquidity.,To the best of authors’ knowledge, in the recent past, a detailed account of the literature on liquidity has not been published. It provides a comprehensive collection and classification of the literature on the liquidity of financial markets. This would be helpful to the future researchers, academics and practitioners in the area of financial markets.

Can energy commodities affect energy blockchain-based cryptos?

Abstract: The purpose of this paper is to shed fresh light into whether an energy commodity price index (ENFX) and energy blockchain-based crypto price index (ENCX) can be used to predict movements in the energy commodity and energy crypto market.,Using principal component analysis over daily data of crude oil, heating oil, natural gas and energy based cryptos, the ENFX and ENCX indices are constructed, where ENFX (ENCX) represents 94% (88%) of variability in energy commodity (energy crypto) prices.,Natural gas price movements were better explained by ENCX, and shared positive (negative) correlations with cryptos (crude oil and heating oil). Using a vector autoregressive model (VAR), while the 1-day lagged ENCX (ENFX) was significant in estimating current ENCX (ENFX) values, only lagged ENCX was significant in estimating current ENFX. Granger causality tests confirmed the two markets do not granger cause each other. One standard deviation shock in ENFX had a negative effect on ENCX. Weak forecasting results of the VAR model, support the two markets are not robust forecasters of each other. Robustness wise, the VAR model ranked lower than an autoregressive model, but higher than a random walk model.,Significant structural breaks at distinct dates in the two markets reinforce that the two markets do not help to predict each other. The findings are limited by the existence of bubbles (December 2017-January 2018) which were witnessed in energy blockchain-based crypto markets and natural gas, but not in crude oil and heating oil.,As per the authors’ knowledge, this is the first paper to analyze the relationship between leading energy commodities and energy blockchain-based crypto markets.

Do mergers and acquisitions create value? The post-M&A performance of acquiring firms in China and India

Abstract: The purpose of this paper is to study whether mergers and acquisitions (M&As) create value in Indian and Chinese markets.,The authors study abnormal returns (AR) created by the acquiring firms in Indian and Chinese markets relating to M&A announcements, using the following three different statistical methods: i.e. mean, market and ordinary least squares adjusted return models.,On average, M&A announcements do not create value for the firms in Chinese and Indian economies. For the mean model, M&As create value for Chinese firms, whereas for the Indian firms no such value is created for the same event windows. The regression results showed that debt has a positive impact on the AR and cumulative average abnormal returns at 1, 5 and 10 per cent significance levels, respectively.,This study suggests increasing the sample size and period and using the instrumental variables regression to ensure the estimator’s impartiality, consistency and efficiency. With the investigative period surrounding a financial crisis, the estimators may have omitted bias.,Multiple methods used in this paper made it possible to capture the level of method variance in the AR, which is unusual in the Chinese and Indian context. Hence, the current study provides local knowledge and further strengthens the literature about M&As. The authors also regress AR with firm-specific factors, the consideration of which is scarce in the previous literature. Furthermore, much of what the authors know about M&A is relevant to developed economies.

A new approach to forecast market interest rates through the CIR model

Abstract: The purpose of this study is to suggest a new framework that we call the CIR#, which allows forecasting interest rates from observed financial market data even when rates are negative. In doing so, we have the objective is to maintain the market volatility structure as well as the analytical tractability of the original CIR model.,The novelty of the proposed methodology consists in using the CIR model to forecast the evolution of interest rates by an appropriate partitioning of the data sample and calibration. The latter is performed by replacing the standard Brownian motion process in the random term of the model with normally distributed standardized residuals of the “optimal” autoregressive integrated moving average (ARIMA) model.,The suggested model is quite powerful for the following reasons. First, the historical market data sample is partitioned into sub-groups to capture all the statistically significant changes of variance in the interest rates. An appropriate translation of market rates to positive values was included in the procedure to overcome the issue of negative/near-to-zero values. Second, this study has introduced a new way of calibrating the CIR model parameters to each sub-group partitioning the actual historical data. The standard Brownian motion process in the random part of the model is replaced with normally distributed standardized residuals of the “optimal” ARIMA model suitably chosen for each sub-group. As a result, exact CIR fitted values to the observed market data are calculated and the computational cost of the numerical procedure is considerably reduced. Third, this work shows that the CIR model is efficient and able to follow very closely the structure of market interest rates (especially for short maturities that, notoriously, are very difficult to handle) and to predict future interest rates better than the original CIR model. As a measure of goodness of fit, this study obtained high values of the statistics R2 and small values of the root of the mean square error for each sub-group and the entire data sample.,A limitation is related to the specific dataset as we are examining the period around the 2008 financial crisis for about 5 years and by using monthly data. Future research will show the predictive power of the model by extending the dataset in terms of frequency and size.,Improved ability to model/forecast interest rates.,The original value consists in turning the CIR from modeling instantaneous spot rates to forecasting any rate of the yield curve.

Sensitivity of economic policy uncertainty to investor sentiment: Evidence from Asian, developed and European markets

Abstract: This paper aims to explore the impact of investor sentiments on economic policy uncertainty (EPU). The analysis also considers the momentum effect, stock market returns volatility and equity pricing inefficiencies across markets, which, to the best of the authors’ knowledge, has not been addressed in the literature. The role of these control variables has collectively been considered to have important behavioral implications for international investors,Quantile regressions are used for estimation purpose, as it provides robust and more efficient estimates rather than those coming from the traditional regression model.,The momentum effect is negative and significant only at higher quantiles, while oil prices are positive and significant across all quantiles. The exchange rate exerts a negative and significant effect on EPU, whereas equity price volatility (i.e. investor sentiment) exerts a negative and significant impact on EPU in most of the quantiles.,The results have important implications for international investors and policymakers, especially in terms of the breakdown of economic policy uncertainty across different sample markets. The breakdown of complete sample period into sub-samples acts as a robust analysis and documents the similarity of the results for the Asian and developed markets cases, but not in the case of the European markets.,The findings imply the importance of financial stability that impacts the accumulation of systemic risks and adds smoothness to the financial cycle in particular geographical areas.,The contribution of this paper is threefold. First, existing literature highlights and empirically tests the impact of economic policy uncertainty on different market, macro-economic and global control variables. The analysis, however, performs it in the reverse order, i.e. analyzing the impact of the momentum effect (investor sentiment variables), equity market inefficiencies and volatility (market variables) and exchange rates and Brent oil (control variables). Second, to check the sensitivity of economic policy uncertainty, the analysis analyzes a wide range of markets, segregated as emerging, developed and European regions over the sample period to generate region-wise implications. Finally, the analysis explores the relationship of aforementioned variables with economic policy uncertainty keeping in view the non-linear structure and prior evidence and investor sentiments and economic policy uncertainty in the regression model.

The evolution of herd behavior: Will herding disappear over time?

Abstract: The purpose of this paper is to examine the evolutionary nature of herding phenomenon in the context of a frontier stock market, the Colombo Stock Exchange of Sri Lanka.,This study applies the cross-sectional absolute deviation methodology for daily frequencies of data of all the common stocks listed during the period from April 2000 to March 2018. The regression coefficients are estimated by using both the ordinary least square and the quantile regression procedures.,The findings reveal significant changes to the pattern of herding over different market periods, each with specific characteristics. Herding is strongly evident in up and down market days in the 2000-2009 period, during which the market was highly uncertain with the impact of the political instability of the country due to the Civil War on the stock trading. Even after this Civil War period, herd tendency is strongly manifested toward the up market direction as a result of the investors’ optimism about the country’s economy and political stability, which caused to a speculative bubble in the market. After that, it is turned into negative herding due to the panic selling occurred in view of the uncertainty of the inflated prices, which led to a market crash. Notably, herding appears to be consistently absent over the period after the crash, despite the presence of herd motives such as high market uncertainties triggered by political instability and economic crisis during that period.,The findings suggest that herd behavior is an evolving phenomenon in financial markets. Consistent with the adaptive market hypothesis, the absence of herding evident after the market crash could be attributed to the investors’ learning of the irrationality of herding/negative herding for adapting to market conditions. As a result, herding and negative herding tendencies declined and disappeared at the aggregate market level.,This study contributes to the literature by providing novel evidence on the evolutionary nature of behavioral biases, particularly herding, as predicted by the adaptive market hypothesis. With the application of the quantile regression procedure, in addition to customary used ordinary least squares approach, it also provides robust evidence on this phenomenon.

Crude oil price and implied volatility: Insights from non-parametric quantile regressions

Abstract: Purpose The purpose of this study is to investigate empirically the pattern of co-movement between prices and implied volatility in the future markets for crude oil. Design/methodology/approach The tool of non-parametric quantile regression is applied to daily price returns and implied volatility changes from 2007 to 2018. Findings For the total sample period, the link between price returns and forward-looking volatility expectations is contemporaneous, negative and asymmetric, and it exhibits an (approximately) inverted U-shaped pattern suggesting that: the pricing of implied volatility is heavier for large (in absolute value terms) changes relative to small ones and it is lighter for large positive changes relative to large negative ones. The pattern of co-movement, therefore, appears to be in line with the theoretical postulates of fear, exuberance and loss aversion. The main characteristics of the relationship are present in some (but not in all) sub-periods, which are also considered in this study. Originality/value Less than a handful of works have assessed the link between implied volatility and prices for commodity ETFs. This is the first one relying on flexible non-parametric quantile regressions.

The impact of financial regulation policy uncertainty on bank profits and risk

Abstract: The purpose of this paper is to explore the impact of financial regulation policy uncertainty (FRPU) on bank profit and risk.,This study applies dynamic panel techniques and uses the Baker et al. (2016) FRPU index and macroeconomic variables to assess FRPU’s impact on bank profit and risk using Federal Deposit Insurance Corporation call reports from Q1 2000 to Q4 2016 for over 4,760 commercial banks.,The effect of FRPU on profitability (Return on Assets [ROA] and Return on Equity [ROE]) and risk (standard deviation of ROA and ROE) produces complex results. FRPU negatively (positively) impacts profits for small and large banks (money center banks). There is a positive impact on FRPU for small and medium-sized banks, with no impact reported for the large and money center banks.,Findings lead to several implications for financial services regulators, investors and executives as summarized in the conclusion. It is essential to ensure that clear communication channels are open especially to small and medium-sized banks for proper strategic planning, given their greater sensitivity to regulatory uncertainty.,This paper contributes to the literature as follows. First, it explores the impact of FRPU on bank profits and risk using a novel index introduced by Baker et al. (2016). This news-based continuous measure presents a bank profit modeling approach that differs from traditional event study methodology. Second, a large sample of US commercial banks is used which represents an important departure from banking regulation studies.

How well can investors diversify with commodities? Evidence from a flexible copula approach

Abstract: This paper aims to investigate empirically the linkages between stock and commodity futures markets.,It involves the application of a flexible copula approach to weekly total returns from the S&P 500 index and from three commodity sub-indices (agriculture, metals and energy) from 1995 to 2017.,Co-movement is by no means frequent and symmetric. It was predominantly zero before the last financial crisis, and since then, it is positive and asymmetric. The pattern of asymmetry is consistent with transmission of shocks under extreme negative shocks only. Recently, total returns of commodity futures are very poor. At the same time, commodity futures markets move in step (out of step) with stock markets when the latter plunge (rise), pointing to limited diversification benefits. These appear to justify the concerns of investors and researchers whether including commodities in a portfolio of assets is still a prudent investment strategy.,It is the only manuscript that combines a flexible copula approach and co-movement measurement along both the positive and negative diagonals. The findings are in sharp contrast with those reported by Delatte and Lopez (2013) and are very important for portfolio management.

Fair premium rate of the deposit insurance system based on banks’ creditworthiness

Abstract: Deposit insurance is a key element in modern banking, as it guarantees the financial safety of deposits at depository financial institutions. It is necessary to have at least a dual fair premium rate system based on creditworthiness of financial institutions, as considering singular premium system for all banks will have moral hazard. This paper aims to develop theoretical and empirical model for calculating dual fair premium rates.,The definition of a fair premium rate in this paper is a rate that covers the operational expenditures of the deposit insuring organization, provides it with sufficient funds to enable it to pay a certain percentage share of deposit amounts to depositors in case of bank default and provides it with sufficient funds as precautionary reserves. To identify and classify healthier and more stable banks, the authors use credit rating methods that use two major dimensional reduction techniques. For forecasting nonperforming loans (NPLs), the authors develop a model that can capture both macro shocks and idiosyncratic shocks to financial institutions in a vector error correction model.,The response of NPLs/loans to macro shocks and idiosyncratic innovations shows that using a model with macro variables only is insufficient, as it is possible that under favorable economic conditions, some banks show negative performance due to bank level reasons such as mismanagement or vice versa. The final results show that deposit insurance premium rate needs to be vary based on banks’ creditworthiness.,The results provide interesting insight for financial authorities to set fair deposit insurance premium rate. A high premium rate reduces the capital adequacy of individual financial institutions, which endangers the stability of the financial system; a low premium rate will reduce the security of the financial system.

NFL betting market efficiency, divisional rivals, and profitable strategies

Abstract: This paper aims to examine market inefficiencies in the National Football League (NFL) betting market from the 2003 season to the 2016 season.,The author examines the impact that division rivals and previously known determinants of inefficiencies have on the current NFL gambling market.,The results show that games against division rivals have a lower chance of the home team covering the spread and the chance the game will result in an over. This result demonstrates that the sportsbooks underestimate the familiarity that teams have with each other’s players, coaches and tendencies from playing each other twice per year. Moreover, using this result in conjunction with previous known inefficiencies, the author puts forth a model to test out of sample predictions. The results from these tests show profitable strategies in the point spread and totals market with a win rate of nearly 57 per cent.,Overall, this paper demonstrates inefficiencies in the NFL betting market that future bettors may be able to take advantage of.

The impact of major life events on household asset portfolio rebalancing

Abstract: This paper aims to model the asset portfolio rebalancing decisions of Australian households experiencing a severe life event shock.,The paper uses household longitudinal data from the Household, Income, and Labour Dynamics in Australia (HILDA) survey since 2001. The major life events are serious illness or injury, death of a spouse, job dismissal or redundancy and separation from a spouse. The asset classes are bank accounts, cash investments, equities, superannuation (private pensions), life insurance, trust funds, owner-occupied housing, investor housing, business assets, vehicles and collectibles. The authors use both static and dynamic Tobit models to assess the impact and duration of impact of the shocks.,Serious illness and injury, loss of employment, separation and spousal death cause households to rebalance portfolios in ways that can have detrimental effects on long-term wealth accumulation through poor market timing and the incurring of transaction costs.,The survey results are only available since 2001, and the wealth module from which the asset data are drawn is self-reported and not available every year.,Relevant to policymakers working on the ongoing retirement of the “baby boomer” generation and for financial planners guiding household investment decisions.,Most research on shocks to household wealth concern a narrower range of assets and only limited shocks. Also, this is one of the few studies to use a random effects model to allow for unspecified heterogeneity among households.

Bank-based and market-based development and economic growth: an international investigation

Abstract: Purpose The purpose of this paper is to investigate the relative impact of bank-based and market-based financial developments on economic growth from 1984 to 2015, using 60countries. Design/methodology/approach This study uses fixed effect and generalized method of moments (GMM) to investigate the relative impact of bank-based and market-based financial developments on economic growth from 1984 to 2015, using 60 countries. The study further controls regional effects and the Asian crisis, as well as the global economic crisis. Findings The empirical results of the study revealed that market-based development positively affects economic growth. Besides, market-based financial development indirectly promotes investment, which has the potential to strongly enhance growth. The findings of this study, therefore, provide more support to pro-market-based financial development policies in these regions. Interestingly, bank-based development has no direct impact on development, but indirectly encourages investment, which also promotes growth. Originality/value This paper is the first of its kind to empirically examine fixed effect and GMM to investigate the relative impact of bank-based and market-based financial developments on economic growth from 1984 to 2015, using 60 countries.

Stock market, banking sector and economic growth: A cross-country analysis over different economic cycles

Abstract: The purpose of this paper is to examine the causal relationship between economic development and financial sector development for 28 countries at different stages of their development. The authors specifically focus on the nature of causality during economic boom and tranquil cycles.,The study uses quarterly time series panels of 17 developed and 11 emerging countries, during 1993Q1-2014Q4 with each having three sub-panels – full sample, a period of the economic uptrend (UP), and period of the economic downtrend. The authors use a univariate analysis for initial screening followed by panel unit root test, panel co-integration and causality test proposed by Toda–Yamamoto to examine the causal relationship.,The principal results suggest that for developed economies, there is a causal flow from financial sector to real sector in line with the “supply-leading” hypothesis, whereas for emerging economies, it is from real sector to financial sector, in line with the “demand-following” hypothesis. This overall relationship is strong for both emerging and developed economies during economic boom or UP cycles, but becomes weak during economic downturns or tranquil periods.,This study is different from previous studies on this issue and contributes to the existing literature in a number of ways. First, the focus of this paper revolves around identification of differential patterns in causal flows between real and financial sectors for different economies, across different economic cycles. Second, to present a robust representation of financial sector, the authors consider both banking sector and stock market parameters as the proxy for financial sector development. Third, the authors address the “stock-flow problem” in the measurement of financial variables a typical criticism of some of the previous studies. Finally, the authors use a rich sample size comprising of about 2,500 quarterly observations for each variable, with about 1,500 observations from developed and 1,000 from emerging economies.

Modelling industry interdependency dynamics in a network context

Abstract: Interdependency among industries is vital for understanding economic structures and managing industrial portfolios. However, it is hard to precisely model the interconnecting structure among industries. One of the reasons is that the interdependencies show a different pattern in tail events. This paper aims to investigate industry interdependency with the tail events.,General predictive model of Rapach et al. (2016) is extended to an interdependency model via least absolute shrinkage and selection operator quantile regression and network analysis. A dynamic network approach was applied on the Fama–French industry portfolios to study the time-varying interdependencies.,A denser network with heterogeneous central industries is found in tail cases. Significant interdependency varieties across time are shown under dynamic network analysis. Market volatility is identified as an influential factor of industry connectedness as well as clustering tendency under both normal and tail cases. Moreover, combining dynamic network with prediction direction information into out-of-sample industry return forecasting, a lower tail case is obtained, which gives the most accurate prediction of one-month forward returns. Finally, the Sharpe ratio criterion prefers high-centrality portfolios when tail risks are considered.,This study examines the industry portfolio interactions under the framework of network analysis and also takes into consideration tail risks. The combination of economic interpretation and statistical methodology helps in having a clear investigation of industry interdependency. Moreover, a new trading strategy based on network centrality seems profitable in our data sample.

Excess liquidity premia of single-name CDS vs iTraxx/CDX spreads: 2007-2017

Abstract: The aim of this research is twofold. First, we study average levels of liquidity for long-run through-the-cycle periods, which potentially allow eliminating procyclicality from risk parameters used for expected credit-loss calculations. Second, we investigate to what extent the relative illiquidity of individual credit default swap (CDS) contracts affects their spreads in comparison with the respective CDS indices.,Based on the iTraxx Europe CDS index covering European firms and the CDX North America CDS index covering US firms, as well as on individual CDS transactions involving the reference entities constituting these two benchmark indices, we investigate the excess liquidity premia in spreads of the single-name CDS contracts over the spreads of the iTraxx and CDX indices over 2007-2017.,First, single-name CDS excess liquidity premia depend on CDS contract maturity. Second, the long-run average spread of a benchmark index may stay as low as three-fourths of the respective long-run average of the mean of the single-name CDS spreads, meaning that the excess liquidity premium may be as high as one-fourth of the firm-specific CDS spread. Third, the term structure of the excess liquidity differs between the Europe and North America geographies. Fourth, on average, the excess liquidity premia in the single-name CDS spreads over the respective CDS indices diminish with increasing maturities of CDS contracts.,No previous research addresses differences between the liquidity component in a benchmark CDS index spreads and the mean spread averaged across the constituents of the index. Our work fills this gap.

Stock market performance and cross-border mergers and acquisitions in South Africa: 1991 to 2014

Abstract: Since the attainment of fully fledged democracy in 1994, South Africa witnessed a substantial increase in both the number and the value of completed mergers and acquisitions (M&As) targeting South African firms. In spite of this development, studies on foreign direct investment (FDI) on South Africa have not looked at determinants of entry-mode choice of FDI such as M&A. The purpose of this paper is to fill the gap in the literature by investigating locational factors that make South Africa an attractive destination for M&A activity in Africa.,The authors analyse both the number and the value of M&As, the dependent variable. They analyse the number of firms acquired each quarter in South Africa from 1991 to 2014 using a count model – the negative binomial model. They then compare the results for this model with those of benchmark models such as the normal count and the Poisson count models. In this paper, the authors test for stationarity of the time series using the Augmented Dickey–Fuller (ADF) and the Kwiatkowski–Phillips–Schmidt–Shin (KPSS) tests. They examine the long-run relationship between the value of M&As and the selected macroeconomic variables using Johansen’s co-integration technique.,This paper finds that both the number and the value of M&As in South Africa are positively influenced by the performance of the Johannesburg Securities Exchange during the period 1991 to 2014. This result confirmed the expectations hypothesis that stock markets facilitate M&A activity. The authors also observed that other financial and macroeconomic variables – exchange rate volatility, relative inflation rate and economic growth – are important locational factors for M&A activity. Among these factors, the exchange rate volatility exerts the greatest influence on M&As. The rate of growth of gross domestic product (GDP) matters for M&A activity in emerging market economies such as South Africa.,The data for the number of M&As are more complete than that of values. This is because some firms choose not to report the value of deals after a transaction takes place, resulting in missing data for the value of M&A deals.,This paper shows the important role played by pull factors on the direction of capital flows in the long run. It is recommended that policy-makers should further strengthen and improve the efficiency of domestic financial markets. Stable and reliable monetary policy framework that maintains low levels of inflation and mitigates the volatility of exchange rate is important for FDI and M&A flows to emerging market economies. There is a need to put the necessary measures in place to improve South Africa's economic growth rate, which has been weak since the global financial crisis of 2008.,Most academic literature has examined determinants of aggregate FDI without consideration of entry-mode choice. This paper focused on the M&A entry-mode for an emerging market economy. The authors show that equity markets play a key role in facilitating M&A activity. The expectations hypothesis by Nelson (1959) that stock markets facilitate M&A activity is confirmed in this way for South Africa.

Further insights into the oil and equity market relationship

Abstract: Purpose This paper aims to assess the asymmetric effects of oil price shocks and the impact of oil price volatility on the Eurozone’s supersector returns, with a particular emphasis on the impact of the subprime crisis and the euro debt crisis (EDC) on this relationship. Design/methodology/approach Empirical data consist of daily observations of the 19 EURO STOXX supersector indices and the Brent crude oil price index for the period January 2001 to August 2015. This paper uses a non-linear multifactor market model. This model accounts for heteroscedasticity and breakpoints that are identified by the Bai and Perron (1998, 2003) tests. Findings The results show that supersector returns are sensitive to oil price shocks. However, in most cases, their responsiveness to oil price volatility is not significant. The relationship between oil price shocks and supersector returns changes through time and depends on the sector. Financial turbulence affects the oil-stock market nexus. In most cases, the subprime crisis has had a positive impact on the oil-stock market relationship, whereas the EDC has had an overall negative effect. Before the subprime crisis, there is an evidence of asymmetric effects for some supersectors. Meanwhile, for most sectors, the asymmetric effects disappear after 2008. Originality/value The study improves understanding of the interaction between oil price risk and the Eurozone sector indices returns. Furthermore, it enables global investors to manage the risk inherent to the portfolio managers’ positions.

Market dynamics, cyclical patterns and market states: Is there a difference between digital currencies markets?

Abstract: In this paper, the authors seek to investigate the dynamics of Bitcoin, Litecoin, Ethereum and Ripple daily returns and volatilities.,In this paper, the authors apply the MS-ARMA model on daily returns of Bitcoin (19/04/2013-13/02/2018), Ripple (05/08/2013-14/02/2018), Litcoin (29/04/2013-14/02/2018) and Ethereum (08/02/2015-14/02/2018). This model allows capture of the nonlinear structure in both the conditional mean and the conditional variance of cryptocurrency returns.,All the cryptocurrency markets show regime switching in the return-generating process. Market dynamics seem to be governed by two different states which differ from one cryptocurrency market to another in terms of mean return, volatility and interstate dynamics. These findings can be explained by investors’ behavior, i.e. speculative trading and herding behavior. By choosing to participate (or imitating some investors) in some cryptocurrency markets (in particular Bitcoin market), they affect the price movements and therefore the market dynamics in the short run.,Identifying the different market states provides information for investors to make more accurate portfolio decisions in the virtual market and follow the market timing strategy.,This paper attempts to analyze potential nonlinear structure in cryptocurrencies returns and analyze if there is a difference between the cryptocurrencies market cycles. So, the search for congruent and adequate specification to reproduce the stock returns dynamics in the virtual market still remains the concern of several empirical studies. This research not only examines the behavior of stock returns in the cryptocurrencies’ market but also highlights the existence of nonlinearity propriety as a stylized fact.

Acquirer size, political connections and mergers and acquisitions performance: Evidence from China

Abstract: The purpose of this paper is to empirically examine the relationships between acquirer size and performance outcomes of the different process of acquisition in the Chinese context and the moderating effect of political connections on the size-performance relationship.,Building upon agency theory, the paper examines the relationship between acquirer size and acquisition announcement returns to find whether the acquirer size effect exists in China. Moreover, the paper investigates whether large firms can perform better in the long run arising from scale economy. Finally, the paper examines the moderating effect of political connections on the size-performance relationship. Accounting for the complexity of political connections in China, the paper uses two methods to capture political connections.,The paper finds that acquirer size plays a significant negative role on announcement returns, suggesting that the acquirer size effect also exists in China. However, acquirer size has a significant positive impact on long-term performance, indicating that large acquirers perform better in the integration process. Although no evidence shows that political connections can bring some off-setting benefits to acquirer size effect argued by Humphery-Jenner and Powell (2014), political connections, indeed, have a positive effect on mergers and acquisitions (M&As) announcement returns.,The paper contributes to the corporate characteristic, political connections and M&A performance literature. Due to agency problem and scale economy, the effect of firm size on acquisition performance varies with the stage of M&A. Political connections can bring some benefits to M&A deals.

The monitoring role of institutional investors: Geographical proximity and investment horizon

Abstract: This paper aims to examine the monitoring role of institutional investors in corporate decision-making by classifying financial institutions based on geographical proximity and investment horizon from 1980 to 2014.,By using unique data sets on firm and institution location and investor horizon measure (Gaspar et al., 2005), the authors categorize institutional investors into six proximity-horizon classifications. This method captures the heterogeneity of investors. The corporate decisions assessed include firm investment, financing, payout policy, misbehavior, takeover defenses and profitability.,Both geographical proximity and investment horizon are directly related to institutional investors' monitoring cost. As a result, the effectiveness of institutional monitoring may vary based on geographical proximity and investment horizon. This paper collectively examines both dimensions of financial institutions and provides evidence that institutional investors present different preferences for corporate policies. Given stronger information advantage, both local and nonlocal investors that are long-term oriented fulfill better roles in monitoring corporate decisions but from different perspectives.,Different from previous studies that treat institutional investors homogeneously, this paper provides empirical support that investors are indeed different in influencing firm policies.,To the authors’ best knowledge, this is the first study that classifies investors based on two dimensions, geographical proximity and investment horizon, and examines their joint effects on corporate policies. This proximity-horizon classification allows the authors to better disentangle the effects of institutional ownership structure on the monitoring outcomes.

Price formation in call auctions with insider information

Abstract: Purpose: This study investigates -theoretically and empirically- if call auctions incorporate asymmetric information into prices. Design/methodology/approach: First, this study introduces a new model of price formation in a call auction with insider information. In this call auction model, insider trading gives rise to an asymmetric information component of transaction costs. Next, this study estimates the model using twenty stocks from Euronext Paris and investigates if the asymmetric information component is present. Findings: The theoretical analysis reveals that call auctions incorporate asymmetric information into prices. The empirical analysis finds strong evidence for the asymmetric information component. Testable implications provide further support for the model. Practical implications: Call auctions have recently been proposed as an alternative to continuous limit order book markets to overcome problems associated with high frequency trading. However, it is still an open question whether call auctions efficiently aggregate asymmetric information. The findings of this study imply that call auctions facilitate price discovery and, therefore, are a viable alternative to continuous limit order book markets. Originality/value: There is no generally accepted measure of trading costs for call auctions. Therefore, the measure introduced in this study is of great value to anyone who wants to (i) quantify trading costs in call auctions; (ii) understand the determinants of trading costs in call auctions; or (iii) compare trading costs and their components between continuous markets and call auctions. This study also contributes to the literature devoted to estimating the probability of information-based trading

How did regulation and market discipline influence banking distress in Europe? Lessons from the global financial crisis

Abstract: This paper aims to examine the relationship between regulation, market discipline and banking distress.,To address the empirical question put forward above, a multivariate logit model is applied to an international sample of 586 banks from 21 European countries in the period between 2000 and 2012. To give robustness to the results, different variables have been used to test the role played by market discipline and regulation as well as an alternative methodology known as duration/survival analysis.,It can be found that market discipline is a good indicator in signalling banking distress, that is, market discipline has penalized more banks with a higher likelihood of being in distress. Nonetheless, as broadly acknowledged, market discipline was not sufficient per se to avoid banking distress in Europe. With regard to regulation, this paper evidences that the adoption of other regulatory measures beyond the simple transposition of changes occurred in the EU Directives such as borrower-based measures and limits on pre-emptive exposures’ concentration, have contributed toward reducing the probability of distress of EU banks, showing that the introduction of this kind of measures was necessary and relevant. In addition, in this paper, it can be found that the NPL ratio, size, capital (including the well-known regulatory capital ratio, as well as the novel leverage ratio which discards the risk weights present in the former one) and liquidity are good indicators of banking distress which lead us to conclude that the new regulatory framework known as Basel III is on the right path to mitigate the probability that a new banking crisis similar to the last one takes place again.,The first limitation regards the period of time chosen, that is, from 2000 to 2012, empirically neglecting, to some extent the important regulatory changes occurred after the aforementioned period. Nonetheless, as mentioned in the Data and Methodology section, the period ends in 2012 because it is difficult to flag a reasonable number of banks’ bailouts afterwards, to properly run the type of model used in this paper. The second limitation is the fact that the possible changes in the risk management and risk assessment by institutions and in the behaviour of investors, acknowledge as weak and inappropriate before the on-set of the global financial crisis, albeit very relevant, are not in the scope of this paper.,Despite the welcomed changes performed by regulators so far, some aspects are not complete yet and new areas deserve more empirical work and attention by the regulators and supervisors. Some of them stem directly from the results obtained from this paper such as the enhancement and a close monitoring of the current Pillar 3 framework the increase of the adoption of more targeted tools, in a more preemptive way, to counter the build-up of risks and the implementation of the leverage ratio.,In the aftermath of the financial crisis, the identification of leading indicators signalling emerging risks to the banking system has become a major priority to central banks and supervisory authorities. As a consequence, several studies have formulated the aim of analysing predictive characteristics of a set of macroeconomic variables, such as GDP Growth, Credit-to-GDP, Inflation, M2-to-GDP, among others. Other studies take a different perspective and complement the analysis with bank-specific risk indicators. Nonetheless the aforementioned studies do not consider the relationship between regulation and market discipline and banking distress. This is the gap the authors wanted to fill, and this assessment is the main contribution of this paper.

New methods of modeling and estimating preferences

Abstract: This paper aims to quantify preferences without having to have any utility data.,We use duality theory, Taylor’s theorem and nonlinear regressions.,We presented pioneering quantitative methods in economics and business. These methods can be applied to numerous topics in empirical and theoretical economics and business. Moreover, this paper highlighted the interdisciplinary nature of economics. In doing so, it emphasized the interface between economics, marketing, management, statistics and mathematics. Furthermore, it circumvented a major obstacle in the literature: the curse of dimensionality.,The authors introduce a novel and convenient approach to utility modeling. In doing so, they present a general utility function in a simple form. Furthermore, they develop a method to measure preferences without any utility data. They also devise a method to measure the marginal utility. Then, they develop new methods of modeling and measuring the consumer utility. In so doing, they overcome a major obstacle: the curse of the dimensionality. In addition, they introduce new methods of modeling and measuring the consumer demand for the firm’s good.

Hedging performance and the heterogeneity among market participants

Abstract: This paper aims to apply the heterogeneous autoregressive model of realized volatility (HAR-RV) model to minimum-variance hedge ratio estimation and compares the hedging performance of presenting a model with that of a conventional rolling ordinary-least-square (OLS) hedging model. Moreover, this paper empirically analyzes the relationship between hedging performance and the heterogeneity of investors with different trading frequency in forming the expectation for the spot volatility, futures volatility and the covariance in the market.,Use HAR-RV to form expectations of participants of spots and futures market for the next period volatility based on two parts. One is the current observable realized volatility at the same time scale. The other is the expectation for the next longer time scale horizon volatility. Compare hedging performance with rolling OLS model and HAR-RV model. Present a three-times-scale-length (daily, weekly and monthly) HAR-RV model for the spot and futures returns and volatility to analyze the relationship between the hedging performance and the heterogeneity among participants in each market.,The empirical results show that HAR-RV model outperforms the rolling OLS in terms of variance reduction and expected utility in the out-of-sample period. The results also indicate that the greater variance reduction occurs when investors with different trading frequency have a less heterogeneous expectation for spot volatility and more heterogeneous expectation for futures volatility and the covariance. In addition, the expected utility increases along with lower heterogeneity in spot volatility and higher in futures volatility and the covariance. Hedging performance improves along with decreasing heterogeneity of investors in spot volatility and increasing heterogeneity in futures volatility and the covariance.,This paper considers the heterogeneity of participants in spot and futures market, the authors apply HAR-RV model to MVHR estimation and compare the hedging performance of presenting a model with that of conventional rolling OLS hedging model, providing more evidence in hedging literature. This paper analyzes in depth the relationship between hedging performance and the heterogeneity in the market.