Int. J. Financial Stud., Volume 6, Issue 3 (September 2018) – 22 articles

In response to the financial crisis, a number of reforms to bank regulation have been introduced. Many of these reforms seek to improve the resilience of banks through making changes to their structure. In the U.K., the Banking Reform Act 2013 was enacted. This study attempts to examine the market’s reaction to this important financial reform, on the stock price of banks and insurance companies and contributes to the current regulatory debate. As reform proposals take time to get converted into Law, this paper focuses on three legislative events extracted from the Parliament website; the third reading at the House of Commons, the third reading at the House of Lords, and the Royal Assent, effectively the stages from which reform proposals convert to Law. This study employs an event study methodology, based on a sample consisting of 24 major banks and insurance companies listed on the London Stock Exchange (LSE) for which data are available from 30/11/2012 to 18/12/2013 covering all three events. The findings are that banks’ shares reacted positively, whereas insurance companies’ shares reacted negatively to the passage of the Banking Reform Act 2013 in the House of Commons (first event); insurance companies experienced negative returns, whereas banks’ returns did not react significantly in relation to the passage of the Act in the House of Lords (second event); and finally, banks’ shares reacted positively while insurance companies’ shares reacted negatively when the Act received the Royal Assent (third event). One of the main intentions of the Banking Reform Act 2013, was to contain the risk taken by banks. Market reaction on banks’ shares shows that the market accepted this; on the other hand, the negative effect on the shares of insurance companies would imply that insurance companies are perceived to have taken on some additional risk as a consequence of the Act. Full article

Price evaluations of municipal bonds have traditionally been performed by human experts based on their market knowledge and trading experience. Automated evaluation is an attractive alternative providing the advantage of an objective estimation that is transparent, consistent, and scalable. In this paper, we present a statistical model to automatically estimate U.S municipal bond yields based on trade transactions and study the agreement between human evaluations and machine generated estimates. The model uses piecewise polynomials constructed using basis functions. This provides immense flexibility in capturing the wide dispersion of yields. A novel transfer learning based approach that exploits the latent hierarchical relationship of the bonds is applied to enable robust yield estimation even in the absence of adequate trade data. The Bayesian nature of our model offers a principled framework to account for uncertainty in the estimates. Our inference procedure scales well even for large data sets. We demonstrate the empirical effectiveness of our model by assessing over 100,000 active bonds and find that our estimates are in line with hand priced evaluations for a large number of bonds. Full article

The buy and hold stock market strategy, which gained tremendous popularity in the 1970s, may no longer be such a profitable method for accumulating wealth for the average investor in the new millennium. This paper investigates the relationship between compound return and holding period length to see how long an Exchange Traded Fund (ETF) investment must be held before a positive return on principal is 100% likely. Because the ETF is a relatively new investment vehicle that could be considered particularly well-suited to the requirements of the buy and hold strategy, we begin our investigation here. We find that the compound returns earned over a rolling holding period are much more volatile than one might assume given historic rules of thumb for average return expectations. Using monthly return data for all listed NASDAQ ETFs between their date of inception and 2015, we find it takes ten years for the average probability of a gain on principal to be over 95 percent. Full article

This study investigated bank-specific and macroeconomic determinants of bank profitability in Azerbaijan, an oil-dependent economy in transition. A huge drop in oil prices, a significant devaluation of the national currency, and the financial distress were the main motivations of the study. We applied Panel Generalized Method of Moments to the data in the framework of dynamic model of the bank profitability. It was found that bank size, capital, and loans, as well as economic cycle, inflation expectation, and oil prices were positively related to the profitability, whereas deposits, liquidity risk, and exchange rate devaluation were negatively associated with it. We further found that the bank profitability demonstrated moderate persistence and ignoring the country-specific features could lead to bias and poor performance in estimations. The conclusions of this research would aid in setting banking policies towards increasing profitability. This may be supplemented by ensuring strong research departments within the banks tasked with analyzing and forecasting the main macroeconomic indicators. The novel features of the study include utilizing recent economic trends, accounting for country-specific features, and for the first time, examining the effects of the economic cycle on the bank profitability in Azerbaijan. In addition, the study featured proper addressing time series properties of the panel data, and performances of robustness checks for consistency of results. Full article

This study investigates that how investment banks select alternative valuation models to price Initial Public Offerings (IPOs) and examine the value-relevance of each valuation model using the data of 88 IPOs listed on the Pakistan Stock Exchange (PSX) during 2000–2016. This study investigates that investment banks used Dividend Discount Model (DDM), Discounted Cash Flow (DCF) and comparable multiples valuation models on the basis of firm-specific characteristics, aggregate stock market returns and volatility before the IPOs. In this study, a binary logit regression model is used to estimate the cross-sectional determinants of the choice of valuation models by investment banks. The results reveal that underwriters are more likely to use DDM to value firms that have dividends payout trail. The investment banks select DCF when valuing the younger firms, that have more assets-in-tangible, firms that have negative sales growth and positive market returns before the IPO; while comparable multiples are used for mature firms and firms that have less assets-in-tangible. Furthermore, this study also used OLS regressions to examine the value-relevance of each valuation model and Wald-test to examine the predictive power of cross-sectional variation in the market values. The findings unveil that P/B ratio has highest but DCF has lowest predictive power to market values. The Wald-test results depict that none of the valuation methods produces an unbiased estimate of market values. Full article

The CKLS process (introduced by Chan, Karolyi, Longstaff, and Sanders) is a typical example of a mean-reverting process. It combines random fluctuations with an elastic attraction force that tends to restore the process to a central value. As such, it is widely used to model the stochastic behaviour of various financial assets. However, the calibration of CKLS processes can be problematic, resulting in high levels of uncertainty on the parameter estimates. In this paper we show that it is still possible to draw solid conclusions about certain qualitative aspects of the time series, as the corresponding indicators are relatively insensitive to changes in the CKLS parameters. Full article

This paper studies an optimal trading problem that incorporates the trader’s market view on the terminal asset price distribution and uninformative noise embedded in the asset price dynamics. We model the underlying asset price evolution by an exponential randomized Brownian bridge (rBb) and consider various prior distributions for the random endpoint. We solve for the optimal strategies to sell a stock, call, or put, and analyze the associated delayed liquidation premia. We solve for the optimal trading strategies numerically and compare them across different prior beliefs. Among our results, we find that disconnected continuation/exercise regions arise when the trader prescribe a two-point discrete distribution and double exponential distribution. Full article

Towards improving the socio-economic condition of low-income households, development organizations offer a repertoire of initiatives. This study focused on the impacts of access to working capital and enterprise development training programs, on the performance and sustainability of micro-enterprises owned and managed by low-income households, in the state of Kelantan, Peninsular Malaysia. The data of 450 micro-entrepreneurs, was randomly selected from the participants’ list of three development organizations servicing Kelantan: Amanah Ikhtiar Malaysia (AIM); National Entrepreneurs Economic Group Fund (TEKUN); and Malaysia Fisheries Development Board (LKIM). This study revealed several participation indicators (i.e., years of participation, total number of trainings, total number of training hours received, and number of center meetings or discussions attended, etc.), which have a positive effect on micro-enterprise performance and sustainability. However, the findings were inconclusive as one of the key participation indicators, ‘total amount of economic loans received’, showed a negative (not statistically significant) effect on micro-enterprise performance and sustainability. This study expanded the limited literature on micro-enterprise performance and sustainability, and the role of working capital and enterprise development training programs; thus providing a clearer understanding of the effectiveness of current development initiatives. Full article

Brexit, the withdrawal of the United Kingdom (UK) from the European Union (EU), has led to significant exchange rate fluctuations and to uncertainty in financial markets and in UK–EU trade relations. In this article, we use a non-linear model to study how this uncertainty affects export companies. Exports tend to react in spurts when exchange rate fluctuations go beyond a band of inaction, referred to here as a “play area”. We apply an algorithm to study this hysteretic relationship with ordinary least squares (OLS) regressions. We examine the export relationship between Europe (Belgium, Germany, France, Italy, and The Netherlands) and the UK. To guarantee the robustness of the results, we estimate a variety of specifications for modeling economic uncertainty: (a) constant uncertainty, (b) exchange rate volatility, (c) volatility in European equity markets, (d) the Treasury Bill EuroDollar Difference (TED-spread), (e) the Economic Policy Uncertainty Index (EPUI), and (f) a combination of exchange rate volatility and the EPUI. Since the results show little evidence of hysteretic effects on British exports, we focus on the European side. The specifications including exchange rate and equity market volatility show a significant effect of hysteresis. Full article

This study investigates the impact of commodity price volatility (including soft commodities, precious metals, industrial metals, and energy) on the dynamics of corporate sukuk returns. Using a sample of sukuk indices from Gulf Cooperation Council (GCC) countries, we study the dynamic conditional correlation using a multivariate generalized autoregressive conditional heteroskedasticity dynamic conditional correlation (GARCH-DCC) process. Empirical results show a time-varying negative correlation between GCC sukuk returns and commodity prices. In fact, a negative conditional correlation among assets of a given portfolio implies higher gain-to-risk ratios. An understanding of volatility and dynamic co-movements in financial and commodity markets is important for portfolio allocation and risk management practices. Full article

Revenue sharing is a common league policy in professional sports leagues. Several motivations for revenue sharing have been explored in the literature, including supporting small market teams, affecting league parity, suppressing player salaries, and improving team profitability. We investigate a different motivation. Risk-averse team owners, through their commissioner, are able to increase their utility by using revenue sharing to affect higher order moments of the revenue distribution. In particular, it may reduce the variance and kurtosis, as well as affecting the skewness of the league distribution of team local revenues. We first determine the extent to which revenue sharing affects these moments in theory, then we quantify the effects on utility for Major League Baseball over the period 2002–2013. Our results suggest that revenue sharing produced significant utility gains at little cost, which enhanced the positive effects noted by other studies. Full article

Fifty years ago, I published the initial, classic version of the Z-score bankruptcy prediction models. This multivariate statistical model has remained perhaps the most well-known, and more importantly, most used technique for providing an early warning signal of firm financial distress by academics and practitioners on a global basis. It also has been used by scholars as a benchmark of credit risk measurement in countless empirical studies. Practical applications of the Altman Z-score model have also been numerous and can be divided into two main categories: (1) from an external analytical standpoint, and (2) from an internal to the distressed firm viewpoint. This paper discusses a number of applications from the former’s standpoint and in doing so, we hope, also provides a roadmap for extensions beyond those already identified. Full article

This study aims to explore the relationship between economic growth, financial innovation, and stock market development of Bangladesh for the period 1980–2016. To investigate long-run cointegration, this study used the autoregressive distributed lagged (ARDL) bounds testing approach. In addition, the Granger-causality test is used to identify directional causality between research variables under the error correction term. Study findings from the ARDL bound testing approach confirm the existence of a long-run association between financial innovation, stock market development, and economic growth. Furthermore, the findings from the Granger-causality test support bidirectional causality between financial innovation, economic growth and stock market development, and economic growth both in the long run and short run. These findings support the theory that market-based financial development and financial innovation in the financial system can spur economic development. Full article

This paper investigates the predictability of exchange rate changes by extracting the factors from the three-, four-, and five-factor model of the relative Nelson–Siegel class. Our empirical analysis shows that the relative spread factors are important for predicting future exchange rate changes, and our extended model improves the model fitting statistically. The regression model based on the three-factor relative Nelson–Siegel model is the superior model of the extended models for three-month-ahead out-of-sample predictions, and the prediction accuracy is statistically significant from the perspective of the Clark and West statistic. For 6- and 12-month-ahead predictions, although the five-factor model is superior to the other models, the prediction accuracy is not statistically significant. Full article

This study investigated the impact of banking management on credit risk using a sample of Indian commercial banks. The study employed dynamic panel estimations to evaluate the link between banking management variables and credit risk. The empirical results show that an increase in loan portion over total assets does not necessarily increase problem loans. The findings suggest that high capital requirements and large bank size do not reduce default risk, whereas high profitability and strong income diversification policies lower the likelihood of default risk. The overall empirical results supported the “operating efficiency”, “diversification” and “too big to fail” hypotheses, confirming that credit quality in the banking industry is mainly driven by profitability, banking supervision, high credit standards and strong investment strategies. The findings are relevant to bank managers, investors and bank regulators, in formulating effective credit policies and investment strategies. Full article

The purpose of this article is to examine what affected the technical efficiency of banks in Central and Eastern European countries during the financial crisis. Firstly, this article analyzes the technical efficiency of banks in the selected countries in Central and Eastern Europe during the period 2006–2013. In this article, the technical efficiency of Central and Eastern European banks is explored in respect to the size of the banks (large or small) and their belonging in a specific group of countries. The results of the analysis show a strong association between the numbers of efficient banks and belonging of banks in the group of V4 countries (Visegrad countries are the Czech Republic, Hungary, Poland, and Slovakia). The banks in Balkan countries have a negative association with the number of efficient banks in the group; the banks in this group of countries have the highest average efficiency (when the output was net interest margin). There is a weak association between the number of efficient banks and their belonging in the group of Baltic countries. The bank efficiency and the size of the bank’s assets are also weakly associated. Secondly, the results of panel regression models for the specific groups of countries (V4, Baltic, and Balkan countries), as well as for the whole group of Central and Eastern European countries show that the customer deposits had a positive impact on the technical efficiency of banks during the financial crisis. Full article

The UK’s withdrawal from the EU will have far-reaching consequences on the European economy. However, the ultimate consequences of Brexit, especially for financial markets, depend on the final agreement, which is still under negotiation. Currently, regulated financial services can be provided across borders under simplified conditions. Without a special agreement, these EU passports cease to apply for business activities between both jurisdictions after Brexit. The EU third-country regimes for non-EEA companies are too few and too unsecure for intensive relations in trade and services. Knowing that London is the leading global financial center, an adequate agreement needs to be found, to ensure affordable and sufficient financial services for business, investors, and consumers. Unfortunately, it appears almost impossible to find solutions for the often contrary interests and various thematic areas in the remaining negotiating period—a no deal scenario becomes more likely. As a result, market participants have started to adapt structures and processes accordingly, by relocating certain functions to the EU27. Nevertheless, it is up to the negotiators to reach an agreement, which achieves the best possible outcome for all affected parties taking into account the opportunity costs of a failure in present Brexit negotiations. Full article

In today’s interrelated economies, financial information travel at speed of light to reach investors around the globe. Global financial markets experience regular shocks that transmit negative waves to other equity markets and different asset classes. Given the unique characteristics of exchange-traded funds (ETFs), this paper examines how different ETFs that are traded on London Financial center reacted to the Brexit event in 23 June 2016. The unexpected referendum result the day after is viewed as the next significant financial event since 2008. The paper employs an event study market model on daily and abnormal returns of the selected ETFs with respect to FTSE 250 around the event date. Contrary to what is expected, the world equities fund experienced significant positive abnormal return on the event day. Emerging markets again proved to be a preferred investment destination in times of financial turmoil; the emerging equities fund gained 3% while enjoying an 11.5% positive significant abnormal returns. The US T-Bond fund recorded a 9% return with a significant 7.2% abnormal return. The gold fund soared as much as 4% as investors seeks refuge from Brexit, and the oil fund retraced 1% amid concerns of slowing global demand. Full article

In this paper, we develop a contingent claim model to evaluate a bank’s equity and liabilities that integrates the premature default risk conditions with loan rate-setting behavioral mode and multiple shadow banking activities under capital regulation. The barrier options theory of corporate security valuation is applied to the contingent claims of a bank. The barrier reports that default can occur at any time before the maturity date. We focus on a type of earning-asset portfolio, consisting of balance-sheet banking activities of loans and liquid assets and shadow banking activities of wealth management products (WMPs) and entrusted loans (ELs). The optimal bank interest margin, i.e., the spread between the loan rate and the deposit rate, is derived and analyzed. The results provide an alternative explanation for the decline in bank interest margins, which better fits the narrative evidence on bank spread behavior under capital regulation in particular during a financial crisis. Raising either WMPs or ELs leads to a transfer of wealth from equity holders to the debt holders, and hence increases the deposit insurance liabilities. We also show that the multiple shadow banking activities of WMPs and ELs captured by scope equities may produce superior return performance for the bank. Tightened capital requirements may reinforce the superior return performance by a surge in shadow banking activities that makes the bank less prudent and more prone to risk-taking at a reduced margin, thereby adversely affecting banking stability. We demonstrate that financial disturbance may be created because of the potential for shadow banking activities to spill over to regular banking activities and damage the real economy. Full article

In this paper, we apply information theory measures and Markov processes in order to analyse the inequality in the distribution of the financial risk in a pool of countries. The considered financial variables are sovereign credit ratings and interest rates of sovereign government bonds of European countries. This paper extends the methodology proposed in our previous work, by allowing the possibility to consider a continuous time process for the credit rating evolution so that complete observations of rating histories and credit spreads can be considered in the analysis. Obtained results suggest that the continuous time model fits real data better than the discrete one and confirm the existence of a different risk perception among the three main rating agencies: Fitch, Moody’s and Standard & Poor’s. The application of the model has been performed by a software we developed, the full code is available on-line allowing the replication of all results. Full article

Using DCC-GARCH model, this paper finds that, since 1990, the relationship between crude oil prices and the US dollar index is time-varying, demonstrating a process of ‘very weak correlation—negative correlation—enhanced negative correlation—weakening negative correlation’, but the existing research does not provide enough reasonable explanation. Therefore, this paper proposed a ‘key mediating factors’ hypothesis which points out that whether there is a common ‘key mediating factor’ is important source of the time-varying relationship between two assets. We argue that market trend and financial market sentiment undertook the role of ‘key mediating factor’ during the period of the 2002 to the financial crisis and financial crisis to 2013, while other periods lack the ‘key mediating factors’. Full article

In developed countries, the first studies on forecasting bankruptcy date to the early 20th century. In Central and Eastern Europe, due to, among other factors, the geopolitical situation and the introduced economic system, this issue became the subject of researcher interest only in the 1990s. Therefore, it is worthwhile to analyze whether these countries conduct bankruptcy risk assessments and what their level of advancement is. The main objective of the article is the review and assessment of the level of advancement of bankruptcy prediction research in countries of the former Eastern Bloc, in comparison to the latest global research trends in this area. For this purpose, the method of analyzing scientific literature was applied. The publications chosen as the basis for the research were mainly based on information from the Google Scholar and ResearchGate databases during the period Q4 2016–Q3 2017. According to the author’s knowledge, this is the first such large-scale study involving the countries of the former Eastern Bloc—which includes the following states: Poland, Lithuania, Latvia, Estonia, Ukraine, Hungary, Russia, Slovakia, Czech Republic, Romania, Bulgaria, and Belarus. The results show that the most advanced research in this area is conducted in the Czech Republic, Poland, Slovakia, Estonia, Russia, and Hungary. Belarus Bulgaria and Latvia are on the other end. In the remaining countries, traditional approaches to predicting business insolvency are generally used. Full article