Research articles for the 2019-06-25
SSRN
In this paper, we propose a general valuation framework for option pricing problems related to skew diffusions based on a continuous-time Markov chain approximation to the underlying stochastic process. We obtain an explicit closed-form approximation of the transition density of a general skew diffusion process, which facilitates the unified valuation of various financial contracts written on assets with natural boundary behaviors, e.g. in foreign exchange market with target zones, and equity markets with psychological barriers. Applications include valuation of European call and put options, barrier and Bermudan options, zero-coupon bonds, and arithmetic Asian options. Motivated by the presence of psychological barriers in the market volatility, we also propose a novel "skew stochastic volatility" model, in which the latent stochastic variance follows a skew diffusion process. The framework is shown to be able to also handle the case of skew jump diffusions. Numerical results demonstrate that our approach is accurate and efficient, and recover various benchmark results in the literature in a unified fashion.
SSRN
A number of studies have found that the cross-section of stock returns reflects a risk premium for bearing downside risk; however, existing measures of downside risk have poor power for predicting returns. Therefore, this paper proposes a novel measure of downside risk, the ES-implied beta, to improve the prediction of the cross-section of asset returns. The ES-implied beta explains stock returns over the same period as well as the widely used downside beta,but also has strong predictive power over future returns. In the empirical analysis, while the widely used downside beta shows a weak relation with future expected returns, the ES-implied beta implies a statistically and economically significant risk premium of 0.5% per month. The predictive power of the ES-implied beta is not explained by the cross-sectional effects from the CAPM beta, size, book-to-market ratio, momentum, coskewness, cokurtosis or liquidity beta,nor does it depend on the design of the empirical analysis.
arXiv
Modeling stock returns is not a new task for mathematicians, investors, and portfolio managers, but it remains a difficult objective due to the ebb and flow of stock markets. One common solution is to approximate the distribution of stock returns with a normal distribution. However, normal distributions place infinitesimal probabilities on extreme outliers, but these outliers are of particular importance in the practice of investing. In this paper, we investigate the normality of the distribution of daily returns of major stock market indices. We find that the normal distribution is not a good model for stock returns, even over several years' worth of data. Moreover, we propose using the Laplace distribution as a model for daily stock returns.
SSRN
This paper explores whether asset market equilibria in cryptocurrency markets exist. In doing so, it distinguishes between privacy and non-privacy coins. Most recently, privacy coins have attracted increasing attention in the public debate as non-privacy cryptocurrencies, such as Bitcoin, do not satisfy some usersâ demands for anonymity. Analyzing ten cryptocurrencies with the highest market capitalization in each sub-market in the 2016â"2018 period, we find that privacy coins and non-privacy coins exhibit two distinct market equilibria. Contributing to the current debate on the market efficiency of cryptocurrency markets, our findings provide evidence of market inefficiency. Moreover, the asset market equilibrium of privacy coins appears to be unrelated to the market equilibrium in the non-privacy coin markets, implying that the privacy coin market is emerging as a distinct asset market among cryptocurrency markets.
SSRN
We conduct a comprehensive examination of the effect that boardroom independence has on corporate default risk. When measuring board independence using the regulatory definition or relying on directorâs social ties with the CEO, we find no association with default risk. In contrast, measures of independence based on board co-option are strongly and positively associated with default risk, the incidence of bankruptcy, and technical defaults. We find that our baseline results are not driven by incentive misalignment problems, but rather are the consequence of co-opted boards facilitating poorer quality decision making due to lower engagement and work ethic among board members. We find that external oversight mechanisms, in the form of institutional investors, equity analysts, takeover susceptibility, and media coverage, discipline board members and curtail the negative externalities of co-opted boards. Overall, our study documents new evidence on the adverse effect of co-opted boards on firm default probability.
SSRN
The study has motivated to assess the impacts of border fencing on the saving-spending patterns. Reviewing the related literature it has framed three hypotheses and adopting a cross-sectional study design with Convenience sampling technique, 112 respondents have been chosen and a survey has been conducted in Akhaura land customs station locality of Indo-Bangla border area of Agartala. The interview-schedule prior to the survey has been pre-tested with randomly chosen 30 respondents for assessing its reliability and validity. Significant statistical results have supported to refute all the null hypotheses and it has concluded selective demographics impact savings; construction of fencing has affected socio-economic status and saving-spending patterns of the borderland population. It has acknowledged few limitations, indicated policy implications and has sketched the roadmap for future research.
SSRN
We analyze long-term art auction sales data focusing on and around financial crisis periods with other investment returns in a major volatile emerging market. In general, Turkish art returns are either negatively correlated or at low correlation with other investments, including the equity market. We have the view that art can be considered as a hedging mechanism especially during uncertain times to enhance returns and to decrease risk of portfolios and improve diversification. The number of art transactions also increase after the crisis years, which may be a sign of liquidity requirement of some investors. First a hedonic price index is created using data from a reputable auction house using two decades of sales data (1994-2014). In line with literature, results show that art returns were lower than stock and bond returns including the contraction years of financial crisis periods of 1994, 2001 and 2009 and the major earthquake year of 1999. Although, the auction data on the crisis period is limited, results of and around crisis periods may suggest emerging markets art as a hedging instrument. The benefit is visible especially during years of contractions, which do not end with a very severe crisis, since the art auction market liquidity dries if the crisis is severe.
SSRN
This paper studies whether and when independent directors monitor effectively in companies with controlling shareholders. Exploiting a 2004 regulatory change in Hong Kong that compelled some companies to increase the number of independent directors in a triple-differences setup, we find robust evidence that post-reform treated firms received 10.9-13.5% higher market abnormal returns on their announcement of ânonproppingâ types of connected transactions. Moreover, treated firms reduced their use of connected transactions relative to armâs length transactions by 14.9% in the postreform period. Taken together, our evidence suggests that independent directors, despite chosen by controlling shareholders, can safeguard shareholder value if an apposite legal design is put in place.
SSRN
I find that corporate European leverage variation between 2007 and 2015 is largely driven by firm and industry characteristics. Conventional, time-varying firm characteristics explain as much leverage variation as country and industry fixed effects combined. Cross-sectional leverage disparities are more distinct between industries than between countries. Corporate tax rate does have a significant positive effect on leverage, as predicted by the traditional tradeoff theory. The impact is however negligibly small relative to firm- and industry-specific effects. Evidence on both the tradeoff and pecking order model is, at best, mixed. Moreover, macroeconomic conditions are largely insignificant and unable to explain leverage differences in a linear regression context. Macroeconomic effects on capital structure might however channel through firm and industry determinants, thus affecting financing choice indirectly. A more dynamic, possibly nonlinear model specification is needed. Effects of the financial crisis of 2008 and the subsequent European debt crisis are apparent across all of corporate Europe and are most severe for Southern European firms.
SSRN
The first wave of digitization has automated the front-end of banking institution, now itâs the turn for digitizing back-end and use technology in risk management for gaining a competitive advantage. Machine learning and predictive analysis are being used for assessing various credit proposals. While digitizing provides added benefits, institutions must always be cautious regarding cyber and outsourcing risk involved. Regulatory and supervisory guidance will also play prominent role in this going forward.
SSRN
I present a model to rationalize the pro-cyclical nature of executive compensation and malpractice. The model features a principal-agent setting where effort and misreporting incentives are at conflict, and investors compete for managerial talent. In equilibrium, governance standards decrease, and bonuses increase in the level of managerial talent. An increase in industry profitability, a reduction in the market rate of return, and an increase in top managerial talent increase aggregate output, malpractice, and incentive compensation. Extensions of the model generate endogenous episodes of "bonus cultures" based on short-term performance measures. Embedded into a dynamic general equilibrium with household savings and endogenous rates of return, the model reproduces the build-up of malpractice during booms and their reduction in worse states of the economy.
SSRN
Cross-border bank credit is dominated by a small number of very sizeable links between banks in one country and borrowers in another. The largest-sized cross-border banking links are mainly between major advanced economies. Concentration increased up until the Great Financial Crisis (GFC) and has abated only slightly since. It is higher for interbank credit than for credit to the non-bank sector. Despite the substantial decline in interbank credit in the aftermath of the GFC, concentration in the interbank segment has remained high.
SSRN
Earlier research documented that cryptocurrencies, including Bitcoin, have experienced dramatic fluctuations in both market capitalization and market share in recent years. Unsurprisingly, Bitcoin returns exhibit higher volatility than traditional G-10 currencies. Our paper extends earlier research and investigates the potential impact of news originating from the Bitcoin market. Confirming earlier studies, we find that Bitcoin exhibits dramatically higher volatility than the dollar factor. Surprisingly, our findings indicate that only hacking incidents that occur in the Bitcoin market result in high levels of co-movement in the risk of both markets the cryptocurrency and the G-10 currency market, whereas good news do not have such effects. Our findings may serve as an important tool for guiding policy makers who target financial stability across markets.
SSRN
Using a sample of cross-listed firms from 50 countries and a difference-in-differences approach, we provide evidence that firms tend to engage in less tax avoidance after cross-listing. This effect is more pronounced for firms with lower quality and less independent external auditors and weaker internal auditing committees prior to cross-listing, and from countries with weaker shareholder protection and disclosure requirements. The results indicate that cross-listing in the U.S. aligns managersâ and shareholdersâ interests and decreases managerial diversion. This finding is consistent with the view that both firm- and country-level corporate governance are important determinants of corporate tax-sheltering activities.
SSRN
Elasticity is a well-known concept that has been applied in numerous diverse situations. This study develops an elasticity relation between loan balances and their associated credit loss. This elasticity relation can be applied as a ârule of thumbâ approach for measurement and forecasting. The empirical results are significant at conventional levels for the elasticity.
SSRN
Our society suffers a lot from the things that are thrown uselessly; these things may be beneficial to our society. On the other hand, communities suffer a lot of waste especially plastic waste; this has led to environmental pollution and depletion of natural resources. Therefore, this research aims to achieve sustainable development and achieve part of the Saudi Arabia vision 2030. Hence we have distributed a questionnaire to 88 responders, and based on the results of this study, which shows the importance of recycling and its impact on the environment and the extent of community interest in this subject and their supporters, The Let's Recycle site, based on the results of the questionnaire, will improve waste and plastics disposal in an environmentally positive manner.The proposed system was developed using the Unified Modelling Language (UML) and Microsoft Visual Studio2010 programming language.
SSRN
I investigate the dynamics of analyst forecast errors relative to economic policy uncertainty and find a significant positive relation between economic policy uncertainty and analyst forecast errors. A doubling of economic policy uncertainty is associated with a 4.29 percentage points increase in earnings (EPS) forecast errors, and the volatility and dispersion in analyst forecast errors are positively related to the economic policy uncertainty. Earnings forecast errors are higher for firms with higher sensitivity to the economic policy uncertainty, and the uncertainty factor retains its significance when compared to other risk factors. Additionally, firms with higher idiosyncratic risks show a higher sensitivity to the economic policy uncertainty.
SSRN
We study whether managersâ industry experience matters for hedge fund activism. We find that hedge fund managers with previous executive and outside director experience in target industries hold target shares longer and are more likely to serve as directors on target boards than those without such experience. Moreover, the targets of hedge funds whose managers have industry experience realize higher acquisition announcement returns and better operating performance, and show increases in payouts and reductions in CEO compensation and investment after acquisitions. The results suggest that managersâ industry expertise is an important source of value creation in hedge fund activism.
arXiv
This note outlines a method for clustering time series based on a statistical model in which volatility shifts at unobserved change-points. The model accommodates some classical stylized features of returns and its relation to GARCH is discussed. Clustering is performed using a probability metric evaluated between posterior distributions of the most recent change-point associated with each series. This implies series are grouped together at a given time if there is evidence the most recent shifts in their respective volatilities were coincident or closely timed. The clustering method is dynamic, in that groupings may be updated in an online manner as data arrive. Numerical results are given analyzing daily returns of constituents of the S&P 500.
SSRN
Measurement of Operational Risk can be quite burdensome task as there is a paucity of historical data. Added to this is the way technology is changing the landscape of overall business processes. In many jurisdiction, even regulators have issued guidelines and sanctions for compromised data privacy or cybersecurity incidents (eg GDPR). The paper further discusses the importance of AML and KYC guidelines and how emergence of FinTech companies would facilitate KYC compliance.
SSRN
[The African Commission on Human and Peoplesâ Rights was set up pursuant to the coming into force of the African Charter on Human and Peoples Rights, saddled with the responsibilities of promoting and enforcing the rights of the African people and further checkmating human rights breaches amongst its member states. This paper will contend that the commission while performing its duties is faced with numerous challenges and setbacks which tend to dissuade it, and which have in fact, hindered the effective realization of the intendments of the African Charter and the expectations of the African people. A further detailed juxtaposition of the African system with its international counterpart is done which would serve as a benchmark in evaluating the achievements of the African Commission while enforcing human rights in the region in line with international standard and best practice.]
SSRN
Employing daily data on ten cryptocurrencies that exhibit the highest market capitalization, we find one instance of cointegration equilibrium in the 2016 ̶ 2018 period. Contrary to earlier studies that report cryptocurrency markets are developing toward market efficiency, our findings suggest that even the most liquid cryptocurrency markets are inefficient.
SSRN
This paper focuses on revisiting an old issue by advanced econometrics analysis: the risks in the U.S. stock market. We analyze the firm's exposure to exchange rate, interest rate, and market shocks by the pooled regression with the error cross-section dependency. We not only examine the exchange market, and interest rate exposure to U.S. firm values in 396 samples, but we also investigate those patterns to the firms within each of the 10 specific industries by which way we may detect the direction of capital flows before and after two well-known financial crises that occurred in 2001 and 2008. All empirical results show the significant industry-specific sensitivity to these three risks which are in marked contrast to the findings that have been assessed thus far in current literature. Our results indicate: (i) in which industry the capital flows go (industry-specific effect) before and after crises; (ii) which currency, market index, and interest rate play a more important role in the sensitivity to U.S. firm stock returns before and after crises; and (iii) the prospect on hedging portfolio setting for investors before and after crises, which is consistent with the finding of Campbell {it et al.} (2010) and Lusting {it et al.} (2011).
SSRN
Financial crisis can trigger policy reversals, i.e. they can lead to a process of re- regulation of financial markets. Using a recent comprehensive dataset on financial liberalization across 94 countries for the period between 1973 and 2015, we formally test the validity of this prediction for the member states of the European Union as well as for a global sample. We contribute by (a) using a new up-to-date dataset of reforms and crises and (b) subjecting it to a combination of difference-in-differences and local projection estimations. In the global sample, our findings consistently confirm that crises lead to a reversal of liberal reforms, suggesting that governments react to crises by re-regulating financial markets. However, in a dynamic setting with impulse-responses, we also find that these new regulations are only temporary and a liberalization process restarts a few years after a financial crisis. One decade later, financial markets have returned to their pre-crisis level of liberalization. In the EU sample, however, we do not find sufficient evidence to support these observations.
SSRN
This study investigated the relationship between the use of financial derivatives by non-financial corporations and tax aggressiveness in Brazil. In research on the American market, evidence was identified that non-financial entity users of financial derivatives were more tax aggressive. However, there is no reason to assume that this behavior is replicated in the Brazilian market, since tax legislation does not offer the same economic incentives, i.e., since it imposes limits on the tax deductibility of losses with these financial instruments, except in derivativesâ well-documented and proven use as a hedge tool. To verify this point, companies were classified into users and non-users of first-generation financial derivatives, and associated this classification with tax aggression metrics, such as total and current effective tax rate (ETR), as well as book-taxes differences (BTD). The study focus was 384 non-financial companies listed on the B3 in the period from 2005 to 2015. The results of regression analysis using a probit estimate have pointed, in a distinctly different way than the American reality, that the most tax aggressive companies tend to use fewer financial derivatives. In other words, derivatives are most used by the least tax aggressive companies. However, when the use of derivative instruments as a hedge was controlled, it was found that when a company adopts hedge accounting, it is more likely it will be more tax aggressive. The result is presumably explained by the Brazilian tax treatment that authorizes the deductibility of losses, regardless of earnings, when using the derivative as a hedge tool.
SSRN
This paper examines financial spillovers between the four largest equity markets (by market capitalization) in the GCC region using a VAR-GARCH (1,1) framework that sheds light on interdependence as well as the effects of the 2014 oil crisis. Since the UAE is a federation including two stock exchanges (Abu Dhabi and Dubai), it is possible to test whether being part of a federal union matters more than market size in terms of financial integration. Our results suggest that the latter is more important, since we could not find evidence of stronger linkages between the Abu Dhabi and Dubai markets compared to those between other markets in the region. By contrast, there are significant spillover effects, both in the mean and in the volatility, from the largest market of Saudi Arabia to Qatar and the two markets in the UAE, which confirms that market capitalization is a more important determinant of financial integration than belonging to a federal union. Further, spillovers from the larger markets have become stronger as a result of the 2014 oil crisis. Finally, there is also evidence of spillovers from the smaller to the larger markets.
SSRN
This study proposes the housing "beta" and tests whether the housing "beta" is a significant determinant for stock returns in a multifactor framework. We hypothesize that the housing market is a systematic risk factor given the impact of the housing market on the overall economy and economics growth of most countries, as well as the effect of homes in the overall wealth of individual investors. The housing market directly affect GDP growth through residential fixed investment and housing services. In addition, the housing market indirectly impacts economic activities via consumption. Our results who that the housing "bets" is positive and significant in explaining stock returns after controlling several other factors from the prior literature. This relationship is stronger as expected, during the financial crisis period. We conducted several robustness checks using a different study period and housing market indices and obtain results which are consistent with our main findings.
arXiv
The prediction of stock prices is an important task in economics, investment and financial decision-making. It has for several decades, spurred the interest of many researchers to design stock price predictive models. In this paper, the symbiotic organisms search algorithm, a new metaheuristic algorithm is employed as an efficient method for training feedforward neural networks (FFNN). The training process is used to build a better stock price predictive model. The Straits Times Index, Nikkei 225, NASDAQ Composite, S&P 500, and Dow Jones Industrial Average indices were utilized as time series data sets for training and testing proposed predic-tive model. Three evaluation methods namely, Root Mean Squared Error, Mean Absolute Percentage Error and Mean Absolution Deviation are used to compare the results of the implemented model. The computational results obtained revealed that the hybrid Symbiotic Organisms Search Algorithm exhibited outstanding predictive performance when compared to the hybrid Particle Swarm Optimization, Genetic Algorithm, and ARIMA based models. The new model is a promising predictive technique for solving high dimensional nonlinear time series data that are difficult to capture by traditional models.
SSRN
We investigate the informational content of credit default swap (CDS) spreads for future volatility of firm assets and equity, and compare our results with information provided by historical volatilities. CDS implied asset (equity) volatilities explain as much as 68.40% (only 18.56%) of the cross-sectional variation in future realized asset (equity) volatilities. This informational content is clearly superior, and almost subsumes (is similar, and complements), the informational content of historical asset (equity) volatilities. We show that these results are explained by the leverage effect component in equity volatility, and the interconnection between leverage and asset volatility documented earlier in the literature.
SSRN
This paper examines that how stability can lead to instability via our changed behavioral pattern. In the wake of globalization and interconnectedness the benefits of diversification are becoming thinner and thinner. Further, the interest rate risk faced by the banks has become more aggravated due to fast moving capital across boundaries. Finally, the landscape of cyber risk has increased considerably and banks need to provide adequate budget for the same.
SSRN
Using high-frequency transaction and Limit Order Book (LOB) data, we extend the identification dimensions of High Price Impact Trades (HPITs) by using LOB matchedness. HPITs are trades associated with disproportionately large price changes relative to their proportion of volume. We find that a higher presence of HPITs leads to a decline in volatility due to more contrarian trades against uninformed traders, but this decline varies with information environments and liquidity levels. Further, we show that more HPITs lead to higher price efficiency for stocks with greater public disclosure and higher liquidity. Our empirical results provide evidence that HPITs mainly reflect fundamental-based information in a high public information environment, and belief-based information in a low public information environment.
SSRN
French Abstract: Alors que lâimpact du Brexit sur lâAfrique anglophone était un sujet majeur dans les discussions controversées britanniques sur les avantages et les inconvénients du Brexit, les répercussions possibles sur lâAfrique francophone ont rarement été mentionnées. Pourtant, la gamme d'effet possible du Brexit est impressionnante, y inclut la renaissance des réseaux sociaux progressistes en Afrique francophone. Ces derniers demandent déjà plus de souveraineté politique et économique, par exemple vis-à -vis de la monnaie de plus en plus anachronique du F CFA. Cependant, compte tenu du manque de puissance compensatrice de la Grande-Bretagne au sein de l'UE dans le cas du Brexit, le réseau trouble de la Françafrique pourrait également être revitalisé et consolidé. Enfin, le Brexit et ses effets de propagation pourraient également avoir une incidence négative sur les droits de l'homme acquis, tant en Europe qu'en Afrique. Le retrait du Royaume-Uni en général aura des implications sur lâ éthique jusque-là partagée. En fait, le Brexit constitue un pas en arrière dans la promotion d'un climat politique et socioculturel humanitaire. Ce dernier pourrait ressembler dans le futur à celui de l'Afrique du Sud de l'apartheid. Cela inclut la poursuite d'objectifs ultranationalistes et la compromission des droits de l'homme établis, par exemple en ce qui concerne l'inégalité croissante et la croisade contre les infidèles et les étrangers. Plus généralement, le Brexit aura également un impact négatif sur l'éthique acquise concernant la participation populaire, tant en Europe qu'en Afrique.English Abstract: Whereas the impact of Brexit on Anglophone Africa was a major issue in the controversial British discussions on the pros and cons of Brexit, possible repercussions on French-speaking Africa have been rarely mentioned up to now. Yet, the range of possible Brexit effect is impressive, including the revival of progressive social networks in Francophone Africa. The latter are already demanding more political and economic sovereignty, for example with respect to the increasingly anachronistic F CFA currency. Yet, in view of the lack of countervailing power of Britain within the EU in the case of Brexit, the murky network of Françafrique could be re-vitalized and consolidated as well. Finally, the Brexit and its spread-effects could also impact negatively on acquired human rights, both in Europe and in Africa. The withdrawal in general will have widely disregard implications for hitherto shared ethics. In fact, the Brexit constitutes a retrograde step in promoting a political and socio-cultural climate which could become similar to that of Apartheid South Africa. This includes the pursuit of ultranationalist goals and compromising on established human rights, for example with respect to growing inequality and the crusade against infidels and outsiders. More generally, the Brexit will also impact negatively on acquired ethics concerning popular anticipation, both in Europe and in Africa.
arXiv
Lead-lag relationships among assets represent a useful tool for analyzing high frequency financial data. However, research on these relationships predominantly focuses on correlation analyses for the dynamics of stock prices, spots and futures on market indexes, whereas foreign exchange data have been less explored. To provide a valuable insight on the nature of the lead-lag relationships in foreign exchange markets here we perform a detailed study for the one-minute log returns on exchange rates through three different approaches: i) lagged correlations, ii) lagged partial correlations and iii) Granger causality. In all studies, we find that even though for most pairs of exchange rates lagged effects are absent, there are many pairs which pass statistical significance tests. Out of the statistically significant relationships, we construct directed networks and investigate the influence of individual exchange rates through the PageRank algorithm. The algorithm, in general, ranks stock market indexes quoted in their respective currencies, as most influential. Altogether, these findings suggest that all market information does not spread instantaneously, contrary to the claims of the efficient market hypothesis.
arXiv
We introduce a computational framework for dynamic portfolio valuation and risk management building on machine learning with kernels. We learn the replicating martingale of a portfolio from a finite sample of its terminal cumulative cash flow. The learned replicating martingale is given in closed form thanks to a suitable choice of the kernel. We develop an asymptotic theory and prove convergence and a central limit theorem. We also derive finite sample error bounds and concentration inequalities. Numerical examples show good results for a relatively small training sample size.
arXiv
We analyze the behavior of approximate Bayesian computation (ABC) when the model generating the simulated data differs from the actual data generating process; i.e., when the data simulator in ABC is misspecified. We demonstrate both theoretically and in simple, but practically relevant, examples that when the model is misspecified different versions of ABC can yield substantially different results. Our theoretical results demonstrate that even though the model is misspecified, under regularity conditions, the accept/reject ABC approach concentrates posterior mass on an appropriately defined pseudo-true parameter value. However, under model misspecification the ABC posterior does not yield credible sets with valid frequentist coverage and has non-standard asymptotic behavior. In addition, we examine the theoretical behavior of the popular local regression adjustment to ABC under model misspecification and demonstrate that this approach concentrates posterior mass on a completely different pseudo-true value than accept/reject ABC. Using our theoretical results, we suggest two approaches to diagnose model misspecification in ABC. All theoretical results and diagnostics are illustrated in a simple running example.
SSRN
Available empirical evidence on the significance of the (micro) risk-taking channel of monetary policy is not sufficient to indicate a threat to financial stability. This research has the objective of determining whether conventional and unconventional monetary policies have resulted in systemic risk-taking. To that end, it uses statistical measures that capture systemic risk in the banking sector of the euro area in all its forms allowing for the time-varying non-linearities and feedback effects typical of financial markets. The methodology is a structural factor-augmented vector autoregressive (FAVAR) model. The main result is that there is systemic risk-taking in the euro area banking sector. It takes the form of an increase in the banking sectorâs vulnerability via contagion and interconnectedness. Banksâ balance sheets, however, do not account for the full transmission from (micro) risk taking to systemic risk-taking confirming the importance of accounting for time-varying non-linearities and feedback effects. The main policy implication is that persistently accommodative monetary policy geared toward preserving price stability may face a trade-off with financial stability. In that case, monetary policy will require coordination with macro-prudential policy.
SSRN
This paper uses a Markov-switching non-linear specification to analyse the effects of cyber attacks on returns in the case of four cryptocurrencies (Bitcoin, Ethernam, Litecoin and Stellar) over the period 8/8/2015 - 28/2/2019. The analysis considers both cyber attacks in general and those targeting cryptocurrencies in particular, and also uses cumulative measures capturing persistence. On the whole, the results suggest the existence of significant negative effects of cyber attacks on the probability for cryptocurrencies to stay in the low volatility regime. This is an interesting finding, that confirms the importance of gaining a deeper understanding of this form of crime and of the tools used by cybercriminals in order to prevent possibly severe disruptions to markets.
arXiv
Attempts to allocate capital to a selection of different investment objects often face the problem that investors' decisions are made under limited information (no historical return data) and an extremely limited timeframe. Nevertheless, in some cases, rational investors with a certain level of experience are able to ordinally rank investment alternatives through relative assessments of the probability that an investment will be successful. However, to apply traditional portfolio optimization models, analysts must use historical (or simulated/expected) return data as the basis for their calculations. Our paper develops an alternative portfolio optimization framework that is able to handle this kind of information (given by the ordinal ranking of investment alternatives) and to calculate an optimal capital allocation based on a Cobb-Douglas function. Considering risk-neutral investors, we show that the results of this portfolio optimization model usually outperform the output generated by the (intuitive) Equally Weighted Portfolio (EWP) of the different investment alternatives, which is the result of optimization when one is unable to incorporate additional data (the ordinal ranking of the alternatives). In a further extension, we show that our model is also able to address risk-averse investors to capture diversification benefits.
SSRN
We study the relative risk aversion of an individual with particular social preferences: his wellbeing is influenced by his relative wealth, and by how concerned he is about having low relative wealth. Holding constant the individual's absolute wealth, we obtain two results. First, if the individual's level of concern about low relative wealth does not change, the individual becomes more risk averse when he rises in the wealth hierarchy. Second, if the individual's level of concern about low relative wealth intensifies when he rises in the wealth hierarchy and if, in precise sense, this intensification is strong enough, then the individual becomes less risk averse: the individual's desire to advance further in the wealth hierarchy is more important to him than possibly missing out on a better rank.
SSRN
We analyze a setting in which an actor chooses between N ex ante identical options. She can exert effort to learn about the quality of each option, but can ultimately choose only one. There are up to N! unique optimal effort vectors, and each is asymmetric: a large amount of effort is expended learning about one arbitrarily chosen option, less on another, even less on a third, etc. This implies asymmetric likelihoods of each item being chosen. If the actor has an infinitesimal bias in favor of one option, then the actor selects an effort vector that maximizes the likelihood of her favored option being chosen. Small biases are magnified, sometimes enormously. We also show that a glass ceiling can arise, in which favored types are increasingly prevalent as one ascends the corporate ladder. These results have implications for portfolio selection (e.g., home bias, socially responsible investment funds), hiring (e.g., CEO choice, the glass ceiling), start-up funding, and a variety of other applications.
SSRN
The research focuses to report the association of demographics and household budgetary allocation and to appreciate the influence of diverse expenses on the latter. Using Cross-Sectional research design, a survey is executed with interview-schedule comprising 47 questions to collect data from 125 randomly selected respondents of Mohanpur, a town of North-Eastern Indian state of Tripura. The data is tested for its reliability and validity. A model is formed and data reduction is carried out. Cross Tabulations and Multiple Regressions are performed to test the null hypotheses. The empirical results document that demographics and different expenses have statistical significance in the household budgetary allocation. Policy relevance are drawn and the study acknowledges a few short comings like the small sample size, defined study area, study period, selective variables and the limitations of statistical tools while generalising the results. It also indicates the road map for future researches.
SSRN
The purpose of this study is to incorporate some of the influential findings in the forecasting literature in an integrated framework to examine whether a real-time optimizing investor can benefit from the stock market by allocating assets based on a predictive model that only uses industry portfolio and interest rate data as predictors. The proposed method aims to allow economic performance measures to have an impact on all steps of model building from variable selection to model combination without undermining the statistical performance measure. The predictors/models are selected from almost 300 variables by a multi-objective genetic algorithm considering both statistical and economic measures. I chose a subset of models from the Pareto-optimal frontier using a number of heuristic methods from the multi-criteria decision making (MCDM) literature and the concept of knee-point of a curve. The forecast of the next period is obtained by combining the forecasts of the selected subset of predictive linear regressions using a Bayesian variable selection and model averaging method called Stochastic Search Variable Selection (SSVS). The investorâs utility function is used to obtain the weight of a risky asset based on the output of the forecasting model. All aforementioned steps only use data up to the current time and before the forecasting time. The results are compared to common benchmarks such as the buy-and-hold strategy and additional benchmarks that are based on the findings of previous literature. The findings indicate that using the proposed approach can improve the portfolio performance measures relative to all benchmarks.
SSRN
I develop a consumption-based model with dynamically inconsistent preferences where risk aversion decreases with the delay. With a naive representative agent, this model generates high equity premia and low interest rates. Moreover, the term structure of equity premia is decreasing. Finally, risk aversion and the market price of risk are counter-cyclical, provided the elasticity of intertemporal substitution is below unity. The preferences are a simple transformation of the standard model. As in the habit formation model of Campbell and Cochrane (1999), risk aversion depends on past consumption. As in the long-run risks model of Bansal and Yaron (2004), counter-cyclicality will depend on news about long-term consumption prospects.
RePEC
Portugal's export performance over the past decade has been impressive, helping to reduce external imbalances. This partly owed to a sequence of structural reforms that benefited the productivity of the export sector and led to an increase in its size. Nonetheless, exports as a share of GDP and the stock of foreign direct investment remain below that of other comparable small European economies. Further shifting the orientation of the economy to the external sector is vital for Portugal given the strong link between trade openness and GDP per capita. To do this, policymakers must ensure that policy settings incentivise exporting firms to expand and improve their competitiveness, both through lower price and improved quality. For example, regulatory barriers that reduce competition in professional services should be lowered to improve the cost and quality of intermediate inputs. Increasing the efficiency of domestic infrastructure is also key, especially through competition-enhancing reforms to the port sector. To further differentiate and improve Portuguese export products, skills in the business sector need to be enhanced through better-targeted lifelong learning opportunities. At the same time, there is a need to focus innovation policies on raising the participation of small and medium enterprises in innovative activities.
arXiv
Since the quasiconvex risk measures is a bigger class than the well known convex risk measures, the study of quasiconvex risk measures makes sense especially in the financial markets with volatility. In this paper, we will study the quasiconvex risk measures defined on a special space $L^{p(\cdot)}$ where the variable exponent $p(\cdot)$ is no longer a given real number like the space $L^{p}$, but a random variable, which reflects the possible volatility of the financial markets. The dual representation for this quasiconvex risk measures will also provided.
SSRN
This paper considers the link between macroeconomic policy and housing demand in an upper middle-income transition economy, Kazakhstan. The paper further explores price cointegration and contagion across cities. We find evidence that some parts of the housing market lead others but that, overall, regional housing markets are only weakly interlinked. The markets also tend to respond weakly to policy interventions â" a matter of possible concern to the nationâs central bank.
SSRN
The rapid journey from central planning to EU (euro area) membership stress-tested the social learning processes of FTEs. The desire to be anchored to the West, and to enter the EU spurred major reform waves and led to the introduction of best practice institutions very rapidly. This process most likely accelerated social learning, but apparently in many FTEs this learning was not fast enough to keep pace with the rapid reforms, leaving best-practice institutions with social norms that were not sufficiently strong to maintain them. So not surprisingly, widespread reversals emerged in the region, especially when the crisis hit these countries. In other words, reversals seem an inherent characteristic of the FTEs' journey towards a modern social market economy. Reform reversals can be formal reversals, which change legislation (or formal rules), or behavioral reversals, which erode the quality of an institution by materially changing the way it works, or a combination of the two. Spillovers, from formal to behavioral reversals (and vice versa), from reversals in one area to another one, and from one institution to another can play an important role in reform reversals by strongly impacting their nature and dynamics. In many cases, it was this interaction of reversals in different sectors that created a full-blown reform reversal episode. The financial sector seems particularly prone to behavioral reversals, both in public and private institutions. The Washington institutions played a dominant role in shaping the transition process. Following the start of the EU accession process, however, the EU gradually took over as the dominant external anchor. The EU acted as a strong anchor that could prevent or reverse formal reform reversals in areas covered by EU law. The anchoring role of the EU was however much weaker in the case of behavioral reversals. Our analysis naturally leads to the conclusion that the ultimate solution to prevent reform reversals is to accelerate social learning processes, particularly among parallel communities. It is also important to focus on the quality and internal coherence of reforms and newly created institutions.
SSRN
A portfolio replication approach is used to determine the implied cost of risk for a customer's portfolio. This allows us to quantify with a single number, the extent an investment manager is delivering on the twin goals of (1)~Sharpe ratios as high as possible, and (2) having actual risk as close as possible to target risk. A CAPM-like world for credit portfolios is assumed: idiosyncratic risk may be diversified away and only the remaining systematic risk is priced. The broad idea is however more widely applicable.
SSRN
It is widely acknowledged now, by many financial and macroeconomists, that in the past, only little attention has been paid to âsystemic riskâ and âfinancial contagionâ. Rochet and Tirole point out that the âanxiety about systemic risk is perhaps strongest among bank executives and regulatorsâ. Galati and Moessner state that âthere has been a fundamental lack of understanding of system-wide riskâ. Battiston et al. confirm the latter statement by saying that the ârecent financial crisis has shown that systemic risk has been dramatically underestimatedâ. Fouque and Langsam emphasis this fact when they say that the â[r]ecent history has shown us not only the enormous cost of a systemic crisis but also how woefully unprepared and ill-equipped governments and private markets have been to prevent systemic crisis or minimize its impactâ. According to Geanakoplos et al. Macroeconomists were completely surprised by the financial crisis of 2007-2009. Up until then they had concentrated on macroeconomics with a capital M: global imbalances, interest rates, monetary policyâ. Therefore, as Martınez-Jaramillo et al. put it, the âunderstanding of systemic risk is of central importance for maintaining financial stabilityâ.
arXiv
As systemic risk has become a hot topic in the financial markets, how to measure, allocate and regulate the systemic risk are becoming especially important. However, the financial markets are becoming more and more complicate, which makes the usual study of systemic risk to be restricted. In this paper, we will study the systemic risk measures on a special space $L^{p(\cdot)}$ where the variable exponent $p(\cdot)$ is no longer a given real number like the space $L^{p}$, but a random variable, which reflects the possible volatility of the financial markets. Finally, the dual representation for this new systemic risk measures will be studied. Our results show that every this new systemic risk measure can be decomposed into a convex certain function and a simple-systemic risk measure, which provides a new ideas for dealing with the systemic risk.
SSRN
Risk is building in the leveraged loan and collateralized loan obligation (âCLOâ) markets. These two markets are connected: leveraged loans are being repackaged into CLOs just as mortgages and mortgage-backed securities were used to create collateralized debt obligations (âCDOsâ), the financial products at the heart of the financial crisis 11 years ago.There are important differences but also troubling parallels between the leveraged loan/CLO markets and the earlier mortgage/CDO markets. One alarming similarity is the decline in leveraged loan underwriting standards: the market is now dominated by âcovenant-lite loans.â Covenant-lite loans permit greater leverage by borrowers and remove an early warning system for lenders.Purchases of CLOs by banks and other regulated financial institutions made in order to game crucial regulatory capital requirements (âregulatory capital arbitrageâ) remain a significant concern.Like mortgages and CDOs, leveraged loans and CLOs form a pipeline or system. Disruptions at either end of the system can cause financial havoc on the other end and then ricochet back. This is akin to a coiled spring or âcrisis accordion.âLosses or disruptions in the leveraged loan/CLO markets, even if they do not approach the levels of mortgages/CDOs in the global financial crisis could still be significant, e.g., amplifying a recession. We should be humble about our ability to predict the upper bound of financial market disruptions or crises. Some tranches of CLO securities appear not to trade actively. Many CLO securities trade on opaque markets lacking transparent prices. A lack of trading of CLO securities undermines the economic rationale of these securities, as well as their safety and favorable regulatory treatment. A lack of transparent prices means that neither the marketplace nor regulators can rely on prices to police risk-taking in the CLO market.Regulators must monitor and analyze data on leveraged loans and CLO markets. The OFR needs cooperation from other financial regulators in assessing risk in these markets. Lack of data sharing among financial regulators remains a crucial weakness. The OFR needs an independent source of funding. Regulators need minimum standards in their examinations with respect to assessing bank exposure to leveraged loans.I also recommend:- Stress testing of financial markets, not just individual institutions;- Requiring financial regulators to conduct war games to prepare for market disruptions;- Underscoring that the burden is on financial institutions to prove that leveraged loans and CLOs are safe rather than on regulators to prove that they are unsafe.If data gathering reveals significant systemic risk in leveraged lending/CLO markets, regulators should use a mix of tools, including limiting bank investments in CLOs, enhanced and countercyclical capital requirements, and the Volcker Rule âcovered fundsâ provisions.
SSRN
In this paper, we investigate the association between banks' operational losses and macroeconomic variables, Governance Indicators and banks' specific covariates. We do so in a panel data setting, which includes both censoring (since losses below a given threshold are not reported) and attrition (since banks may not operate in a given Country over some fraction of the data temporal dimension). We develop an asymptotic theory to estimate parameters of interest and their standard errors consistently, allowing us to conduct valid inference.The results of our analysis uncover interesting links between macroeconomic variables, Governance Indicators and banks' losses, whereas banks' specific variables seem to play a less prominent role.
RePEC
Beyond bitcoin, blockchain technology has acquired attention and importance in its own right. Today, it is conceptually accepted that blockchain stands out as a disruptive technology that will change a number of processes in financial services and could in turn impact corporate governance. This paper explores the recent applications of blockchain technology in financial services and outlines regulatory responses, to set the scene for future work in this area on corporate governance. This paper provided background for the Corporate Governance Committee's roundtable discussion on blockchain technology and the implementation of the G20/OECD Principles of Corporate Governance on 10 April 2018. A subsequent presentation of the paper was given at the OECD Workshop on Digital Financial Assets on the 16 May 2018, and at the OECD-Asian Roundtable on Corporate Governance in Malaysia on 7-8 November 2018. This work also provides a contribution to the work of the OECD Blockchain Policy Centre.
SSRN
We provide evidence that direct real estate investments are less profitable and more risky in the long run than previously thought. We hand-collect property-level data on realized income, expenses, and transaction prices from the archives of four large institutional investors in the U.K. â" historically important Oxbridge colleges â" for the period 1901â"1970. Gross income yields mostly fluctuate around 5%, but trend to lower (higher) levels for agricultural and residential (commercial) real estate near the end of our sample period. Operating costs mean that net yields are about one third lower than gross yields on average. Long-term real income growth rates are between -1.0% and 0.0% for the three main property types. Together these findings imply limited long-run capital gains and real annualized net total returns of less than 4% across all property types. Moreover, we find substantial volatility in net income streams and variation in relative price levels across transacted properties, revealing the considerable idiosyncratic risks associated with real estate investments.
SSRN
The study explores how central bank communication affects the exchange rate. The paper constructs sentiment by employing textual information from the European Central Bank press conferences. Using high frequency data, we find that a more positive/negative sentiment is associated with appreciation/depreciation of euro, and de- creasing/increasing exchange rate volatility. We apply Latent Dirichlet Allocation ap- proach to decompose central bank communication into a variety of topics. The results indicate that EUR-USD responds most strongly to topics of economic growth, mone- tary policy stance central bank liquidity provision, lending activities, and risk outlook) while the response of the exchange rate mutes with historical or current economic discussion (e.g. monetary policy decision, monetary policy assessment).
SSRN
We study the impact that two trading rule changes in the interdealer spot foreign exchange market, a reduction in the "tick size'' and a subsequent increase, had on the trading behavior of various types of market participants. We find that the most notable impact of the tick size reduction was a substantial increase in the liquidity demand of high-frequency traders (HFTs), not the decrease in their liquidity provision predicted by recent literature. We show that this change in behavior was linked to the richer information environment that arose after the tick size reduction and to the ability of faster traders to exploit it. Following the tick size decrease, and owing importantly to the increase in liquidity consumption by HFTs, the role of the spot market in price discovery dropped relative to that of the futures market. This points to the need for a balanced market ecology in financial markets where fast and slow traders coexist.