# Research articles for the 2019-10-10

A Holistic Approach to the Institutional Architecture of Financial Supervision and Regulation in the EU
Ringe, Wolf-Georg,Morais, Luis Silva,Ramos Muñoz, David
SSRN
A growing consensus has emerged in the post-crisis financial regulatory agenda that the European architecture of financial supervision and regulation is far from ideal. Rather than moving to a â€˜holisticâ€™, cross-sectoral regime such as the â€˜twin peaksâ€™ model, the post-crisis reform simply upgraded the previous supervisory colleges to EU agencies, resulting in the three sectoral bodies for banking (EBA), securities markets (ESMA), and insurance (EIOPA). The major risk of such a sectoral architecture is that separate agencies may fail to recognise any cross-sectoral problems and risks that are evolving, may fail to adequately address financial conglomerates, and may more generally encounter fundamental challenges in adopting a more holistic approach to financial regulation and supervision.This paper examines the case for adopting a more integrated architecture in the EU. We show that lawmakers were not only unable to seize opportunities for reform â€" largely, due to path dependencies â€" but have also let those opportunities pass by when they presented themselves â€" such as Brexit or the ESAs review. The present political climate does not leave us to expect any significant reform anytime soon. Therefore, we strongly argue that the reform architecture of the EU should be modified incrementally, and without need for Treaty revision. Hence, a bottom-up experimentalist approach appears as a viable path towards the implementation of a twin peaks model, or, possibly as a more viable and desirable path, a hybrid model that nevertheless preserves some of its main advantages.

A Note on Markowitz Model
Vidal-GarcÃ­a, Javier
SSRN
The Markowitz's model can be very useful in practice. Portfolio managers and private investors can use it easily having the necessary software for its correct application. In our study we show that the Markowitz model is able to provide portfolios that beat reference market portfolios (FTSE 100 and FTSE All-Share Index), obtaining higher returns with a lower risk. Both the FTSE 100 and the FTSE All-Share Index are not efficient portfolios, not reflecting the behaviour of the theoretical market portfolio. Therefore, the Markowitz model, as a tool for investment selection, provides portfolios with better performance than market benchmarks.

A Note to 'Do ETFs Increase Volatility?': An Improved Method to Predict Assignment of Stocks into Russell Indexes
Ben-David, Itzhak,Franzoni, Francesco A.,Moussawi, Rabih
SSRN
A growing literature uses the Russell 1000/2000 reconstitution event as an identification strategy to investigate corporate finance and asset pricing questions. To implement this identification strategy, researchers need to approximate the ranking variable used to assign stocks to indexes. We develop a procedure that predicts assignment to the Russell 1000/2000 with significant improvements relative to previous approaches. We apply this methodology to extend the tests in Ben-David, Franzoni, and Moussawi (2018).

C, Viswanatha Reedy
SSRN
Maximizing shareholder value has become the new corporate paradigm. Corporations in world wide have started disclosing EVA information from the beginning of 90s as a measure of corporate performance. It is believed that market value of a firm (i.e., the shareholdersâ€™ wealth) would increase with the increase in EVA. Many studies conducted in US and India also confirmed this belief. EVA is a residual income that subtracts the cost of capital from the operating profits generated by a business. The present study makes an attempt to find the relevance of Stewart's claim that market value of the firm is largely driven by its EVA generating capacity in the Indian context. Based on the data from the annual reports of Dr Reddyâ€™s laboratories Ltd, over a period of five years, the study shows that market value of a firm can be well predicted by estimated future EVA streams. The study has also found that market value of the firm is explained more by current operational value than future growth value of the company.

Artificial Neural Network For Option Pricing With And Without Asymptotic Correction
Funahashi, Hideharu,Uzawa, Ken
SSRN
This paper proposes a mixed approach of asymptotic expansion (AE) and artificial neural network (ANN) methods for option pricing in order to improve computational speed, stability, and approximation accuracy. In practice, there is wide use of complex stochastic volatility models (SVMs) which can allow for skew and smile shapes. However, under these models, it is usually hard to obtain analytical solutions for options written on the asset price. AE can compute option prices and their sensitivities effectively, but it can usually only compute a finite sum of terms of the complete of the solution because, as the expansion order increases, both analytical and numerical calculations become tedious and messy and the computational cost grows exponentially. On the other hand, using ANN, one can separate the pricing procedure into two steps: (1) approximating ANN that can be trained off-line and (2) using the ANN predicted option price obtained on-line. The off-line procedure has an extremely high computational cost because it requires tens to hundreds of thousands of Monte Carlo (MC) or PDE numerical simulations in order to train several hidden layers and several dozens of nodes. Moreover, deep learning (DL) for option pricing shows unstable and poor quality because the sensitivity of the derivatives price with respect to the input often takes a bell-shape, which induces rapid changes in value. By combining the strong points and making up for the weak points of the two methods, our new approach offers the following improvements: (1) much less training data, layers, and nodes are required: (2) the training becomes more robust: and (3) it speeds up both the off-line and the on-line calculations.

Behavioral Finance and the Architecture of the Asset Management Industry
Verlaine, Michel
SSRN
The standard portfolio approach assumes that investors maximize Expected Utility functions and that the Markowitz Mean-Variance Standard Portfolio Optimization approach can be applied. Behavioral Research, however, indicates that investorsâ€™ behavior with respect to risk or uncertainty is not consistent with EU. Notably, decision makers transform probabilities. Most of the academic literature integrating those aspects, however, focuses on so-called financial market anomalies but does not focus on the structural impact those behavioral aspects might have, notably in terms of industrial organization of the asset management industry. This paper analyzes the industrial organization of the asset management industry and argues that the architecture of the asset management industry is inconsistent with the standard EU framework. The origin of the industrial organization of the asset management industry stems from the convexity of the Flow-performance relationship, which is due to Prospect Theory effects. The convexity of the Flow-performance relationship explains the inflation of Mutual Funds and Fund families, a phenomenon inconsistent with the Mutual Fund Separation Theorem.

Block Ownership, Investment and Uncertainty: Evidence from U.S. Firms
Abhyankar, Abhay,Li, Jinlin
SSRN
We study how macroeconomic, firm-level and higher-order uncertainty affects real corporate investment in firms with different levels of active and passive block ownership. Our ownership data are extracted from statutory SEC filings that block-holders are required to file indicating their active or passive status. Our main results are as follows. First, investment is more sensitive, to firm-level compared to macroeconomic and higher-order uncertainty shocks. Second, one standard deviation change in all types of uncertainty shocks has a higher negative effect on investment rate for firms held by active block-holders than for those held by passive block holders. Higher-order uncertainty has the most negative impact followed by macro-economic and firm-level uncertainty. Third, using a Bartik-style instrument for firm-level uncertainty we find that our main results still hold. Taken together, these results imply that the stated intentions of block-holders in statutory filings have an impact on how firm investment reacts to future economic uncertainty. Our results have implications for the current debate about the effects of ownership concentration in publicly listed firms.

Blockchain: A Misunderstood Digital Revolution. Things You Need to Know about Blockchain
SSRN
Blockchain and distributed ledger technology (DLT) are used interchangeably. In the aftermath of the 2008 global financial crisis, Bitcoin gave birth to blockchain, or vice versa. A decade has passed since the launch of the first successful cryptocurrency in January 2009 by a mysterious creator under the alias Satoshi Nakamoto. Now along with Bitcoin, 2,915 altcoins are trading with a combined market cap of $222 billion, Bitcoinâ€™s market cap alone is$150 billion (67.6% of the market). Blockchainâ€™s potential is much bigger than Bitcoin; if regulatory uncertainty alleviates, the blockchainâ€™s value can easily increase by hundred-fold to $3 to$4 trillion dollars by 2030. Although financial sector leads blockchain adoption, blockchainâ€™s opportunities in non-financial sectors are immense. In the simplest terms, blockchain is a distributed ledger made up of two parts, blocks containing of data and a chain that holds them together. Blocks are like storage units that store anything of value related to minting coins (i.e. Bitcoin) via a mining process and keeps a chronology of transactions (e-commerce); chain can be metaphorically viewed as a string that holds all the blocks together, created using a consensus algorithm based on proof-of-work (PoW) or proof-of-stake (PoS). Blockchains are often organized into three most common forms; as such, public blockchain (purely peer-to-peer, decentralized and permissionless; any miner (i.e. node) at any time can access the network to add, verify or validate data without restrictions), private blockchain (permissioned, it is controlled by a central authority which grants permission to pre-selected people who can add and verify records), and consortium blockchain (also formed as permissioned, a group of nodes governs all transactions). It is true that blockchain provides anonymity making identities of its users pseudonymous; but contrary to popular belief, blockchain will not possibly solve all our problems and a permissionless blockchain will not guarantee complete privacy since all transactions become visible to all nodes of the network.

Book Review: Valentino Cattelan (Editor) Islamic Social Finance: Entrepreneurship, Cooperation and the Sharing Economy, Routledge, London, 2018.
Belabes, Abderrazak
SSRN
The aim of this review is to discuss the notion of Islamic social finance, or what social finance is according to some researchers in Islamic finance, and the theoretical corpus on which it is based, as discussed in the book, both on the conceptual (tawá¸¥Ä«dÄ« paradigm) and teleological (maqÄá¹£id al-SharÄ«Ê¿ah) levels. This review goes beyond the approach that Islamic social finance refers to the social dimension of entrepreneurship financed Islamically, as advocated in the book. With reference to specialized literature in social and solidarity economy, it is argued that the object of social finance should focus on how social organizations â€" primarily awqÄf which dates back to ancient times â€" provide funding to continue to play a role in societies. This means that the waqf is more than a simple financing instrument or financial engineering tool and that the financial aspect is not the only or the main resource in the life of societies. Waqf and all other social institutions feed above all on the social link which is an inestimable treasure and provides protection for life. Would we exchange that which is better (social relationship) for that which is lower (mÄl)?

Can Ethics be Taught? Evidence from Securities Exams and Investment Adviser Misconduct
Kowaleski, Zachary T,Sutherland, Andrew,Vetter, Felix
SSRN
We study the consequences of a 2010 change in the investment adviser qualification exam that reallocated coverage from the rules and ethics section to the technical material section. Comparing advisers with the same employer in the same location and year, we find those passing the exam with more rules and ethics coverage are one-fourth less likely to commit misconduct. The exam change appears to affect advisersâ€™ perception of acceptable conduct, and not just their awareness of specific rules or selection into the qualification. Those passing the rules and ethics-focused exam are more likely to depart employers experiencing scandals. Such departures also predict future scandals. Our paper offers the first archival evidence on how rules and ethics training affects conduct and labor market activity in the financial sector.

Common Ownership and Competition in Mergers and Acquisitions
SSRN
We examine the impacts of common ownership on competition in the takeover market. We find that one common owner between the acquirer and potential competing acquirers reduces the likelihood that the target receives a competing bid by 45 percent. The common ownership effects are robust to a long battery of additional tests and are causal according to two identification strategies, one based on mergers between financial institutions that shock common ownership and the other based on lagged common ownership as an instrumental variable. Abated competition between potential acquirers leads to better acquisition deals with greater synergy gains, and enables the acquirer shareholders to obtain a larger share of the synergy gains.

Creating a unique mobile financial services framework for Myanmar: A Review
Dr Ma Nang Laik,Chester Mark Hong Wei
arXiv

Myanmar is languishing at the bottom of key international indexes. United Nations considers the country as a structurally weak and vulnerable economy. Yet, from 2011 when Myanmar ended decades of military rule and isolationism and transited towards democracy, its breakneck development has led to many considering the country to be one of the final frontiers for growth in the Asia region. One such industry that has benefitted from the opening of the country is telecommunications. The mobile penetration rate at 4.8% in 2011 has increased significantly to 90% in 2016. Despite renewed optimism and development in the economy, one statistic remains disappointing. According to a report by Asian Development Bank (ADB), only 23% of the adult population have access to a bank account. This highlights a need to reach out and increase access to financial resources to a population that is severely unbanked and underbanked. This creates an interesting proposition of allowing both the telecommunications and financial sector to form the mobile financial services (MFS) sector and meet the need of improving access to financial resources for the population. This report explores the government role in supporting, growing and sustaining the MFS sector and conducts a comparative research into Singapore, Malaysia and Thailand to understand the steps taken by these governments to develop their own Financial Technology (FinTech), specifically MFS, industry. Finally, the report will present preliminary recommendations that the Myanmar government could consider implementing to drive growth in its MFS sector.

Cross-sectional Learning of Extremal Dependence among Financial Assets
Xing Yan,Qi Wu,Wen Zhang
arXiv

We propose a novel probabilistic model to facilitate the learning of multivariate tail dependence of multiple financial assets. Our method allows one to construct from known random vectors, e.g., standard normal, sophisticated joint heavy-tailed random vectors featuring not only distinct marginal tail heaviness, but also flexible tail dependence structure. The novelty lies in that pairwise tail dependence between any two dimensions is modeled separately from their correlation, and can vary respectively according to its own parameter rather than the correlation parameter, which is an essential advantage over many commonly used methods such as multivariate $t$ or elliptical distribution. It is also intuitive to interpret, easy to track, and simple to sample comparing to the copula approach. We show its flexible tail dependence structure through simulation. Coupled with a GARCH model to eliminate serial dependence of each individual asset return series, we use this novel method to model and forecast multivariate conditional distribution of stock returns, and obtain notable performance improvements in multi-dimensional coverage tests. Besides, our empirical finding about the asymmetry of tails of the idiosyncratic component as well as the market component is interesting and worth to be well studied in the future.

Dynamic Ownership, Private Benefits, and Stock Prices
Corvino, Raffaele
SSRN
I quantify private benefits of control, and their impact on stock prices, by estimating a structural model of optimal shareholding using data on the ownership dynamics of Italian public companies. The results show that controlling shareholders generally have positive and persistent impact on stock prices, and the impact is larger during the last Eurozone debt crisis. The results imply that controlling shareholders are particularly beneficial for the rest of the company shareholders during negative economic cycles. I also provide evidence of a synergistic effect when the controlling shareholder is a corporation.

Economics of Technology, Securities and Capital Markets
Malinova, Katya
SSRN
In this survey, I focus on the economic implications of FinTech innovation for securities and capital markets. I outline the key economic issues that have emerged in this area, review the literature that has studied these issues, and discuss open questions. The survey is structured around the key technological developments that affect capital market infrastructure and data analytics. The topics include electronic trading venues and high-frequency trading, blockchain technology, cloud computing, and machine learning and artificial intelligence. We further discuss new investment and financing tools, which were enabled by recent technological advances, such as exchange-traded funds and blockchain-based assets.

Estimating and decomposing most productive scale size in parallel DEA networks with shared inputs: A case of China's Five-Year Plans
arXiv

Attaining the optimal scale size of production systems is an issue frequently found in the priority questions on management agendas of various types of organizations. Determining the most productive scale size (MPSS) allows the decision makers not only to know the best scale size that their systems can achieve but also to tell the decision makers how to move the inefficient systems onto the MPSS region. This paper investigates the MPSS concept for production systems consisting of multiple subsystems connected in parallel. First, we propose a relational model where the MPSS of the whole system and the internal subsystems are measured in a single DEA implementation. Then, it is proved that the MPSS of the system can be decomposed as the weighted sum of the MPSS of the individual subsystems. The main result is that the system is overall MPSS if and only if it is MPSS in each subsystem. MPSS decomposition allows the decision makers to target the non-MPSS subsystems so that the necessary improvements can be readily suggested. An application of China's Five-Year Plans (FYPs) with shared inputs is used to show the applicability of the proposed model for estimating and decomposing MPSS in parallel network DEA. Industry and Agriculture sectors are selected as two parallel subsystems in the FYPs. Interesting findings have been noticed. Using the same amount of resources, the Industry sector had a better economic scale than the Agriculture sector. Furthermore, the last two FYPs, 11th and 12th, were the perfect two FYPs among the others.

Firm Financing and the Relative Demand for Labor and Capital
ElFayoumi, Khalid
SSRN
Using a European panel of mostly small and medium firms between 2004 and 2013, this paper introduces new stylized facts on how firms' relative demand for labor and capital evolved as their capital structure adjusted to the events of 2008 crisis. It also provides the first micro-level evidence that firms substitute capital for labor when their cost of financing rises, and that this substitution effect is driven by an incentive to raise holdings of collateralizable capital. Identification of exogenous variations in firm financing costs relies on the heterogeneous effects of ECB monetary policy surprises on financing costs (credit channel) across the firm distribution; less credit worthy firms experience a larger unexpected change in their borrowing and equity issuance costs in reaction to ECB surprises, generating exogenous variations in financing costs across and within firms. The analysis supports the message that maintaining a well functioning credit market should be an essential part of policies aiming at increasing the labor share of economic growth.

Fractal Markets, Frontiers, and Factors
Berghorn, Wilhelm,Schulz, Martin T.,Otto, Sascha
SSRN
In this work we develop an alternative view to the modern finance theory that essentially suggests equilibria in efficient markets by taking a risk-based view of asset returns in stock markets. Based on a mathematical analysis of stock market data using multi-scale approaches, we will alternatively describe markets and factors as trend-based fractal processes and analyze well-known factor premiums, which leads to a return-based view of markets and a model of investors reacting to market environments. We conclude that markets could be viewed alternatively as fractal, non-stationary and, at most, asymptotically efficient.

In for a Bumpy Ride? Cash Flow Risk and Dividend Payouts
Andres, Christian,Hofbaur, Ulrich
SSRN
This paper investigates the relation between cash flow risk and dividend policy. Consistent with the notion that shareholders expect stable dividends once a payout has been established, firms with high cash flow risk are more reluctant to initiate dividend payouts. For dividend payers, we find changes in cash flow risk to have an asymmetric effect on dividend changes: While decreases in cash flow risk lower the propensity to cut dividends, firms are not more likely to increase dividends if cash flow risk decreases. Analyzing dividend smoothing, we further document a positive effect of cash flow risk on the speed of dividend adjustments, indicating that higher cash flow risk is partly passed on to shareholders via more volatile dividends.

Informed Trading, Order Flow Shocks And The Cross-section Of Expected Returns In Borsa Ä°stanbul
TiniÃ§, Murat,Salih, AslÄ±han
SSRN
This paper examines the relationship between information asymmetry and stock returns in Borsa Ä°stanbul. For all stocks that are traded in Borsa Ä°stanbul between March 2005 and April 2017, we estimate the probability of informed trading (PIN) by Duarte and Young (2009) factorization and a grid-search algorithm similar to Yan and Zhang (2012). Firm level cross-sectional regressions indicate a statistically insignificant relationship between PIN estimates and future returns. Moreover, univariate and multivariate portfolio analyses assert that investors that hold stocks that have high information asymmetry do not obtain significant future returns. Consequently, our results suggest that information asymmetry proxied by PIN is a firm-specific risk and can be eliminated with portfolio diversification. Findings are robust to different factorization in estimating PIN and free of any bias due to trade classification algorithms, boundary solutions, floating point exceptions and systematic order flow shocks.

Intraday Time Series Momentum: International Evidence
Li, Zeming,Sakkas, Athanasios,Urquhart, Andrew
SSRN
Gao et al. (2018) provide strong evidence of intraday time-series momentum (ITSM) in US ETFs, in which the first half-hour return of the trading day significantly predicts the last half-hour return. In this paper, we examine the pervasiveness of ITSM around the world by studying 16 developed markets. We find strong economic and statistical evidence of ITSM across markets. Low correlation between them offers substantial diversification benefits to investors. By adopting various portfolio construction techniques we demonstrate that investing in ITSM globally results in superior performance than when investing in individual market ITSM or global passive strategies. A global equally-weighted ITSM portfolio cannot be explained by global equity factors. Instead, it generates significant alphas to which we show that a time-varying factor is a major contributor. We also show that the global ITSM is related to infrequent rebalancing (Bogousslavsky, 2016) and investor inattentiveness (Da et al., 2014).

Islamic Microfinance and Rehabilitation Model for the Slum and Floating Population by Waqf Funds, the Case of Bangladesh: A Proposal for Muslim Countries
Hossain, Basharat
SSRN
This paper designs a conceptual model of Islamic microfinance and rehabilitation by using the waqf funds for the slum and floating population. It analyzes both the primary and the secondary data on the current status of Islamic microfinance coverage (in thirteen countries), waqf estates (in seven countries), and the slum and floating population in thirty-five Muslim countries of the world. The primary data was accumulated on 150 microfinance borrowers and 100 non-borrowers of Bangladesh. This paper presents a multifunctional structure of an autonomous waqf management institution to execute the model of this paper. This institution will be formed by the joint venture of the government, the national, as well as international Islamic agencies. Furthermore, this model will be implemented through five stages, the revival and registration of the waqf estate, accumulation of funds, initiating the Islamic microfinance and rehabilitation for the slum population, and finally, forward linkage that may help the slum people to contribute to the society.

Market Timing and Time Frequency
Vidal-GarcÃ­a, Javier,Vidal, Marta
SSRN
This paper shows the usefulness of selecting the appropriate time frequency to examine mutual fund market timing. Using a sample of daily returns for the UK, we find evidence of the benefit to increase the temporal frequency of the observations to estimate market timing as results present a greater significance when we use daily data in the analysis. We show that using daily instead of monthly observations increases the number of significant estimates of market timing ability. This suggests that the return frequency is important when examining mutual funds market timing performance. Another conclusion we can draw from this study is the small proportion of mutual funds that manage to beat the market by performing correct timing strategies, thus the UK mutual fund market confirms the conclusion from previous studies in another markets.

Measuring the Effect of Digitalization Efforts on Bank Performance
Kriebel, Johannes,Debener, JÃ¶rn
SSRN
There is an ongoing debate on whether digitalization can increase bank performance and more specifically which technologies do so. The debate to date suffers from a lack of data. We suggest new measures of digitalization efforts in banks by using text mining methods on annual reports. Our results on all banks listed on the New York Stock Exchange imply that digitalization efforts improve performance for some successful cases but not in all cases. Practitioners should therefore carefully monitor the implementation of digitalization efforts. Considering technologies, business intelligence and IT infrastructure are most crucial in generating profits. Distribution channels are less important in comparison.

Microfoundations of Discounting
arXiv

An important question in economics is how people choose between different payments in the future. The classical normative model predicts that a decision maker discounts a later payment relative to an earlier one by an exponential function of the time between them. Descriptive models use non-exponential functions to fit observed behavioral phenomena, such as preference reversal. Here we propose a model of discounting, consistent with standard axioms of choice, in which decision makers maximize the growth rate of their wealth. Four specifications of the model produce four forms of discounting -- no discounting, exponential, hyperbolic, and a hybrid of exponential and hyperbolic -- two of which predict preference reversal. Our model requires no assumption of behavioral bias or payment risk.

Option-Implied Volatility-Managed Asset Pricing Risk Factors and Resurrection of the Value Factor
Grobys, Klaus
SSRN
Option-implied volatility-managed risk factor models produce higher maximum squared Sharpe ratios than the recently proposed six-factor model, which is used as a benchmark model in this study. A model that incorporates option-implied volatility-managed risk factors based on dynamic scaling factors that systematically overestimate the expected market risk, as measured by the VIX, is superior to other asset pricing model specifications. After the death of the value factor has been repeatedly declared, it is surprising news that multivariate spanning regressions reveal that both the option-implied volatility-managed momentum and value factor are the only option-implied volatility-managed risk factors that generate alpha and that are therefore the cause of the asset pricing modelâ€™s superiority.

Passive Blockholders, Informational Efficiency of Prices, and Firm Value
Chung, Kee H.,Lee, Choonsik,Shen, Carl Hsin-han
SSRN
This paper analyzes the role of passive blockholders in corporate governance using data on Schedule 13G filings. We show that firm value increases with the number and aggregate ownership of passive blockholders after controlling for other possible determinants of firm value. More importantly, we show that the informational efficiency of prices (IEP) increases with the number and aggregate ownership of passive blockholders, and IEP is a channel through which passive blockholders affect firm value. Overall, our results suggest that managers perform better when stock prices reflect the economic consequences of their actions promptly and accurately through information-based trading of blockholders.

Policies for stronger productivity growth in Latvia
Yashiro, Naomitsu,Klein, Caroline,Rastrigina, Olga,Thiemann, Ania
RePEC
Latvia's productivity growth is held back by weak innovation and inefficient resource allocation. The shortage of skilled workers which constrains innovation and the adoption of digital technologies must be addressed through further alignment of vocational and tertiary education with labour market demand. Strengthening the innovation ecosystem by improving the quality of research and collaboration between firms and research institutions would help to diffuse digital technologies more widely across the economy. Fighting widespread informality, improving the low debt recovery through a more efficient insolvency regime, and reducing substantial state ownership would improve the allocation of resources. Latvia also relies heavily on EU funds to finance its important structural policies. The continuity of the most effective EU funded policy instruments needs to be ensured in the medium term, by integrating them into the national budget.This Working Paper relates to the 2019 OECD Economic Survey of Latvia(http://www.oecd.org/economy/surveys/latvia-economic-snapshot/)

Price Gap Anomaly in the US Stock Market: The Whole Story
Plastun, Oleksiy,Sibande, Xolani,Gupta, Rangan,Wohar, Mark E.
SSRN
This paper analyses the price gap anomaly in the US stock market (comprised of the DJI, S&P 500 and NASDAQ) covering the period 1928 to 2018. This paper aims to investigate whether or not price gaps create market inefficiencies. Price gaps occur when the current dayâ€™s opening price is different from the previous dayâ€™s closing price due orders placed before the opening of the market. Several hypotheses are tested using various statistical tests (Studentâ€™s t-test, ANOVA, Mann-Whitney test), regression analysis, and special methods, that is, the modified cumulative returns and the trading simulation approaches. We find strong evidence in favour of abnormal price movements after price gaps. We observe that during a gap day prices tend to change in the direction of the gap. A trading strategy based on this anomaly was efficient in that its results were not random, indicating that this market was not efficient. The momentum effect was found to be temporary and no evidence of seasonality in price gaps was found. Lastly, our results were also contrary to the myth that price gaps tend to get filled.

Properly Discounted Asset Prices Are Semimartingales
BÃ¡lint, DÃ¡niel Ãgoston,Schweizer, Martin
SSRN
We study general undiscounted asset price processes, which are only assumed to be non-negative, adapted and RCLL (but not a priority semimartingales). Traders are allowed to use simple (piecewise constant) strategies. We prove that under a discounting-invariant condition of absence of arbitrage, the original prices discounted by the value of any simple strategy with positive wealth must follow semimartingales. As a side result, we establish two corresponding versions of the fundamental theorem of asset pricing that involve supermartingale discounters with some additional strict positivity property.

Reassessing Common Ownership: Corrections to Azar, Schmalz, and Tecu (2018)
Egland, Mark,Hearey, Owen,Schatzki, Todd,Verbeck, Jr, Channing
SSRN
Azar, Schmalz, and Tecu (2018, â€œASTâ€) purport to show a positive relationship between ticket prices and common ownership in the U.S. airline industry. We replicate ASTâ€™s results and show that their conclusion is a result of incorrect and unsubstantiated assumptions about:(1) financial incentives of asset managers, (2) corporate control and financial incentives during bankruptcy, and (3) changes in industry structure over time. After correcting any one of these flawed assumptions, we conclude there is no statistically significant association between ticket prices and common ownership.

Regulatory Capital Planning and Deferred Tax Assets in a Post-Financial Crisis Environment
Eastman, Evan,Ehinger, Anne,Meegan, Cathryn
SSRN
In this study we examine the role of accounting discretion in calculating regulatory capital in financial institutions by specifically examining deferred tax assets (DTAs). We use the insurance industry as our setting as regulators substantially relaxed rules relating to DTA inclusion in regulatory capital calculations during and following the financial crisis. Many DTAs depend upon future taxable income for realization, making them less liquid relative to other assets. We examine whether firms use the increased discretion in regulation to increase the proportion of their regulatory capital relating to DTAs and find evidence that they do so. As DTAs are less liquid relative to other assets, our study raises the concern that financial institutions may appear more financially stable than the reality of their underlying economic condition. Consistent with this concern, we find firms with relatively low levels of regulatory capital included higher levels of DTAs in their regulatory capital calculations relative to their peers. We also document that higher levels of DTAs are associated with a higher likelihood of insolvency and ratings agencies are not incorporating DTAs into their life insurer rating criteria. Our study has important implications for regulators considering changes to capital standards for other financial institutions.

Risk as Challenge: A Dual System Stochastic Model for Binary Choice Behavior
Samuel Shye,Ido Haber
arXiv

Challenge Theory (CT), a new approach to decision under risk departs significantly from expected utility, and is based on firmly psychological, rather than economic, assumptions. The paper demonstrates that a purely cognitive-psychological paradigm for decision under risk can yield excellent predictions, comparable to those attained by more complex economic or psychological models that remain attached to conventional economic constructs and assumptions. The study presents a new model for predicting the popularity of choices made in binary risk problems. A CT-based regression model is tested on data gathered from 126 respondents who indicated their preferences with respect to 44 choice problems. Results support CT's central hypothesis, strongly associating between the Challenge Index (CI) attributable to every binary risk problem, and the observed popularity of the bold prospect in that problem (with r=-0.92 and r=-0.93 for gains and for losses, respectively). The novelty of the CT perspective as a new paradigm is illuminated by its simple, single-index (CI) representation of psychological effects proposed by Prospect Theory for describing choice behavior (certainty effect, reflection effect, overweighting small probabilities and loss aversion).

Simultaneous Two-Dimensional Continuous-Time Markov Chain Approximation of Two-Dimensional Fully Coupled Markov Diffusion Processes
Xi, Yuejuan,Ding, Kailin,Ning, Ning
SSRN
In this paper, we propose a novel simultaneous two-dimensional continuous-time Markov chain (CTMC) approximation method, in contrast to the existing double-layer approach, to approximate the general fully coupled Markov diffusion processes which cover all the classical models. Extensive simulation studies on different kinds of financial option pricing problems in the European, American, and barrier settings, confirm that the proposed methodology has superior accuracy and outperforms the widely applicable Monte Carlo (MC) simulation approach consistently.

Sovereign Risk Spill-Overs to Banking Sectors in Central America and the Caribbean
Robinson, C Justin,Bangwayo-Skeete, Prosper,Noel, Dorian M.,Brei, Michael
SSRN
Banking regulations (such as, risk-based capital framework and reserve requirements) have had the unintended consequence of incentivizing banks to hold more sovereign debt on their balance sheets than suggested by their strategic motives. As a result, bank stability now depends more heavily than before on the creditworthiness of governments. Despite this new reality, the impact of sovereign credit ratings on bank stability is still hotly debated in the Financial Economics literature. As this debate ensues little is known about the impact of sovereign credit ratings on bank stability in the Central American and Caribbean context, where sovereign debt crises have been frequent.This paper, therefore, examines the impact of sovereign credit ratings on bank stability as measured by non-performing loans (NPLs), in the Central American and Caribbean region. We use bank data on 24 countries from Central America and the Caribbean spanning the period from 1998â€"2014. Our results highlight the presence of a significant impact of sovereign rating downgrades on bank stability. The risk spill-over is particularly pronounced in countries that are externally vulnerable, measured by the degree of global exposure, and where financial disclosure requirements are weak. This strongly supports the global coordinated approach on macroprudential oversight.

Stock market microstructure inference via multi-agent reinforcement learning
J. Lussange,S. Bourgeois-Gironde,S. Palminteri,B. Gutkin
arXiv

Quantitative finance has had a long tradition of a bottom-up approach to complex systems inference via multi-agent systems (MAS). These statistical tools are based on modelling agents trading via a centralised order book, in order to emulate complex and diverse market phenomena. These past financial models have all relied on so-called zero-intelligence agents, so that the crucial issues of agent information and learning, central to price formation and hence to all market activity, could not be properly assessed. In order to address this, we designed a next-generation MAS stock market simulator, in which each agent learns to trade autonomously via model-free reinforcement learning. We calibrate the model to real market data from the London Stock Exchange over the years 2007 to 2018, and show that it can faithfully reproduce key market microstructure metrics, such as various price autocorrelation scalars over multiple time intervals. Agent learning thus enables model emulation of the microstructure with superior realism.

Taxation and Social Justice
Boyan Durankev
arXiv

The link between taxation and justice is a classic debate issue, while also being very relevant at a time of changing environmental factors and conditions of the social and economic system. Technologically speaking, there are three types of taxes: progressive, proportional and regressive. Although justice, like freedom, is an element and manifestation of the imagined reality in citizens minds, the state must comply with it. In particular, the tax system has to adapt to the mass imagined reality in order for it to appear fairer and more acceptable.

Understanding Distributional Ambiguity via Non-robust Chance Constraint
Qi Wu,Shumin Ma,Cheuk Hang Leung,Wei Liu
arXiv

We propose a non-robust interpretation of the distributionally robust optimization (DRO) problem by relating the impact of uncertainties around the distribution on the impact of constraining the objective through tail probabilities. Our interpretation allows utility maximizers to figure out the size of the ambiguity set through parameters that are directly linked to the chance parameters. We first show that for general $\phi$-divergences, a DRO problem is asymptotically equivalent to a class of mean-deviation problems, where the ambiguity radius controls investor's risk preference. Based on this non-robust reformulation, we then show that when a boundedness constraint is added to the investment strategy. The DRO problem can be cast as a chance-constrained optimization (CCO) problem without distributional uncertainties. Without the boundedness constraint, the CCO problem is shown to perform uniformly better than the DRO problem, irrespective of the radius of the ambiguity set, the choice of the divergence measure, or the tail heaviness of the center distribution. Besides the widely-used Kullback-Leibler (KL) divergence which requires the distribution of the objective function to be exponentially bounded, our results apply to divergence measures that accommodate well heavy tail distribution such as the student $t$-distribution and the lognormal distribution. Comprehensive testings on synthetic data and real data are provided.