Showing papers on "Market liquidity published in 2019"
TL;DR: This article developed an asset pricing model with flexible heterogeneity in asset demand across investors, designed to match institutional and household holdings, with a portfolio choice model implying characterist characteristics of asset demand.
Abstract: We develop an asset pricing model with flexible heterogeneity in asset demand across investors, designed to match institutional and household holdings. A portfolio choice model implies characterist...
230 citations
TL;DR: In this article, the authors used C o V a R to estimate the conditional tail-risk in the markets for bitcoin, ether, ripple and litecoin and found that these cryptocurrencies are highly exposed to tail risk within cryptomarkets.
202 citations
TL;DR: In this paper, the authors compare the time-varying weak-form efficiency of Bitcoin prices in terms of US dollars (BTCUSD) and euro (BTCEUR) at a high-frequency level by using permutation entropy.
175 citations
TL;DR: In this article, the authors investigate the cross-sectional determinants of corporate bond returns and find that downside risk is the strongest predictor of future bond returns, and introduce common risk factors based on the prevalent risk characteristics of corporate bonds (downside risk, credit risk, and liquidity risk).
167 citations
TL;DR: Li et al. as mentioned in this paper proposed an entropy-based TOPSIS model to measure the maturity of carbon market, which used the entropy method to objectively weight the indicators, and the TOPsIS method to measure maturity of the carbon market.
138 citations
TL;DR: In this article, a detailed observation by including 973 forms of cryptocurrency and 30 international indices from a dynamic perspective was made. And the empirical results mainly show that cryptocurrency is a safe haven but not a hedge for most of the international indices.
131 citations
TL;DR: In this article, the causality of geopolitical risk, oil prices and financial liquidity in Saudi Arabia was assessed by means of wavelet analysis, which aims to investigate whether such relationships support the monetary equilibrium model.
131 citations
TL;DR: In this paper, the authors study a model where two countries each issue sovereign bonds to satisfy investors' safe asset demands, and the countries differ in the float of their bonds and their resources/fundamentals available to rollover debts.
Abstract: What makes an asset a “safe asset”? We study a model where two countries each issue sovereign bonds to satisfy investors' safe asset demands. The countries differ in the float of their bonds and their resources/fundamentals available to rollover debts. A sovereign's debt is more likely to be safe if its fundamentals are strong relative to other possible safe assets, but not necessarily strong on an absolute basis. Debt float can enhance or detract from safety: If global demand for safe assets is high, a large float can enhance safety. The large float offers greater liquidity which increases demand for the large debt and thus reduces rollover risk. If demand for safe assets is low, then large debt size is a negative as rollover risk looms large. When global demand is high, countries may make fiscal/debt-structuring decisions to enhance their safe asset status. These actions have a tournament feature, and are self-defeating: countries may over-expand debt size to win the tournament. Coordination can generate benefits. The model sheds light on the effects of “Eurobonds” – i.e. a coordinated Euro-area-wide safe bond design. Eurobonds deliver welfare benefits only when they make up a sufficiently large fraction of countries' debts. Small steps towards Eurobonds may hurt countries and not deliver welfare benefits.
125 citations
TL;DR: In this article, the authors provide a thorough assessment of Islamic banks' (IBs) liquidity risk compared to conventional banks (CBs) by employing a simultaneous structural equation approach on a comprehensive dataset of 52 IBs and CBs from selected Organization of Islamic Cooperation Countries for the period of 2007-2015.
118 citations
TL;DR: In this paper, the authors examined the determinants of profitability of Indian commercial banks and found that bank size, the number of branches, assets management ratio, assets quality ratio, and liquidity ratio are the most important bank-specific determinants that affect the profitability as measured by ROA.
Abstract: The current study examines the determinants of profitability of Indian commercial banks. The analysis is conducted over a period of 10 years in which the Indian banking sector has gone under different changes such as demonetization and issues related to banking sector sustainability and banking sector frauds. The analysis is based on balanced panel data over a period ranging from 2008 to 2017 for 69 commercial Indian banks. Profitability of Indian banks is measured by two proxies, namely, return on assets (ROA) and return on equity (ROE), whereas bank size, assets quality, capital adequacy, liquidity, operating efficiency, deposits, leverage, assets management, and the number of branches are used as bank‐specific factors. Further, a set of macroeconomic determinants such as gross domestic product, inflation rate, interest rate, exchange rate, financial crisis, and demonetization are used as independent variables. Stationary test along with pooled, fixed, random effect models and panel correction standard error are used in this study. The results revealed that bank size, the number of branches, assets management ratio, operational efficiency, and leverage ratio are the most important bank‐specific determinants that affect the profitability of Indian commercial banks as measured by ROA. Furthermore, among the bank‐specific determinants, the results revealed that bank size, assets management ratio, assets quality ratio, and liquidity ratio are found to have a significant positive impact on ROE. With regard to the macroeconomic determinants, the results revealed that the inflation rate, exchange rate, the interest rate, and demonization are found to have a significant impact on ROA. However, in the case of ROE, the results show that all macroeconomic determinants except demonization have a significant impact on the bank's profitability as measured by ROE.
104 citations
TL;DR: In this paper, the authors derive sufficient conditions for equivalence and apply them in the context of the Chicago Plan, cryptocurrencies, the Indian de-monetization experiment, and Central Bank Digital Currency (CBDC).
TL;DR: In this article, the authors used a data set covering one quarter of the U.S. general-purpose credit card market and found that 29% of accounts regularly make payments at or near the minimum payment.
TL;DR: Denis et al. as mentioned in this paper studied the negative causal impact of insider stock pledging on shareholders' wealth and found that margin calls triggered by severe price falls exacerbate the crash risk of pledging firms.
Abstract: We study a widespread yet under-explored corporate governance phenomenon: the pledging of company stock by insiders as collateral for personal bank loans. Utilizing a regulatory change that exogenously decreases pledging, we document a negative causal impact of pledging on shareholder wealth. We study two channels that could explain this effect. First, we find that margin calls triggered by severe price falls exacerbate the crash risk of pledging firms. Second, since margin calls may cause insiders to suffer personal liquidity shocks or to forgo private benefits of control, we hypothesize and find that pledging is associated with reduced firm risk-taking.Received March 2, 2017; editorial decision January 24, 2019 by Editor David Denis. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
TL;DR: The difference in transactions costs likely reflects the differences in market structures, since underlying technological changes have likely reduced costs of matching buyers and sellers as discussed by the authors, which is not the case in the over-the-counter market.
TL;DR: In this article, the authors examine whether common ownership affects voluntary disclosure and find that common ownership is associated with increased market liquidity, i.e., instances where investors simultaneously own significant stakes in competing firms.
TL;DR: Li et al. as mentioned in this paper investigated the influences of credit policy and financial constraints on tangible and research & development investments from China's firm-level renewable energy industry using dynamic panel generalized moments of method (GMM) analysis.
01 Jul 2019
TL;DR: Reinforcement learning in stock/forex trading is still in its early development and further research is needed to make it a reliable method in this domain.
Abstract: Recently there has been an exponential increase in the use of artificial intelligence for trading in financial markets such as stock and forex. Reinforcement learning has become of particular interest to financial traders ever since the program AlphaGo defeated the strongest human contemporary Go board game player Lee Sedol in 2016. We systematically reviewed all recent stock/forex prediction or trading articles that used reinforcement learning as their primary machine learning method. All reviewed articles had some unrealistic assumptions such as no transaction costs, no liquidity issues and no bid or ask spread issues. Transaction costs had significant impacts on the profitability of the reinforcement learning algorithms compared with the baseline algorithms tested. Despite showing statistically significant profitability when reinforcement learning was used in comparison with baseline models in many studies, some showed no meaningful level of profitability, in particular with large changes in the price pattern between the system training and testing data. Furthermore, few performance comparisons between reinforcement learning and other sophisticated machine/deep learning models were provided. The impact of transaction costs, including the bid/ask spread on profitability has also been assessed. In conclusion, reinforcement learning in stock/forex trading is still in its early development and further research is needed to make it a reliable method in this domain.
TL;DR: Korajczyk et al. as mentioned in this paper utilized a unique data set that provides all orders and trades, with (masked) trader identity known, for all equities traded on Canadian exchanges.
Abstract: We utilize a unique data set that provides all orders and trades, with (masked) trader identity known, for all equities traded on Canadian exchanges. We identify and characterize designated market makers (DMMs) and high frequency traders that act as market makers (HFTs). We also identify large institutional trade packages and characterize how HFTs and DMMs provide liquidity to these trades. Both HFTs and DMMs provide liquidity to large institutional trades, with HFTs providing substantially more. In high volume stocks, HFTs reduce liquidity provision for “stressful” trades by 42 percent while DMM liquidity provision remains mostly unchanged. Implementation shortfall (price) of large trades is significantly affected by HFT (and to a lesser extent DMM) choice of liquidity provision during the trade. ∗We thank the Investment Industry Regulatory Organization of Canada (IIROC) for providing us with access to the data used for this study and Victoria Pinnington and Helen Hogarth of IIROC for answering our innumerable questions regarding the data and Canadian market structure details. We also thank Torben Andersen, Oleg Bondarenko, Kevin Crotty, Hanh Le, and Brian Weller for useful comments on the paper. All errors are our own. †Kellogg School of Management, Northwestern University, 2001 Sheridan Road, Evanston, IL, 60208-2001; tel: (847) 491-8336; e-mail: r-korajczyk@kellogg.northwestern.edu. ‡University of Illinois at Chicago, College of Business, Department of Finance, 601 South Morgan Street, Chicago, IL, 60607-7121; tel: (312) 355-4372; e-mail: murphyd@uic.edu.
TL;DR: In this paper, the authors develop an analytical framework to systematically review the literature on stranded asset risk across the investment chain: for physical assets, securities, investment portfolios, the creditworthiness of financial institutions, and the stability of the financial system.
Abstract: Investment in sustainable and renewable technologies must be doubled if globally agreed climate targets are to be met. The ways in which stranded asset risk from climate change could impact the risk-return preferences and capital allocation decisions is therefore receiving increased attention. We develop an analytical framework to systematically review the literature on stranded asset risk across the investment chain: for physical assets, securities, investment portfolios, the creditworthiness of financial institutions, and the stability of the financial system. We find that there has been a strong focus on evaluating stranding risk for illiquid assets at the earlier points in the investment chain: fossil fuel reserves and the energy generation sector. These studies identify stranding risk for high cost or carbon-intensive reserves and for energy generation technologies dependent on these resources, in particular coal. There is also some evidence that owners of financial assets could also be exposed to stranding risk because the valuations of coal, oil and gas companies could be overstated, particularly for undiversified companies with high capital exposure to carbon-intensive resources. Moving along the investment chain, there are fewer studies quantifying risks for the creditworthiness of counterparties, asset portfolio managers, financial institutions and the stability of the financial system. While there is some evidence that stranding risk may be an issue for financial institutions and investment portfolios, other studies find that risks to more liquid assets are less acute and can be managed by diversification strategies. These are areas meriting further research.
TL;DR: In this article, the effects of uncertainty on market liquidity using Hurricane Sandy as a natural experiment were tested using a difference-in-differences setting, using the market reactions of Real Estate Investment Trusts (REITs) with and without properties in the widely published evacuation zone of New York City prior to landfall.
TL;DR: The authors found that Islamic banks create more liquidity per unit of assets than conventional banks, primarily on the asset side of the balance sheet, and that CB liquidity creation results in reduced national financial stability, particularly in high-income countries.
TL;DR: In this article, the authors examined the intraday variables of the leading Bitcoin exchange with the highest information share over 4 years' worth of data to reveal how they have developed over time.
TL;DR: In this paper, the authors examined the relationship between non-performing loans (NPLs) and financial (sector) development and found that NPLs are negatively associated with regulatory capital ratio and bank liquidity.
Abstract: This paper examine the relationship between non-performing loans (NPLs) and financial (sector) development. The study is motivated by the scant knowledge on how financial development structures impact non-performing loans across banking sectors around the world. In the pooled full country empirical analysis, we find that (i) private credit to GDP ratio is positively associated with non-performing loans, (ii) NPLs are inversely associated with bank efficiency, loan loss coverage, banking competition and banking system stability, and (iii) NPL is positively associated with foreign bank presence, banking crises and bank concentration. We also find that efficient and stable banking sectors experience higher non-performing loans. In the regional empirical analysis, NPLs are negatively associated with regulatory capital ratio and bank liquidity while the graphical analysis show that NPLs are inversely related to financial development and profitability in several regions.
TL;DR: In this paper, a path analysis with software Linear Structural Relationship (LISREL) version 8.8 was employed to analyze the data and proved that leverage is a variable which mediates the effect of liquidity, size and profitability on the firm value.
Abstract: The objective of this present research is to obtain empirical evidence of the effects of leverage in mediating the firm size, profitability and liquidity on the firm value. The object of the research was go public property and real estate firms in the Indonesia Stock Exchange in the period of 2012-2016. Thirty one firms serving as the sample were taken using a purposive sampling method. A path analysis with software Linear Structural Relationship (LISREL) version 8.8 was employed to analyze the data. The results of the research showed that it was merely profitability variable which directly gave a significant and positive effect on the firm value. Whereas liquidity and size variables directly gave a negative, although insignificant effect. The results of the testing proved that leverage is a variable which mediates the effect of liquidity, size and profitability on the firm value.
Keywords: liquidity, Leverage, firm size, profitabilit, firm value.
TL;DR: This paper studied credit booms exploiting the Spanish matched credit register over 2001-2009 and found that higher bank real-estate exposure increases risk-taking, by relaxing standards of existing borrowers, and by expanding credit on the extensive margin to first-time borrowers that default substantially more.
TL;DR: In this paper, the authors assess the performance of markets for Guarantee of Origin certificates in twenty European countries, and construct four market performance indicators and analyse their development over 2001-2016: the churn rate, price volatility, the certification rate and the expiration rate.
TL;DR: In this paper, the authors found that changes in global factors do not affect all emerging markets equally, even for the same type of flow, and that EMs relying more on global mutual funds are more sensitive in their gross equity and bond inflows.
TL;DR: In this paper, the influence of bank capital, bank liquidity level and credit risk on the profitability of commercial banks in the postcrisis period between 2011 and 2017 is explored, and the authors explore the influence on bank profitability.
Abstract: The purpose of this study is to explore the influence of bank capital, bank liquidity level and credit risk on the profitability of commercial banks in the postcrisis period between 2011 and 2017 i...
TL;DR: In this article, the authors analyze whether high-frequency traders (HFTs) lean against large institutional orders that execute through a series of child orders, and they find that HFTs initially lean against these orders but eventually change direction and take positions in the same direction for the most informed institutional orders.
Abstract: Liquidity suppliers lean against the wind. We analyze whether high-frequency traders (HFTs) lean against large institutional orders that execute through a series of child orders. The alternative is HFTs trading with the wind, that is, in the same direction. We find that HFTs initially lean against these orders but eventually change direction and take positions in the same direction for the most informed institutional orders. Our empirical findings are consistent with investors trading strategically on their information. When deciding trade intensity, they seem to trade off higher speculative profits against higher risk of being detected and preyed on by HFTs.
TL;DR: In this article, the authors investigated the extent to which herding towards the market consensus for Russian stocks is driven by fundamental and non-fundamental factors and found evidence that investors on the Moscow Exchange herd without any reference to fundamentals during unanticipated financial crises coupled with high uncertainty, in falling markets, and during days with extreme upward oil price movements.