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This study aims to investigate the determinants of credit spreads in hotel loans securitized into commercial mortgage-backed securities (CMBS) between 2010 and 2015.

The sample represents 1,579 US hotel fixed interest rate whole loans with an aggregate mortgage value of $26.6bn at loan origination. The relationship between credit spreads and property, loan and market characteristic is examined via multiple regression analysis. Additionally, the method of 2-stage least squares is used to control for endogeneity bias and identify the effect of the loan-to-value (LTV) ratio on credit spreads.

The multiple regression models explain 80 per cent of the variation in credit spreads and show a significant association of credit spreads with hotel and loan characteristics and market conditions. The findings indicate the debt coverage ratio to be the most important predictor of credit spreads followed by the loan maturity term, implied capitalization rate, LTV and yield curve. The results show the debt yield premium to be a stronger predictor of credit spreads than the debt yield ratio. The spread between the debt yield ratio and mortgage interest rate could be used in future research as an instrumental variable to identify the effect of the LTV on credit spreads.

This study is limited to the CMBS market and the period after the financial crisis. Additional limitations include sample selection bias, exclusion of multi-property loans and variable interest rate loans.

Interest rate increases in an expanding economy would likely increase the cost of borrowing for hotel owners leading to higher debt service payments and lower profitability. If an increase in interest rates is offset by a decline in credit spreads, hotel owners will still benefit from the ensuing stability in borrowing interest rates. The evidence also suggests that CMBS lenders favor select service and extended stay hotels. Owners and operators of these efficient and profitable hotels will likely obtain loans with lower credit spreads given their lower risk of default.

The current study provides evidence on the effects of loan and property characteristics in the pricing of loan risk and serves to inform CMBS market participants about the factors that drive credit spreads in hotel mortgage loans.

To test the effects of underpricing and share retention (i.e. the proportion of shares retained by the pre‐initial‐public‐offering (IPO) owners) on IPO aftermarket liquidity.

Uses both percentage spread and turnover ratio to measure liquidity. The percentage spread is the quoted bid‐ask spread divided by the quoted midpoint and measures the trading cost relative to share price. Turnover ratio is the daily trading volume divided by the number of shares offered and measures the speed of transaction. Both non‐parametric analyses and multiple regressions are conducted to investigate the effects of underpricing and share retention on liquidity.

Results indicate that initial return is positively related to turnover ratio and negatively related to percentage spread. These relations are significant even after controlling for other factors. Also finds that the pre‐IPO owners’ retention rate is positively related to turnover ratio and negatively related to percentage spread. High retention rates attract more trades, provide quality assurance, and improve IPO aftermarket liquidity.

This paper investigates the theoretical links between underpricing and liquidity and provides direct evidence on Booth and Chua's liquidity theory. In addition, this is one of the first empirical studies to analyze the effect of share retention on aftermarket liquidity.

The purpose of this paper is to examine stock market reactions and liquidity effects following the first bank loan announcement of zero-leverage firms.

The authors use an event studies methodology in both a univariate and multivariate framework. The authors also use regression analysis.

Using a sample of 96 zero-leverage firms listed on the FTSE 350 index over the time period of 2000–2015, the authors find evidence of a significant and permanent stock price increase as a result of the initial debt announcement. The loan announcement results in a sustained increase in trading volume and liquidity. This improvement continues to persist once the authors control for stock price and trading volume effects in both the short and long run. Furthermore, the authors examine the spread decomposition around the same period, and discover the adverse selection of the bid–ask spread is significantly related to the initial bank loan announcement.

The results can be attributed to the information cost/liquidity hypothesis, suggesting that investors demand a lower premium for trading stocks with more available information.

This is the first paper to look at multiple industries, more than one loan and information asymmetry effects.

In 2009, effective the second-quarter, the financial accounting standards board mandated that all banks need to disclose the fair value of loans in their 10-Q filings in addition to their 10-K filings. This paper aims to investigate whether these disclosures reduced the level of information asymmetry about the riskiness of bank loan portfolios during the financial crisis.

The paper examines the impact of these disclosures on the bid-ask spread of a panel of 246 publicly traded bank holding companies. The spread serves as a proxy for information asymmetry and the ratio of the fair value of a bank’s loan portfolio to its book value is a proxy for the credit and liquidity risk associated with the same. The reaction to the first-quarter filing serves as a control to assess the reaction at the time of the second-quarter filing.

There is a significant negative association between bid-ask spread and the ratio indicating that the fair value information was useful in reducing information asymmetry during the financial crisis. A pattern was observed in the information dissemination related to the fair value of loans that is consistent with the literature that documents a delayed investor reaction to complex financial information.

Investors may use the fair value information to better assess the risk profile of a BHC’s loan portfolio. Also, loan fair values provide managers with data to better implement stress test models and determine optimal capital buffers.

This study examines whether green buildings enjoy more favorable financing terms compared to their non-green counterparts, exploring the presence of a green discount in commercial real estate lending. Despite the extensive research on green premiums on the equity side, lending has received limited attention in the existing literature, even as regulations have increased and ambitious net-zero targets have been set in the banking sector.

In this study, the authors leverage a unique dataset comprising European commercial loan data spanning from 2018 to 2023, with a total loan value exceeding €30 billion. Hedonic regression analysis is used to isolate a potential green discount. Specifically, the authors rely on property assessments conducted by lenders to investigate whether green properties exhibit lower interest rate spreads and higher loan-to-value (LTV) ratios.

The findings reveal the existence of a green discount in European commercial real estate lending, with green buildings enjoying a 5.35% lower contracted loan spread and a 3.92% lower target spread compared to their non-green counterparts. However, this analysis does not indicate any distinct advantage in terms of LTV ratios for green buildings.

This research contributes to a deeper understanding of the interaction between green properties and commercial real estate lending, offering valuable insights for both lenders and investors.

This study, to the best of the authors’ knowledge, represents the first of its kind in a European context and provides empirical evidence for the presence of a green discount.

The authors examine the factors that impact the growth of exchange traded funds (ETFs) from 1990 to 2020. The authors show the first-mover and winner-takes-all effects from top ETF issuers. Besides the longer history and larger asset under management (AUM), the ETFs being managed by top issuers have exhibited lower risks and higher trading volume. Delisted ETFs on the contrary has a shorter history, lower AUM, higher risks, and lower trading volume. For zombie ETFs, the authors find longer history, lower risks but lower AUM and trading volume, controlled for total expense ratio, return, volatility, Amihud (2002) illiquidity, bid-ask spread, turnover ratio, as well as year, issuer, asset class and region fixed effects. The authors further study the ETFs’ AUM and trading activities over the 2008 Global Financial Crisis (GFC) and COVID-19 pandemic crisis, and find that the GFC has a significant negative impact while the COVID-19 has a positive impact on the ETFs’ popularity. The significant increase in AUM of ETF relative to common stocks during the COVID-19 is associated with retail investors’ holdings, as the authors document a significant reduction of institutional holdings at the aggregate level.

This paper aims to investigate the performance of estimators of the bid-ask spread in a wide range of circumstances and sampling frequencies. The bid-ask spread is important for many reasons. Because spread data are not always available, many methods have been suggested for estimating the spread. Existing papers focus on the performance of the estimators either under ideal conditions or in real data. The gap between ideal conditions and the properties of real data are usually ignored. The consistency of the estimates across various sampling frequencies is also ignored.

The estimators and the possible errors are analysed theoretically. Then we perform simulation experiments, reporting the bias, standard deviation and root mean square estimation error of each estimator. More specifically, we assess the effects of the following factors on the performance of the estimators: the magnitude of the spread relative to returns volatility, randomly varying of spreads, the autocorrelation of mid-price returns and mid-price changes caused by trade directions and feedback trading.

The best estimates come from using the highest frequency of data available. The relative performance of estimators can vary quite markedly with the sampling frequency. In small samples, the standard deviation can be more important to the estimation error than bias; in large samples, the opposite tends to be true.

There is a conspicuous lack of simulation evidence on the comparative performance of different estimators of the spread under the less than ideal conditions that are typical of real-world data. This paper aims to fill this gap.

The purpose of this paper is to investigate the determinants of bankruptcy protection duration of Canadian public firms, and also investigate the duration for various bankruptcy outcomes including the liquidation and re-emergence of bankrupt firms.

This study uses data on all Canadian public firms that applied for bankruptcy protection over the period 1992–2014. The authors mainly apply duration and survival analyses to draw the main conclusions.

The authors find that larger and older firms with more complicated structures and issues to settle tend to remain under protection from creditors longer, and also ascertain that the fate of relatively successful companies is determined faster. Moreover, the authors report that it takes less time to achieve a final solution for firms under bankruptcy protection when interest rates are increasing and the term spread is high. Finally, firms that file for protection under the Companies’ Creditors Arrangement Act (CCAA) spend longer restructuring than firms that file under the Bankruptcy and Insolvency Act.

The paper investigates only publicly listed firms. The data on private firms that are required to conduct the research are not available.

Various stakeholders including regulators can predict the bankruptcy protection period using the paper’s findings. Depending on the desired outcomes (reduce uncertainly, safeguard jobs or protect creditors’ rights), specific rules can be followed.

To the authors; knowledge, this is the first paper that investigates the Canadian bankruptcy protection duration. It uses the unique Canadian framework to infer the determinants of bankruptcy protection duration and bankrupt firms’ outcomes.

The purpose of this paper is to examine changes in stock returns, liquidity, institutional ownership, analyst following and investor awareness for companies added to and deleted from the Dow Jones Industrial Average (DJIA) index. Previous studies report conflicting evidence regarding the market reactions to changes in the DJIA index membership.

This study uses the event-study methodology to calculate abnormal returns and trading volume around the announcement and effective days of DJIA index changes from 1929 to 2015. It also tests for significant changes in liquidity, institutional ownership, analyst following and investor awareness in the 1990–2015 period. Multivariate regressions are used to perform a simultaneous analysis of competing hypotheses.

This study resolves the mixed results of previous DJIA index papers by documenting different stock price and trading volume reactions over the 1929–2015 period. Focusing on the most recent period, 1990–2015, the study finds that stocks added to (deleted from) the index experience a significant permanent stock price gain (loss). The observed stock price reaction seems to be associated with changes in liquidity proxies thus lending support for the liquidity hypothesis.

Limited data availability for the periods prior to 1990 prevents this study from identifying the exact reasons for different stock price and trading volume reactions across subperiods of the 1929–2015 period.

This study provides the most comprehensive examination of market reactions to changes in the DJIA index and resolves the mixed results of previous studies. A better understanding of market reactions around the DJIA index changes can help both individual and institutional investors with developing effective trading strategies and index managing companies with designing optimal announcement policies.

Meal left after extraction of microalgae functional compounds is not finding its application in food. Hence, present study was aimed for the development of the cookies supplemented with meal of microalgae Chlorella sp. (Abca-17) obtained after solvent extraction of chlorophyll.

Cookies were prepared by substituting refined wheat flour (RWF) with microalgae meal (MM) at incorporation levels of 3, 6, 9 and 12 per cent. The effect of replacement of RWF with MM was analyzed on the pasting properties of the flour blends and physical, chemical, sensory and textural characteristics of the cookies.

MM exhibited high water and oil absorption capacity of 0.8 g/g and 1.2 g/g, respectively. Weight and thickness of the cookies increased, whereas the diameter, spread ratio and spread factor decreased with the increased proportion of meal in flour blends. The moisture and ash content (0.8-2.0 per cent) of the cookies increased, whereas fat content showed no pronounced variation. Sensory evaluation of cookies revealed no significant difference at 6 per cent level of incorporation and further supplementation resulted in dark colour and increased hardness. Texture profile analysis of cookies also revealed that the peak positive force for breaking the cookies increased (3115.6-7372.1 N) with increase in the level of incorporation of meal.

MM can be used in the development of the cookies at level of incorporation of 6 per cent and presents novice approach for utilization of bioprocessing waste.

The present study is a pioneer effort in demonstration of utilization of MM as alternate food ingredient. MM of Chlorella sp. (Abca-17) was characterized as food ingredient using physicochemical analysis and model food system using cookies.