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The purpose of this paper is to establish an optimum mix of liquid, publicly traded assets that may be added to a real estate portfolio, such as those held by open-ended funds, to provide the liquidity required by institutional investors, such as UK defined contribution pension funds. This is with the objective of securing liquidity while not unduly compromising the risk-return characteristics of the underlying asset class. This paper considers the best mix of liquid assets at different thresholds for a liquid asset allocation, with the performance then evaluated against that of a direct real estate benchmark index.

The authors employ a mean-tracking error optimisation approach in determining the optimal combination of liquid assets that can be added to a real estate fund portfolio. The returns of the optimised portfolios are compared to the returns for portfolios that employ the use of either cash or listed real estate alone as a liquidity buffer. Multivariate generalised autoregressive models are used along with rolling correlations and tracking errors to gauge the effectiveness of the various portfolios in tracking the performance of the benchmark index.

The results indicate that applying formal optimisation techniques leads to a considerable improvement in the ability of the returns from blended real estate portfolios to track the underlying real estate market. This is the case at a number of different thresholds for the liquid asset allocation and in cases where a minimum return requirement is imposed.

The results suggest that real estate fund managers can realise the liquidity benefits of incorporating publicly traded assets into their portfolios without sacrificing the ability to deliver real estate-like returns. However, in order to do so, a wider range of liquid assets must be considered, not just cash.

Despite their importance in the real estate investment industry, comparatively few studies have examined the structure and operation of open-ended real estate funds. To the authors’ knowledge, this is the first study to analyse the optimal composition of liquid assets within blended or hybrid real estate portfolios.

This study aims to demonstrate and measure the impact of liquidity shocks on a bank’s solvency, especially when the bank does not hold sufficient liquid assets.

The proposed model is an extension of Merton’s (1974) model. It assesses the bank’s probability of default over one or two (short) periods relative to liquidity shocks. The shock scenarios are materialised by different net demands for the withdrawal of funds (NDWF) and may lead the bank to sell illiquid assets at a depreciated value. We consider the possibility of second-round effects at the beginning of the second period by introducing the probability of their occurrence. This probability depends on the proportion of illiquid assets put up for sale following the initial shock in different dependency scenarios.

We observe a positive relationship between the initial NDWF and the bank’s probability of default (particularly over the second period, which is conditional on the second-round effects). However, this relationship is not linear, and a significant proportion of liquid assets makes it possible to attenuate or even eliminate the effects of shock scenarios on bank solvency.

The proposed model enables banks to determine the necessary level of liquid assets, allowing them to resist (i.e. remain solvent) different liquidity shock scenarios for both periods (including eventual second-round effects) under the assumptions considered. Therefore, it can contribute to complementing or improving current internal liquidity adequacy assessment processes (ILAAPs).

The proposed microprudential approach consists of measuring the impact of liquidity risk on a bank’s solvency, complementing the current prudential framework in which these two topics are treated separately. It also complements the existing literature, in which the impact of liquidity risk on solvency risk has not been sufficiently studied. Finally, our model allows banks to manage liquidity using a solvency approach.

This paper aims to explore the effects of illiquidity on portfolio weight and return dynamics.

Using a novel continuous-time framework, the paper makes two key contributions to the literature on asset pricing and illiquidity. The first is to study the effects of illiquidity on portfolio weight dynamics. The second contribution is to analyze how illiquidity affects the risk/return dynamics of a portfolio.

The numerical results highlight that investors should be prepared for potentially large and skewed variations in portfolio weights and can be away from optimal diversification for a long time when adding illiquid assets to a portfolio. Additionally, the paper shows that illiquidity increases portfolio risk. Interestingly, this effect gets more pronounced when the return correlation between the illiquid and liquid asset is low. Thus, there is a correlation effect in the sense that illiquidity costs, as measured by the increase in overall portfolio risk, are inversely related to the return correlation of the assets.

This is the first paper that highlights that the increase in portfolio risk caused by illiquidity is inversely related to the return correlation between the liquid and illiquid assets. This important economic result contrasts with the widely used argument that the benefit of adding illiquid (alternative) assets to a portfolio is their low correlation with (traditional) traded assets. The results imply that the benefits of adding illiquid assets to a portfolio can be much lower than typically perceived.

The paper examines how equity mutual funds manage their liquidity. Specifically, the authors investigate what strategies fund managers use to meet investor redemption demand, whether these strategies vary over time, whether different type of funds employ different liquidation practices in response to fund outflows, and whether liquidity strategies impact fund performance.

This study uses a sample of U.S. actively managed equity funds over the period 1990–2019. The authors use three different measures to capture funds' liquidity management practices. The authors examine the relationship between fund liquidity measures and net flow by estimating panel regressions over the entire sample period, on 2 sub-sample periods of different market conditions measured by the magnitude of implied market volatility (VIX), and on 2 sub-samples of funds with different liquidity profiles. The authors also examine the relationship between funds liquidity status and near-term performance through both a portfolio approach and regression analysis.

The authors find that on average, mutual funds reduce their cash position and the most liquid asset holdings to meet investor redemption demand. Furthermore, the authors find that fund managers choose different liquidity strategies under different market conditions. During highly volatile markets, mutual funds use cash and their most liquid assets to meet redemption demand while maintaining their portfolio liquidity. During low volatility markets, mutual funds rely heavily on cash but less on liquidity assets and tend to increase their portfolio illiquidity. Upon further examination of funds across portfolio liquidity profiles, the authors find that liquid funds increase portfolio liquidity when facing outflows, whereas illiquid funds maintain their portfolio liquidity position. The different liquidity strategies have significant impact on funds' near-term performance. Specifically, liquid funds underperform illiquid funds following the increase in their portfolio liquidity.

This paper contributes to the literature on liquidity management by asset managers by taking a holistic approach to examine funds liquidation practice at the portfolio holdings level. Considering the recent increase in market volatility, mutual fund liquidity management has drawn an increasing share of interest and attention from policy makers, investment professionals, and academia. This study covers both uncertain and stable market states during a long sample period and provides empirical evidence on the flow-induced liquidation decisions by equity mutual funds. In addition, this paper also contributes to the literature on mutual fund performance by providing evidence that funds' liquidity strategies significantly impact their near-term performance.

The purpose of this study is two‐fold. The first purpose is to properly measure the level of US property and liability (P/L) insurers liquidity creation, applying the liquidity creation measure developed by Berger and Bouwman. The second purpose is to identify factors affecting P/L insurers' liquidity creation using a regression. Particularly, this paper tests two competing hypotheses regarding the relationship between the level of capital and liquidity creation.

The paper calculates liquidity creation for the US P/L insurers. First, the paper categorizes all items in assets, liabilities and surplus into liquid, semi‐liquid, or illiquid. This process is based on the ease, cost, and time for insurers to meet their contractual obligation to obtain liquid funds or to pay off their liability. The paper also constructs the regression model to test the impact of insurers' surplus level on liquidity creation while controlling for the firm‐specific variables. The paper examines this relationship for the time period between 1998 and 2007.

Contrary to the study of depository institutions, the paper reports that P/L insurers are liquidity destroyers than liquidity creators. This paper also provides that liquidity destruction varies over time and differs among insurers in different size. The total amount of liquidity destruction ranges from 47 to 58 percent of insurer total asset. In addition, the results of a regression show that insurer capital is negatively related to the level of liquidity creation. This provides implications that insurers with lower level of capital face more regulatory requirements and are forced to meet liquidity demand more.

The level of liquidity creation and the trend of liquidity creation of P/L insurers are of particular interest to regulators and consumers because the level of liquidity creation as shown during the financial crisis has a significant adverse impact on the financial intermediaries.

The paper do not aware of any study that attempts to measure liquidity creation by insurers and its relationship with both organizational and financial characteristics. The paper reports that P/L insurers are, unlike depository institutions, liquidity destroyers. Whether or not P/L insurers create/destroy liquidity is an interesting economic question to shed light on the roles of P/L insurers as a financial intermediary.

The purpose of this paper is twofold: first, this paper measures how much liquidity is transformed by the US life insurance industry for the sample period; and Second, this study tests the “risk absorption” hypothesis and “financial fragility-crowding out” hypothesis to identify the impact of capital on liquidity creation in the US life insurance industry. In addition, a regression model is conducted to explore the relationship between liquidity creation and other firm characteristics.

In order to construct the liquidity creation measures, all assets and liabilities are classified as liquid, semi-liquid, or illiquid with appropriate weights to these classifications, which will then be combined to measure the amount of liquidity creation. In addition, a regression model is analyzed. The level of insurers’ liquidity creation is regressed on the capital ratio (surplus over total assets) and other financial and organizational variables to test two prevailing hypotheses.

This paper finds that the US life insurers de-create liquidity. The authors provide that the amount of liquidity de-creation is related to the size of insurers such that liquidity de-creation has increased as assets grow and that large insurers de-create most of liquidity. The US life insurance industry de-created $2.1 trillion in liquidity, i.e., 43 percent of total industry assets, in 2008. The empirical results support the “financial fragility-crowding out” hypothesis. Life insurers’ liquidity de-creation is mainly caused by the large portion of liquid assets, which is required by regulation and capital is not a main factor of liquidity de-creation.

There is no known study on the issue of liquidity creation by life insurers. Thus, the extent of liquidity creation by the life insurance industry, if any, is an empirical matter to investigate, but also an important matter to regulators and the academia since the products and business operations (e.g. asset portfolio and asset and liability management) of life insurers are different from those of property and liability insurers.

This research aims to analyze and compare the effectiveness of liquidity risk management of Islamic and conventional banking in Egypt to ascertain which of the two banking systems are performing better.

A sample of six conventional banks (CBs) and two Islamic banks (IBs) in Egypt was selected. Using the liquidity ratios, the investigation involves analyzing the financial statements for the period of 2004-2011. The data were obtained from Bank scope database.

The research found that in Egypt, CBs perform better in terms of liquidity risk management than IBs. The liquidity risk management significant differences between IBs and CBs could be attributed more cash availability to CBs than to IBs, in addition, Egyptian Central Bank regulations on capital and liquidity requirements for IBs disconcert IBs’ performance.

This research facilitates the bankers, academician, scholars and bankers to have an alluded picture about Egyptian banking developments in liquidity risk management. The results can be used by bankers’ policy decision-makers to improve and enhance their consideration for liquidity risk management.

This research covers a period and a country that compares CBs’ and IBs’ liquidity risk management. Its value is attributed to the increasing differentiation between CBs and IBs.

The study analyzes the relationship between homeownership and financial investment of households in the context of emerging markets like India. It also examines how homeownership affects the portfolio decisions of Indian households.

Using the nationally representative All-India Debt and Investment Survey of 2019 and employing an instrumental variable approach, the authors analyze the relationship between homeownership and the share of financial assets held by Indian households. The study also employs several sensitivity checks, including alternate estimation techniques and alternative definitions of the housing variables, and accounts for additional factors to ensure that the authors are able to capture the effect of homeownership on the outcome variable.

The analysis suggests homeownership crowds out financial investment in India due to high repair and maintenance costs. The negative effect is mainly observed in urban households. Further, the findings imply that homeownership leads households to reallocate their asset portfolio. Homeowners have a lower share in liquid short term deposits, indicating the high liquidity risk of their portfolios. On the other hand, homeownership increases the share of long term retirement funds along with no effect on risky asset share. The authors observe that the crowding out effect is more striking for younger households and poorer households with low income, and the effect is lower for indebted households.

The findings underscore the need for financial awareness programs so that housing does not crowd out liquid investments of households. Additionally, the results highlight that policies should first focus on young and poor households as the negative effect is more prominent for these groups. Finally, there is scope for policies to support repair and maintenance costs incurred by vulnerable households to reduce the negative effect of housing on liquid financial investments.

This paper is among the few studies that provide insights into how homeownership relates to financial investment and portfolio decisions in the context of an emerging economy. Furthermore, the heterogeneous effects based on poor economic status and age underscore the need for complementary policies.