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Understanding the pricing of real estate equities is a central objective of real estate research. This paper aims to investigate the impact of liquidity on European real estate equity returns, after accounting for well-documented systematic risk factors.

Based on risk factors derived from general equity data, the authors extend the Fama-French time-series regression approach by a liquidity factor, using a pan-European sample of 272 real estate equities.

The empirical results indicate that liquidity is a significant pricing factor in real estate stock returns, even after controlling for market, size and book-to-market factors. In addition, the authors detect that real estate stock returns load predominantly positively on the liquidity risk factor, suggesting that real estate equities tend to behave like illiquid common equities. These findings are underpinned by a series of robustness checks. Running a comparative analysis with alternative factor models, the authors further demonstrate that the liquidity-augmented asset-pricing model is most appropriate for explaining European real estate stock returns.

The inclusion of sentiment and downside risk factors could provide further insights into real estate asset pricing in European capital markets.

This is the first study to examine the role of liquidity as a systematic risk factor in a pan-European setting.

The purpose of this paper is to originate a proactive approach for the quantification and analysis of liquidity risk for trading portfolios that consist of multiple equity assets.

The paper presents a coherent modeling method whereby the holding periods are adjusted according to the specific needs of each trading portfolio. This adjustment can be attained for the entire portfolio or for any specific asset within the equity trading portfolio. This paper extends previous approaches by explicitly modeling the liquidation of trading portfolios, over the holding period, with the aid of an appropriate scaling of the multiple‐assets' liquidity‐adjusted value‐at‐risk matrix. The key methodological contribution is a different and less conservative liquidity scaling factor than the conventional root‐t multiplier.

The proposed coherent liquidity multiplier is a function of a predetermined liquidity threshold, defined as the maximum position which can be unwound without disturbing market prices during one trading day, and is quite straightforward to put into practice even by very large financial institutions and institutional portfolio managers. Furthermore, it is designed to accommodate all types of trading assets held and its simplicity stems from the fact that it focuses on the time‐volatility dimension of liquidity risk instead of the cost spread (bid‐ask margin) as most researchers have done heretofore.

Using more than six years of daily return data, for the period 2004‐2009, of emerging Gulf Cooperation Council (GCC) stock markets, the paper analyzes different structured and optimum trading portfolios and determine coherent risk exposure and liquidity risk premium under different illiquid and adverse market conditions and under the notion of different correlation factors.

This paper fills a main gap in market and liquidity risk management literatures by putting forward a thorough modeling of liquidity risk under the supposition of illiquid and adverse market settings. The empirical results are interesting in terms of theory as well as practical applications to trading units, asset management service entities and other financial institutions. This coherent modeling technique and empirical tests can aid the GCC financial markets and other emerging economies in devising contemporary internal risk models, particularly in light of the aftermaths of the recent sub‐prime financial crisis.

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.

The aim of this paper is to examine the role of liquidity in asset pricing in a tiny market, such as the Portuguese. The unique setting of the Lisbon Stock Exchange with regards to changes in classification from an emerging to a developed stock market, allows an original answer to whether changes in the development of the market affect the role of liquidity in asset pricing.

The authors propose and compare two alternative implications of liquidity in asset pricing: as a desirable characteristic of stocks and as a source of systematic risk. In contrast to prior research for major stock markets, they use the proportion of zero returns which is an appropriated measure of liquidity in tiny markets and propose the separated effects of illiquidity in a capital asset pricing model framework over the whole sample period as well as in two sub-samples, depending on the change in classification of the Portuguese market, from an emerging to a developed one.

The overall results of the study show that individual illiquidity affects Portuguese stock returns. However, in contrast to previous evidence from other markets, they show that the most traded stocks (hence the most liquid stocks) exhibit larger returns. In addition, they show that the illiquidity effects on stock returns were higher and more significant in the period from January 1988 to November 1997, during which the Portuguese stock market was still an emerging market.

These findings are relevant for investors when they make their investment decisions and for market regulators because they reflect the need of improving the competitiveness of the Portuguese stock market. Additionally, these findings are a challenge for academics because they exhibit the need for providing alternative theories for tiny markets such as the Portuguese one.

The results have important implications for individual and institutional investors who can take into account the peculiar effect of liquidity in stock returns to make proper investment decision.

The Portuguese market provides a natural experimental area to analyse the role of liquidity in asset pricing, because it is a tiny market and during the period studied it changed from an emerging to a developed stock market. Moreover, the authors have to highlight that previous evidence almost exclusively focuses on the US and major European stock markets, whereas studies for the Portuguese one are scarce. In this context, the study provides an alternative methodological approach with results that differ from those theoretically expected. Thus, these findings are a challenge for academics and open a theoretical and a practical debate.

This paper aims to expand foreign investors' understanding of potential return enhancement and risk diversification advantages offered by equity market of Pakistan through comparing its performance to performances in other markets and investigating what matters for investing in Pakistan's market.

Comparative analysis of Pakistan Stock Exchange is performed using data for 22 developed and 22 emerging markets over the period 1993–2019. Cross-sectional analysis is performed using data for 130 non-financial firms from Pakistan and Carhart (1997) and Fama and French (2015) models are applied. The role of liquidity with five-factor model is analyzed using turnover rate and Amihud (2002) illiquidity cost as liquidity measures.

Pakistan's equity offers substantial diversification benefits if added to developed market portfolios. However, observed large returns come together with inverted premia for most traditional factors indicating that investors may want to invest preferably in big stocks with low book-to-market and momentum. Finally, global investors can invest in high yielding stocks with low liquidity risk owing to positive connection between liquidity and returns.

This study will provide investment model for foreign investors to enhance their portfolio returns. Policy makers in Pakistan must identify regulatory steps to facilitate foreign investments.

To the best of the authors' knowledge, this is the first study which identifies efficiency gains offered by Pakistan's equity for global investors.

The purpose of this study is to examine the performances of liquidity factors in the stock market cycle. It aims to investigate whether the contribution of liquidity factors changes with stock market trends.

Six liquidity proxies and two-factor construction methods are compared in this study. The spanning regression method was applied to examine the contribution of liquidity factors to the asset pricing model, while the Fama and MacBeth regression method was used for examining the pricing power of liquidity factors.

The result shows that liquidity factors are accretive to models explaining returns in bull markets but not accretive to models in bear markets. The most appropriate method of constructing liquidity factors in the Japanese stock market has also been clarified.

In the Japanese stock market, there has never been a comprehensive test of the role of the liquidity risk factor in different market trends using the long-run data. This study helps with identifying the importance of liquidity pricing risk in different market trends. It also fills the gaps by comparing liquidity factors that are constructed through different methods and proxies and provides evidence for further confirming the correct asset pricing model in the future.

To discuss a September 22, 2015 Securities and Exchange Commission (“SEC”) proposal for a set of broad and sweeping rules mandating that open-end mutual funds and exchange-traded funds (“ETFs”) develop and implement formalized and written liquidity risk management programs (“LRMPs”).

Describes the purpose of an LRMP, the six “liquidity buckets,” the nine factors that must be considered in determining an instrument’s liquidity, the need to continuously monitor the liquidity of each position, the set of eight mandated factors used to assess a fund’s liquidity risk, the requirement for a fund to define a three-day liquid asset minimum, the role of the fund’s board of directors, a separate rule permitting “swing pricing” to adjust net asset value to take into account the costs of unexpected redemptions or cash infusions, disclosure requirements, and proposed compliance dates.

In proposing this new program, the SEC stated that its goal was to enhance effective liquidity risk management practices by funds and thereby reduce the risk that funds will be unable to meet redemptions under reasonably foreseeable stressed market conditions.

Expert guidance by experienced financial services lawyers.

To provide an overview of the US Securities and Exchange Commission’s (SEC) recently adopted rule 22e-4 (Rule 22e-4) under the Investment Company Act of 1940, as amended (1940 Act) regarding investment company liquidity risk management programs.

Reviews and summarizes the specific requirements of Rule 22e-4 to better enable investment companies and their boards to comply by the general compliance date of December 1, 2018 (smaller complexes have until June 1, 2019).

The SEC clarifies that each fund should tailor its particular Program to ensure that it is adequately assessing and managing its specific liquidity risk based on its investment strategies and risks; however, it is not expected that a fund would eliminate all adverse impacts of liquidity risk. In addition, under the final rule, while the board does have certain duties and responsibilities with respect to certain aspects of a fund’s Program, the SEC pared back much of what had been in the Proposing Release to ensure that the board’s role remains one of oversight and not management.

Although the compliance date does not occur for almost two years, funds and their boards should begin reviewing the Rule 22e-4 requirements now and developing their Program.

Practical guidance from experienced investment management attorneys that provides insight into expectations for compliance with Rule 22e-4.

This study aims to compare the fundamental indexation (FI) portfolio vis-à-vis the cap-weighted index (CWI). It also explored the return-generating attributes of the FI portfolios.

This study extracted relevant data from the Centre for Monitoring Indian Economy’s Prowess database from March 1996 to March 2017 from a sample of National Stock Exchange (NSE) 500 companies. The FI portfolios were constructed with First_50 and Next_50 stocks using the latest and five years of trailing average aggregations. Further, the regression technique was used to identify the return-generating attributes of FI portfolios.

It was found that the FI portfolios based on First_50 and Next_50 stocks outperformed the CWI (i.e. NSE_First_50 and NSE_Next_50) in the Indian capital market, and between the two, the FI portfolios based on Next_50 stocks were superior to the FI portfolios based on First_50 stocks. The cross-sectional superiority of FI portfolios is obvious if they are sorted according to four fundamentals, namely, total income, sales, operating cash flows and profit before depreciation interest tax and amortisation. The return-generating process of FI portfolios is well-explained by market premium followed by value premium and investment premium.

This study may enable portfolio managers and investors to measure FI portfolios’ superiority in the Indian capital market and identify the return-generating attributes of FI portfolios so that the loadings can be switched amongst different priced factors for higher yield. Further, this study extends the FI literature, providing evidence from one of the world’s fastest-growing economies.

To the best of the knowledge, this is amongst the first few studies to explore the performance of FI portfolios vis-à-vis CWIs in India, and to use Fama and French (2015) asset pricing models to understand the return-generating attributes of FI portfolios. It is also novel in the sense that it considers the FI portfolios for a longer duration, predating 1997 and coinciding with the inception of CWIs, namely, NSE_First_50 (inception: 1995) and NSE_Next_50 (inception: 1996), reducing the apprehensions of data-snooping biases.

This study aims to assess the relationship between cash management and fund performance in index fund portfolios.

Using a sample of 104 index mutual funds that track the Standard and Poor 500 stock market index from January 1999 to December 2016, the authors employ quintile portfolios and different regression models to assess the differences in risk-adjusted monthly returns experienced by index funds managing different cash levels in their portfolios. To ensure the robustness of the results, different sub-periods and market states are considered in the analyses as well as other exogenous factors and fund characteristics affecting the level of portfolio cash holdings and index fund performance.

Results show that index funds holding higher levels of cash and cash equivalents performed significantly worse than their low-cash counterparts. This evidence remains even after considering different sub-periods and bullish and bearish market conditions and controlling for fund expenses and other variables that could drive this cash-performance relationship.

This study expands the extant literature analyzing cash management in the mutual fund industry. More specifically, the analyses focus on index fund portfolios that replicate a specific benchmark, given that their performance differences should not be related to the market evolution but to the factors derived from the fund management and other exogenous issues. These findings are of interest to managers and investors willing to improve their risk-adjusted returns while investing as diversified as a stock market index.

El objetivo de este estudio es analizar la relación existente entre la gestión de efectivo y el desempeño consiguiente en las carteras de fondos de inversión indexados.

Utilizando una muestra de 104 fondos que replican el índice bursátil Standard and Poor's 500 desde enero de 1999 hasta diciembre de 2016, se emplean carteras hipotéticas que invierten en fondos similares y diferentes análisis de regresión para analizar las diferencias en las rentabilidades ajustadas mensuales entre fondos indexados que gestionan diferentes niveles de efectivo en sus carteras. Por motivos de robustez, se tienen en cuenta diversos subperiodos y estados de mercado, así como otros factores exógenos y características de los fondos que afectan tanto al nivel de efectivo mantenido en la cartera indexada como al desempeño de la misma.

Los resultados muestran que los fondos indexados que gestionan niveles de efectivo más elevados experimentan un desempeño significativamente menor que otros fondos comparables que mantienen menores porcentajes de efectivo en sus carteras de inversión. Se obtiene una evidencia similar tras considerar diferentes subperiodos y momentos alcistas y bajistas de mercado, así como al considerar los gastos propios de cada fondo y otras variables que podrían afectar esta relación entre el rendimiento y el efectivo gestionado.

Este estudio contribuye a la literatura existente que analiza la gestión de efectivo en la industria de fondos de inversión. Más específicamente, los análisis se centran en carteras de fondos que replican un índice bursátil específico, dado que las diferencias en sus rendimientos en este tipo de fondos no deberían originarse por la evolución del mercado, sino a causa de factores relacionados con la gestión de sus carteras y otros componentes exógenos al índice bursátil. Estos hallazgos son de interés para gestores e inversores que pretendan mejorar sus rentabilidades ajustadas al invertir mediante una estrategia tan diversificada como un índice bursátil.