Cash holding and performance analysis of mutual funds: a case of an emerging financial market

PurposeThis study is about the determinants of cash holding and impact of cash holding on mutual funds’ performance. In addition, the study analyzes the impact of performance-related determinants of cash holding on funds' performance.Design/methodology/approachPanel data of ten years of 190 open-end mutual funds are analyzed through fixed effect regression technique. The risk-adjusted funds' performance of cash based portfolios is computed through capital asset pricing model (CAPM) (1964), Fama and French (1993) and Carhart (1997) models.FindingsThe results indicate that small size funds, high charging front-end load funds, high turnover ratio funds, high 12-month fund returns run up, high dividend paying funds and high redemption level funds hold more cash for precautionary purpose to avoid costs of cash short-falls. Further, monthly average raw returns and risk-adjusted performance of funds with the lowest raw and residual cash holding are found higher than the funds with the highest cash holding. An increase in cash is found to dilute performance.Originality/valueThis is a pioneer study in a corporate environment with shallow capital market, reliance of businesses on bank credit, firms exposed to agency issues, wealth expropriations and existence of business groups with political linkages but with opportunities of investments due to expected favorable geo-socio-political situation. The study generates outcomes relevant for other similar economies.

DRAWBACKS IN THE 3-FACTOR APPROACH OF FAMA AND FRENCH (2018)

This paper features a statistical analysis of the monthly three factor Fama/French return series. Rolling OLS regressions explore the relationship between the 3 factors, using data from July 1926 to June 2018, available on French’s website. The results suggest there are significant and time-varying relationships between the factors. A sub-sample from July 1990 to July 2018 is used to analyze the three series using two-stage least squares and the Hausman test to check for issues related to endogeneity. The empirical results suggest that the factors, when combined in OLS regression analysis, as suggested by Fama and French (2018), are likely to suffer from endogeneity. Ramsey’s RESET tests suggest a nonlinear relationship exists between the three series. We use two instruments to estimate the market betas, and compare them to betas estimated not using instruments. Non-parametric tests of the two sets of betas suggest significant differences. The results suggest that using these factors in linear regression analysis, as recommended by Fama and French [(2018). Choosing factors. Journal of Financial Economics, 128(2), 234–252] is problematic in that the estimated coefficients are highly sensitive to the correct model specification.

Market Backwardation and The Theory of Storage: An Empirical Investigation of Indian Gold Futures Markets

The backwardation and contango in the futures markets are explained by two popular theories, namely the theory of storage and the theory of risk premium. The investment assets tend to follow the theory of risk premium, whereas the consumption assets are likely to follow the theory of storage. As India is the largest importer of gold, and gold is used for consumption purposes (mostly by jewellers, who store gold as a consumption commodity), we empirically test whether backwardation in the gold market is explained by the theory of storage. We use the indirect test of the theory of storage developed by Fama and French (1988 , Journal of Finance, Vol. 4, p. 1075), calculate the interest adjusted basis (IAB) and test the implications of the theory of storage. We also use two asymmetric models of the Generalized Autoregressive Conditional Heteroscedastic (GARCH) family to understand the asymmetric volatility of IAB. We find that the Indian gold futures markets partially follow the theory of storage; however, we do not find any support of asymmetric behaviour of IAB in the contango and backwardation markets. Our results suggest that in the context of the Indian gold market, keeping inventory has minimal benefits, and gold behaves more like an investment asset.

The Effect of Quantitative Easing through Google Metrics on US Stock Indices

The purpose of this study is to investigate the fluctuations that occur in stock returns of US stock indices when there is an increase in the volume of Google internet searches for the phrase “quantitative easing” in the US. The exponential generalized autoregressive conditional heteroscedasticity model (EGARCH) was applied based on weekly data of stock indices using the three-factor model of Fama and French for the period of 1 January 2006 to 30 October 2020. The existence of a statistically significant relationship between searches and financial variables, especially in the stock market, is evident. The result is strong in three of the four stock indices studied. Specifically, the SVI index was statistically significant, with a positive trend for the S&P 500 and Dow Jones indices and a negative trend for the VIX index. Investor focus on quantitative easing (QE), as determined by Google metrics, seems to calm stock market volatility and increase stock returns. Although there is a large body of research using Google Trends as a crowdsourcing method of forecasting stock returns, this paper is the first to examine the relationship between the increase in internet searches of “quantitative easing” and stock market returns.

Is the Long Memory Factor Important for Extending the Fama and French Five-Factor Model: Evidence from China

This paper proposes a new factor model, which is built upon the marriage of the Fama and French five-factor model and a long memory factor based on the monthly data of the A-share market in the Chinese stock market from January 2010 to July 2020. We first examine the explanatory power of the Fama and French five-factor model. We find strong market factor return of market (RM), size factor small minus big (SMB), and value factor high minus low (HML) but weak factor robust minus weak (RMW) and investment factor conservative minus aggressive (CMA). Then, both the Hurst exponent and the momentum factors (MOM) are added to the model to test the improvement of the explanatory power of these two new factors. We find that both the momentum factor and the Hurst exponent factor can effectively improve the explanatory power of the model. The momentum factor captures the short-term trend, but it cannot completely replace the Hurst exponent, which reflects the long memory effect.

Does the fundamental indexation portfolio perform better? An Indian investigation

Purpose 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. Design/methodology/approach 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. Findings 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. Practical implications 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. Originality/value 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.

Empirical Evidence of Asset Pricing Based on Single Index Model, Fama, and French Three and Five-Factor Models in Indonesia Stock Exchange

This empirical test aims to estimate the beta parameters of the risk premium and other risk factors and compare the performance of the single-index model, Fama and Frech three and five-factor models. The sample used as the study object is companies in the property and real estate subsector with data collected from datastream Thomson Reuters from January 2014 to December 2018. The results are consistent with the previous studies that asset pricing using the Fama and French five-factor model can better explain stock returns than the other two models. The property and real estate subsector seems to provide a positive and statistically significant abnormal return, indicating that asset pricing with the three models is irrelevant to Indonesia. These results suggest that the stock market in Indonesia is still inefficient.

The contribution of corporate social responsibility to financial performance: a factor model of Canadian stocks

This paper studies the effect of corporate social responsibility (CSR) on the returns of Canadian stocks. It employs the 3-factor asset-pricing model created by Fama and French (1993) and adds a new CSR factor (2x3 sorts) to examine if the explanatory power of the model is improved by the CSR factor. I, also, introduce an alternative method to create a 4-factor model (2x2x2 sorts). The results of my tests show the CSR factor does not improve the explanatory power of the Fama French models. Furthermore, replacing HML by CSR captures no more excess returns and I conclude that corporate social responsibility is not a priced factor in Canadian capital markets. In addition, the 3-factor model (based on Rm-Rf, SMB, HML) generates the exactly same results as Fama-French (1993 and 2015) models. Finally, I find that large firms, especially big size-low BE/ME companies, tend to be more “ethical”.

The contribution of corporate social responsibility to financial performance: a factor model of Canadian stocks

This paper studies the effect of corporate social responsibility (CSR) on the returns of Canadian stocks. It employs the 3-factor asset-pricing model created by Fama and French (1993) and adds a new CSR factor (2x3 sorts) to examine if the explanatory power of the model is improved by the CSR factor. I, also, introduce an alternative method to create a 4-factor model (2x2x2 sorts). The results of my tests show the CSR factor does not improve the explanatory power of the Fama French models. Furthermore, replacing HML by CSR captures no more excess returns and I conclude that corporate social responsibility is not a priced factor in Canadian capital markets. In addition, the 3-factor model (based on Rm-Rf, SMB, HML) generates the exactly same results as Fama-French (1993 and 2015) models. Finally, I find that large firms, especially big size-low BE/ME companies, tend to be more “ethical”.

Applying the Fama and French three-factor model to analyze risk/reward in the Spanish REITs: an ARDL approach

Purpose This paper aims to analyse the risk and excess returns of the Spanish real estate investment trusts (S-REITs) using various methods, though focusing primarily on the Fama-French three-factor (FF3) model, over the period from 2007Q3 to 2017Q2. Design/methodology/approach The autoregressive distributed lag model is used for the empirical analysis to test long-term stable relationships between variables. Findings The findings indicate that the FF3 model is suitable for the S-REITs market, better explaining the S-REITs’ returns variation than the traditional single-index capital asset pricing model (CAPM) and the Carhart four-factor model. The empirical evidence is reasonably consistent with the FF3 model; the values for the market, size and value are highly statistically significant over the analysis period, with 68.7% variation in S-REITs’ returns explained by the model. In the long run, the market factor has less explanatory power than the size and value factors; the positive long-term multiplier of the size factor indicates that small S-REIT companies have higher returns, along with higher risk, while the negative multiplier of the value indicator suggests that S-REITs portfolios prefer to allocate growth REITs with low book-to-market ratios. The empirical findings from a modified FF3 model, which additionally incorporates Spain’s gross domestic product (GDP) growth rate, two consumer price index (CPI) macro-factors and three dummy variables, indicates that GDP growth rate and CPI also affect S-REITs’ yields, while investment funds with capital calls have a small influence on S-REITs’ returns. Practical implications The regression results of the standard and extended FF3 model can help researchers understand S-REITs’ risk and return through a general stock pattern. Potential investors are given more information to consider the new Spanish investment vehicle before making a decision. Originality/value The paper uses standard techniques but applies them for the first time to the S-REIT market.