Credit risk – Return puzzle: Evidence from India

Nedumparambil, Elizabeth; Bhandari, Anup Kumar

doi:10.1016/j.econmod.2019.12.021

Cited by 9 publications

(3 citation statements)

References 66 publications

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“…Size, value, momentum, profitability and investment factors have been constructed using standard construction practice as followed in the asset pricing literature (Carhart, 1997; Fama & French, 2015; Nedumparambil & Bhandari, 2020). Any multicollinearity problem is sorted out before introducing these factors in the F–F framework.…”

Section: Methodsmentioning

confidence: 99%

Equity Market Anomalies, VIX and Asset Pricing: Trading Strategies for India

Pandey

2019

The Indian Economic Journal

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In this article we examine five prominent equity anomalies, viz., size, value, profitability, investment and momentum for Indian capital market using data from July 2001 to June 2019. We test the sample anomalies through four prominent factor models and find that all the factor anomalies remain significant for India, however, size and value anomaly provide substantial risk adjusted returns to be exploited by portfolio managers. We further evaluate if the anomalies tend to reverse under different macro-economic uncertainty, which is proxied by VIX. We find barring Size effect none of the anomaly reverses under different macro-economic conditions. We further observe that Fama French three factor model subsumes the majority of the alpha effect, however, none of the factor models fully explain the alphas of sample anomalies. Finally, we find that few of the sample anomalies are countercyclical in nature and thus, provide time diversification opportunity. Profitability-size anomaly provides risk adjusted time diversification opportunity. Our results have significant implications for portfolio managers, policy makers and academia.

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Section: Methodsmentioning

confidence: 99%

Equity Market Anomalies, VIX and Asset Pricing: Trading Strategies for India

Pandey

2019

The Indian Economic Journal

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“…Lee et al, (2016) analyze the impact of SCR changes on equity liquidity in 40 countries between 1990 and 2009 and find that effect is more robust with a downgrade than an upgrade, and the event is not linear in size. Using credit rating as a measure of credit risk, Nedumparambil and Bhandari (2020) examine the existence of a risk-return puzzle in India between July 2011 and March 2019. Contrary to the asset valuation theory, there is a negative relationship between risk and return.…”

Section: How Is Financial Market Development Linked With Credit Rating?mentioning

confidence: 99%

Impact of Sovereign Credit Rating Disclosure on Chinese Financial Market

Pervaiz

Khan

et al. 2022

Sage Open

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The sustainable economic role of the financial markets is essential for a trade-dependent economy such as China. Notably, the Chinese financial market has shown some unpleasant trends over the past two decades, coupled with the mounting national debt. Most of the earlier literature on the impact of the sovereign credit rating (SCR) on the financial market development (FMD) of China is confined to the event study approach, which provides policy input for short-term decision making. In this scenario, it is worthwhile investigating how the SCR asymmetrically affected the FMD of China and the threshold point (level) where the relationship of SCR-FMD turns non-linear. The Non-Linear Autoregressive Distributed Lag model’s empirical findings show that the reaction of FMD to SCR disclosure is asymmetric. In addition, the result of the threshold estimator finds a single threshold level of 3.628 above which the relationship of SCR-FMD turns non-linear. It is important to note that up to a threshold of 3.628 the coefficient is −.516 and −.627 which turns positive afterwards, no matter whether the variation explained is relatively less with the coefficient of .058 and .056 respectively. This implies that policymakers and regulators need to consider this benchmark of 3.628 to formulate future policy matters related to the equity market.

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“…If the financial distress risk is indeed a systematic risk, the rational investor should demand a positive risk premium (Choi et al, 2020). However, studies show that stocks with high financial distress risk earn abnormally low returns (Avramov et al, 2013; Auer & Hiller, 2019; Campbell, Hilscher, & Szilagyi [hereafter CHS], 2008; Dichev, 1998; Nedumparambil & Bhandari, 2020; Sha et al, 2020). The return premium, generated by long low distress risk stocks and short high distress risk stocks, is persistent and the capital asset pricing model (CAPM) and the Fama–French three‐factor (FF‐3) models have failed to explain it.…”

Section: Introductionmentioning

confidence: 99%

What drives the distress risk–return puzzle? A perspective on limits of arbitrage

Sha

Wang

2022

Int. J Fin Econ

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Empirical research has documented a negative relationship between distress risk and stock returns. This negative risk–return trade‐off, known as the distress puzzle, poses a challenge to asset pricing models. In this study, we provide a new explanation of the distress puzzle by considering the effect of arbitrage asymmetry. We find that the negative distress risk–return relation is stronger in stocks that have higher limits of arbitrage. The investors are virtually unable to short sell mispriced high distress risk stocks due to the low supply of lendable stocks from institutions and that arbitrage is costly. In addition, we show that the limits of arbitrage effect is distinct from liquidity effect in explaining the distress puzzle.

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Credit risk – Return puzzle: Evidence from India

Cited by 9 publications

References 66 publications

Equity Market Anomalies, VIX and Asset Pricing: Trading Strategies for India

Equity Market Anomalies, VIX and Asset Pricing: Trading Strategies for India

Impact of Sovereign Credit Rating Disclosure on Chinese Financial Market

What drives the distress risk–return puzzle? A perspective on limits of arbitrage

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