Risk-Managed Momentum: An Evidence from Indian Stock Market

Singh, Simarjeet; Walia, Nidhi; Panda, Pradiptarathi; Gupta, Sanjay

doi:10.1177/23197145211023001

Cited by 4 publications

(4 citation statements)

References 72 publications

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“…However, they also found that momentum investing is more effective in markets with high levels of liquidity, implying that market conditions may influence the success of momentum strategies. Singh et al (2022) studied the momentum factor in the Indian market and found no significant effect on fund performance. They suggested that the weak momentum effect may be attributed to market inefficiencies and information asymmetry in the region.…”

Section: Mutual Fund Performance and Momentum Factormentioning

confidence: 99%

Analyzing the Performance of Pakistan Equity Mutual Funds Using Multifactor Models: Pre-COVID Analysis

Danial,

Iftikhar,

Shah

2023

BMS

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Previous literature has primarily focused on examining the determinants that impact mutual fund returns in developed and emerging economies. However, there is a dearth of empirical research on how multifactor models are associated with mutual fund returns in underdeveloped economies. The inconsistent literature regarding the efficiency of the literature posed a question of whether the fund managers can generate extra returns for the investors. To address this research gap, this study aims to analyze mutual fund returns using multifactor models, specifically the Capital Asset Pricing Model (CAPM), Fama-French three-factor model, Carhart four-factor model, Treynor-Mazuy and Fama Net-Selectivity. The first three models analyze the funds with four factors: market factor, growth factor, value factor and momentum factor. The results of the study indicate that the risk premium factor plays a crucial role in understanding mutual fund returns, as it exhibits significant value across all three models. However, the value and size factors were found to be insignificant in both the Fama-French and Carhart models. Additionally, the momentum factor was not significant in the Carhart model. Notably, the significant alpha observed in all multifactor models suggests the skill of mutual fund managers, which was further confirmed using the Treynor-Mazuy and Fama Net-Selectivity models to assess their timing and selectivity abilities in actively managed funds. Furthermore, the finding of the study suggests the inefficiency of the market. The investors could earn extra return from their investments. However, the managers play important role in generating the abnormal returns as suggested by Treynor-Mazuy and Fama Net-selectivity model significance. In addition to that, investors should consider the market risk premium in their investment returns.

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Section: Mutual Fund Performance and Momentum Factormentioning

confidence: 99%

Analyzing the Performance of Pakistan Equity Mutual Funds Using Multifactor Models: Pre-COVID Analysis

Danial,

Iftikhar,

Shah

2023

BMS

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“…Jain et al (2021) investigate stock selection using the fuzzy analytical hierarchy process framework. Singh et al (2021) analyze and propose a risk-managed momentum approach to avoid momentum losses in the Bombay Stock Exchange. We complement these previous studies by focusing on how commodities provide hedging benefits across financial assets (stocks, bonds and FX) portfolios.…”

Section: Review Of Literaturementioning

confidence: 99%

“…(2021) investigate stock selection using the fuzzy analytical hierarchy process framework. Singh et al. (2021) analyze and propose a risk-managed momentum approach to avoid momentum losses in the Bombay Stock Exchange.…”

Section: Review Of Literaturementioning

confidence: 99%

Commodity hedging benefits: analyses among different financial assets

Chalid

Handika

2022

JES

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PurposeThis study aims to investigate the benefits of commodity hedging in the global stock index, bond and foreign currency (FX) portfolios.Design/methodology/approachThe authors compare various hedging strategies and factor transaction costs. The authors analyze equally weighted, dynamic hedging ratio, risk parity and reward to risk timing strategies. Volatilities are estimated using historical, GARCH(1,1), and APARCH(1,1) methods. In addition, the authors evaluate the portfolio's hedging performance (HP) based on four different dimensions: volatility (annualized standard deviation), Sharpe ratio (SR), HP, and high-low ratio (HL).FindingsThe authors observe different benefits of the commodity hedging strategy among financial assets (stocks, bonds or FX).The authors find that commodity hedging in the stock markets is the best option, if the authors optimize the hedging ratio using dynamic hedging from historical data. The authors also document that for stock portfolio managers, adding commodities will generate a more conservative strategy, whereas for bond and/or FX portfolio managers, adding commodities will generate a more aggressive strategy.Originality/valueThis study contributes to the literature by investigating commodity hedging in the global stock index, bond and FX portfolios. First, the authors provide details on the diversification benefits in the commodities. Second, the authors document the hedging strategy that is the best as a part of the diversification strategy by adding commodities. Third, the authors provide a practical analysis by reporting the financial assets portfolio that is appropriate for commodity hedging following the portfolio managers' objectives (e.g. reducing risks or improving the risk-reward ratio).

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“…Apart from that, the majority of research on risk-managed momentum techniques has been on relative momentum. Furthermore, executing these risk-managed momentum techniques necessitates the computation of intricate parameters and the provision of additional cash (Singh et al, 2021). All these considerations make existing risk-managed momentum techniques unattractive amongst practitioners.…”

Section: Introductionmentioning

confidence: 99%

Risk-managed time-series momentum: an emerging economy experience

Singh

Walia²,

Bekiros³

et al. 2022

JEFAS

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PurposeThis research study aims to design a novel risk-managed time-series momentum approach. The present study also examines the time-series momentum effect in the Indian equity market. Apart from this, the study also proposes a novel risk-managed time-series momentum approach.Design/methodology/approachThe study considers the adjusted monthly closing prices of the stocks listed on the Bombay Stock Exchange from January 1996 to December 2020 to formulate long-short portfolios. Newey–West t statistics were used to test the significance of momentum returns. The present research has considered standard risk factors, i.e. market, size and value, to evaluate the risk-adjusted performance of time-series momentum portfolios.FindingsThe present research reports a substantial absolute momentum effect in the Indian equity market. However, absolute momentum strategies are exposed to occasional severe losses. The proposed time-series momentum approach not only yields 2.5 times higher return than the standard time-series momentum approach but also causes substantial enhancement in downside risks and higher-order moments.Practical implicationsThe study's outcomes offer valuable insights for professional investors, capital market regulators and asset management companies.Originality/valueThis study is one of the pioneers attempting to test the time-series momentum effect in emerging economies. Besides, current research contributes to the escalating literature on risk-managed momentum by suggesting a novel revised time-series momentum approach.

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Risk-Managed Momentum: An Evidence from Indian Stock Market

Cited by 4 publications

References 72 publications

Analyzing the Performance of Pakistan Equity Mutual Funds Using Multifactor Models: Pre-COVID Analysis

Analyzing the Performance of Pakistan Equity Mutual Funds Using Multifactor Models: Pre-COVID Analysis

Commodity hedging benefits: analyses among different financial assets

Risk-managed time-series momentum: an emerging economy experience

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