Feasible momentum strategies: Evidence from the Swiss stock market

Rey, David; Schmid, Markus

doi:10.1007/s11408-007-0051-9

Cited by 32 publications

(4 citation statements)

References 44 publications

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“…For momentum investing, we use the price momentum calculated as a price return over a certain period of J in the past (Leivo and Pätäri, 2011). The lag of J is defined as a formation period (Rey and Schmid, 2007). This is a common measure for momentum, where the lags may vary from one month to twelve months 2 .…”

Section: Fundamental Variablesmentioning

confidence: 99%

Combining momentum, value, and quality for the Islamic equity portfolio: Multi-style rotation strategies using augmented Black Litterman factor model

Dewandaru¹,

Masih

Bacha

et al. 2015

Pacific-Basin Finance Journal

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This study constructs active Islamic portfolios using a multi-style rotation strategy, derived from the three prominent styles, namely, momentum, value, and quality investing. We use the stocks that are consistently listed in the U.S. Dow Jones Islamic index for a sample period from 1996 to 2012. We also include two macroeconomic mimicking portfolios to capture the premiums of industrial production growth and inflation innovation, accommodating the economic regime shifts. Based on the information coefficients, we find the six-month momentum and the fractal measure as momentum factors; the enterprise yield (gross profit/TEV) and the book to market ratio as valuation factors; the gross profit to total assets, the return on capital, and the scaled total accruals as quality factors. We further construct active portfolios using the augmented Black Litterman (ABL) factor model to avoid the factor alignment problem, with the factor views predicted using Markov Switching VAR, MIDAS, and Bayesian Model Averaging. The out-of-sample performance of our portfolios can produce information ratios of 0.7-0.8 over the composite indices, and information ratios of 0.42-0.48 over the style indices, with the annualized alphas of 10-11%. Even when we put the constrained tracking error of 1% over the benchmark, our portfolios still produce information ratios of 0.9-1.2 before transaction costs, and 0.6-0.8 after transaction costs. We provide intuitive explanations for each premium changing over time, and suggest the promising strategy for Islamic equity investors to outperform the market.

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Section: Fundamental Variablesmentioning

confidence: 99%

Combining momentum, value, and quality for the Islamic equity portfolio: Multi-style rotation strategies using augmented Black Litterman factor model

Dewandaru¹,

Masih

Bacha

et al. 2015

Pacific-Basin Finance Journal

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“…Oscillations could be caused by a cooperation of forces resulting from momentum and level trading techniques. This research is also supported by momentum studies of Pesaran and Timmermann (1995), Chan et al (1996), Stankevičienė and Gembickaja (2012), Donefer (2010), Easley et al (2011Easley et al ( , 2012; Franck et al (2013), Rey and Schmid (2007), Witzany (2009Witzany ( ), Žďárek (2012.…”

Section: Model Assemblingmentioning

confidence: 57%

Complex Model of Market Price Development and Its Simulation

Stádník

Miečinskienė

2015

Journal of Business Economics and Management

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The purpose of this study is to suggest a complex model of market price development for liquid assets, which is able to simulate all of the main features particular to the real price development and has a realistic financial explanation. First, the paper defines assumptions for the model construction from empirically observed processes. Then, the model is implemented in the real simulation environment. Finally, the ability of the model is checked to simulate empirically observed features, e.g. leptokurtic characteristics or skewness of the price distribution. Also, this paper newly defines and implements the resonance effect. FFT analysis is used to support oscillation processes. Finally, selected markets are provided with parameter optimisation of the model based on empirical observations. It was found that the model built under the previously mentioned assumptions was able to explain empirically observed effects that reversely support the correctness of those assumptions. The practical value of the constructed model can be found in many areas, including risk management and asset valuation.

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“…In addition, other researchers have individually checked different stock markets over different time periods, and have consistently reported positive abnormal returns after implementing momentum strategies. Some of these include Rey and Schmid (2007) for Swiss, Chelley-Steeley and Siganos (2008) for the UK, Du, Huang and Liao (2009) for Taiwan, Phua, Chan, Faff and Hudson (2010) for Australian and, Alphonse and Nguyen (2013) for Vietnam stock markets. In the Indian context, however, the studies are limited.…”

Section: Literature Reviewmentioning

confidence: 99%

Market State and Investment Strategies: Evidence from the Indian Stock Market

Maheshwari

Dhankar

2018

IIM Kozhikode Society & Management Review

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This study contributes to the growing literature on momentum and overreaction effect by investigating the same within the framework of the Indian stock market. Based on the most adopted methodology that employs monthly data, the empirical results derived confirm the existence of momentum and long-term overreaction effect in the Indian stock market. The overall results from the study are consistent with DeBondt and Thaler (1985) and Jegadeesh and Titman (1993) findings for the US stock market. In addition, we tested the profitability of momentum and contrarian strategies under different market states. The results indicated a strong relationship between the state of the market and momentum profitability, wherein strong momentum profits were observed following an ‘up’ market. On the contrary, long-term contrarian strategies were found to be stronger following a ‘down’ market in the Indian stock market. The market-dependent asset pricing model failed to explain excess momentum profits in the Indian stock market. The evidence from the study provides partial support to various behavioural models to explain these effects in the Indian stock market. However, there exists a need to develop a single behavioural model that could explain these anomalies completely in the emerging markets like India.

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Feasible momentum strategies: Evidence from the Swiss stock market

Abstract: Momentum strategies, Large-caps, Event study analysis, Stock market predictability, Under- and overreaction, G11, G12,

Cited by 32 publications

References 44 publications

Combining momentum, value, and quality for the Islamic equity portfolio: Multi-style rotation strategies using augmented Black Litterman factor model

Combining momentum, value, and quality for the Islamic equity portfolio: Multi-style rotation strategies using augmented Black Litterman factor model

Complex Model of Market Price Development and Its Simulation

Market State and Investment Strategies: Evidence from the Indian Stock Market

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