Risk-managed industry momentum and momentum crashes

This paper investigates Barroso and Santa-Clara’s [J. Financ. Econ., 2008, 116, 111–120] risk-managed momentum strategy in an industry momentum setting. We investigate several traditional momentum strategies including that recently proposed by Novy-Marx [J. Financ. Econ., 2012, 103, 429–453]. We moreover examine the impact of different variance forecast horizons on average pay-offs and also Daniel and Moskowitz’s [J. Financ. Econ., 2016, 122, 221–247] optionality effects. Our results show in general that neither plain industry momentum strategies nor the risk-managed industry momentum strategies are subject to optionality effects, implying that these strategies have no time-varying beta. Moreover, the benefits of risk management are robust across volatility estimators, momentum strategies and subsamples. Finally, the ‘echo effect’ in industries is not robust in subsamples as the strategy works only during the most recent subsample.     

The 52-week high momentum strategy in international stock markets

We study the 52-week high momentum strategy in international stock markets proposed by George and Hwang [George, T., Hwang, C.Y., 2004. The 52-week high and momentum investing. Journal of Finance 59, 2145-2176.]. This strategy produces profits in 18 of the 20 markets studied, and the profits are significant in 10 markets. The 52-week high momentum profits exist independently from the Jegadeesh and Titman [Jegadeesh, N., Titman, S., 1993. Returns to buying winners and selling losers: implications for market efficiency. Journal of Finance 48, 65-91.] individual stock and Moskowitz and Grinblatt [Moskowitz, T.J., Grinblatt, M., 1999. Do industries explain momentum? Journal of Finance 54, 1249-1290] industry momentum strategies. These profits do not show reversals in the long run. We find that the 52-week high is a better predictor of future returns than macroeconomic risk factors or the acquisition price. The individualism index, a proxy to the level of overconfidence, has no explanatory power to the variations of the 52-week high momentum profits across different markets. However, the profits are no longer significant in most markets once transaction costs are taken into account.     

The performance of enhanced-return index funds: evidence from bootstrap analysis

We apply the bootstrap technique proposed by Kosowski et al. [J. Finance, 2006, 61, 2551–2595] in conjunction with Carhart's [J. Finance, 1997, 52, 57–82] unconditional and Ferson and Schadt's [J. Finance, 1996, 51, 425–461] conditional four-factor models of performance to examine whether the performances of enhanced-return index funds over the 1996 to 2007 period are based on luck or superior ‘enhancing’ skills. The advantages of using the bootstrap to rank fund performance are many. It eliminates the need to specify the exact shape of the distribution from which returns are drawn and does not require estimating correlations between portfolio returns. It also eliminates the need to explicitly control for potential ‘data snooping’ biases that arise from an ex-post sort. Our results show evidence of enhanced-return index funds with positive and significant alphas after controlling for luck and sampling variability. The results are robust to both stock-only and derivative-enhanced index funds, although the spread of cross-sectional alphas for derivative-enhanced funds is slightly more pronounced. The study also examines various sub-periods within the sample horizon.     

Commodities momentum: A behavioral perspective

The growth in commodity-related investments has sparked interest in the performance of momentum strategies in these markets. This paper introduces a behavioral proxy of the 52-week high and low momentum that explains a significant proportion of the variation of conventional momentum returns after controlling for commodity specific risk factors. Our findings show that the 52-week high strategy generates significant profits after accounting for transaction costs. We report that the 52-week high strategy is a better predictor of returns than conventional momentum. Our findings suggest that term structure and hedging pressure risk factors provide only a partial explanation of the results.     

The timing of 52-week high price and momentum

We propose a new momentum strategy based on the timing of a stock’s 52-week high price. We find that the stocks that attained the 52-week high price in the recent past significantly outperform the stocks that attained the 52-week high price in the distant past. In particular, the top 10% of the stocks with the most recent 52-week high price outperform the bottom 10% of the stocks with most distant 52-week high price by 0.70% per month. Further, conditioning on the recency of 52-week high price significantly increases the profitability of momentum strategy based on the nearness of current price to the 52-week high price. Specifically, the average monthly return of this strategy is about twice as large for stocks with recent 52-week high price as compared with stocks with distant 52-week high price.     

New empirical evidence on the investment success of momentum strategies based on relative stock prices

This paper provides significant extensions and tests of momentum trading strategies based on relative prices that were first explored by George and Hwang (2004). We develop new momentum strategies based on the ratio of the current stock price to each of five different reference points in past prices: 52-week high, 52-week median, 52-week low, half-year high, and 2-year high. We measure their investment performance on the basis of the Fama and French 3-Factor and Momentum Model (Carhart four-factor model), and further employ the technique of nested trading strategies to measure incremental performance. The strategy based on the ratio of current stock price to its 52-week high price is the most profitable, and its performance is robust when tested over a wide range of financial and economic factors. Our results provide strong new evidence of the investment merits of a momentum trading strategy based on the 52-week high price ratio, and add new weight to challenges to the hypothesis that the stock market is efficient in the semi-strong sense.     

A novel Monte Carlo approach to hybrid local volatility models

We present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant. Finance, 2014, 14, 1899–1922], Piterbarg [Risk, 2007, April, 84–89], Tataru and Fisher [Quantitative Development Group, Bloomberg Version 1, 2010], Lipton [Risk, 2002, 15, 61–66]—and the local volatility model incorporating stochastic interest rates—see e.g. Atlan [ArXiV preprint math/0604316, 2006], Piterbarg [Risk, 2006, 19, 66–71], Deelstra and Rayée [Appl. Math. Finance, 2012, 1–23], Ren et al. [Risk, 2007, 20, 138–143]. For both model classes a particular (conditional) expectation needs to be evaluated which cannot be extracted from the market and is expensive to compute. We establish accurate and ‘cheap to evaluate’ approximations for the expectations by means of the stochastic collocation method [SIAM J. Numer. Anal., 2007, 45, 1005–1034], [SIAM J. Sci. Comput., 2005, 27, 1118–1139], [Math. Models Methods Appl. Sci., 2012, 22, 1–33], [SIAM J. Numer. Anal., 2008, 46, 2309–2345], [J. Biomech. Eng., 2011, 133, 031001], which was recently applied in the financial context [Available at SSRN 2529691, 2014], [J. Comput. Finance, 2016, 20, 1–19], combined with standard regression techniques. Monte Carlo pricing experiments confirm that our method is highly accurate and fast.     

Pricing American options written on two underlying assets

This paper extends the integral transform approach of McKean [Ind. Manage. Rev., 1965, 6, 32–39] and Chiarella and Ziogas [J. Econ. Dyn. Control, 2005, 29, 229–263] to the pricing of American options written on more than one underlying asset under the Black and Scholes [J. Polit. Econ., 1973, 81, 637–659] framework. A bivariate transition density function of the two underlying stochastic processes is derived by solving the associated backward Kolmogorov partial differential equation. Fourier transform techniques are used to transform the partial differential equation to a corresponding ordinary differential equation whose solution can be readily found by using the integrating factor method. An integral expression of the American option written on any two assets is then obtained by applying Duhamel’s principle. A numerical algorithm for calculating American spread call option prices is given as an example, with the corresponding early exercise boundaries approximated by linear functions. Numerical results are presented and comparisons made with other alternative approaches.     

The 52-week high,momentum, and investor sentiment

This paper examines the link between the profitability of the 52-week high momentum strategy and investor sentiment. We hypothesize that investors' investment decisions are subject to behavioral biases when the level of investor sentiment is high, resulting in higher profits for the 52-week high momentum following high-sentiment periods. Our empirical results confirm this prediction. In addition, we find that the significant profit of the 52-week high momentum following high-sentiment periods persists up to five years. Further investigations show that the strong persistence of the 52-week high winners (losers) is concentrated in stocks with higher (lower) earnings surprises, especially during periods following high sentiment. Overall, our results provide supportive evidence for the anchoring biases in explaining the 52-week high momentum, especially when the role of investor sentiment is taken into account.     

International comparison of returns from conventional,industrial and 52-week high momentum strategies

The performance of industrial and 52-week high momentum strategies is compared to the conventional strategy, using a large sample of stocks drawn from multiple countries covering a quarter of century to 2007. The sample of 51,879 stocks in 51 countries removes the potential for criticism, such as data mining, and provides more generalisable findings and knowledge concerning the robustness and usefulness of return from momentum strategies. Both the industry and 52-week high strategies generate positive returns but neither is greater than the conventional momentum strategy. A new 52-week high industry momentum strategy is examined and it achieves a similar result.     

ON INDUSTRY MOMENTUM STRATEGIES

In this article, we investigate industry momentum strategies. We find that industry portfolios that outperformed in the previous month generate on average significantly higher returns in the holding period than those that underperformed. Plain and risk-managed strategies using this short-run industry momentum are not subject to optionality effects. Also, the tail risks of these strategies are uncorrelated with traditional industry momentum strategies. The spread associated with the risk-managed strategy both meets necessary conditions as a risk factor and is significantly priced in the cross-section of U.S. industry portfolios.     

Valuation of forward start options under affine jump-diffusion models

Under the general affine jump-diffusion framework of Duffie et al. [Econometrica, 2000, 68, 1343–1376], this paper proposes an alternative pricing methodology for European-style forward start options that does not require any parallel optimization routine to ensure square integrability. Therefore, the proposed methodology is shown to possess a better accuracy–efficiency trade-off than the usual and more general approach initiated by Hong [Forward Smile and Derivative Pricing. Working paper, UBS, 2004] that is based on the knowledge of the forward characteristic function. Explicit pricing solutions are also offered under the nested jump-diffusion setting proposed by Bakshi et al. [J. Finance, 1997, 52, 2003–2049], which accommodates stochastic volatility and stochastic interest rates, and different integration schemes are numerically tested.     

Hedging jump risk,expected returns and risk premia in jump-diffusion economies

This article presents a pure exchange economy that extends Rubinstein [Bell J. Econ. Manage. Sci., 1976, 7, 407–425] to show how the jump-diffusion option pricing model of Black and Scholes [J. Political Econ., 1973, 81, 637–654] and Merton [J. Financ. Econ., 1976, 4, 125–144] evolves in gamma jumping economies. From empirical analysis and theoretical study, both the aggregate consumption and the stock price are unknown in determining jumping times. By using the pricing kernel, we determine both the aggregate consumption jump time and the stock price jump time from the equilibrium interest rate and CCAPM (Consumption Capital Asset Pricing Model). Our general jump-diffusion option pricing model gives an explicit formula for how the jump process and the jump times alter the pricing. This innovation with predictable jump times enhances our analysis of the expected stock return in equilibrium and of hedging jump risks for jump-diffusion economies.     

The 52-week high,momentum, and predicting mutual fund returns

George and Hwang (J Finance 59:2145–2176, 2004) have shown that the 52-week high share price carries significant predictive ability for individual stock returns, dominating other common momentum-based trading strategies. Based upon their results and other methods, this paper examines and compares the performance of three momentum trading strategies for mutual funds, including an analogous 1-year high measure for the net asset value of mutual fund shares. Strategies based on prior extreme returns and on fund exposure to stock return momentum are also examined. Results show that all three measures have significant, independent, predictive ability for fund returns. Further, each produces a distinctive pattern in momentum profits, whether measured in raw or risk-adjusted returns, with profits from momentum loading being the least transitory. Nearness to the 1-year high and recent extreme returns are significant predictors of fund monthly cash flows, whereas fund momentum loading is not.     

Are tightened trading rules always bad? Evidence from the Chinese index futures market

This paper investigates the impact of tightened trading rules on the market efficiency and price discovery function of the Chinese stock index futures in 2015. The market efficiency and the price discovery of Chinese stock index futures do not deteriorate after these rule changes. Using variance ratio and spectral shape tests, we find that the Chinese index futures market becomes even more efficient after the tightened rules came into effect. Furthermore, by employing Schwarz and Szakmary [J. Futures Markets, 1994, 14(2), 147–167] and Hasbrouck [J. Finance, 1995, 50(4), 1175–1199] price discovery measures, we find that the price discovery function, to some extent, becomes better. This finding is consistent with Stein [J. Finance, 2009, 64(4), 1517–1548], who documents that regulations on leverage can be helpful in a bad market state, and Zhu [Rev. Financ. Stud., 2014, 27(3), 747–789.], who finds that price discovery can be improved with reduced liquidity. It also suggests that the new rules may effectively regulate the manipulation behaviour of the Chinese stock index futures market during a bad market state, and then positively affect its market efficiency and price discovery function.     

Characterizations of optimal reinsurance treaties: a cost-benefit approach

This article investigates optimal reinsurance treaties minimizing an insurer’s risk-adjusted liability, which encompasses a risk margin quantified by distortion risk measures. Via the introduction of a transparent cost-benefit argument, we extend the results in Cui et al. [Cui, W., Yang, J. & Wu, L. (2013). Optimal reinsurance minimizing the distortion risk measure under general reinsurance premium principles. Insurance: Mathematics and Economics 53, 74–85] and provide full characterizations on the set of optimal reinsurance treaties within the class of non-decreasing, 1-Lipschitz functions. Unlike conventional studies, our results address the issue of (non-)uniqueness of optimal solutions and indicate that ceded loss functions beyond the traditional insurance layers can be optimal in some cases. The usefulness of our novel cost-benefit approach is further demonstrated by readily solving the dual problem of minimizing the reinsurance premium while maintaining the risk-adjusted liability below a fixed tolerance level.     

The systematic pricing of market sentiment shock

ABSTRACT

We show that market sentiment shocks create demand shocks for risky assets and a systematic risk for assets. We measure a market sentiment shock as the unexpected portion of the University of Michigan Consumer Sentiment Index’s growth. This shock prices stock returns in arbitrage pricing theory framework at 1% after controlling for market, size, value, momentum, and liquidity risk factors. Its premium lowered the implied risk aversion by 97.9% to 11.46 between 1978 and 2009 in our sentiment consumption-based capital-asset-pricing model. Merton’s [1973. “An Intertemporal Capital Asset Pricing Model.” Econometrica 41: 867–887]. intertemporal capital-asset-pricing model reconfirms our finding that this market sentiment shock is a systematic risk factor that provides investment opportunities.     

Beating the DAX,MDAX, and SDAX: investment strategies in Germany

Motivated by two recent papers of Asness et al. (J Portf Manag Fall 40(5):75–92, 2014; J Portf Manag Fall 42(1):34–52, 2015), we investigate whether momentum and value strategies outperformed a buy-and-hold strategy in the three biggest German equity indices, DAX, MDAX, and SDAX from 1988 to 2015. Our findings show that a momentum premium was present only in the SDAX and that value strategies did not work in any of the three indices. Consequently, we conclude that at least the DAX and MDAX are efficient indices and that some supposedly abnormal returns could be illusionary, as limits to arbitrage obstruct any profitable exploitation in practice. Finally, we find a negative correlation between momentum and value in the DAX and show that mixing both strategies can substantially decrease a portfolio’s risk.     

Testing the growth option theory: the profitability of enhanced momentum strategies in Australia

Recent literature relates growth option theory to various return regularities. Sagi and Seasholes (2007) (S&S) develop a model that explains momentum profitability using growth option theory. We test the model’s predictions in the Australian market by examining three momentum strategies. Two of these strategies examine the profitability of momentum strategies conditioned on stocks characteristics, whereas the third conditions on previous market returns. Our results are largely supportive of the S&S model. As predicted by S&S, the two strategies that use firm‐specific characteristics yield a higher profit than a simple momentum strategy. The third strategy that conditions on the previous market return also leads to differences in momentum profitability between bull and bear markets, but these differences are small and largely insignificant.