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Dec
2
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May
10
Stock returns however exhibit nonormal skewness and kurtosis as pointed out by Hull (1993) and Nattenburg (1994). Moreover, the volatility skews are a consequence of the empirical normality assumption violation. For this reason, Corrado and Su (1996) extend the Black-Scholes formula to account for nonnormal skewness and kurtosis in stock returns.
This package calculates the European put and call option prices using the Corrado and Su (1996) model. This method explicitly allows for excess skewness and kurtosis in an expanded Black-Scholes option pricing formula. The approach adapts a Gram-Charlier series expansions of the standard normal density function to yield an option price formula that is the sum of a Black–Scholes option price plus adjustment terms for nonnormal skewness and kurtosis (Corrado and Su, 1997).
For skewness = 0 and kurtosis = 3, the Corrado-Su option prices are equal to the prices obtained using the Black and Scholes (1973) model.
You can download the Matlab code at Corrado and Su (1996) European Option Prices.
References:
Corrado, C.J., and Su T. Skewness and kurtosis in S&P 500 Index returns implied by option prices. Financial Research 19:175–92, 1996.
Corrado, C.J., and Su T. Implied volatility skews and stock return skewness and kurtosis implied by stock option prices. European Journal of Finance 3:73–85, 1997.
Hull, J.C., "Options, Futures, and Other Derivatives", Prentice Hall, 5th edition, 2003.
Luenberger, D.G., "Investment Science", Oxford Press, 1998.
This package calculates the European put and call option prices using the Corrado and Su (1996) model. This method explicitly allows for excess skewness and kurtosis in an expanded Black-Scholes option pricing formula. The approach adapts a Gram-Charlier series expansions of the standard normal density function to yield an option price formula that is the sum of a Black–Scholes option price plus adjustment terms for nonnormal skewness and kurtosis (Corrado and Su, 1997).
For skewness = 0 and kurtosis = 3, the Corrado-Su option prices are equal to the prices obtained using the Black and Scholes (1973) model.
You can download the Matlab code at Corrado and Su (1996) European Option Prices.
References:
Corrado, C.J., and Su T. Skewness and kurtosis in S&P 500 Index returns implied by option prices. Financial Research 19:175–92, 1996.
Corrado, C.J., and Su T. Implied volatility skews and stock return skewness and kurtosis implied by stock option prices. European Journal of Finance 3:73–85, 1997.
Hull, J.C., "Options, Futures, and Other Derivatives", Prentice Hall, 5th edition, 2003.
Luenberger, D.G., "Investment Science", Oxford Press, 1998.
May
1
A paper published in The Journal of Portfolio Management, 2013, 39 (3), pp 102-111, by James X. Xiong, Rodney N. Sullivan, and Peng Wang.
Basically this article examines a portfolio strategy that buys stocks and sells bonds when the market is less liquid, thus enjoying a higher liquidity premium, this strategy outperforms a benchmark with equal weights on stocks and bonds by generating a higher sharpe ratio and positive alpha.
Journal paper Working paper
We propose a model of portfolio selection that adjusts an investors’ portfolio allocation in accordance with changing market liquidity environments and market conditions. We found that market liquidity provides a useful “leading indicator” in dynamic asset allocation. Specifically, market liquidity risk premium cycles anticipate economic and market cycles. Investors can therefore act to avoid markets with low liquidity premiums, waiting to extract liquidity risk premiums when the likelihood of extracting a liquidity premium improves. The result, meaningfully enhanced portfolio performance through economic and market cycles, and is robust to transactions costs and alternate specifications.
Basically this article examines a portfolio strategy that buys stocks and sells bonds when the market is less liquid, thus enjoying a higher liquidity premium, this strategy outperforms a benchmark with equal weights on stocks and bonds by generating a higher sharpe ratio and positive alpha.
Journal paper Working paper
Feb
15
Improving the accuracy of mutual funds' performance prediction is an interesting and endless topic. A paper published in Review of Financial Studies by Amihud and Goyenko (2013) No. 26 (3) investigates this issue at a new angle: Lower R2 indicates greater selectivity, and it significantly predicts better performance. Nice.
Journal paper, Working paper.
We propose that fund performance can be predicted by its R2, obtained from a regression of its returns on a multifactor benchmark model. Lower R2 indicates greater selectivity, and it significantly predicts better performance. Stock funds sorted into lowest-quintile lagged R2 and highest-quintile lagged alpha produce significant annual alpha of 3.8%. Across funds, R2 is positively associated with fund size and negatively associated with its expenses and manager's tenure.
Journal paper, Working paper.
Jan
31
A paper published in the Journal of Portfolio Management, 2013, Vol. 39, No. 2: pp. 28-40, by Alexandre Hocquard, Sunny Ng, and Nicolas Papageorgiou.
The idea is simple, easy to implement, has a good performance based on the authors' results.
Journal paper, Working paper.
Since Lehman Brothers collapsed in 2008, tail-risk hedging has become an increasingly important concern for investors. Traditional approaches, such as purchasing options or variance swaps as insurance, are often expensive, illiquid, and result in a substantial drag on performance. A more prudent, cost-effective way to maintain a constant risk exposure is to actively manage portfolio exposure according to the prevailing volatility level within underlying assets. The authors implement a robust methodology based on Dybvig’s payoff distribution model to target a constant level of volatility and normalize monthly returns. This approach to portfolio and risk management can help investors obtain their desired risk exposures over both short and longer time frames, reduce exposure to tail risk, and in general increase portfolios’ risk-adjusted performance.
The idea is simple, easy to implement, has a good performance based on the authors' results.
Journal paper, Working paper.
Jan
21
A paper published in Management Science written by Zymler, S., Kuhn, D., and Rustem, B. Nice & Practical.
Journal, Working paper in PDF.
Portfolio optimization problems involving value at risk (VaR) are often computationally intractable and require complete information about the return distribution of the portfolio constituents, which is rarely available in practice. These difficulties are compounded when the portfolio contains derivatives. We develop two tractable conservative approximations for the VaR of a derivative portfolio by evaluating the worst-case VaR over all return distributions of the derivative underliers with given first- and second-order moments. The derivative returns are modelled as convex piecewise linear or—by using a delta–gamma approximation—as (possibly nonconvex) quadratic functions of the returns of the derivative underliers. These models lead to new worst-case polyhedral VaR (WPVaR) and worst-case quadratic VaR (WQVaR) approximations, respectively. WPVaR serves as a VaR approximation for portfolios containing long positions in European options expiring at the end of the investment horizon, whereas WQVaR is suitable for portfolios containing long and/or short positions in European and/or exotic options expiring beyond the investment horizon. We prove that—unlike VaR that may discourage diversification—WPVaR and WQVaR are in fact coherent risk measures. We also reveal connections to robust portfolio optimization.
Journal, Working paper in PDF.
