Working Papers by Kuntara Pukthuanthong
# | Title | Authors | Date | Length | Paper | Abstract | |
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1446 | Changing Expected Returns Can Induce Spurious Serial Correlation | Pukthuanthong, Kuntara Roll, Richard Subrahmanyam, Avanidhar | 09/21/2021 | 59 | sswp1446_revised.pdf | Changing expected returns can induce spurious autocorrelation in returns. We show why this happens with simple examples and investigate its prevalence in actual equity data. In a key contribution, we use ex ante expected return estimates from options prices, factor models, and analysts' price targets to investigate our premise. Absolute shifts in expected returns are indeed strongly and positively related to autocorrelations in the cross-section of individual stocks, as predicted by our analysis. Well-studied risk factors show no evidence of spurious components. We also show how our analysis implies spurious cross-autocorrelation and find supporting evidence for this phenomenon as well. | |
1431 | A Protocol for Factor Identification | Pukthuanthong, Kuntara Roll, Richard Subrahmanyam, Avanidhar | 07/28/2017 | 51 | sswp1431.pdf | We propose a protocol for identifying genuine risk factors. The underlying premise is that a risk factor must be related to the covariance matrix of returns, must be priced in the cross-section of returns, and should yield a reward-to-risk ratio that is reasonable enough to be consistent with risk pricing. A market factor, a profitability factor, and traded versions of macroeconomic factors pass our protocol, but many characteristic-based factors do not. Several of the underlying characteristics, however, do command material premiums in the cross-section. | |
1405 | An Agnostic and Practically Useful Estimator of the Stochastic Discount Factor | Pukthuanthong, Kuntara Roll, Richard | 03/05/2015 | 72 | SSWP_1405R.pdf | We propose an estimator for the stochastic discount factor (SDF) which is agnostice because it does not require macroeconomic proxies or preference assumptions. It depends only on observed asset returns. Nonetheless, it is immune to the form of the multivariate return distribution, including the distribution's factor structure. Putting our estimator to work, we find that a unique positive SDF prices all U.S. asset classes and satisfies the Hansen/Jagannathan variance bound. In contrast, the Chinese and Indian equity markets do not share the same SDF and hence do nto seem to be integrated. | |
1392 | Resolving the Errors-in-Variables Bias in Risk Premium Estimation | Roll, Richard Wang, Junbo Pukthuanthong, Kuntara | 07/21/2014 | 57 | SSWP_1392.pdf | The Fama-Macbeth (1973) rolling-B method is widely used for estimating risk premiums, but its inherent errors-in-variables bias remains an unresolved problem, particularly when using individual assets or macroeconomic factors. We propose a solution with a particular instrumental variable, B calculated from alternate observations. The resulting estimators are unbiased. In simulations, we compare this new approach with several existing methods. The new approach corrects the bias even when the sample period is limited. Moreover, our proposed standard errors are unbiased, and lead to correct rejection size in finite samples.
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