Idiosyncratic Volatility: Evidence from Asia

The traditional Capital Asset Pricing Model states that assets can earn only higher returns if they have a high beta. However, evidence shows that the single risk factor is not quite adequate for describing the cross-section of stock returns. The current consensus is that firm size and book-to-market equity factors are pervasive risk factors besides the overall market factor. Malkiel and Xu (1997 and 2000) further the debate in empirical asset pricing by stating that idiosyncratic volatility is useful in explaining the cross-sectional expected returns. In this paper we provide international evidence on the relationship between expected stock returns, overall market factor, firm size and idiosyncratic volatility. Our findings suggest that size and idiosyncratic volatility premium are real and pervasive. We find that small and high idiosyncratic volatility stocks generate superior returns and hence suggest that such firms carry risk premia. Our findings also suggest that idiosyncratic volatility is more powerful than the CAPM beta and the firm size effect. Our findings challenge the portfolio theory of Markowitz (1952) and the CAPM of Sharpe (1964), which advances the notion that it is rational for a utility maximizing investor to hold a well-diversified portfolio of investments to eliminate idiosyncratic risks.Idiosyncratic risk, Portfolio Theory, Capital Asset Pricing Model, Size effect and Beta.

DistancePPG: Robust non-contact vital signs monitoring using a camera

Vital signs such as pulse rate and breathing rate are currently measured using contact probes. But, non-contact methods for measuring vital signs are desirable both in hospital settings (e.g. in NICU) and for ubiquitous in-situ health tracking (e.g. on mobile phone and computers with webcams). Recently, camera-based non-contact vital sign monitoring have been shown to be feasible. However, camera-based vital sign monitoring is challenging for people with darker skin tone, under low lighting conditions, and/or during movement of an individual in front of the camera. In this paper, we propose distancePPG, a new camera-based vital sign estimation algorithm which addresses these challenges. DistancePPG proposes a new method of combining skin-color change signals from different tracked regions of the face using a weighted average, where the weights depend on the blood perfusion and incident light intensity in the region, to improve the signal-to-noise ratio (SNR) of camera-based estimate. One of our key contributions is a new automatic method for determining the weights based only on the video recording of the subject. The gains in SNR of camera-based PPG estimated using distancePPG translate into reduction of the error in vital sign estimation, and thus expand the scope of camera-based vital sign monitoring to potentially challenging scenarios. Further, a dataset will be released, comprising of synchronized video recordings of face and pulse oximeter based ground truth recordings from the earlobe for people with different skin tones, under different lighting conditions and for various motion scenarios.Comment: 24 pages, 11 figure

On the Value Premium in Malaysia

Davis, Fama and French (2000) report that the value premium in United States’ stocks is robust. Herein, we present out-of-sample evidence for Malaysia, finding that value stocks outperform growth stocks and document an arbitrage opportunity. We observe that the mean monthly returns are substantially higher for the two mimic portfolios (SMB and HML) when compared with the market portfolio. For the period 1991 through 1999, an investor generated 1.92% (annually) holding the market portfolio in Malaysia, compared with the two mimic portfolios, SMB and HML with returns of 17.70% and 17.69% respectively. We also observe that the standard deviations for the two mimic portfolios are significantly lower than the standard deviation of the market portfolio. Moreover, the findings presented in this study reject the notion of survivorship bias advanced by Kothari, Shanken and Sloan (1995) and the data-snooping hypothesis attributed to Black (1993) and Mackinlay (1995) as an explanation for the value premium.Asset pricing, multifactor models, value premium, arbitrage

ASSET PRICING IN THE ASIAN REGION

In this asset pricing study, three questions are addressed. First, does the multifactor model of Fama and French (1993) capture returns in Asian stock markets in a meaningful manner? Second, do small firms and high book-to-market equity firms carry a risk premia? Third, can competing hypotheses (such as survivorship bias, data-snooping and irrationality) explain the multifactor model results? The answers from this study are as follows: The multifactor model of Fama and French (1993) provides a parsimonious description of the cross-section of returns, with the relationship between firm size, book-to-market equity and average stock returns being robust for Asian markets over the 1990s. We find that small firms and high book-to-market equity firms carry a risk premia, providing opportunities for mean-variance efficient investors. Finally, our findings reject the claim that the results of multifactor model can be explained by competing hypotheses for the Asian experience.Multifactor asset pricing models, Asian region, size effect, book-to-market equity effect.

Do Momentum Strategies Work?: - Australian Evidence

This paper investigates the profitability of momentum investment strategy and the predictive power of trading volume for equities listed in the Australian Stock Exchange. Recent research finds that momentum and trading volume appear to predict subsequent returns in U.S. market and past volume helps to reconcile intermediate-horizon “under reaction” and long-horizon “overreaction” effects. However, bulk of the evidence on this important relationship between past returns and future returns is limited to U.S. portfolios. This study provides an out of sample evidence by examining the relationship between “trading volume” (measured by the turnover ratio) and “momentum” strategies in an Australian setting. We document a strong momentum effect for the Australian market during the period 1988 through 2002 and find that momentum plays an important role in providing information about stocks. We also find that past trading volume predicts both the magnitude and persistence of price momentum. In summary, our findings are consistent with the U.S. evidence.

IDIOSYNCRATIC RISK AND AUSTRALIAN EQUITY RETURNS

In this paper we investigate the relationship between portfolio returns and idiosyncratic risk for Australian stocks. We report that the portfolio with highest idiosyncratic volatility generates an average annual return of over 45%. We observe additionally that the outcome is consistent with an exponential growth process for stock prices. Further, consistent with Malkiel and Xu, we observe that a stock’s idiosyncratic volatility is inversely correlated with the size of the underlying firm. Thus, our model advances an interpretation of the Fama and French finding that portfolios of stocks of small firms offer superior risk-adjusted returns. Moreover, our findings challenge the portfolio theory of Markowitz (1959) and the asset-pricing model of Sharpe (1964).Idiosyncratic risk, Capital Asset Pricing Model, Size effect

Is Idiosyncratic Volatility Priced? Evidence from the Shanghai Stock Exchange

This paper employs the mimicking portfolio approach of Fama and French (1996) and asks whether idiosyncratic volatility is priced. This paper also provides evidence on whether returns on small stocks are higher in January than in remaining months. Our findings reveal that (a) idiosyncratic volatility is priced; and, (b) the multifactor model provides a better description of average returns than the traditional CAPM. We also find that the absolute pricing errors of the CAPM are large when compared with the multifactor model. We argue that firm size and idiosyncratic volatility may serve as proxies for systematic risk. We also dismiss the claim that returns on small stocks are on average higher in January than in remaining months. In summary, investors interested in taking additional risks should invest in small and low idiosyncratic volatility firms in addition to the market portfolio. This is because our findings indicate that investors can generate substantial returns by investing in strategies unrelated to market movements.Idiosyncratic Volatility, Firm Size, Asset Pricing, China.