I investigate the information content in the implied volatility spread, which is the spread in implied volatilities between a pair of call and put options with the same strike price and time-to-maturity. By constructing the implied volatility time series for each stock, I show that stocks with larger implied volatility spreads tend to have higher future returns during 2003-2013. I also find that even volatilities implied from untraded options contain such information about future stock performance. The trading strategy based on the information contained in the actively traded options does not necessarily outperform its counterpart derived from the untraded options. This is inconsistent with the previous research suggesting that the information contained in the implied volatility spread largely results from the price pressure induced by informed trading in option markets. Further analysis suggests that option illiquidity is associated with the implied volatility spread, and the magnitude of this spread contains information about the risk-neutral distribution of the underlying stock return. A larger spread is associated with smaller risk-neutral variance, more negative risk-neutral skewness, and seemingly larger risk-neutral kurtosis, and this association is primarily driven by the systematic components in risk-neutral higher moments. I design a calibration study which reveals that the non-normality of the underlying risk-neutral return distribution relative to the Brownian motion can give rise to the implied volatility spread through the channel of early exercise premium.

This dissertation consists of two essays in asset allocation. In the first essay, I measure the value of active money management. I explore this issue by comprehensively examining the parametric rule proposed by Brandt, Santa-Clara and Valkanov (2009) (the BSV rule) out-of-sample for portfolio selection among 3516 stocks in CRSP and comparing this rule to the mean-variance (MV) rule and the naïve 1/N rule recently advocated by DeMiguel, Garlappi and Uppal (2009). The BSV rule outperforms both the MV and 1/N rules and the outperformance is robust to investment horizons and stock market states. The BSV rule is effective for investors with different preferences or investment opportunities. The effectiveness of the BSV rule is robust to data screening criteria, estimation periods, portfolio performance evaluation models, the business cycle, and stock market states. In the second essay, I explore the question of whether macroeconomic state variables are able to predict cross-sectional stock returns from the perspective of asset allocation. I find that conditioning on macroeconomic state variables leads to optimal portfolios with a Carhart alpha that is 125 basis points per month higher than unconditional optimal portfolios out-of-sample. Unfortunately, conditioning on macroeconomic states is subject to an "overfitting" problem and can lead investors to experience unexpected huge losses. My results suggest that macroeconomic state variables mare able to predict cross-sectional stock returns but risk-averse investors need to combine other funds (e.g. market portfolio) to take advantage of this predictability.

This thesis includes three essays on topics related to the predictability of market returns. I investigate i) the predictability of market returns from an adjusted version of cay ratio (cayadj), ii) the explanatory power of a conditional version of the consumption-CAPM which uses predictor variables to scale the pricing kernel, and iii) whether information about future market returns can be extracted from a large set of commodity data. The first essay studies the predictive ability of cayadj . In Campbell and Mankiw (1989), the consumption-wealth ratio is represented as a linear function of expected market returns and consumption growth. Lettau and Ludvigson (2001) build their study on Campbell and Mankiw (1989) and estimate the ratio cay as a proxy for the consumption-wealth ratio, assuming that the fluctuation in expected consumption growth is constant. I argue that the variation in expected consumption growth should be taken into consideration and propose adjusting the cay ratio by the estimates of expected consumption growth. After making the adjustment, I find that the predictabilities of market returns, particularly at annual, bi-annual, and tri-annual horizons, are greatly improved. The significant predictive ability of cayadj still holds in out-of-sample forecasts. The second essay examines the performance of a conditional version of the consumption-CAPM, where conditioning variables are used to scale the pricing kernel. I find that incorporating the conditioning information into the standard consumption-CAPM greatly improves the performance in asset pricing tests, particularly when using cayadj as the conditioning variable. Moreover, the performance of conditional consumption-CAPM is as good as the ultimate consumption risk model (Parker and Julliard, 2005) which measures the consumption risk over several quarters. Further tests show that the factors of conditional consumption-CAPM drive out the consumption risk measured over several quarters. The third essay evaluates the ability of lagged commodity returns to forecast market returns. In order to exploit the predictive information from a relatively large amount of commodity returns, I apply the partial-least-squares (PLS) method pioneered by Kelly and Pruitt (2013). I find that the commodity returns measured over previous twelve months show strong predictive power in monthly and three-month forecasts, in-sample and out-of-sample. The findings are robust to controlling for risk factors such as momentum, Fama-French three factors and industry returns previously identified to be significant predictors of market returns (Hong, Torous and Valkanov, 2007).

<p>In Chapter 1, I construct a new proxy for Tobin's q that incorporates the replacement cost of patent capital. This proxy, PI (physical plus intangible) q, explains up to 64\% more variation in investment than other proxies for q. Furthermore, investment is more sensitive to PI q than to other proxies for q. Although investment is predicted more accurately by, and is more sensitive to, PI q, controlling for PI q leads to relatively higher, not lower, cash flow coefficients. All results are stronger in subsamples with more patent capital. Overall, using PI q strengthens the historically weak investment-q relation.</p> <p><br></p> <p>Chapter 2 includes Noah Stoffman and M. Deniz Yavuz as co-authors, and in this chapter, we find that small innovators (i.e., small, innovative firms) earn higher returns than small non-innovators for up to five years. We find no such innovative premium among large firms. A battery of tests shows that our results are explained by risk, not investor underreaction. Small innovators are especially risky because they focus more on risky product innovation and rely more on organization capital that amplifies their systematic risk. In addition, small innovators contribute significantly to the size premium. Overall, small innovators have a higher cost of equity, which potentially explains why they rely heavily on internal capital.</p>

We evaluate the validity of the Adaptive Market Hypothesis (AMH) in a Swedish context by testing for stock return predictability on the OMXS30 stock index between 1986 and 2014 using daily returns and monthly two year moving subsamples. To our knowledge, this is the first study to evaluate the AMH in a Swedish context. Three tests for linear independence based on Lo and MacKinlay (1988) variance ratio test, namely the Chow and Denning joint test as well as Wright (2000) joint rank and sign tests are used. We also test for non-linear independence using the BDS test statistics. Presented in our findings is evidence of time-varying predictability where stock returns go through periods of return predictability and non-predictability. When evaluating the different market conditions (volatility, bull, bear, up, down and normal markets) we find that these different market conditions govern the degree of stock return predictability in different ways. Our findings support the AMH on the OMXS30 stock index and in contrast to previous research regarding market efficiency on the Swedish stock market, we do not find persistent stock return predictability over the short and long term.