My research interests include Empirical Asset Pricing, Portfolio Optimization, Behavioural Finance. My PhD thesis consists of three empirical essays on behavioural finance. In the first chapter I assess the relative performance of strategies stemming from the mean-variance, kelly and universal portfolio literature. The second chapter estimates style herding of US mutual funds and it studies its determinants and consequences. The third chapter adopts Bayesian statistical methods to estimate a two-regime Markov-switching state space representation of the present-value model with periodically collapsing bubbles.
with Joshua C.C. Chan
Abstract. We incorporate a speculative bubble subject to a surviving and a collapsing regime into the present-value model by Binsbergen et al. (2010), who pioneer the latent variables approach to estimate expected returns and expected dividend growth rates. To estimate this new high-dimensional model, we develop an efficient Markov chain Monte Carlo sampler to simulate from the joint posterior distribution. We apply our present-value model to artificial as well as real-world datasets. Our setup is able to correctly identify 92.27% of all the bubble collapsing dates in the artificial datasets. And it never signals a bubble when there is none in the data generating process. We then show the existence of significant Markov-switching structures in real-world stock price bubbles. The results indicate that dividend growth rates are highly predictable. Further, we argue that present-value models should not ignore the bubble component of stock prices. Indeed, we find that bubble variation accounts for most of the variation in the price-dividend ratio in the US, UK, Malaysia and Japan, and more than 35% of the price-dividend variation in Brazil. Moreover, bubble variation explains also a large share of unexpected return variation.
Relative performance of Mean-Variance, Kelly and Universal Portfolios in the Equity Market
with Giulio bottazzi
Abstract. We employ monthly and daily returns of US stocks to evaluate the out-of-sample performance of investment rules stemming from the mean-variance, Kelly and universal portfolio literature. We find that none of the strategies considered is significantly better or worse than all the others. Moreover, we show that the theoretical goal of the different strategies, be it either the maximization of the risk-adjusted portfolio return or the final wealth, is not related to their out-of-sample performance relative to the different measures adopted. Conversely, agents should take into account the properties (return, risk and correlation) of the set of stocks selected for investment when they are choosing the portfolio model to follow. Specifically, on the one hand if stocks are highly heterogeneous in terms of return and they have a low risk profile, the Kelly investor will get richer. On the other hand, if stocks have similar returns the minimum-variance and the universal portfolio will increase performance. However, relative performance of the latter remains poor. Finally, although the performance of the mean-variance rule is not significantly influenced by portfolio characteristics, it performs no worse than the other strategies when stocks have heterogeneous returns.
Exploring style herding by mutual funds
with Remco C.J. Zwinkels
Abstract. This paper analyses style herding in the value-growth and size dimensions of U.S. domestic equity mutual funds. We document that mutual fund herding in styles is significant and persistent. Furthermore, the results show that mutual fund herding tends to increase after periods of high cumulative returns and market volatility. A higher sentiment is followed by an increase in mutual fund herding towards small stocks. Instead, mutual fund herding in value stocks significantly decreases after an improvement in economic conditions. Mutual fund herding in styles causes overpricing in the market portfolio, and SMB and HML factors; this effect is stronger when the average fund flows are higher. We also observe that mutual fund herding in styles in some cases affects the autocorrelation structure of factor returns. Finally,
we find that mutual fund herding in styles impacts the average fund flows while it has no effect on the performance of the industry.
Available at SSRN: https://ssrn.com/abstract=2986059
Research Quotient, Optimal R&D and Stock Returns
Abstract. We document that the interaction of the firm’s ability to innovate and R&D expenditure can predict future operating performance; moreover the magnitude of these effects are significantly and substantially higher for firms with an R&D spending above the optimum. We also show that a long-short portfolio strategy which exploits information on the firm’s innovative ability and R&D level is profitable only for overspender firms (RD > RD*), in particular it earns excess returns of 14% annually. However, a risk-averse investor may still prefer to apply the strategy on the entire sample of firms in order to reduce risk. The results are robust to the confounding effects of other documented return predictors. Finally, overspending firms experience a higher level of volatility of stock returns which may explain why the market tends to misvalue innovation of this group of firms.
Available at SSRN: https://ssrn.com/abstract=3170754
Exploring the link between innovation and growth in Chilean firms
with Pietro Santoleri
Small Business Economics (2017), 49(2) https://doi.org/10.1007/s11187-016-9836-4
Abstract. We investigate the relation between the introduction of innovation and subsequent firm growth employing a dataset representative of the Chilean productive structure. By means of quantile treatment effects (QTE), we estimate the effect of the introduction of innovation by comparing firms with a similar propensity to innovate for different quantiles of the firm growth distribution. Our results indicate that process innovation positively affects sales growth for those firms located at the 75th and 90th percentiles. Contrarily, product innovation appears not to be a driver of firm performance. We also find that process innovation benefits mature firms at higher quantiles while it positively affects young firms located at low-medium quantiles.