Stock market correlation and investor attention

This thesis deals with three separate problems in �nance related to covariance. First, I assess the forecasting performance of popular multivariate GARCH, hybrid implied and realised covariance models in terms of statistical and economic criteria. I perform a rigorous analysis across major equity indices using di�erent forecasting horizons, market regimes, loss functions and tests. A Vector Heterogeneous Autoregressive speci�cation is the best among competing models. Less complex models that rely on high-frequency data yield superior forecasts and reduce the portfolio risk. Hybrid estimators that combine optionimplied and high-frequency information also have merit when option-implied volatilities are corrected for the volatility risk-premium. During �nancial turmoil the ranking does not change signi�cantly but forecast accuracy deteriorates. Second, I investigate comovement in investor attention as a determinant of excess stock market comovement proposing a novel proxy, \co-attention". Co-attention is estimated as the correlation in demand for market-wide information across stock markets approximated by the Google Search Volume Index (SVI). My results reveal signi�cant co-attention driven to some extent by correlated news and fundamentals. Most importantly, I �nd that coattention is positively related to excess comovement. This e�ect is more pronounced in developed economies and during recessions. I fail to document signi�cant e�ects of correlated news supply on stock markets, lending support to the idea that information demand governs investing decisions. Co-attention is not only induced through international investors, but domestic investors as well. My results provide evidence of attention-induced �nancial contagion in unrelated economies. However, international investors' co-attention appears to facilitate volatility transmission indirectly across markets. Third, I solve the optimal budget allocation problem across keywords for paid search adiv v vertising accounting for the risk induced by maintaining a portfolio of volatile and correlated keywords. In a mean-variance context, I maximise the growth rates in keyword popularities. Advertising costs and conversion rates are shown to be irrelevant. I demonstrate practical implementation using readily available data from Google Trends database estimating averages, variances and co-variances as growth rates in SVIs. Based on keyword sets for major sectors, I form e�cient frontiers consisting of optimal combinations of keywords. Optimal keyword portfolios o�er statistically higher risk-adjusted performance against portfolios constructed using popular heuristics. A proposed heuristic based on risk-adjusted performance reduces the computational cost and provides competing results

Keyword portfolio optimization in paid search advertising

This paper uses investment portfolio theory to determine budget allocation in paid online search advertising. The approach focuses on risk-adjusted performance and favors diversified portfolios of unrelated or negatively correlated keywords. An empirical investigation employs averages, variances and co-variances for keyword popularities, which are estimated using growth rates for 15 major sectors taken from the Google Trends database. In line with portfolio theory, the results show that the average keyword popularity growth is strongly related to the standard deviation of growth for each keyword in the sample (R2 = 74%). Hypothesis testing of differences in Sharpe ratios documents a significantly better performance of the proposed approach compared to that of other strategies currently used by practitioners

The economic value of Bitcoin: A portfolio analysis of currencies, gold, oil and stocks

We assess the out-of-sample performance of Bitcoin within portfolios of various asset classes and a well-diversified portfolio under four strategies and estimate the economic gains net of transaction costs. We find statistically significant diversification benefits from the inclusion of Bitcoin which are more pronounced for commodities. Most importantly, the decrease in the overall portfolio risk due to the low correlation of Bitcoin with other assets is not offset by its high volatility. However, the inclusion of Bitcoin pays off little if investors accommodate a battery of economic instruments. Considering non-bubble conditions that are not marked by explosive prices in cryptocurrencies, we document substantially diminished benefits

Flying to Quality: Cultural Influences on Online Reviews

Customers increasingly consult opinions expressed online before making their final decisions. However, inherent factors such as culture may moderate the criteria and the weights individuals use to form their expectations and evaluations. Therefore, not all opinions expressed online match customers’ personal preferences, neither can firms use this information to deduce general conclusions. Our study explores this issue in the context of airline services using Hofstede’s framework as a theoretical anchor. We gauge the effect of each dimension as well as that of cultural distance between the passenger and the airline on the overall satisfaction with the flight as well as specific service factors. Using topic modeling, we also capture the effect of culture on review text and identify factors that are not captured by conventional rating scales. Our results provide significant insights for airline managers about service factors that affect more passengers from specific cultures leading to higher satisfaction/dissatisfaction