Corporate managers,price noise and the investment factor

This study investigates the impact of flows between bond and equity funds on investment factors over the period 1984–2015.It determines contemporaneous mispricing effects and a statistical reversal relation between these flows and both legs of the investment factor.The statistical reversal relationship between previous flows and the investment factor is economically significant.A one-standard-deviation shock to flows causes a 0.29%decrease in investment factor returns,which are reversed within 5 months.A trading strategy based on signals from past flows and the investment factor outperforms the market by 0.68%in the months following positive flows and produces significant alphas after accounting for well-known equity risk factors.The findings are interpreted as evidence in favor of a behavioral explanation,in which sentiment influences actual managerial decisions.When retail investors and managers are swept up in market euphoria,retail investors shift their holdings from bond to equity mutual funds,and high-investment firms invest more aggressively.Market-level euphoria has a different impact on high-and low-investment firms,and thus the investment factor can be influenced.Hence,the mispricing occurs during these periods,and the reversal relationship is especially pronounced for a high-investment portfolio versus a low-investment portfolio.As a result,during the months following periods of positive flows,the investment factor outperforms the market factor.Interestingly,this study’s measure of flows,which serves as a proxy for market-level euphoria,outperforms other measures of investor sentiment.

Whether profitability and investment factors have additional explanatory power compared with Fama-French three-factor model:Empirical evidence on Chinese A-share stock market

Fama and French propose a five-factor model containing the market factor and factors related to size,book-to-market equity ratio,profitability and investment,which outperforms the Fama-French three-factor model in their paper 2014.This study investigates the performance of Fama-French five-factor model and compare with that of Fama-French three-factor model on Chinese A-share stock market.The empirical results show that Fama-French five-factor model explanatory power has differences among different sets of portfolios.Compared with Fama-French three-factor model,the presence of profitability and investment factors donot seem to capture more variations of expected stock returns than the three-factor model except for six value-weighted portfolios formed on size and operating profitability.

Robotics from the Investor＇s Point of View： How to Profit from the Rise of Robots

This research paper evaluates whether Robotics equities traded on Stock Markets worldwide are a good investment opportunity or not. Robotics seems to become more and more attractive for both institutional investors （who act rationally and prefer medium to long term investments） and individual investors （who are driven by irrational behaviour and prefer short term investments）. In order to forecast if robotics is an investment opportunity that could inflate a new financial bubble in the oncoming years, this research paper compares robotics equities with Internet equities and analyses what happened during the Dot-com Mania in the 1990s. A number of similarities come out as well as several key enabling factors that confirm robotics is a major investment opportunity for the next decade.

ST-metric Estimation of Factor Exposures

Non-parametric methods are treasured in data analysis,particularly in finance.ST-metric is a new concept,introduced by Tulunay(2017).It offers non-parametric methods and a new geometric view to data analysis.In that paper,ST-metric concept has been applied to performance measures of portfolios.In this current paper,we purpose another ST-metric method for finding factor exposures in the five-style-factors model.Here the style factors are value,size,minimum volatility,quality and momentum.The main idea is to find the factor exposures(weights)of the five-factors-model by minimizing the ST-metric between benchmark returns and the constructed factor model returns.We compare ST-metric method with Tracking Error method(TE-method)which is used for factor analysis of major indexes,decomposed into the style factors(tradable via Exchange Traded Funds(ETFs))by Ang et al.(2018).We show that ST-metric method gives better estimation of the factor exposures(weights)than tracking error method,in general,and further how ST-metric values vary with respect to fluctuations.This explains the reason behind the efficiency of the ST-metric method.We support this idea with empirical evidences.

Liberalize or Not？ Societal Conflict, Plural Political Competition, and the Political Economy of FDI Liberalization

While the existing literature suggests political liberalization enhances the freedom of foreign direct investment （FDI）, the observation that some countries with more liberal political regimes have more restrictive policies toward direct investment than others remains unexplained. With a theoretical model of plural political competition and empirical evidences gathered from panel data, I argue that the liberalizing effect of political liberty on foreign direct investment hinges on the local factor endowment of the country experiencing democratization. I develop a theory of investment policy formation that takes into account the strategic response from domestic societal actors to redistribution of political power and its impact on FDI liberalization. Consistent with the theoretical prediction, the empirical results show political liberalization is more likely to lead to liberalization of foreign direct investment when the capital-labor ratio in the economy is relatively low.