Knowledge that Transforms

We show that the introduction of a leverage constraint improves the practical implementation of characteristics-based portfolios. The addition of the constraint leads to significantly lower transaction costs, to a reduction of negative portfolio weights, and to a decrease in volatility and misspecification risk. Furthermore, it allows investors to implement any desired level of leverage. In this study, we include 12 characteristics, thereby extending the classical size, book-to-market and momentum paradigm. We report several key indicators such as the proportion of negative weights, Sharpe ratio, volatility, transaction costs, the transaction cost-adjusted certainty equivalent returns, and the Herfindahl–Hirschman index. Analyzing the sensitivity of these key indicators to the choice of multiple combinations of the 12 characteristics, to risk aversion, and to estimation sample size, we show that constrained policies are much less sensitive to these parameters than their unconstrained counterparts. Finally, for quadratic utility, we derive a semi-closed analytical form for the portfolio weights. Overall, we provide a comprehensive extension of characteristics-based portfolio choice and contribute to a better understanding and implementation of the allocation process.

This paper studies the role that risk and mispricing play in the negative relation between extreme positive returns and future returns. We document a strong ‘MAX effect’ in Australian equities over 1991–2013 that is robust to risk adjustment, controlling for other influential stock characteristics and, importantly, manifests in a partition of the 500 largest stocks. While there is no evidence that MAX proxies for sensitivity to risk, the findings are highly consistent with a mispricing explanation. Adapting the recent methodological innovation of Stambaugh et al. (2015) to classify stocks by their degree of mispricing, we show that the MAX effect concentrates amongst the most-overpriced stocks but actually reverses amongst the most-underpriced stocks. Consistent with arbitrage asymmetry, the magnitude of the MAX effect amongst overpriced stocks exceeds that amongst underpriced stocks, leading to the overall negative relation that has been well documented.

Defining systematic risk management (SRM) skill as persistently low fund systematic risk, we find evidence of time varying allocation of hedge fund management effort across the business cycle. In weak market states, skilled managers focus on minimization of systematic risk via dynamic reallocations across asset classes at the cost of fund alpha and foregoing market timing opportunities. As markets strengthen, attention shifts to asset selection within consistent asset classes. The superior performance of low systematic risk funds previously documented arises due to the superior asset selection ability of managers in strong market states. Incremental allocations by investors arise due to this superior performance and not due to recognition of SRM skill.

Using a gravity model, we analyze the determinants of the probability that commercial banks in 89 acquiring countries and 118 target countries will undertake M&As over a 30-year period (1981–2010) and of the value of these M&As. We find that the value of cross-border M&As increases with the size of the acquiring country, and that both the probability and value of M&As vary positively with the depth of the financial market in acquirer countries and the presence of corporate and non-corporate customers from acquiring countries in target countries, and negatively with the geographic, psychic, and time zone distances between acquirer and target countries. Our study highlights the role of non-corporate customers and of psychic distance in the cross-border expansion of commercial banks through M&As.

This paper examines the relation between chief executive officer (CEO) inside debt holdings and corporate debt maturity. We provide robust evidence that inside debt has a positive effect on short-maturity debt and that this effect is concentrated in financially unconstrained firms that face lower refinancing risk. Our analysis further shows that CEO inside debt helps reduce the cost of debt financing. Overall, our results indicate that managerial holdings of inside debt facilitate access to external debt financing and reduce refinancing risk, thus incentivizing managers to use less costly shorter term debt.

This paper introduces variants of strangles, called Euro-American or hybrid strangles, and it promotes a new numerical pricing technique. We highlight and compare the properties of European, American, and hybrid strangles with pricing and hedging in mind. The new quadrature approach we propose can account for systems of coupled integral equations that locate the early exercise boundaries of finite-lived contracts. We show that this method is efficient, accurate, and fast for pricing all types of early exercisable strangles. Other advantages of this technique are that it avoids the non-monotonic gradient problem faced by others and it allows users to control for errors. We then investigate the hedging of all strangles, we derive analytical expressions for some Greek parameters, and we stress how these parameters can differ (or not) from each other.

Technical traders attempt to exploit trends in market prices and the order flow. Despite this little is known about how these traders behave in a micro-structure context. We consider a model of an order book based financial market. The market contains two groups: informed traders and technical traders. A numerical technique is used to identify a Markov perfect equilibrium of the trading game and so determine the optimal strategies. We find that technical trading rules are profitable and allow traders to increase their returns. The effect of technical traders on the market, however, is ambiguous. They decrease volatility and pricing errors but also increase trading costs despite primarily acting as liquidity suppliers.

This paper presents the first theoretical model of the profit maximizing price-setting policy for the issuers of exchange-traded retail certificates. Unlike previous theoretical microstructure models, the market considered is unique in that the market makers do not face significant inventory costs or risk from informed traders. The model derives the time structure of the optimal markups over a certificate’s fair theoretical value and its relationship with optimal spreads, unhedgeable risk faced by the issuer and investors’ buying and selling decisions. It shows that (i) the optimal markups decrease inter-temporally, (ii) issuers adjust the markups according to investors’ demand, (iii) unhedgeable risk results in higher markups and influences their time structure, (iv) the markups and the spread are negatively related. Using data from the German market for leverage certificates, we find strong empirical support for the model-derived hypotheses, except for (iv). We find spreads exhibit little variation and this suggests that markups and spreads are not substitute profit sources for issuers in this market.

The Japanese banking system provides a distinctive platform for the examination of the long-lasting effect of problem loans on efficiency. We measure technical efficiency by modifying a translog enhanced hyperbolic distance function with two undesirable outputs, identified as problem loans and problem other earning assets. Our unique database allows us to distinguish between bankrupt and restructured loans to investigate the underlying causality between these loans and efficiency. From the flexible panel vector autoregression specification, primary results reveal that bankrupt loans have a positive impact on efficiency related to the “moral hazard, skimping” hypothesis, with the causality originating from bankrupt loans. In contrast, findings for the relationship between restructured loans and efficiency support the “bad luck” hypothesis.

Using a text-based measure of geographic dispersion that captures the economic ties between a firm and its geographically distributed economic interests, this study provides evidence that financial analysts issue less accurate, more dispersed and more biased earnings forecasts for geographically dispersed firms. We observe the degree to which a firm has an overlapping distribution of economic centers in comparison to industry competitors and suggest that geographically similar firms have lower information gathering costs and thereby more precise earnings forecasts. Empirical evidence supports this prediction. We further find that the geographic dispersion across the U.S. is less likely to affect forecast precision when a firm has economic activities in states with highly correlated local shocks. Our findings suggest that the effect of geographic dispersion is more pronounced for soft-information environments where information is more difficult to make impersonal by using technological advances. Consistent with the information asymmetry argument, we find that geographically dispersed firms have less comparable and more discretionary managed earnings, have less extensive than industry competitors segment information, are more likely to restate sale segment information, and issue annual and quarterly filings with a delay.