Corporate Multinationality and Acquirer Returns

This paper provides evidence on how corporate multinationality from the perspective of acquiring firms relates to M&A returns. Using multivariate regressions and a large dataset of over 6,000 M&As (both cross-border and domestic) by UK firms during 1987 to 2014, the paper finds multinationality to be associated with significantly higher short-run announcement returns and long-run operating performance. While the multinationality premium (higher M&A returns for multinationals) persists over time, it seems to be restricted to firms with superior resource/managerial capabilities and minimal agency problems. Finally, the multinationality premium appears to be driven by foreign acquisitions into advanced economies. The results are robust to correcting for sample selection bias and controlling for several firm and deal characteristics, as well as accounting for firm-, industry-, and year-fixed effects. Collectively, the findings imply that multinationality could be a source of value creation for acquiring firms, particularly in foreign acquisitions, which tend to be complex, and, thereby, require superior managerial capabilities to succeed.     

FX Intervention in the New Keynesian Model

We develop an open-economy New Keynesian Model with foreign exchange (FX) intervention in the presence of a financial accelerator and shocks to risk appetite in international capital markets. We obtain closed-form solutions for optimal monetary and FX intervention policies assuming the central bank cannot commit to future policies, and we compare the solution to that under policy commitment. We show how FX intervention can help reduce the volatility of the exchange rate, of inflation, and of the output gap, thus mitigating welfare losses associated with shocks in the international capital markets. We also show that, when the financial accelerator is strong, there is a risk of indeterminacy (self-fulfilling currency and inflation movements) although FX intervention can reduce this risk and thus reinforce the credibility of the inflation targeting regime. Model simulations match well the impact of a VIX shock obtained by local projections on a panel of inflation targeting emerging markets.     

Share price anticipation of earnings and management's discussion of operations and financing

This paper combines research on the measurement of disclosure quality and the measurement of share price anticipation of earnings to produce a new test of the usefulness of the information disclosed in management discussions of operations and financing for predicting future earnings. Market-Based Accounting Research has shown that earnings changes are anticipated and impounded in prices well before the financial year for which earnings are reported. This price anticipation leads to downward biased earnings response coefficients (ERCs) in the commonly estimated regression model of returns on contemporaneous earnings changes. We exploit predictable differences in the biasedness of the ERC estimate across firm-years to test the hypothesis that share prices are better informed when the annual report contains a detailed discussion of the firm's operations and financing. Our results suggest that such voluntary disclosure may have been useful in predicting future earnings changes. The effect would appear to be strongest (1) in models that examine one-period-ahead and two-period-ahead share price anticipation and (2) when we employ a disclosure index that captures forward-looking information.     

A behavioral analysis of investor diversification

This paper studies the link between individual investors’ portfolio diversification levels and various personal traits that proxy informational advantages and overconfidence. The analysis is based on objective data from the largest Turkish brokerage house tracking 59,951 individual investors’ accounts with a total of 3,248,654 million transactions over the period 2008–2010. Wealthier, highly educated, older investors working in the finance sector and those trading relatively often show higher diversification levels possibly because they are better equipped to obtain and process information. Finance professionals, married investors, and those placing high-volume orders through investment centers show poorer diversification possibly as a reflection of overconfidence. Our analysis reveals important nonlinear effects, implying that the marginal impact of overconfidence on diversification is not uniform across investors but varies according to the investor's information gathering and processing abilities.     

Home-field advantage or a matter of ambiguity aversion? Local bias among German individual investors

This paper investigates whether familiarity induced by ambiguity aversion can help explaining the local bias phenomenon among individual investors. Using geographic closeness as a proxy for investor familiarity, we find that investors pull out of (unfamiliar) remote stocks and pour into (familiar) local stocks during times of increased market uncertainty. Moreover, the magnitude of this ‘flight to familiarity’ increases in the spread of an investor's ambiguity (about expected returns) between local and remote stocks. Our results prove robust to a number of alternative explanations of local bias. Specifically, we rule out a ‘home-field advantage’, where investors are able to translate information advantages about nearby companies into excess returns on their local stockholdings. We conclude that individual investors’ local bias is induced by ambiguity aversion in the portfolio selection process rather than a trading strategy based on superior information about local companies.     

Exploring Portfolio Diversification Opportunities Through Venture Capital Financing: Evidence from MGARCH-DCC,Markov Switching,and Wavelet Approaches

Islamic financial institutions are being pressurized by critics to offer profit and loss sharing (PLS) financing, such as venture capital (VC) financing, for the purpose of entrepreneurial development aligned to the principle of equity risk sharing. Our study aims to link PLS investments with portfolio optimization opportunities for the Islamic asset managers. Using portfolio analysis with dynamic conditional correlation, Markov switching, and maximal overlap discrete wavelet transformation, our findings tend to indicate that there is indeed a portfolio optimization opportunity in investment universe for the fund managers who invested in PLS investments in the context of VC asset class over the long run.     

Technological diversity,related diversification,and firm performance

Previous findings that related diversification creates value have been called into question over concerns about methodology and measures. Reviewing existing theory to consider how a firm's knowledge base interacts with its product market activity, I address several of these concerns by creating a measure of technological diversity based on citation‐weighted patents. The measure indicates a firm's opportunity for corporate diversification based on economies of scope in valuable knowledge assets, is defined for both single‐ and multibusiness firms, and is not correlated with more fundamental aspects of diversification, such as the number of businesses in the corporate portfolio. Evidence from a large sample of firms shows the positive relationship between diversification based on technological diversity and market‐based measures of performance, controlling for R&D intensity and capital intensity as further indicators of the type of assets underlying diversification. Results hold when controlling for the endogeneity of diversification and performance in a cross‐sectional sample or when controlling for unobserved factors using panel data. Copyright © 2006 John Wiley & Sons, Ltd.     

Do analysts add value when they most can? Evidence from corporate spin‐offs

This article investigates how securities analysts help investors understand the value of diversification. By studying the research that analysts produce about companies that have announced corporate spin‐offs, we gain unique insights into how analysts portray diversified firms to the investment community. We find that while analysts' research about these companies is associated with improved forecast accuracy, the value of their research about the spun‐off subsidiaries is more limited. For both diversified firms and their spun‐off subsidiaries, analysts' research is more valuable when information asymmetry between the management of these entities and investors is higher. These findings contribute to the corporate strategy literature by shedding light on the roots of the diversification discount and by showing how analysts' research enables investors to overcome asymmetric information. Copyright © 2013 John Wiley & Sons, Ltd.     

The pricing of volatility risk in the US equity market

We analyze whether the pricing of volatility risk depends on the asset pricing framework applied in the tests, the specified volatility proxies, and the portfolio sorts used for spanning the asset universe. For this purpose, we compare the results using a macroeconomic and fundamental based asset pricing model using three proxies of volatility and uncertainty, using size/value sorted and industry sector portfolios. Our results reveal that the marginal pricing effect of the VIX volatility factor is strong and statistically significant throughout the models and specifications, while the effect of an EGARCH-based volatility factor is mixed, mostly smaller but with the correct sign. In most cases, the EGARCH factor does not impair the pricing effect of the VIX. The portfolio sorts have a substantial impact on the volatility premiums in both model frameworks. The size of the volatility risk premium is more uniform across the models if the industry sector portfolio sort is used. Finally, the size/value portfolio sort generates larger volatility risk premiums for both models.     

Linear programing models for portfolio optimization using a benchmark

We consider the problem of constructing a perturbed portfolio by utilizing a benchmark portfolio. We propose two computationally efficient portfolio optimization models, the mean-absolute deviation risk and the Dantzig-type, which can be solved using linear programing. These portfolio models push the existing benchmark toward the efficient frontier through sparse and stable asset selection. We implement these models on two benchmarks, a market index and the equally-weighted portfolio. We carry out an extensive out-of-sample analysis with 11 empirical datasets and simulated data. The proposed portfolios outperform the benchmark portfolio in various performance measures, including the mean return and Sharpe ratio.