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Building upon the framework of the tradeoff model of capital structure and motivated by the equity market timing theory, we examine whether equity misvaluation is a source of adjustment “costs” that will affect a firm’s leverage adjustment speed toward target. We also investigate whether the quality of a firm’s long-term growth options will influence the decisions of managers to exploit the mispriced equity to converge to the optimum. Using a sample of listed Taiwanese firms during 1992–2014 and employing the market-to-book decomposition as developed by Rhodes-Kropf, Robinson, and Viswanathan (2005), we find that overleveraged and overvalued firms demonstrate faster adjustment speed than overleveraged but undervalued firms. Furthermore, controlling for the misvaluation status, high-growth firms converge to target faster than their low-growth counterparts. The effect of growth options on the relation between equity mispricing and adjustment speed does not mirror the effect of financing deficits. With the detailed financial information of the local companies across a rather long time series, this study provides incremental inputs to the literature of capital structure from the determinants of target leverage, the estimation of leverage adjustment speeds, to the identification of the sources of adjustment costs in an emerging market where institutional environment is strikingly different from the US.

The most popular method for calculating asset prices is the Capital Asset Pricing Model (CAPM). What is the appropriate amount of years to use in the estimation and which variation of the capital asset pricing beta provides the best results? This research looks at the out-of-sample forecasting capabilities of three popular CAPM ex-post constant beta models from 2005 to 2014. A total of 11 portfolios, five from developed and six from developing markets, are used to test the amount of input years that will reduce the mispricing in both types of markets. It is found that the best beta model to use varies between developed and developing markets. Additionally, in developing markets, a shortened span of historical years improves the pricing, contrary to popular studies that use 5 to 10 years of historical data. There are many different CAPM studies implementing various betas, using different data input lengths and run in various countries. This study empirically tests the best practices for those interested in successfully using the CAPM for their basic needs, finding that overall the simple ex-post constant beta is mispriced by 0.2 (developing) to 0.3 percent (developed). It is better to use short three-year estimation windows with the market beta in developing economies and longer nine-year estimation windows with the adjusted beta in developed economies.

The change in CEO pay after their firms make large corporate investments is examined. Whether the change in CEO pay is a beneficial practice or harmful practice to firms is investigated.

A sample of firms that make large corporate investments is identified. For this sample, we identify the change in CEO pay before and after the investment, and we also measure the pay-for-size sensitivity of these investing firms.

For firms that make large corporate investments, CEOs get significantly more option grants when their firms’ stock returns are negative after the investments and these investing CEOs get more option grants than noninvesting CEOs.

The present study suggests that firms may have to increase CEO pay after large corporate investments to encourage investment. However, the results may also be consistent with an agency cost explanation. Future research should try to distinguish between the two explanations.

The study reveals a potential way to prevent CEOs from underinvesting.

The study provides important insights to shareholders on how to encourage CEOs to get their firms to invest, and on how to view CEO pay increases after their firms invest.

We examine the impact of the unique Japanese stock market microstructure on the pricing of stock index futures contracts. We use intraday transactions data for the Nikkei 225 Futures contracts in Osaka and the corresponding Nikkei 225 Index in Tokyo. Incorporating more realistic transaction-cost estimates and various institutional impediments in Japan, we find that the time-varying liquidity of some component shares of the index in Tokyo represents the most critical impediment to intraday arbitrage and often causes futures prices in Osaka to deviate significantly and persistently from their no-arbitrage boundary, especially for longer-lived contracts.

Behavioral strategy completes the analyses of superior profitability by highlighting how non-economic, behavioral barriers generate an alternative source of strategic opportunities. Existing internal and external analysis frameworks fail to explain why strategic factors can be systematically mispriced and why large firms’ structural and resource advantage are regularly disrupted by entrepreneurs. We argue that the systematic biases documented in the behavioral and organizational sciences in fact illuminate an alternative source of competitive advantage. Strategists could develop superior insights into the value of resources and recognize factors that are either under- or overvalued while competitors remain blind to such possibilities. Our argument is illustrated by how three “underdogs” disrupted the incumbents in their industries by exploiting rivals’ predictable biases and blind spots. We conclude by discussing how our ideas can be generalized as an alternative, behavioral approach for strategy.

Following the Supreme Court’s 1988 decision in Basic, securities class plaintiffs can invoke the “rebuttable presumption of reliance on public, material misrepresentations regarding securities traded in an efficient market” [the “fraud-on-the-market” doctrine] to prove classwide reliance. Although this requires plaintiffs to prove that the security traded in an informationally efficient market throughout the class period, Basic did not identify what constituted adequate proof of efficiency for reliance purposes.

Market efficiency cannot be presumed without proof because even large publicly traded stocks do not always trade in efficient markets, as documented in the economic literature that has grown significantly since Basic. For instance, during the recent global financial crisis, lack of liquidity limited arbitrage (the mechanism that renders markets efficient) and led to significant price distortions in many asset markets. Yet, lower courts following Basic have frequently granted class certification based on a mechanical review of some factors that are considered intuitive “proxies” of market efficiency (albeit incorrectly, according to recent studies and our own analysis). Such factors have little probative value and their review does not constitute the rigorous analysis demanded by the Supreme Court.

Instead, to invoke fraud-on-the-market, plaintiffs must first establish that the security traded in a weak-form efficient market (absent which a security cannot, as a logical matter, trade in a “semi-strong form” efficient market, the standard required for reliance purposes) using well-accepted tests. Only then do event study results, which are commonly used to demonstrate “cause and effect” (i.e., prove that the security’s price reacted quickly to news – a hallmark of a semi-strong form efficient market), have any merit. Even then, to claim classwide reliance, plaintiffs must prove such cause-and-effect relationship throughout the class period, not simply on selected disclosure dates identified in the complaint as plaintiffs often do.

These issues have policy implications because, once a class is certified, defendants frequently settle to avoid the magnified costs and risks associated with a trial, and the merits of the case (including the proper application of legal presumptions) are rarely examined at a trial.

Stock selection models often use momentum and analysts’ expectation data. We find that earnings forecast revisions and direction of forecast revisions are more important than analysts’ forecasts in identifying mispriced securities. Investing with expectations data and momentum variables is consistent with maximizing the geometric mean and Sharpe ratio over the long run. Additional evidence is revealed that supports the use of multifactor models for portfolio construction and risk control. The anomalies literature can be applied in real-world portfolio construction in the U.S., international, and global equity markets during the 1998–2009 time period. Support exists for the use of tracking error at risk estimation procedures.

While perfection cannot be achieved in portfolio creation and modeling, the estimated model returns pass the Markowitz and Xu data mining corrections test and are statistically different from an average financial model that could have been used to select stocks and form portfolios. We found additional evidence to support the use of Arbitrage Pricing Theory (APT) and statistically-based and fundamentally-based multifactor models for portfolio construction and risk control. Markets are neither efficient nor grossly inefficient; statistically significant excess returns can be earned.

The ratio between share price and current earnings per share, the Price Earning (PE) ratio, is widely considered to be an effective gauge of under/overvaluation of a corporation’s stock. Arguably, a more reliable indicator, the Cyclically Adjusted Price Earning ratio or CAPE, can be obtained by replacing current earnings with a measure of permanent earnings i.e. the profits that a corporation is able to earn, on average, over the medium to long run. In this study, we aim to understand the cross-sectional aspects of the dynamics of the valuation metrics across global stock markets including both developed and emerging markets. We use a time varying DCC model to exploit the dynamics in correlations, by introducing the notion of value spread between CAPE and the respective Market Index from 2002 to 2014 for 34 countries. Value spread is statistically significant during the 2008 crisis for asset allocation. The signal can be utilized for better asset allocation as it allows one to interpret the common movements in the stock market for under/overvaluation trends. These estimates clearly indicate periods of misvaluation in our sample. Furthermore, our simulations suggest that the model can provide early warning signs for asset mispricing in real time on a global scale and formation of asset bubbles.