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We investigate the impact of the creation of a new incentive structure for CEOs resulting from firms introducing equity-based compensation (EBC) as a means of paying top executives on policy decisions. Contrasting a firm’s stock and operating performance in the period the CEO is compensated with EBC (EBC period) and the period when EBC is not a component of the same executive’s pay (No EBC period) leads us to conclude that awarding stock options and restricted shares to executives is not associated with improved firm performance. However, firms initiate EBC after superior performance suggesting that CEOs are awarded compensation in this form as a reward for past performance. Firms have higher unsystematic and total risk levels in the EBC period suggesting EBC influences CEOs’ risk-taking behavior and reduces agency costs arising from managerial risk aversion. While there is no change in R&D expenses and cash ratios there is a decrease in capital expenditures in the EBC period, which is consistent with reduced overinvestment agency costs. Finally, leverage and payout ratios are similar in both periods implying that firms’ financing policy is not influenced by changes in CEOs’ compensation structure.

Today, firm performance must be measured not only on traditional metrics but also on those that reflect the changing imperatives and new metric knowledge. Thus, the focus of managers, investors, and researchers is shifting from rubrics like sales and profitability to growth as a more appropriate measure of firm performance. We aim to highlight the effects that growth of a firm can have on the level of its systematic risk. Using a sample of 203 firms across nine industries taken from the Indian manufacturing sector for a period of 17 years (1998–2014), we develop and test a panel vector autoregressive (VAR) model to analyze the causal relationship between growth aspects and systematic risk of firms. Results depict that a growth option available to firms increase their level of systematic risk and the risk decreases when firms start chasing this growth by increasing their assets in place. Sustainable growth rate, which depicts the growth potential of firms, plays an important role in reducing the level of systematic risk. The findings of this chapter are relevant to managers who think that growth is always beneficial.

Portfolio selection has been extensively studied in field of business and economics. Many methods have been developed to construct a well-diversified portfolio that is expected to result in higher investment return with minimum risk. One of the most foundational works contributing to modern portfolio selection is the Markowitz mean variance optimization approach. The Markowitz approach heavily relies on past stock price performance, both in term of correlation structure and the return, to predict the future outcome. We constructed both Markowitz portfolio and the Fundamental Indexing portfolio independently, then using Buffet ratio to weight, combined both portfolio into a newly blended portfolio, test out-of-sample the new portfolio in term of return and then compare it to the Indonesian LQ45 benchmark index. The result shows that the new combined portfolio returns annually on average 43.89% higher than the benchmark index.

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.

We identify a novel concept of discretionary idiosyncratic volatility proxied by the idiosyncratic volatility component not related to the non-systematic industry volatility as a source of agency problems that have implications for firms’ cash holdings and their investment decisions. We find that firms with low discretionary idiosyncratic volatility, which likely captures discretionary effort and risk-taking by managers, have smaller cash reserves. Moreover, while high discretionary idiosyncratic volatility firms spend cash internally (internal capital building), low discretionary idiosyncratic volatility firms use it for external acquisitions, consistent with the “quiet life” hypothesis. Our findings thus indicate a need for reinforcement of existing regulations and corporate laws to control for agency costs, which could in turn reduce firm risk and the probability of financial meltdown at the aggregate level.

This chapter addresses the general process of determining the value of a particular company, with additional detail on how valuation processes might be adapted to produce credible value conclusions of emerging technology ventures. There are three primary approaches to business valuation. There is the income approach, which indicates that value is a product of expected future cash flows – cash flows that are discounted to equate them to dollars in-hand (present value). There is the market approach, which attempts to draw conclusions of value based on the market prices of similar companies in the public and/or private markets. Finally, there is the asset approach, which indicates that the value of a company is equal to the sum of the values of its net assets. Specific adjustments are appropriate with respect to each of these approaches where the value of an emerging technology company is concerned. Professional valuation standards require that all of these approaches be considered in the valuation, even if the available information does not permit their credible application. Often, multiple approaches and techniques can be applied. The results of applying multiple techniques often do not overlap, and it is the analyst’s very important task to reconcile differing valuation results, or to decide which result or results should be discarded.