Does decentralized decision making increase company performance through its Information Technology infrastructure investment?

A company's Information Technology (IT) infrastructure is a key factor in its sustainability and ongoing success and profitability. This paper explores the relationship between a company's investment in IT and its performance. Performance is measured, with the help of a Balanced Scorecard (BSC), in four ways; financial, internal business processes, innovation & learning and customer perspective. The relationship between each BSC category serves as indicators of the effect of IT investment on a company's performance. This will help establish the benefits of both financial and non-financial indicators. We focus on the Electrical and Electronic manufacturing performance of companies Malaysia. System Resource Theory (SRT) is used as the background theory to explain the concepts of organizational effectiveness, efficiency, productivity and multidimensional performance measurements and to link the variables used in this study. We conduct an empirical study in order to confirm the moderating effects of decentralized decision making. The results suggest that IT investment produces a significant relationship with all BSC perspectives, but the moderating effect is only significant only from a customer perspective.     

Does the stock market reward innovation? European stock index reaction to negative news during the global financial crisis

This study uses data on 27 European stock indices over the period from January 2007 to December 2012 to investigate the relationship between innovations and the market reaction to negative news during the financial crisis. We use the bivariate BEKK-GARCH approach to estimate time-varying betas and abnormal returns. We show that index prices of countries in the high (low) innovation groups experience significantly positive (negative) abnormal returns on and following the negative news announcement dates. We also find that index beta changes following the arrival of bad news is negatively associated with a country's innovativeness. This finding suggests that innovations promote economic stability and enhance investors' confidence in a country's ability to cope during difficult times. Thus, policy makers who are concerned with sustainable growth should encourage R&D investments by adopting effective policies and avoid unnecessary cuts in R&D expenditures even during times of crisis. A study of the pre-crisis period from January 2001 to December 2006, using the same methods, indicates that investors value innovation more during difficult times.     

The Net Benefits to Leverage

I estimate the market's valuation of the net benefits to leverage using panel data from 1994 to 2004, identified from market values and betas of a company's debt and equity. The median firm captures net benefits of up to 5.5% of firm value. Small and profitable firms have high optimal leverage ratios, as predicted by theory, but in contrast to existing empirical evidence. Companies are on average slightly underlevered relative to the optimal leverage ratio at refinancing. This result is mainly due to zero leverage firms. I also look at implications for financial policy.     

Assessing Project Risk

Finding the appropriate discount rate, or cost of capital, for evaluating investment projects requires an accurate estimate of project risk. This can be challenging because project risk cannot be estimated directly using the CAPM, but must instead be inferred from a set of traded securities, typically the equity betas of comparable firms in the same industry. These equity betas are then unlevered to undo the effect of comparable companies' financial leverage and obtain estimates of “asset” betas, which are then used to estimate project risk. The authors show that asset betas estimated in this way are likely to overestimate project risk. The equity returns of companies are risky not only because of their existing projects but also because of their growth opportunities. Such growth opportunities often include embedded “real options,” such as the option to delay, expand, or abandon a project. Because such real options are similar to leveraged positions in the underlying project, a company's growth opportunities are typically riskier than its existing projects. Therefore, to properly assess project risk, analysts must also unlever the asset betas derived from comparable company stock returns for the leverage contributed by their growth options. The authors derive a simple method for unlevering asset betas for growth options leverage in order to properly assess project risk. They then show that standard methods for assessing project risk significantly overestimate project costs of capital—by as much as 2–3% in industries such as healthcare, pharmaceuticals, communications, medical equipment, and entertainment. Their method should also be applied to stock return volatility to derive project volatility, an important input for determining the value of a firm's growth opportunities and the appropriate time for investing in these opportunities.     

Can unpredictable risk exposure be priced?

We study the link between beta predictability and the price of risk. An investor who desires exposure to a certain risk factor needs to predict what next period’s beta will be. We use a simple model to show that an ambiguity averse agent’s demand is lower when betas are hard to predict, leading to a reduction in risk premiums. We test the implications for downside betas and VIX betas. We find that they have economically and statistically small prices of risk once we account for the fact that an investor cannot observe ex-post realized betas when determining asset demand.     

Time-varying beta and the Asian financial crisis: Evidence from Malaysian and Taiwanese firms

This paper empirically investigates the effects of the Asian financial crisis of 1997–1998 on the time-varying beta of 10 firms from each of Malaysia and Taiwan. Daily data from 1990 to 2001 and the bivariate MA-GARCH model (BEKK) are applied to create the time-varying betas for the firms. Results provide ample evidence of the influence of the financial crisis and the period after on the time-varying betas of the twenty firms. Results provided are somewhat mixed, indicating a rise in the beta in some cases and a fall in other cases. Results also show that the 10 Malaysian firms applied were more affected than the Taiwanese firms.     

Beta Asymmetry in the Global Stock Markets Following the Subprime Mortgage Crisis

I set out in this study to examine the asymmetry in beta responses using the dynamic conditional correlation threshold generalized autoregressive conditional heteroskedasticity (DCC-GJR-GARCH) model. The empirical results reveal that asymmetry is discernible in both volatility and betas in the global stock markets. Furthermore, when leverage is linked with the price-to-book ratio, the results indicate that the beta asymmetry is attributable to the leverage effect. The results of this study also reveal that the declines in the price-to-book ratio following the subprime mortgage crisis have led to an overall increase in betas.     

The Beta Dilemma in Emerging Markets

In principle, emerging markets analysts employ the same analytical framework when estimating the value of businesses as their counterparts in developed economies: they forecast future cash flows and discount those to the present with appropriate costs of capital that are estimated using the Capital Asset Pricing Model (CAPM) framework. But in practice, emerging market analysts have a more complicated job because the task of estimating costs of equity in emerging markets is more difficult. Whereas developed economies have an abundance of historical data on overall stock market movements, industry share price behavior, and many individual share price histories, emerging market economies often do not. There may be no comparable local firms that are publicly traded—or if there are, their CAPM betas may be unreliable. And if analysts instead use the beta of a U.S. competitor as a surrogate for the emerging market beta, they face the question of whether domestic betas are equivalent across borders. As a consequence, appraisers of emerging market companies confront a “beta dilemma.” Part of this is a data problem stemming from shorter share price histories in emerging markets and the absence of publicly traded companies in some industries. In such cases, analysts may be inclined to use industry betas calculated with U.S. share prices as a substitute. But this creates an equivalence problem—the possibility, as confirmed by the author's research, that domestic U.S. and emerging market betas are not statistically equivalent for most industries. The author proposes a solution to this problem that involves grouping emerging markets into a single, distinctive asset class that allows for reliable calculations of industry betas. He also suggests ways of testing emerging market industry betas to determine whether they are statistically comparable.     

Does the equity premium puzzle persist during financial crisis? The case of the French equity market

This paper examines the effects of the financial crisis that began in 2008 on the equity premium of 6 French sector indices. Since the systematic risk coefficient beta remains the most common explanatory element of risk premium in most asset pricing models, we investigate the impact of the crisis on the time-varying beta of the six sector indices cited. We selected daily data from January 2003 to December 2012 and we applied the bivariate MA-GARCH model (BEKK) to estimate time-varying betas for the sector indices. The crisis was marked by increased volatility of the sector indices and the market. This rise in volatility led to an increase in the systematic risk coefficient during the crisis and first post-crisis period for all the major indices. The results are intuitive and corroborate findings in the empirical literature. The increase of the time-varying beta is considered by investors as an additional risk. Therefore, as expected, investors tend to increase their equity premiums to b ear the impact of financial crisis.     

The Time-Series Behavior of IPO Betas

We examine individual IPO betas and provide further evidence that the documented decline in IPO betas results primarily from a seasoning or information effect and not from the delisting of high beta securities. We employ stochastic coefficient regression analysis which permits the estimation of individual IPO betas at all points in time, and therefore avoids disadvantages associated with grouped cross-sectional beta estimates and average individual time-series beta estimates. We find that IPO firms with the lowest betas are more likely to delist, and that individual IPO betas, on average, decline over time which provides support for the information hypothesis.     

Factor beta,overnight and intraday expected returns in China

We study the relationship between common factor betas and the expected overnight versus intraday stock returns. Using data from the Chinese A-share markets, we find that the Fama-French five-factor betas and expected returns exhibit contrasting relationships overnight versus intraday. The market, value, and profitability factors earn positive beta premiums overnight and negative premiums intraday, while the size and investment factors' beta premiums behave oppositely. The night and day factor beta premium differentials are more muted among stocks with higher investor sophistication and vary across macroeconomic conditions. The contrasting day and night beta premiums extend to some other common factors and Chinese B shares, and vary their signs for some factors in the U.S. market.     

The impact of geographical factors on churn prediction: an application to an insurance company in Madrid's urban area

Geography has previously been noted as a decisive factor in business literature. This paper provides evidence of the significant role geography plays in customer lapse behaviour in an urban environment. This novel approach is based on the idea that the customers who cancel all policies and leave the company are not randomly distributed; rather, a mimetic performance of close individuals is noted. The physical proximity of the customer to the geographical focus (strategical centre, as insurance offices) and the interaction with nearby customer are spatial factors that increase (or decrease) the probability of churning. An empirical analysis using more than 7000 spatially georeferenced offline customers of a Spanish insurance company in the urban area of Madrid (Spain) demonstrated that the customer's proximity to offices of such insurance company under study decreases the probability of churning, whereas high lapse risk was detected in customers in the surroundings of the company's competitor branches. In addition, we identified spatial autocorrelation in churn probability, thus demonstrating that the probability of churn of a customer increases if nearby customers churn.     

Conditional beta pricing models: A nonparametric approach

We propose a two-stage procedure to estimate conditional beta pricing models that allows for flexibility in the dynamics of asset betas and market prices of risk (MPR). First, conditional betas are estimated nonparametrically for each asset and period using the time-series of previous data. Then, time-varying MPR are estimated from the cross-section of returns and betas. We prove the consistency and asymptotic normality of the estimators. We also perform Monte Carlo simulations for the conditional version of the three-factor model of Fama and French (1993) and show that nonparametrically estimated betas outperform rolling betas under different specifications of beta dynamics. Using return data on the 25 size and book-to-market sorted portfolios, we find that the nonparametric procedure produces a better fit of the three-factor model to the data, less biased estimates of MPR and lower pricing errors than the Fama–MacBeth procedure with betas estimated under several alternative parametric specifications.     

Explaining the default risk anomaly by the two-beta model

This study attempts to explain the anomaly that firms with high-default risk earn low average realized returns. We measure default risk according to Ohlson's (1980) O-score and Campbell, Hilscher, and Szilagyi's (2008) failure probability and further implement Duffie, Saita, and Wang's (2007) doubly-stochastic intensity model to estimate default probabilities that incorporate the dynamics of the changes in covariates. We then employ Campbell and Vuolteenaho's (2004) two-beta model to estimate firms' cash-flow and discount-rate betas according to the default risk. The default risk anomaly persists when using Duffie el al.'s (2007) method. We show that cash-flow and discount-rate betas, respectively, earn a high and low premium and find that high-default firms tend to have relatively high discount-rate and low cash-flow betas. Hence, high-default firms deliver low expected returns. Importantly, 25.5% of the default risk anomaly can be explained by the two-beta model and that, on average, also accounts for 49.2% of the cross-sectional variation across the portfolios formed on default risk. This result implies that investors believe that high-default firms are unlikely to generate significantly extra cash flows when market-wide profitable opportunities improve.     

A Direct Test of Roll's Conjecture on the Firm Size Effect

Empirical research indicates that small firms earn higher average rates of return than large firms, even after accounting for beta risk. Roll conjectured that the small firm effect might be attributed to improper estimation of security betas. The evidence shows that while the direction of the bias in beta estimation is consistent with Roll's conjecture, the magnitude of the bias appears to be too small to explain the firm size effect.     

Inalienable Customer Capital,Corporate Liquidity,and Stock Returns

We develop a model in which customer capital depends on key talents' contribution and pure brand recognition. Customer capital guarantees stable demand but is fragile to financial constraints risk if retained mainly by talents, who tend to quit financially constrained firms, damaging customer capital. Using a proprietary, granular brand‐perception survey, we construct a firm‐level measure of the inalienability of customer capital (ICC) that captures the degree to which customer capital depends on talents. Firms with higher ICC have higher average returns, higher talent turnover, and more precautionary financial policies. The ICC‐sorted long‐short portfolio's spread comoves with financial constraints factor.     

An Examination of Blume and Vasicek Betas

This paper examines the Vasicek and Blume methods for correcting OLS betas. The primary conclusions are that typical applications of Vasicek's method seem to mistakenly equate the prior distribution with the cross-sectional distribution of estimated rather than true betas, that Blume's implicit forecast of any tendency for true betas to regress towards one may not be desirable, that preliminary partitioning of firms into industry type groups (as is typical for Vasicek) is desirable, and that conversion of OLS equity betas to asset betas before applying the correction process is also desirable.     

Regulator's Determination of Return on Equity in the Absence of Public Firms: The Case of Automobile Insurance in Ontario

In a regulated market, such as automobile insurance (AI), regulators set the return on equity that insurers are allowed to achieve. Most insurers are engaged in a variety of insurance lines of business, and thus the full information beta methodology (FIB) is commonly employed to estimate the AI beta. The FIB uses two steps: first, the beta of each insurer is estimated, and then the beta of each line of business is estimated, as the beta of an insurer is a weighted average of the betas of the lines of business. When there are a sufficient number of public companies, company and market returns are used. Otherwise, researchers have resorted to using accounting data in the FIB. Theoretically, the two steps are not separable and the estimation should be done with one step. We introduce the one‐step methodology in our article. The one‐step and two‐step methodologies are compared empirically for the Ontario market of AI. Insurers in Ontario are predominantly private companies; thus, accounting data are used to estimate the AI beta. We show that a significant bias is introduced by the traditional, two‐step FIB methodology in estimating the betas for different lines of business, while insurers’ betas are very similar under both methods. This has a significant application to the estimation of betas of “pure players” in classic corporate finance. It implies that their betas and hence the resulting, required rates of return used in the net present value calculations should be estimated based on the one‐step method that we develop in this article.     

Why do CEOs reciprocally sit on each other's boards?

The reciprocal interlocking of chief executive officers is a non-trivial phenomenon: among large companies in 1991, about one company in seven was in a relationship whereby the CEO of one company sat on a second company's board and the second company's CEO sat on the first company's board. We develop hypotheses to distinguish whether this practice furthers the interests of shareholders or the private interests of the CEOs. Using a sample of large companies, we employ a probit model to test these hypotheses. Our empirical findings are that these reciprocal CEO interlocks primarily benefit the CEOs rather than their shareholders.     

Beyond Financial Reporting An Integrated Approach to Disclosure

A company's market value is a key determinant of its future success, affecting its ability to raise capital, recruit and retain key employees, and make strategic acquisitions. Confident, well‐informed investors are necessary for achieving and maintaining accurate valuation of a company's stock. But standard disclosure practice has left many companies releasing a great deal of data while conveying only limited understanding to outsiders. This article presents the outline of an integrated approach to corporate disclosure in which each of the three major elements–required financial reports, supplemental disclosure, and interactions with investors and intermediaries–are consistent and mutually reinforcing. Such an approach begins with required reports that refiect as closely as possible the economic reality of a company's business. But if GAAP income statements and balance sheets are often useful for communicating current and past performance, they are not designed to convey management's strategic vision and the company's prospects for creating value. To achieve and maintain accurate valuation, management must supplement mandated financial reporting with voluntary communication that highlights value drivers and helps investors understand both the company's strategic goals and management's progress in meeting those goals. Finally, management must interact with investors and capital market intermediaries in ways that provide them with a clear and compelling picture of the company's prospects, which should help both analysts and institutional investors become more effective monitors of the firm's performance. Through consistent communication that goes well beyond the sell side's focus on quarterly earnings per share, management will discover that it has the power to set the agenda for how the company's performance is evaluated by the market. In the process, companies are also likely to find that their investors (and analysts) are more patient than they thought, while their operating managers feel less pressure to take shortsighted steps to boost EPS. Both of these expected benefits of an integrated disclosure policy should end up increasing a company's value.