How costly is the Sarbanes Oxley Act? Evidence on the effects of the Act on corporate profitability

The Sarbanes-Oxley Act (SOX) was intended to protect investors by improving the accuracy and reliability of corporate disclosures. However, critics have argued that the costs of SOX far outweigh its intended benefits. Prior studies based on stock-price reactions to SOX-related events document mixed evidence on the expected impact of SOX. In contrast, we provide evidence on the net realized costs of SOX by examining its impact on operating profitability. We find that average cash flows decline by 1.3% of total assets after SOX. These costs are more significant for smaller firms, for more complex firms, and for firms with lower-growth opportunities. Annually, these costs range from $6 million for smaller firms to $39 million for larger firms. Further, we document that net SOX-related costs are not limited to one-time expenses associated with internal-control design and implementation. In aggregate, for the 1428 firms in our sample, these costs amount to about $19 billion per year. Profitability is lower for up to four years post-SOX. To our knowledge, ours are the first estimates of the realized net costs imposed by SOX.     

Predictive regression with order-p autoregressive predictors

Studies of predictive regressions analyze the case where y_t is predicted by x_t ? 1 with x_t being first-order autoregressive, AR(1). Under some conditions, the OLS-estimated predictive coefficient is known to be biased. We analyze a predictive model where y_t is predicted by x_t ? 1, x_t ? 2,… x_t ? p with x_t being autoregressive of order p, AR(p) with p > 1. We develop a generalized augmented regression method that produces a reduced-bias point estimate of the predictive coefficients and derive an appropriate hypothesis testing procedure. We apply our method to the prediction of quarterly stock returns by dividend yield, which is apparently AR(2). Using our method results in the AR(2) predictor series having insignificant effect, although under OLS, or the commonly assumed AR(1) structure, the predictive model is significant. We also generalize our method to the case of multiple AR(p) predictors.     

Exact inference and optimal invariant estimation for the stability parameter of symmetric α-stable distributions

Hill estimation (Hill, 1975), the most widespread method for estimating tail thickness of heavy-tailed financial data, suffers from two drawbacks. One is that the optimal number of tail observations to use in the estimation is a function of the unknown tail index being estimated, which diminishes the empirical relevance of the Hill estimation. The other is that the hypothesis test of the underlying data lying in the domain of attraction of an α-stable law (α < 2) or of a normal law (α ≥ 2) for finite samples, is performed on the basis of the asymptotic distribution, which can be different from those for finite samples. In this paper, using the Monte Carlo technique, we propose an exact test method for the stability parameter of α-stable distributions which is based on the Hill estimator, yet is able to provide exact confidence intervals for finite samples. Our exact test method automatically includes an estimation procedure which does not need the assumption of a known number of observations on the distributional tail. Empirical applications demonstrate the advantages of our new method in comparison with the Hill estimation.     

Command-and-control: Alternative futures of geoengineering in an age of global weirding

In July 2012, Russ George, the founder of Planktos Inc., organized efforts to dump 100 tons of iron sulfate off the coast of Canada to engineer a plankton bloom that would, ostensibly, absorb carbon dioxide and store it in the depths of the Pacific Ocean. As George's geoengineering experiment is one of the largest and first of its kind, many were quick to denounce his rogue action while others were delighted to see that he succeeded as a large algae bloom was reported to have emerged. Using the George event as a point of entry for exploring alternative futures of geoengineering in an age of global weirding, this project fuses the 2 × 2 scenario modeling technique with the “Mānoa School” four-futures method by situating command and control, along X (control) and Y (command) axes as two critical uncertainties and key drivers of change that will impact the design, development, and diffusion of climate mitigation engineering initiatives, which some see as holding the only solution to avert global catastrophe and others condemn as a postnormal remedy.     

Towards an orientation of higher education in the post Rio + 20 process: How is the game changing?

The purpose of this paper is to identify and assess the implications of sustainable development for the future orientation of higher education, especially after the 2012 United Nations Conference on Sustainable Development (Rio + 20). A qualitative trend analysis is being used for this purpose, in the context of which three macro trends are combined: (1) higher education that has been developed via five periods; (2) sustainable development that has evolved through three stages; and (3) the nexus between sustainable development and higher education which has strengthened through three phases. The simultaneous analysis of the macro trends regarding their possible interactive effects (through an expert panel discussion) demonstrates that higher education and universities under the influence of sustainable development elements are entering into a new era in which the function of “higher education for sustainable development” could be interpreted as the seeds of a newly emerging mission for universities. In this regard, it is expected that the concept of “sustainable university” is likely to become more common to meet the emerging mission. Consistent with the Rio + 20 outcomes, the authors analyzed the concept of “sustainable university” and identified the fact that it is practically divided into three interrelated and complementary categories, namely social-, environmental-, and economic-oriented university in pursuit of actualizing sustainable development.     

Market microstructure: A survey

Market microstructure studies the process by which investors’ latent demands are ultimately translated into prices and volumes. This paper reviews the theoretical, empirical and experimental literature on market microstructure relating to: (1) price formation, including the dynamic process by which prices come to impound information, (2) market structure and design, including the relation between price formation and trading protocols, (3) Transparency, the ability of market participants to observe information about the trading process, and (4) Applications to other areas of finance including asset pricing, international finance, and corporate finance.     

Gaining a competitive edge through acquisitions: Evidence from the telecommunications industry

I study the announcement effects of all acquisitions in the recent telecom wave on both the acquirers and their industry competitors. I find evidence of negative rival returns (? 0.55%, t-stat = 2.47) by focusing on non-horizontal acquisitions where rivals are less susceptible to experience positive returns due to increased market power or expectation that some will become future targets themselves. I find that this effect is worse for closer rivals defined as having similar size and being in the same primary service area as the acquirer. Competitor returns are positively correlated with those of the acquirers suggesting that the negative impact experienced by competitors is driven by acquisitions in which the acquirer itself is earning negative abnormal returns. Results are broadly consistent with the Competitive Advantage Hypothesis that posits acquisitions are a means of corporate restructuring in a changing environment, awarding the acquirer a competitive edge and thereby making these acquisitions costly for their non-merging competitors.     

Risk management implications of time-inconsistency: Model updating and recalibration of no-arbitrage models

A widespread approach in the implementation of asset pricing models is based on the periodic recalibration of its parameters and initial conditions to eliminate any conflict between model-implied and market prices. Modern no-arbitrage market models facilitate this procedure since their solution can usually be written in terms of the entire initial yield curve. As a result, the model fits (by construction) the interest rate term structure. This procedure is, however, generally time inconsistent since the model at time t = 0 completely specifies the set of possible term structures for any t > 0. In this paper, we analyze the pros and cons of this widespread approach in pricing and hedging, both theoretically and empirically. The theoretical section of the paper shows (a) under which conditions recalibration improves the hedging errors by limiting the propagation of an initial error, (b) that recalibration introduces time-inconsistent errors that violate the self-financing argument of the standard replication strategy. The empirical section of the paper quantifies the trade-off between (a) and (b) under several scenarios. First, we compare this trade-off for two economies with and without model specification error. Then, we discuss the trade-off when the underlying economy is not Markovian.     

Latency,liquidity and price discovery

The speed of trading is an important factor in modern security markets, although relatively little is known about the effect of speed on liquidity and price discovery, two important aspects of market quality. On April 23, 2007, Deutsche Boerse made an important upgrade to their trading system. With the 8.0 release of Xetra, system latency was reduced from 50 ms to 10 ms. Subsequently, both quoted and effective spreads decreased, which are mainly concentrated in small- and medium-sized stocks. This increase in liquidity is due to dramatically lower adverse selection costs that were only partially translated into higher liquidity. We interpret this as a decrease in the competition between liquidity suppliers who are able to increase their revenues by more than 90 million euros. The contribution of quotes to price discovery doubles to 90% post upgrade, indicating that prices are more efficient.     

The effect of Sarbanes-Oxley on the timely disclosure of restricted stock trading

Our paper investigates the effect of the Sarbanes-Oxley Act (SOX) on the disclosure timeliness of restricted stock trading. Insiders selling restricted stock are required to file a Form 144 because the stock is restricted and also a Form 4 because they are an insider. We confirm that mandatory filing requirements under Section 403 of SOX reduced the Form 4 disclosure delay for restricted stock transactions from 24 days in the pre-SOX period to the mandated 2 days in the post-SOX period. Although SOX did not mandate changes to Form 144 filings, we expect that disclosure timeliness of Form 144 filings is likely impacted by SOX. We find that Form 144 filings of restricted stock sales have become less timely. In the post-SOX period, Form 144, the intent to sell restricted stock, is almost always reported after the Form 4 disclosure of the executed trade. Thus, an unintended consequence of SOX is that by making the Form 4 filing more timely than the Form 144, market participants will know about a trade sooner, but have less information about the type of equity traded. An implication of this finding is that Section 403 of SOX may not have unambiguously improved investor protection as intended.     

The nexus between financial integration and real economy: Solow-growth model concept

This paper aims to investigate the nexus between financial integration and the real economy in ASEAN + 3 economies based on the concept of Solow-Growth Model. The equity indices as a proxy for financial markets are collected from each ASEAN + 3 members and are segmented between two periods; before and after the financial cooperation agreement period. The finding presents several outcomes; 1) no cointegration nexus is found in the system during the pre-agreement periods; 2) the markets are found cointegrated during the post-agreement period, 3) financial integration is found to influence the real sectors of ASEAN + 3 economies. Finally, this study offers policy implications to improve financial integration for stabilizing the real economy.     

The importance of size in private equity: Evidence from a survey of limited partners

Using a comprehensive survey, we show that investors with a larger capital allocation to private equity are more specialized − measured by the degree to which the investor focuses on private equity rather than other classes of investments − and have a wider scope of due diligence and investment activities. Other investor characteristics (experience, type, location, compensation structure, number of funds under management) play no role. In particular, endowments are not special according to the survey measures. These results are consistent with the changing LP–GP relationship in private equity as capital is increasingly concentrated in the hands of large investors.     

Google Internet search activity and volatility prediction in the market for foreign currency

I study whether evolution in the number of Google Internet searches for particular keywords can predict volatility in the market for foreign currency. I find that data on Google searches for the keywords economic crisis + financial crisis and recession has incremental predictive power beyond the GARCH(1,1). These results support the mixture of distributions hypothesis in that volatility is linked to the stochastic rate at which information flows into the marketplace. These results also demonstrate the potential for Google to become a storehouse of information for financial markets.     

Time to equilibrium in exchange rates: G-10 and Eastern European economies

This paper reports different times-to-equilibrium for G-10 developed economies and the Eastern European emerging economies. By applying a novel method of value-weighted index to highly-trade-linked economies, we test the purchasing power parity to the full length of time-to-equilibrium. The times-to-equilibrium obtained are: 6 years for developed and 2 years for emerging economies. These results are consistent with the sticky price hypothesis: economies trading in highly aggregated capital goods take longer time to reach price equilibrium in the face of overshooting exchange rates: the opposite is true for primary exporters. This finding is new for these two groups, and could be compared usefully with the earlier reports of long half-life for developed countries. Also, our method of measurement establishes the actual time of the theory prediction on price-to-currency relationship. It is possible to apply this methodology to study more groups of countries.     

Modeling and forecasting stock return volatility using a random level shift model

We consider the estimation of a random level shift model for which the series of interest is the sum of a short-memory process and a jump or level shift component. For the latter component, we specify the commonly used simple mixture model such that the component is the cumulative sum of a process which is 0 with some probability (1 ? α) and is a random variable with probability α. Our estimation method transforms such a model into a linear state space with mixture of normal innovations, so that an extension of Kalman filter algorithm can be applied. We apply this random level shift model to the logarithm of daily absolute returns for the S&P 500, AMEX, Dow Jones and NASDAQ stock market return indices. Our point estimates imply few level shifts for all series. But once these are taken into account, there is little evidence of serial correlation in the remaining noise and, hence, no evidence of long-memory. Once the estimated shifts are introduced to a standard GARCH model applied to the returns series, any evidence of GARCH effects disappears. We also produce rolling out-of-sample forecasts of squared returns. In most cases, our simple random level shift model clearly outperforms a standard GARCH(1,1) model and, in many cases, it also provides better forecasts than a fractionally integrated GARCH model.     

GHICA — Risk analysis with GH distributions and independent components

Over recent years, a study on risk management has been prompted by the Basel committee for regular banking supervisory. There are however limitations of some widely-used risk management methods that either calculate risk measures under the Gaussian distributional assumption or involve numerical difficulty. The primary aim of this paper is to present a realistic and fast method, GHICA, which overcomes the limitations in multivariate risk analysis. The idea is to first retrieve independent components (ICs) out of the observed high-dimensional time series and then individually and adaptively fit the resulting ICs in the generalized hyperbolic (GH) distributional framework. For the volatility estimation of each IC, the local exponential smoothing technique is used to achieve the best possible accuracy of estimation. Finally, the fast Fourier transformation technique is used to approximate the density of the portfolio returns.The proposed GHICA method is applicable to covariance estimation as well. It is compared with the dynamic conditional correlation (DCC) method based on the simulated data with d = 50 GH distributed components. We further implement the GHICA method to calculate risk measures given 20-dimensional German DAX portfolios and a dynamic exchange rate portfolio. Several alternative methods are considered as well to compare the accuracy of calculation with the GHICA one.     

The New Narrative: Applying narratology to the shaping of futures outputs

Both scenario development and design practices incorporate elements of storytelling, but this use remains undertheorised. This paper will draw upon literary theory, film theory and science fiction criticism to develop an analytical model of narrative structure and rhetorics which speaks to the concerns of scenario developers and designers when engaged in shaping the final outputs or deliverables of a futures project.After highlighting the differing role of telos in art and futures and defining the metacategory of “narratives of futurity”, this paper then defines the terms “story”, “narrative”, “narrator” and “world” in the literary context. It then shows how those concepts map onto futures practice, before going into detail regarding the variety of narrative strategies available across a range of different forms and media, and the qualitative effects that they can reproduce in audiences. There follows the construction of a 2 × 2 matrix based on the critical concepts of narrative mode and narrative logic, within which narratives of futurity might be usefully catalogued and compared, and from which certain broad conclusions may be reached as regards the relation between choice of medium and rhetorical effect. The implications of this analysis are explored in detail.     

Speed of convergence to market efficiency: The role of ECNs

Chordia, Roll and Subrahmanyam (2005, CRS) estimate the speed of convergence to market efficiency based on short-horizon return predictability of the 150 largest NYSE firms. We extend CRS to a broad panel of NYSE stocks and are the first to examine the relation between electronic communication networks (ECNs) and the corresponding informational efficiency of prices. Overall, we confirm CRS's result that price adjustments to new information occur on average within 5–15 min for large NYSE stocks. We further show that it takes about 20 min longer for smaller firms to incorporate information into prices. Most importantly, we demonstrate that the speed of convergence to market efficiency is significantly related to the type of trading platform where orders are executed, even after controlling for relative order flows, trading costs, volatility, informational effects, trading conditions, market quality, institutional trading activity, and other firm-specific characteristics. Our findings provide direct answers and insights to issues raised in a recent SEC concept release document.     

Design and evaluation of an advanced continuous data level auditing system: A three-layer structure

Audit efficiency and effectiveness can be significantly affected by data aggregation during audit procedures. Previous studies highlight that an appropriate level of data aggregation is needed because a continuous auditing (CA) system often generates numerous alarms. To respond to this issue, this study proposes a CA system with a three-layer structure. In the first layer of the proposed system, all journal entry level transactions are classified and aggregated using defined rules; any transactions that deviate from these rules are identified as unusual transactions. The second layer detects the observations that violate controls. Analytical monitoring models are developed in the final layer to identify observations that statistically deviate from an organization’s typical business behaviors. To examine whether the proposed three-layer CA system enhances the effectiveness of a CA system in identifying financial irregularities, this study empirically tests the proposed models using real-world journal entry data from a construction company. The results indicate that the proposed framework enhances audit effectiveness and efficiency.