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.     

Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets

Using two newly available ultrahigh-frequency datasets, we investigate empirically how frequently one can sample certain foreign exchange and U.S. Treasury security returns without contaminating estimates of their integrated volatility with market microstructure noise. Using the standard realized volatility estimator, we find that one can sample dollar/euro returns as frequently as once every 15 to 20 s without contaminating estimates of integrated volatility; 10-year Treasury note returns may be sampled as frequently as once every 2 to 3 min on days without U.S. macroeconomic announcements, and as frequently as once every 40 s on announcement days. Using a simple realized kernel estimator, this sampling frequency can be increased to once every 2 to 5 s for dollar/euro returns and to about once every 30 to 40 s for T-note returns. These sampling frequencies, especially in the case of dollar/euro returns, are much higher than those that are generally recommended in the empirical literature on realized volatility in equity markets. The higher sampling frequencies for dollar/euro and T-note returns likely reflect the superior depth and liquidity of these markets.     

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.     

Persistence and cycles in the us federal funds rate

This paper uses long-range dependence techniques to analyse two important features of the US Federal Funds effective rate, namely its persistence and its cyclical behaviour. It examines annual, monthly, bi-weekly and weekly data, from 1954 until 2017. Two models are considered. One is based on an I(d) specification with AR(2) disturbances and the other one on two fractional differencing structures, one at the zero and the other at a cyclical frequency. Thus, the two approaches differ in the way the cyclical component of the process is modelled. In both cases we obtain evidence of long memory and fractional integration with cycles repeating approximately every 8 years. The in-sample goodness-of-fit analysis supports the second specification in the majority of cases. An out-of-sample forecasting experiment also suggests that the long-memory model with two fractional differencing parameters is the most adequate one, especially over long horizons.     

Do FOMC minutes matter to markets? An intraday analysis of FOMC minutes releases on individual equity volatility and returns

This paper examines the 2006 to 2007 time period to determine the extent to which the release of the Federal Reserve minutes affects equity volatility and returns for 2832 individual firms. Using intraday data, we find that equity returns are essentially unaffected by FOMC minutes releases. We do find evidence of volatility effects, in that conditional volatility is lower prior to the minutes release and higher after the minutes release on release days, relative to a “control” day one week prior to the release date. These differences manifest at the 2:00–2:05 pm interval, and generally dissipate within 15 min. Consistent with previous literature, we also find evidence of both industry-specific and firm size effects in our data. Finally, we see that volatility is higher (lower) when the minutes are released after the Federal Reserve engages in restrictive (expansionary) monetary policy. Our results are robust to a variety of different definitions of the “control” dates, as well as differing industry definitions.     

Dividend privileges and the value of voting rights: Evidence from Italy

The present paper proposes a new measure of the voting right, the Relative Vote Segment, which incorporates dividend privileges into the inferior class of shares. We test and compare it against the standard Relative Price Difference and the Nenova (2003) measure using 1998–2008 data from Italy, a country where dividend privileges are relevant. Results show that when dividend privileges are considered, the average voting right equals + 35.63%, while its estimated value corresponds to a significantly lower + 20.35% and + 1.29% with the Relative Price Difference and the Nenova (2003) measure, respectively. Negative values of voting rights drop significantly with our methodology. Results become even more clear-cut when we clean the sample of possible measurement errors. As far as the determinants of the voting premium are concerned, the choice of the measure does not appear to have a significant impact, as long as the dividend differences are controlled for.     

Atributos relevantes de calidad en el servicio y su influencia hacia la lealtad de marca en la industria aseguradora de automóviles en México

The objective of this study is to identify key quality service attributes in the automobile insurance business and determine their influence on brand loyalty. In this study distinction is made between the service during the hiring of the service and the service provided after an accident. In a preliminary exploratory inquiry quality service attributes were identified with the application of in-depth interviews. In an empirical study, hypothesis related to a direct relationship between the attributes and several measures of brand loyalty are contrasted. A sample of n = 210 of automobile insurance clients was conformed. Five regression models were developed for the data analysis, one for each loyalty measure. These analyses allowed a specific detection of significant attributes for each case. Though it is concluded that attributes related to the service after the accident have a higher degree of influence on the customer loyalty, it is found that a particular attribute during hiring (reputation of the insurance company) also has an important role.     

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.     

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.     

Individual and institutional herding and the impact on stock returns: Evidence from Taiwan stock market

Using high frequency intraday data, this paper investigates the herding behavior of institutional and individual investors in the Taiwan stock market. The study finds evidence of herding by both investors but a stronger herding tendency among institutional than among individual investors. Institutional investors herd more on firms with small capitalizations and lower turnovers and they follow positive feedback strategies. The portfolios that institutional investors herd buy outperform those they sell by an average of 1.009% during the 20 days after intense trading episodes. By contrast, individual investors herd more on firms with small sizes and higher turnovers, and they crowd to buy (sell) stocks with negative (positive) past returns. The portfolios that individual investors herd buy underperform those they sell by an average of − 0.829% during the following 20 days. Moreover, these return differences of both investors are more pronounced under a market with higher pressure and among small stocks. These findings suggest that the herding of institutional investors speeds up the price-adjustment process and is more likely to be driven by correlated private information, while individual herding is most likely to be driven by behavior and emotions.     

Differences in the sophistication of Value-based Management – The role of top executives

This paper responds to recent calls for studying the diffusion of management practices beyond classifying companies as adopters and non-adopters (Ansari et al., 2010, Lounsbury, 2008). In particular, we examine how characteristics of CEOs and CFOs as well as perceived environmental uncertainty (PEU) of the top management team (TMT) affect the sophistication of Value-based Management (VBM) for which we develop a multi-dimensional construct.We base our analyses on a unique dataset that comprises archival data, interviews and survey data from top executives of German HDAX companies (58% response rate). The results of our Partial Least Squares (PLS) model (R² = 55%) support most of our hypotheses and provide interesting findings.We find that the CFOs in our sample have substantially more influence on VBM-sophistication than CEOs. In particular, we document that cognitive styles (educational background in business) of CFOs have a substantial impact on VBM-sophistication. Moreover, short-tenured CFOs are associated with high VBM-sophistication. As expected, the related negative effect of long tenure on VBM sophistication is practically offset if the CFO has an educational background in business.Another relevant finding is that high perceived environmental uncertainty of the top management team is significantly associated with lower VBM-sophistication. The results of our control variables moreover reveal that systematic risk (‘beta’) leads to higher VBM sophistication.     

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.     

Examining dynamic currency linkages amongst South Asian economies: An empirical study

In this paper, we examine the currency market linkages of South Asian member countries using daily data from 6 January 2004 to 31st March 2016. Time invariant and varying Copula GARCH models show that South Asian countries, except for India and Nepal/Bhutan, have low levels of currency market linkages which can be ascribed to poor levels of intra-regional trade intensity and portfolio flows. We reconfirm the copula results through Diebold and Yilmaz methodology and document that currency market connectedness is very limited in the South Asian region. The trends of the fundamental determinants of currency co-movements for the South Asian member countries were compared with its neighbouring regional economic bloc in Asia which has a much longer history and a wider membership base i.e ASEAN + 6. From a comparative analysis, it was found that South Asia member states have to work on their governance parameters, improve on their trade linkages and trade tariffs and work towards greater degree of capital account convertibility with adequate safeguards to achieve higher levels of currency market linkages.     

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.     

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.     

Dynamic news effects in high frequency Euro exchange rates

This paper investigates the dynamic, short-run response of Euro exchange rate returns to the information surprise of global macroeconomic announcements. In addition, it advocates a new approach to modelling intraday exchange rate volatility to allow accurate characterisation of reactions. US macroeconomic news generates far more dramatic responses in EUR–USD returns and returns volatility than news on the macroeconomic performance of other countries. However, some Eurozone and German indicators are also important and UK announcements are important for the EUR–GBP rate. The reaction of exchange rate returns to news is very quick and occurs within the first 5 min of the release with very little reaction in the 15 min before and after. These findings show that exchange rates are strongly linked to fundamentals in the 5-min intervals immediately following the data release. Reactions to news are found to vary in magnitude over the sample, with the largest responses to news occurring in response to turning points in the cumulative flow of news.     

Investor sentiment and stock returns: Wenchuan Earthquake

This paper exploits a natural experiment (the Wenchuan Earthquake in China) to study the effects of investor sentiment on stock returns. We find that during the 12 months following the earthquake, stock returns are significantly lower for firms headquartered nearer the epicenter than for firms further away. Further analyses indicate that this pattern of stock returns does not exist before or long after the earthquake, and cannot be explained by actual economic losses or a change in systematic risk. Overall, our evidence is consistent with the interaction of local bias and investor sentiment affecting stock returns.     

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.     

The home bias is here to stay

Over the last 15 years, dramatically decreasing foreign investment costs have not reduced the home bias. We show that the home bias induced by a given cost is proportional to the factor ρ/(1 − ρ), where ρ is the average correlation between markets. This factor is very sensitive to the correlation, especially when the correlation is high. Empirically, correlations have been steadily increasing from 0.4 in the 90’s to about 0.9 today. Thus, the decreasing extra costs are increasingly magnified, explaining the persistence of the home bias, and predicting its continuation.