When do incentives work in channels of distribution?

The incentive dilemma refers to a situation in which incentives are offered but do not work as intended. The authors suggest that, in an interorganizational context, whether a principal-provided incentive works is a function of how it is evaluated by an agent: for its contribution to the agent's bottom line (instrumental evaluation) and for the extent it is strategically aligned with the agent's direction (congruence evaluation). To further understand when incentives work, the influence of two key contextual variables-industry volatility and dependence-are examined. A field study featuring 57 semi-structured depth interviews and 386 responses from twin surveys in the information technology and brewing industries provide data for hypothesis testing. When and whether incentives work is demonstrated by certain conditions under which the agent's evaluation of an incentive has positive or negative effects on its compliance and active representation. Further, some outcomes are reversed in the high volatility condition. © 2013 Academy of Marketing Science.

Industry concentration and market volatility

In this paper our aim is to gain a better understanding of the relationship between market volatility and industrial structure. As conflicting results have been documented regarding the relationship between market industry concentration and market volatility, this study investigates this relationship in the time series. We have found that this relationship is only significant and positive for Spain. Our results suggest that we cannot generalize across different countries that market industrial structure (concentration) is a significant factor in explaining market volatility.

The Food Service Industry Environment: Market Volatility Analysis

In their dialogue entitled - The Food Service Industry Environment: Market Volatility Analysis - by Alex F. De Noble, Assistant Professor of Management, San Diego State University and Michael D. Olsen, Associate Professor and Director, Division of Hotel, Restaurant & Institutional Management at Virginia Polytechnic Institute and State University, De Noble and Olson preface the discussion by saying: “Hospitality executives, as a whole, do not believe they exist in a volatile environment and spend little time or effort in assessing how current and future activity in the environment will affect their success or failure. The authors highlight potential differences that may exist between executives' perceptions and objective indicators of environmental volatility within the hospitality industry and suggest that executives change these perceptions by incorporating the assumption of a much more dynamic environment into their future strategic planning efforts. Objective, empirical evidence of the dynamic nature of the hospitality environment is presented and compared to several studies pertaining to environmental perceptions of the industry.” That weighty thesis statement presumes that hospitality executives/managers do not fully comprehend the environment in which they operate. The authors provide a contrast, which conventional wisdom would seem to support and satisfy. “Broadly speaking, the operating environment of an organization is represented by its task domain,” say the authors. “This task domain consists of such elements as a firm's customers, suppliers, competitors, and regulatory groups.” These are dynamic actors and the underpinnings of change, say the authors by way of citation. “The most difficult aspect for management in this regard tends to be the development of a proper definition of the environment of their particular firm. Being able to precisely define who the customers, competitors, suppliers, and regulatory groups are within the environment of the firm is no easy task, yet is imperative if proper planning is to occur,” De Noble and Olson further contribute to support their thesis statement. The article is bloated, and that’s not necessarily a bad thing, with tables both survey and empirically driven, to illustrate market volatility. One such table is the Bates and Eldredge outline; Table-6 in the article. “This comprehensive outline…should prove to be useful to most executives in expanding their perception of the environment of their firm,” say De Noble and Olson. “It is, however, only a suggested outline,” they advise. “…risk should be incorporated into every investment decision, especially in a volatile environment,” say the authors. De Noble and Olson close with an intriguing formula to gauge volatility in an environment.

The problem of estimating the volatility of zero coupon bond interest rate

Financial literature and financial industry use often zero coupon yield curves as input for testing hypotheses, pricing assets or managing risk. They assume this provided data as accurate. We analyse implications of the methodology and of the sample selection criteria used to estimate the zero coupon bond yield term structure on the resulting volatility of spot rates with different maturities. We obtain the volatility term structure using historical volatilities and Egarch volatilities. As input for these volatilities we consider our own spot rates estimation from GovPX bond data and three popular interest rates data sets: from the Federal Reserve Board, from the US Department of the Treasury (H15), and from Bloomberg. We find strong evidence that the resulting zero coupon bond yield volatility estimates as well as the correlation coefficients among spot and forward rates depend significantly on the data set. We observe relevant differences in economic terms when volatilities are used to price derivatives.

Effects of mergers and acquisitions in the paper industry

Paperiteollisuus on ollut perinteisesti fragmentoitunut toimiala, mutta viime vuosikymmenen aikana konsolidoitumisprosessi on kiihtynyt. Yrityskaupat ja fuusiot ovat muuttaneet paperiteollisuuden markkinarakennetta merkittävästi. Työn tavoitteena oli tutkia yleisesti markkinarakenteen vaikutusta liiketoiminnan tuloksiin sekä analysoida yrityskauppojen ja fuusioiden syitä, tuloksia ja rajoituksia. Tavoitteena oli myös tutkia paperiteollisuuden konsolidoitumisen vaikutuksia hintakehitykseen, hintaheilahteluihin ja kannattavuuteen. Keskeisenä syynä konsolidoitumiskehitykselle voidaan pitää uusien paperikoneiden huomattavaa investointikustannusten kasvua. Toinen tärkeä tekijä yhdentymiskehitykselle on se, että paperiteollisuus on saavuttanut elinkaaren kypsyysvaiheen Euroopassa, Pohjois-Amerikassa ja Japanissa. Yrityskauppojen ja fuusioiden motiiveja paperiteollisuudessa ovat mm. kasvu kypsillä markkinoilla, tarve parantaa taloudellista tulosta, mahdollisuus toimia globaalisti ja hyödyntää siitä saatavat edut tai mahdollisuus parempaan arvoketjun hallintaan. Näyttää siltä, että suurempien paperiteollisuusyritysten kannattavuus ei ole parempi kuin pienemmillä yrityksillä. Lisäksi useimmissa paperiteollisuuden yrityskaupoissa ja fuusioissa näyttäisi ostavan osapuolen kurssikehitys ilmoitusta seuraavana päivänä olevan negatiivinen.

Observations of Industry Momentum Effect in European Equity Indices

This thesis examines the existence and nature of momentum effect in European equity indices. A set of predefined indicators is used to compose momentum portfolios and different holding periods are used to test the strategies over variable time periods as well as under different economical conditions. The data consists of daily closing prices of STOXX Europe 600 index and its 18 super sector indices. Over the study period we follow the performances of a long position in the Winner portfolio, a position in the market neutral zero-cost portfolio and also a position in the risk-controlled zero-cost portfolio. The investment ratio of the risk-controlled zero-cost portfolio is negatively correlated with the realized market volatility. The results show that momentum effect is present in European industries and is most prominent in the short-term. Indicators that are based on short-term performance tend predict the over- and underperformers for the 1-month holding period more reliably than any other indicator/holding period combination. The examination of the strategies under different economical conditions shows that the market neutral approach can create significant returns in times of recession but in times of economic boom the long position in Winner portfolio outperforms the market neutral portfolio by an extensive margin.

How Is Credit Risk Estimated? Discussion and Evidence based on Cross-Industry Sample Utilizing the KMV Model

The purpose of this thesis is to focus on credit risk estimation. Different credit risk estimation methods and characteristics of credit risk are discussed. The study is twofold, including an interview of a credit risk specialist and a quantitative section. Quantitative section applies the KMV model to estimate credit risk of 12 sample companies from three different industries: automobile, banking and financial sector and technology. Timeframe of the estimation is one year. On the basis of the KMV model and the interview, implications for analysis of credit risk are discussed. The KMV model yields consistent results with the existing credit ratings. However, banking and financial sector requires calibration of the model due to high leverage of the industry. Credit risk is considerably driven by leverage, value and volatility of assets. Credit risk models produce useful information on credit worthiness of a business. Yet, quantitative models often require qualitative support in the decision-making situation.

Effects of overvaluation and exchange rate volatility over industrial investment: empirical evidence and economic policy proposals for Brazil

The present article aims to analyze the recent behavior of real exchange rate in Brazil and its effects over investment per worker in Brazilian manufacturing and extractive industry. Preliminary estimates presented in the article shows an over-valuation of 48% of real exchange rate in Brazil. The reaction between the level (and volatility) of real exchange rate and investment (per worker) in Brazil is analyzed by means of a panel data econometric model for 30 sectors of Brazilian manufacturing and extractive industry. The empirical results show that the level and volatility of real exchange rate has a strong effect over investment per worker in Brazilian industry. Finally, we conclude the article presenting a proposal for a new macroeconomic regime that aims to produce an acceleration of economic growth of Brazilian economy and, by that, a catching-up process with developed countries.

Cross-sectoral variation in the volatility of plant-level idiosyncratic shocks

We estimate the volatility of plant–level idiosyncratic shocks in the U.S. manufacturing sector. Our measure of volatility is the variation in Revenue Total Factor Productivity which is not explained by either industry– or economy–wide factors, or by establishments’ characteristics. Consistent with previous studies, we find that idiosyncratic shocks are much larger than aggregate random disturbances, accounting for about 80% of the overall uncertainty faced by plants. The extent of cross–sectoral variation in the volatility of shocks is remarkable. Plants in the most volatile sector are subject to about six times as much idiosyncratic uncertainty as plants in the least volatile. We provide evidence suggesting that idiosyncratic risk is higher in industries where the extent of creative destruction is likely to be greater.

Firm Market Performance and Volatility in a National Real Estate Sector

We present empirical evidence using daily data for stock prices for 17 real estate companies traded in the Sao Paulo, Brazil stock exchange. from August 26, 2006 to March 31, 2010. We use the U.S. house price bubble, financial crisis and risk measures to instrument for momentums and reversals in the domestic real estate sector. We find evidence of conditional premium persistence and conditional volatility persistence in the market. We find that the conditional risk-return relationship in the sector is consistent with the prospect theory of risk attitudes in this period. Certain companies seem to be operating on a perceived potential industry return above the target, while most others are below the target, and the whole sector is below target on average. (C) 2011 Elsevier Inc. All rights reserved.

Modelling and testing volatility spillovers in oil and financial markets for USA, UK and China

The primary purpose of the paper is to analyze the conditional correlations, conditional covariances, and co-volatility spillovers between international crude oil and associated financial markets. The paper investigates co-volatility spillovers (namely, the delayed effect of a returns shock in one physical or financial asset on the subsequent volatility or co-volatility in another physical or financial asset) between the oil and financial markets. The oil industry has four major regions, namely North Sea, USA, Middle East, and South-East Asia. Associated with these regions are two major financial centers, namely UK and USA. For these reasons, the data to be used are the returns on alternative crude oil markets, returns on crude oil derivatives, specifically futures, and stock index returns in UK and USA. The paper will also analyze the Chinese financial markets, where the data are more recent. The empirical analysis will be based on the diagonal BEKK model, from which the conditional covariances will be used for testing co-volatility spillovers, and policy recommendations. Based on these results, dynamic hedging strategies will be suggested to analyze market fluctuations in crude oil prices and associated financial markets.

Industry-specific effect of CSR initiatives: hotels and airlines

Purpose – This study aims to examine the relationships between a firm's corporate social responsibility (CSR) activities and its performance and risk. The authors hypothesize that industry-level effects are highly determinant of the sign and magnitude of these relationships to establish a ranking of industries to identify the position of the most prominent tourism-related industries: hotels and airlines. Based on the cybernetic model of decision making and the heuristics thereof, shareholders base their investment decisions derived from CSR announcements on the idea that the industries behave differently; their fixed costs being a relevant factor. Design/methodology/approach – The authors estimate the industry-specific effects of CSR initiatives on firms' performance and risk using a sample of 583 announcements from the Spanish Stock Market. Findings – The results show that while CSR announcements have a positive effect on performance when the authors do not account for industry-specific factors, once the authors incorporate these factors into the analysis, the authors find that firm performance and risk vary quite substantially as a function of the industry to which the firm belongs. Interestingly, while the hotel industry presents an average behavior (standing at 9th position in returns, 15th in terms of risk, and 8th according to the ratio returns/volatility), the airline industry presents the worst situation of all industries: last in performance and last in risk. Practical implications – The results help managers assess their decisions and allocate CSR resources optimally. Originality/value – This article is the first attempt to empirically test and comprehensively detect the different relationships between CSR and firm performance across industries.

The relationship between market share and information in a high-tech industry

The role of information in high-technology markets is critical (Dutta, Narasimhan and Rajiv 1999; Farrell and Saloner 1986; Weiss and Heide 1993). In these markets, the volatility and volume of information present managers and researchers with the considerable challenge of monitoring such information and examining how potential customers may respond to it. This article examines the effects of the type and volume of information on the market share of different technological standards in the Local Area Networks (LAN) industry. We identify three different types of information: technological, availability and adoption. Our empirical application suggests that all three types of information have significant effects on the market share of a technological standard, but their direction and magnitude differ. More specifically, technology-related information is negatively related to market share as it demonstrates that the underlying technology is immature and still evolving. Both availability and adoption-related information have a positive effect on market share, but the former is larger than the latter. We conclude that high-tech firms should emphasize the dissemination of information, especially availability-related, as part of their promotional strategy for a new technology. Otherwise, they may risk missing an opportunity to achieve a higher share and establish their market presence.

Measuring, Modeling, and Forecasting Volatility and Correlations from High-Frequency Data

This dissertation contains four essays that all share a common purpose: developing new methodologies to exploit the potential of high-frequency data for the measurement, modeling and forecasting of financial assets volatility and correlations. The first two chapters provide useful tools for univariate applications while the last two chapters develop multivariate methodologies. In chapter 1, we introduce a new class of univariate volatility models named FloGARCH models. FloGARCH models provide a parsimonious joint model for low frequency returns and realized measures, and are sufficiently flexible to capture long memory as well as asymmetries related to leverage effects. We analyze the performances of the models in a realistic numerical study and on the basis of a data set composed of 65 equities. Using more than 10 years of high-frequency transactions, we document significant statistical gains related to the FloGARCH models in terms of in-sample fit, out-of-sample fit and forecasting accuracy compared to classical and Realized GARCH models. In chapter 2, using 12 years of high-frequency transactions for 55 U.S. stocks, we argue that combining low-frequency exogenous economic indicators with high-frequency financial data improves the ability of conditionally heteroskedastic models to forecast the volatility of returns, their full multi-step ahead conditional distribution and the multi-period Value-at-Risk. Using a refined version of the Realized LGARCH model allowing for time-varying intercept and implemented with realized kernels, we document that nominal corporate profits and term spreads have strong long-run predictive ability and generate accurate risk measures forecasts over long-horizon. The results are based on several loss functions and tests, including the Model Confidence Set. Chapter 3 is a joint work with David Veredas. We study the class of disentangled realized estimators for the integrated covariance matrix of Brownian semimartingales with finite activity jumps. These estimators separate correlations and volatilities. We analyze different combinations of quantile- and median-based realized volatilities, and four estimators of realized correlations with three synchronization schemes. Their finite sample properties are studied under four data generating processes, in presence, or not, of microstructure noise, and under synchronous and asynchronous trading. The main finding is that the pre-averaged version of disentangled estimators based on Gaussian ranks (for the correlations) and median deviations (for the volatilities) provide a precise, computationally efficient, and easy alternative to measure integrated covariances on the basis of noisy and asynchronous prices. Along these lines, a minimum variance portfolio application shows the superiority of this disentangled realized estimator in terms of numerous performance metrics. Chapter 4 is co-authored with Niels S. Hansen, Asger Lunde and Kasper V. Olesen, all affiliated with CREATES at Aarhus University. We propose to use the Realized Beta GARCH model to exploit the potential of high-frequency data in commodity markets. The model produces high quality forecasts of pairwise correlations between commodities which can be used to construct a composite covariance matrix. We evaluate the quality of this matrix in a portfolio context and compare it to models used in the industry. We demonstrate significant economic gains in a realistic setting including short selling constraints and transaction costs.