Cross-delisting, financial constraints and investment sensitivities

We investigate the impact of cross-delisting on firms’ financial constraints and investment sensitivities. We find that firms that cross-delisted from a U.S. stock exchange face stronger post-delisting financial constraints than their cross-listed counterparts, as measured by investment-to-cash flow sensitivity. Following a delisting, the sensitivity of investment-to-cash flow increases significantly and firms also tend to save more cash out of cash flows. Moreover, this increase appears to be primarily driven by informational frictions that constrain access to external financing. We document that information asymmetry problems are stronger for firms from countries with weaker shareholders protection and for firms from less developed capital markets.

A nonlinear threshold model for the dependence of extremes of stationary sequences

One of the main implications of the efficient market hypothesis (EMH) is that expected future returns on financial assets are not predictable if investors are risk neutral. In this paper we argue that financial time series offer more information than that this hypothesis seems to supply. In particular we postulate that runs of very large returns can be predictable for small time periods. In order to prove this we propose a TAR(3,1)-GARCH(1,1) model that is able to describe two different types of extreme events: a first type generated by large uncertainty regimes where runs of extremes are not predictable and a second type where extremes come from isolated dread/joy events. This model is new in the literature in nonlinear processes. Its novelty resides on two features of the model that make it different from previous TAR methodologies. The regimes are motivated by the occurrence of extreme values and the threshold variable is defined by the shock affecting the process in the preceding period. In this way this model is able to uncover dependence and clustering of extremes in high as well as in low volatility periods. This model is tested with data from General Motors stocks prices corresponding to two crises that had a substantial impact in financial markets worldwide; the Black Monday of October 1987 and September 11th, 2001. By analyzing the periods around these crises we find evidence of statistical significance of our model and thereby of predictability of extremes for September 11th but not for Black Monday. These findings support the hypotheses of a big negative event producing runs of negative returns in the first case, and of the burst of a worldwide stock market bubble in the second example. JEL classification: C12; C15; C22; C51 Keywords and Phrases: asymmetries, crises, extreme values, hypothesis testing, leverage effect, nonlinearities, threshold models

Misallocation of capital in a model of endogenous financial intermediation and insurance

In this paper we analyze productivity and welfare losses from capital misallocation in a general equilibrium model of occupational choice and endogenous financial intermediation. We study the effects of borrowing and lending, insurance, and risk sharing on the optimal allocation of resources. We find that financial markets together with general equilibrium effects have large impact on entrepreneurs' entry and firm-size decisions. Efficiency gains are increasing in the quality of financial markets, particularly in their ability to alleviate a financing constraint by providing insurance against idiosyncratic risk.

How did the Financial Crisis affect the Real Interest Rate Dynamics in Europe?

We investigate the effects of the financial crisis on the stationarity of real interest rates in the Euro Area. We use a new unit root test developed by Peseran et al. (2013) that allows for multiple unobserved factors in a panel set up. Our results suggest that while short-term and long-term real interest rates were stationary before the financial crisis, they became nonstationary during the crisis period likely due to persistent risk that characterized financial markets during that time. JEL codes: E43, C23. Keywords: Real interest rates, Euro Area, financial crisis, panel unit root tests, cross-sectional dependence.

Rethinking the effects of financial liberalization

During the last few decades, many emerging markets have lifted restrictions on cross-borderfinancial transactions. The conventional view was that this would allow these countries to: (i)receive capital inflows from advanced countries that would finance higher investment and growth;(ii) insure against aggregate shocks and reduce consumption volatility; and (iii) accelerate thedevelopment of domestic financial markets and achieve a more efficient domestic allocationof capital and better sharing of individual risks. However, the evidence suggests that thisconventional view was wrong.In this paper, we present a simple model that can account for the observed effects of financialliberalization. The model emphasizes the role of imperfect enforcement of domestic debts and theinteractions between domestic and international financial transactions. In the model, financialliberalization might lead to different outcomes: (i) domestic capital flight and ambiguous effectson net capital flows, investment, and growth; (ii) large capital inflows and higher investmentand growth; or (iii) volatile capital flows and unstable domestic financial markets. The modelshows how these outcomes depend on the level of development, the depth of domestic financialmarkets, and the quality of institutions.

Testing calibrated general equilibrium models

This paper illustrates the philosophy which forms the basis of calibrationexercises in general equilibrium macroeconomic models and the details of theprocedure, the advantages and the disadvantages of the approach, with particularreference to the issue of testing ``false'' economic models. We provide anoverview of the most recent simulation--based approaches to the testing problemand compare them to standard econometric methods used to test the fit of non--lineardynamic general equilibrium models. We illustrate how simulation--based techniques can be used to formally evaluate the fit of a calibrated modelto the data and obtain ideas on how to improve the model design using a standardproblem in the international real business cycle literature, i.e. whether amodel with complete financial markets and no restrictions to capital mobility is able to reproduce the second order properties of aggregate savingand aggregate investment in an open economy.

Essays in general equilibrium asset pricing

ABSTRACT : Research in empirical asset pricing has pointed out several anomalies both in the cross section and time series of asset prices, as well as in investors' portfolio choice. This dissertation aims to discover the forces driving some of these "puzzling" asset pricing dynamics and portfolio decisions observed in the financial market. Through the dissertation I construct and study dynamic general equilibrium models of heterogeneous investors in the presence of frictions and evaluate quantitatively their implications for financial-market asset prices and portfolio choice. I also explore the potential roots of puzzles in international finance. Chapter 1 shows that, by introducing jointly endogenous no-default type of borrowing constraints and heterogeneous beliefs in a dynamic general-equilibrium economy, many empirical features of stock return volatility can be reproduced. While most of the research on stock return volatility is empirical, this paper provides a theoretical framework that is able to reproduce simultaneously the cross section and time series stylized facts concerning stock returns and their volatility. In contrast to the existing theoretical literature related to stock return volatility, I don't impose persistence or regimes in any of the exogenous state variables or in preferences. Volatility clustering, asymmetry in the stock return-volatility relationship, and pricing of multi-factor volatility components in the cross section all arise endogenously as a consequence of the feedback between the binding of no-default constraints and heterogeneous beliefs. Chapters 2 and 3 explore the implications of differences of opinion across investors in different countries for international asset pricing anomalies. Chapter 2 demonstrates that several international finance "puzzles" can be reproduced by a single risk factor which captures heterogeneous beliefs across international investors. These puzzles include: (i) home equity preference; (ii) the dependence of firm returns on local and foreign factors; (iii) the co-movement of returns and international capital flows; and (iv) abnormal returns around foreign firm cross-listing events in the local market. These are reproduced in a setup with symmetric information and in a perfectly integrated world with multiple countries and independent processes producing the same good. Chapter 3 shows that by extending this framework to multiple goods and correlated production processes; the "forward premium puzzle" arises naturally as a compensation for the heterogeneous expectations about the depreciation of the exchange rate held by international investors. Chapters 2 and 3 propose differences of opinion across international investors as the potential resolution of several international finance `puzzles'. In a globalized world where both capital and information flow freely across countries, this explanation seems more appealing than existing asymmetric information or segmented markets theories aiming to explain international finance puzzles.

THE ROLE OF INFORMATION TECHNOLOGY IN CREATING SUSTAINABILITY VALUE FOR FINANCIAL INSTITUTIONS IN 2020 : a scenario planning approach

The growing importance of global sustainability issues has been causing many changes to the financial services industry. Facts such as climate change, social development and the financial crisis in 2008 have been making banks reconsider the manner that they consider environmental, social and economic factors in their decision-making process. At the same time, information technology (IT) has been transforming the financial service industry and its fast development has casted doubts on the way it should be managed within an organization. This current changing environment brings a number of uncertainties to the future that cannot be addressed using traditional forecasting techniques. This research investigates how IT can bring value to sustainability in the financial service industry in 2020. Through the use of a scenario planning technique, we analyzed how trends in the current environment (considering the relation between sustainability, financial institutions an IT) can lead to four different future scenarios. Then, we discussed how IT can improve a bank’s sustainability performance, considering the limitations of each scenario.

Financial Slack and Bidding Firms’ Takeover Announcement Stock Returns – an Event Study

Despite the fact that the literature on mergers and acquisitions is extensive, relatively little effort has been made to examine the relationship between the acquiring firms’ financial slack and short-term post-takeover announcement abnormal stock returns. In this study, the case is made that the financial slack of a firm is not only an outcome of past business and financing activities but it also may affect the quality of acquisition decisions. We will hypothesize that the level of financial slack in a firm is negatively associated with the abnormal returns following acquisition announcements because slack reduces managerial discipline over the use of corporate funds and also because it may give rise to managerial self-serving behavior. In this study, financial slack is measured in terms of three financial statements ratios: leverage ratio, cash and equivalents to total assets ratio and free cash flow to total assets ratio. The data used in this paper is collected from two main sources. A list comprising 90 European acquisition announcements is retrieved from Thomson One Banker database. The stock price data and financial statements information for the respective firms is collected using Datastream. Our empirical analysis is two-fold. First, we conduct a two-sample t-test where we find that the most slack-rich firms experience lower abnormal returns than the most slack-poor firms in the event window [-1, +1], significant at 5% risk level. Second, we perform a cross sectional regression for sample firms using three financial statements ratios to explain cumulative abnormal returns (CAR). We find that leverage shows a statistically significant positive relationship with cumulative abnormal returns in event window [-1; +1] (significance 5%). Moreover, cash to total assets ratio showed a weak negative relationship with CAR (significant at 10%) in event window [-1; +1]. We conclude that our hypothesis for the inverse relationship between slack and abnormal returns receives empirical support. Based on the results of the event study we get empirical support for the hypothesis that the capital markets expect the acquisitions undertaken by slack-rich firms to more likely be driven by managerial self-serving behavior and hubris than do those undertaken by slackpoor firms, signaling possible agency problems and behavioral biases.

The Cycle Times of Working Capital: Financial Value Chain Analysis Method

Interest towards working capital management increased among practitioners and researchers because the financial crisis of 2008 caused the deterioration of the general financial situation. The importance of managing working capital effectively increased dramatically during the financial crisis. On one hand, companies highlighted the importance of working capital management as part of short-term financial management to overcome funding difficulties. On the other hand, in academia, it has been highlighted the need to analyze working capital management from a wider perspective namely from the value chain perspective. Previously, academic articles mostly discussed working capital management from a company-centered perspective. The objective of this thesis was to put working capital management in a wider and more academic perspective and present case studies of the value chains of industries as instrumental in theoretical contributions and practical contributions as complementary to theoretical contributions and conclusions. The principal assumption of this thesis is that selffinancing of value chains can be established through effective working capital management. Thus, the thesis introduces the financial value chain analysis method which is employed in the empirical studies. The effectiveness of working capital management of the value chains is studied through the cycle time of working capital. The financial value chain analysis method employed in this study is designed for considering value chain level phenomena. This method provides a holistic picture of the value chain through financial figures. It extends the value chain analysis to the industry level. Working capital management is studied by the cash conversion cycle that measures the length (days) of time a company has funds tied up in working capital, starting from the payment of purchases to the supplier and ending when remittance of sales is received from the customers. The working capital management practices employed in the automotive, pulp and paper and information and communication technology industries have been studied in this research project. Additionally, the Finnish pharmaceutical industry is studied to obtain a deeper understanding of the working capital management of the value chain. The results indicate that the cycle time of working capital is constant in the value chain context over time. The cash conversion cycle of automotive, pulp and paper, and ICT industries are on average 70, 60 and 40 days, respectively. The difference is mainly a consequence of the different cycle time of inventories. The financial crisis of 2008 affected the working capital management of the industries similarly. Both the cycle time of accounts receivable and accounts payable increased between 2008 and 2009. The results suggest that the companies of the automotive, pulp and paper and ICT value chains were not able to self-finance. Results do not indicate the improvement of value chains position in regard to working capital management either. The findings suggest that companies operating in the Finnish pharmaceutical industry are interested in developing their own working capital management, but collaboration with the value chain partners is not considered interesting. Competition no longer occurs between individual companies, but between value chains. Therefore the financial value chain analysis method introduced in this thesis has the potential to support value chains in improving their competitiveness.

Latent Variable Models for Stochastic Discount Factors.

Latent variable models in finance originate both from asset pricing theory and time series analysis. These two strands of literature appeal to two different concepts of latent structures, which are both useful to reduce the dimension of a statistical model specified for a multivariate time series of asset prices. In the CAPM or APT beta pricing models, the dimension reduction is cross-sectional in nature, while in time-series state-space models, dimension is reduced longitudinally by assuming conditional independence between consecutive returns, given a small number of state variables. In this paper, we use the concept of Stochastic Discount Factor (SDF) or pricing kernel as a unifying principle to integrate these two concepts of latent variables. Beta pricing relations amount to characterize the factors as a basis of a vectorial space for the SDF. The coefficients of the SDF with respect to the factors are specified as deterministic functions of some state variables which summarize their dynamics. In beta pricing models, it is often said that only the factorial risk is compensated since the remaining idiosyncratic risk is diversifiable. Implicitly, this argument can be interpreted as a conditional cross-sectional factor structure, that is, a conditional independence between contemporaneous returns of a large number of assets, given a small number of factors, like in standard Factor Analysis. We provide this unifying analysis in the context of conditional equilibrium beta pricing as well as asset pricing with stochastic volatility, stochastic interest rates and other state variables. We address the general issue of econometric specifications of dynamic asset pricing models, which cover the modern literature on conditionally heteroskedastic factor models as well as equilibrium-based asset pricing models with an intertemporal specification of preferences and market fundamentals. We interpret various instantaneous causality relationships between state variables and market fundamentals as leverage effects and discuss their central role relative to the validity of standard CAPM-like stock pricing and preference-free option pricing.

Asymmetric Smiles, Leverage Effects and Structural Parameters.

In this paper, we characterize the asymmetries of the smile through multiple leverage effects in a stochastic dynamic asset pricing framework. The dependence between price movements and future volatility is introduced through a set of latent state variables. These latent variables can capture not only the volatility risk and the interest rate risk which potentially affect option prices, but also any kind of correlation risk and jump risk. The standard financial leverage effect is produced by a cross-correlation effect between the state variables which enter into the stochastic volatility process of the stock price and the stock price process itself. However, we provide a more general framework where asymmetric implied volatility curves result from any source of instantaneous correlation between the state variables and either the return on the stock or the stochastic discount factor. In order to draw the shapes of the implied volatility curves generated by a model with latent variables, we specify an equilibrium-based stochastic discount factor with time non-separable preferences. When we calibrate this model to empirically reasonable values of the parameters, we are able to reproduce the various types of implied volatility curves inferred from option market data.

Empirical Assessment of an Intertemporal Option Pricing Model with Latent variables

This paper assesses the empirical performance of an intertemporal option pricing model with latent variables which generalizes the Hull-White stochastic volatility formula. Using this generalized formula in an ad-hoc fashion to extract two implicit parameters and forecast next day S&P 500 option prices, we obtain similar pricing errors than with implied volatility alone as in the Hull-White case. When we specialize this model to an equilibrium recursive utility model, we show through simulations that option prices are more informative than stock prices about the structural parameters of the model. We also show that a simple method of moments with a panel of option prices provides good estimates of the parameters of the model. This lays the ground for an empirical assessment of this equilibrium model with S&P 500 option prices in terms of pricing errors.

Risk Aversion, Intertemporal Substitution, and Option Pricing

This paper develops a general stochastic framework and an equilibrium asset pricing model that make clear how attitudes towards intertemporal substitution and risk matter for option pricing. In particular, we show under which statistical conditions option pricing formulas are not preference-free, in other words, when preferences are not hidden in the stock and bond prices as they are in the standard Black and Scholes (BS) or Hull and White (HW) pricing formulas. The dependence of option prices on preference parameters comes from several instantaneous causality effects such as the so-called leverage effect. We also emphasize that the most standard asset pricing models (CAPM for the stock and BS or HW preference-free option pricing) are valid under the same stochastic setting (typically the absence of leverage effect), regardless of preference parameter values. Even though we propose a general non-preference-free option pricing formula, we always keep in mind that the BS formula is dominant both as a theoretical reference model and as a tool for practitioners. Another contribution of the paper is to characterize why the BS formula is such a benchmark. We show that, as soon as we are ready to accept a basic property of option prices, namely their homogeneity of degree one with respect to the pair formed by the underlying stock price and the strike price, the necessary statistical hypotheses for homogeneity provide BS-shaped option prices in equilibrium. This BS-shaped option-pricing formula allows us to derive interesting characterizations of the volatility smile, that is, the pattern of BS implicit volatilities as a function of the option moneyness. First, the asymmetry of the smile is shown to be equivalent to a particular form of asymmetry of the equivalent martingale measure. Second, this asymmetry appears precisely when there is either a premium on an instantaneous interest rate risk or on a generalized leverage effect or both, in other words, whenever the option pricing formula is not preference-free. Therefore, the main conclusion of our analysis for practitioners should be that an asymmetric smile is indicative of the relevance of preference parameters to price options.

The Shape of the Risk Premium: Evidence from a Semiparametric Garch Model.

We examine the relationship between the risk premium on the S&P 500 index return and its conditional variance. We use the SMEGARCH - Semiparametric-Mean EGARCH - model in which the conditional variance process is EGARCH while the conditional mean is an arbitrary function of the conditional variance. For monthly S&P 500 excess returns, the relationship between the two moments that we uncover is nonlinear and nonmonotonic. Moreover, we find considerable persistence in the conditional variance as well as a leverage effect, as documented by others. Moreover, the shape of these relationships seems to be relatively stable over time.