Fiscal policy and interest rates: the role of financial and economic integration

It is commonly believed that a fiscal expansion raises interest rates. However, these crowding out effects of deficits have been found to be small or non-existent. One explanation is that financial integration offsets interest rate differentials on globalised bond markets. This paper measures the degree of integration of government bond markets, using spatial modelling techniques to take this spillover on financial markets into account. Our main finding is that the crowding out effect on domestic interest rates is significant, but is reduced by spillover across borders. This spillover is important in major crises or in periods of coordinated policy actions. This result is generally robust to various measures of cross-country linkages. We find spillover to be much stronger among EU countries.

Model for interevent times with long tails and multifractality in human communications: An application to financial trading

Social, technological, and economic time series are divided by events which are usually assumed to be random, albeit with some hierarchical structure. It is well known that the interevent statistics observed in these contexts differs from the Poissonian profile by being long-tailed distributed with resting and active periods interwoven. Understanding mechanisms generating consistent statistics has therefore become a central issue. The approach we present is taken from the continuous-time random-walk formalism and represents an analytical alternative to models of nontrivial priority that have been recently proposed. Our analysis also goes one step further by looking at the multifractal structure of the interevent times of human decisions. We here analyze the intertransaction time intervals of several financial markets. We observe that empirical data describe a subtle multifractal behavior. Our model explains this structure by taking the pausing-time density in the form of a superstatistics where the integral kernel quantifies the heterogeneous nature of the executed tasks. A stretched exponential kernel provides a multifractal profile valid for a certain limited range. A suggested heuristic analytical profile is capable of covering a broader region.

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

Innovación, financiación y mercados financieros : análisis de las relaciones entre inversión en I+D, estructura de capital y señalización contable

Aquest treball té com a objectiu determinar l'existència de restriccions en el finançament de projectes empresarials de recerca i desenvolupament (R+D) i analitzar-ne les causes. Els resultats de la investigació mostren els fets següents: en primer lloc, hi ha restriccions financeres per a la realització d'inversions en R+D i es manifesten en la necessitat de les empreses de recórrer a recursos interns i a fons aliens a curt termini; en segon lloc, les restriccions esmentades fonamentalment sorgeixen a causa de dos factors, el desequilibri entre les característiques econòmiques de les inversions d'R+D i el comportament dels agents finançadors en els mercats de capitals, i l'existència d'asimetries d'informació entre agents gestors i finançadors; finalment, en tercer lloc, la formulació per part de les empreses de més informació comptable sobre l'R+D desenvolupada comporta la millora de la valoració de l'empresa en els mercats financers i, per tant, l'assignació de fons als processos d'innovació.

Study and implementation of some quantitative trading models

Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.

Free Flows, Limited Diversification: Explaining the Fall and Rise of Stock Market Correlations, 1890-2001

Using a new dataset on capital account openness, we investigate why equity return correlations changed over the last century. Based on a new, long-run dataset on capital account regulations in a group of 16 countries over the period 1890-2001, we show that correlations increase as financial markets are liberalized. These findings are robust to controlling for both the Forbes-Rigobon bias and global averages in equity return correlations. We test the robustness of our conclusions, and show that greater synchronization of fundamentals is not the main cause of increasing correlations. These results imply that the home bias puzzle may be smaller than traditionally claimed.

Institutions, Public Debt and Foreign Finance

We study the role of domestic financial institutions in sustaining capital flows to the private and public sector of a country whose government can default on its debt. As in recent public debt crises, in our model public defaults weaken banks' balance sheets, disrupting domestic financial markets. This effect leads to a novel complementarity between private capital inflows and public borrowing, where the former sustain the latter by boosting the government's cost of default. Our key message is that, by shaping the direction of private capital flows, financial institutions determine whether financial integration improves or reduces government discipline. We explore the implications of this complementarity for financial liberalization and debt-financed bailouts of banks. We present some evidence consistent with complementarity.

Theoretical notes on bubbles and the current crisis

We explore a view of the crisis as a shock to investor sentiment that led to the collapse of abubble or pyramid scheme in financial markets. We embed this view in a standard model of thefinancial accelerator and explore its empirical and policy implications. In particular, we show howthe model can account for: (i) a gradual and protracted expansionary phase followed by a suddenand sharp recession; (ii) the connection (or lack of connection!) between financial and real economicactivity and; (iii) a fast and strong transmission of shocks across countries. We also use the modelto explore the role of fiscal policy.

Money doctors

We present a new model of money management, in which investors delegate portfolio management to professionals based not only on performance, but also on trust. Trust in the manager reduces an investor's perception of the riskiness of a given investment, and allows managers to charge higher fees to investors who trust them more. Money managers compete for investor funds by setting their fees, but because of trust the fees do not fall to costs. In the model, 1) managers consistently underperform the market net of fees but investors still prefer to delegate money management to taking risk on their own, 2) fees involve sharing of expected returns between managers and investors, with higher fees in riskier products, 3) managers pander to investors when investors exhibit biases in their beliefs, and do not correct misperceptions, and 4) despite long run benefits from better performance, the profits from pandering to trusting investors discourage managers from pursuing contrarian strategies relative to the case with no trust. We show how trust-mediated money management renders arbitrage less effective, and may help destabilize financial markets.

On the impact of leverage constraints on asset prices and trading volume

Researchers have used stylized facts on asset prices and trading volumein stock markets (in particular, the mean reversion of asset returnsand the correlations between trading volume, price changes and pricelevels) to support theories where agents are not rational expected utilitymaximizers. This paper shows that this empirical evidence is in factconsistent with a standard infite horizon perfect information expectedutility economy where some agents face leverage constraints similar tothose found in todays financial markets. In addition, and in sharpcontrast to the theories above, we explain some qualitative differencesthat are observed in the price-volume relation on stock and on futuresmarkets. We consider a continuous-time economy where agents maximize theintegral of their discounted utility from consumption under both budgetand leverage con-straints. Building on the work by Vila and Zariphopoulou(1997), we find a closed form solution, up to a negative constant, for theequilibrium prices and demands in the region of the state space where theconstraint is non-binding. We show that, at the equilibrium, stock holdingsvolatility as well as its ratio to stock price volatility are increasingfunctions of the stock price and interpret this finding in terms of theprice-volume relation.

Insider Trading and Real Investment

In this paper I analyze the effects of insider trading on real investmentand the insurance role of financial markets. There is a single entrepreneurwho, at a first stage, chooses the level of investment in a risky business.At the second stage, an asset with random payoff is issued and then the entrepreneurreceives some privileged information on the likely realization of productionreturn. At the third stage, trading occurs on the asset market, where theentrepreneur faces the aggregate demand coming from a continuum of rationaluniformed traders and some noise traders. I compare the equilibrium withinsider trading (when the entrepreneur trades on her inside information in theasset market) with the equilibrium in the same market without insider trading. Ifind that permitting insider trading tends to decrease the level of realinvestment. Moreover, the asset market is thinner and the entrepreneur's netsupply of the asset and the hedge ratio are lower, although the asset priceis more informative and volatile.

Insuring California earthquakes and the role for catastrophe bonds

The 1994 Northridge earthquake sent ripples to insurance conpanieseverywhere. This was one in a series of natural disasters such asHurricane Andrew which together with the problems in Lloyd's of Londonhave insurance companies running for cover. This paper presents a calibration of the U.S. economy in a model with financial markets forinsurance derivatives that suggests the U.S. economy can deal with thedamage of natural catastrophe far better than one might think.

Crises and growth: A re-evaluation

We address the question of whether growth and welfare can be higher in crisis prone economies. First, we show that there is a robust empirical link between per-capita GDP growth and negative skewness of credit growth across countries with active financial markets. That is, countries that have experienced occasional crises have grown on average faster than countries with smooth credit conditions. We then present a two-sector endogenous growth model in which financial crises can occur, and analyze the relationship between financial fragility and growth. The underlying credit market imperfections generateborrowing constraints, bottlenecks and low growth. We show that under certain conditions endogenous real exchange rate risk arises and firms find it optimal to take on credit risk in the form of currency mismatch. Along such a risky path average growth is higher, but self-fulfilling crises occur occasionally. Furthermore, we establish conditions under which the adoption of credit risk is welfare improving and brings the allocation nearer to the Pareto optimal level. The design of the model is motivated by several features of recent crises: credit risk in the form of foreign currency denominated debt; costly crises that generate firesales and widespread bankruptcies; and asymmetric sectorial responses, wherethe nontradables sector falls more than the tradables sector in the wake of crises.

On the impact of fundamentals, liquidity and coordination on market stability

We develop a coordination game to model interactions betweenfundamentals and liquidity during unstable periods in financial markets.We then propose a flexible econometric framework for estimationof the model and analysis of its quantitative implications. The specificempirical application is carry trades in the yen dollar market, includingthe turmoil of 1998. We find a generally very deep market, withlow information disparities amongst agents. We observe occasionallyepisodes of market fragility, or turmoil with up by the escalator, downby the elevator patterns in prices. The key role of strategic behaviorin the econometric model is also confirmed.

Stock returns, term structure, inflation and real activity: An international perspective

This paper analyses the empirical interdependences among assetreturns, real activity and inflation from a multicountry and internationalpoint of view. We find that nominal stock returns are significantly relatedto inflation only in the US, that the US term structure of interest ratespredicts both domestic and foreign inflation rates while foreign termstructures do not have this predictive power and that innovations in inflationand exchange rates induce insignificant responses of real and financialvariables. An interpretation of the dynamics and some policy implicationsof the results are provided.