848 resultados para Intraday volatility
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This paper has three objectives. First, it aims at revealing the logic of interest rate setting pursued by monetary authorities of 12 new EU members. Using estimation of an augmented Taylor rule, we find that this setting was not always consistent with the official monetary policy. Second, we seek to shed light on the inflation process of these countries. To this end, we carry out an estimation of an open economy Philips curve (PC). Our main finding is that inflation rates were not only driven by backward persistency but also held a forward-looking component. Finally, we assess the viability of existing monetary arrangements for price stability. The analysis of the conditional inflation variance obtained from GARCH estimation of PC is used for this purpose. We conclude that inflation targeting is preferable to an exchange rate peg because it allowed decreasing the inflation rate and anchored its volatility.
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This paper develops a new test of true versus spurious long memory, based on log-periodogram estimation of the long memory parameter using skip-sampled data. A correction factor is derived to overcome the bias in this estimator due to aliasing. The procedure is designed to be used in the context of a conventional test of significance of the long memory parameter, and composite test procedure described that has the properties of known asymptotic size and consistency. The test is implemented using the bootstrap, with the distribution under the null hypothesis being approximated using a dependent-sample bootstrap technique to approximate short-run dependence following fractional differencing. The properties of the test are investigated in a set of Monte Carlo experiments. The procedure is illustrated by applications to exchange rate volatility and dividend growth series.
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We examine the impact of real oil price shocks on labor market flows in the U.S. We first use smooth transition regression (STR) models to investigate to what extent oil prices can be considered as a driving force of labor market fluctuations. Then we develop and calibrate a modified version of Pissarides' (2000) model with energy costs, which we simulate in response to shocks mimicking the behavior of the actual oil price shocks. We find that (i) these shocks are an important driving force of job market flows; (ii) the job finding probability is the main transmission mechanism of such shocks; and (iii) they bring a new amplification mechanism for the volatility and should thus be seen as complementary of labor productivity shocks. Overall we conclude that shocks in oil prices cannot be neglected in explaining cyclical labor adjustments in the U.S.
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This paper studies the relationship between investor protection, entrepreneurial risk taking and income inequality. In the presence of market frictions, better protection makes investors more willing to take on entrepreneurial risk when lending to firms, thereby improving the degree of risk sharing between financiers and entrepreneurs. On the other hand, by increasing risk sharing, investor protection also induces more firms to undertake risky projects. By increasing entrepreneurial risk taking, it raises income dispersion. By reducing the risk faced by entrepreneurs, it reduces income volatility. As a result, investor protection raises income inequality to the extent that it fosters risk taking, while it reduces it for a given level of risk taking. Empirical evidence from a panel of forty-five countries spanning the period 1976-2000 supports the predictions of the model.
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This article analyses stability and volatility of party preferences using data from the Swiss Household-Panel (SHP), which, for the first time, allow studying transitions and stability of voters over several years in Switzerland. Analyses cover the years 1999- 2007 and systematically distinguish changes between party blocks and changes within party blocks. The first part looks at different patterns of change, which show relatively high volatility. The second part tests several theories on causes of such changes applying a multinomial random-effects model. Results show that party preferences stabilise with their duration and with age and that the electoral cycle, political sophistication, socio-structural predispositions, the household-context as well as party size and the number of parties each explain part of electoral volatility. Different results for withinand between party-block changes underlie the importance of that differentiation.
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Abstract: We scrutinize the realized stock-bond correlation based upon high frequency returns. We use quantile regressions to pin down the systematic variation of the extreme tails over their economic determinants. The correlation dependence behaves differently when the correlation is large negative and large positive. The important explanatory variables at the extreme low quantile are the short rate, the yield spread, and the volatility index. At the extreme high quantile the bond market liquidity is also important. The empirical fi ndings are only partially robust to using less precise measures of the stock-bond correlation. The results are not caused by the recent financial crisis. Keywords: Extreme returns; Financial crisis; Realized stock-bond correlation; Quantile regressions; VIX. JEL Classifi cations: C22; G01; G11; G12
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Abstract: We analyze the realized stock-bond correlation. Gradual transitions between negative and positive stock-bond correlation is accommodated by the smooth transition regression (STR) model. The changes in regime are de ned by economic and financial transition variables. Both in sample and out-of- sample results document that STR models with multiple transition variables outperform STR models with a single transition variable. The most important transition variables are the short rate, the yield spread, and the VIX volatility index. Keywords: realized correlation; smooth transition regressions; stock-bond correlation; VIX index JEL Classifi cations: C22; G11; G12; G17
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The Stability and Growth Pact (SGP) was established to govern discretionary fiscal policy in the European Monetary Union. This article studies the effects created when there is uncertainty about the members’ commitment to respecting the established deficit limits in the SGP. We will show that, even if countries respect the SGP deficit ceiling, the presence of uncertainty about their compliance will bring about higher volatility in key economic variables, which could, in turn, affect unemployment and growth negatively. This finding shows that it is important to reduce uncertainty about the members’ commitment towards the SGP. Keywords: fiscal policy rules, monetary union, Stability and Growth Pact, uncertainty, commitment. JEL No.: E63, F55, H62, H87
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Syrian dry areas have been for several millennia a place of interaction between human populations and the environment. If environmental constraints and heterogeneity condition the human occupation and exploitation of resources, socio-political, economic and historical elements play a fundamental role. Since the late 1980s, Syrian dry areas are viewed as suffering a serious water crisis, due to groundwater overdraft. The Syrian administration and international development agencies believe that groundwater overexploitation is also leading to a decline of agricultural activities and to poverty increase. Action is thus required to address these problems.However, the overexploitation diagnosis needs to be reviewed. The overexploitation discourse appears in the context of Syria's opening to international organizations and to the market economy. It echoes the international discourse of "global water crisis". The diagnosis is based on national indicators recycling old Soviet data that has not been updated. In the post-Soviet era, the Syrian national water policy seems to abandon large surface water irrigation projects in favor of a strategy of water use rationalization and groundwater conservation in crisis regions, especially in the district of Salamieh.This groundwater conservation policy has a number of inconsistencies. It is justified for the administration and also probably for international donors, since it responds to an indisputable environmental emergency. However, efforts to conserve water are anecdotal or even counterproductive. The water conservation policy appears a posteriori as an extension of the national policy of food self-sufficiency. The dominant interpretation of overexploitation, and more generally of the water crisis, prevents any controversary approach of the status of resources and of the agricultural system in general and thus destroys any attempt to discuss alternatives with respect to groundwater management, allocation, and their inclusion in development programs.A revisited diagnosis of the situation needs to take into account spatial and temporal dimensions of the groundwater exploitation and to analyze the co-evolution of hydrogeological and agricultural systems. It should highlight the adjustments adopted to cope with environmental and economic variability, changes of water availability and regulatory measures enforcements. These elements play an important role for water availability and for the spatial, temporal, sectoral allocation of water resource. The groundwater exploitation in the last century has obviously had an impact on the environment, but the changes are not necessarily catastrophic.The current groundwater use in central Syria increases the uncertainty by reducing the ability of aquifers to buffer climatic changes. However, the climatic factor is not the only source of uncertainty. The high volatility of commodity prices, fuel, land and water, depending on the market but also on the will (and capacity) of the Syrian State to preserve social peace is a strong source of uncertainty. The research should consider the whole range of possibilities and propose alternatives that take into consideration the risks they imply for the water users, the political will to support or not the local access to water - thus involving a redefinition of the economic and social objectives - and finally the ability of international organizations to reconsider pre-established diagnoses.
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Executive Summary The first essay of this dissertation investigates whether greater exchange rate uncertainty (i.e., variation over time in the exchange rate) fosters or depresses the foreign investment of multinational firms. In addition to the direct capital financing it supplies, foreign investment can be a source of valuable technology and know-how, which can have substantial positive effects on a host country's economic growth. Thus, it is critically important for policy makers and central bankers, among others, to understand how multinationals base their investment decisions on the characteristics of foreign exchange markets. In this essay, I first develop a theoretical framework to improve our knowledge regarding how the aggregate level of foreign investment responds to exchange rate uncertainty when an economy consists of many firms, each of which is making decisions. The analysis predicts a U-shaped effect of exchange rate uncertainty on the total level of foreign investment of the economy. That is, the effect is negative for low levels of uncertainty and positive for higher levels of uncertainty. This pattern emerges because the relationship between exchange rate volatility and 'the probability of investment is negative for firms with low productivity at home (i.e., firms that find it profitable to invest abroad) and the relationship is positive for firms with high productivity at home (i.e., firms that prefer exporting their product). This finding stands in sharp contrast to predictions in the existing literature that consider a single firm's decision to invest in a unique project. The main contribution of this research is to show that the aggregation over many firms produces a U-shaped pattern between exchange rate uncertainty and the probability of investment. Using data from industrialized countries for the period of 1982-2002, this essay offers a comprehensive empirical analysis that provides evidence in support of the theoretical prediction. In the second essay, I aim to explain the time variation in sovereign credit risk, which captures the risk that a government may be unable to repay its debt. The importance of correctly evaluating such a risk is illustrated by the central role of sovereign debt in previous international lending crises. In addition, sovereign debt is the largest asset class in emerging markets. In this essay, I provide a pricing formula for the evaluation of sovereign credit risk in which the decision to default on sovereign debt is made by the government. The pricing formula explains the variation across time in daily credit spreads - a widely used measure of credit risk - to a degree not offered by existing theoretical and empirical models. I use information on a country's stock market to compute the prevailing sovereign credit spread in that country. The pricing formula explains a substantial fraction of the time variation in daily credit spread changes for Brazil, Mexico, Peru, and Russia for the 1998-2008 period, particularly during the recent subprime crisis. I also show that when a government incentive to default is allowed to depend on current economic conditions, one can best explain the level of credit spreads, especially during the recent period of financial distress. In the third essay, I show that the risk of sovereign default abroad can produce adverse consequences for the U.S. equity market through a decrease in returns and an increase in volatility. The risk of sovereign default, which is no longer limited to emerging economies, has recently become a major concern for financial markets. While sovereign debt plays an increasing role in today's financial environment, the effects of sovereign credit risk on the U.S. financial markets have been largely ignored in the literature. In this essay, I develop a theoretical framework that explores how the risk of sovereign default abroad helps explain the level and the volatility of U.S. equity returns. The intuition for this effect is that negative economic shocks deteriorate the fiscal situation of foreign governments, thereby increasing the risk of a sovereign default that would trigger a local contraction in economic growth. The increased risk of an economic slowdown abroad amplifies the direct effect of these shocks on the level and the volatility of equity returns in the U.S. through two channels. The first channel involves a decrease in the future earnings of U.S. exporters resulting from unfavorable adjustments to the exchange rate. The second channel involves investors' incentives to rebalance their portfolios toward safer assets, which depresses U.S. equity prices. An empirical estimation of the model with monthly data for the 1994-2008 period provides evidence that the risk of sovereign default abroad generates a strong leverage effect during economic downturns, which helps to substantially explain the level and the volatility of U.S. equity returns.
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We extend PML theory to account for information on the conditional moments up to order four, but without assuming a parametric model, to avoid a risk of misspecification of the conditional distribution. The key statistical tool is the quartic exponential family, which allows us to generalize the PML2 and QGPML1 methods proposed in Gourieroux et al. (1984) to PML4 and QGPML2 methods, respectively. An asymptotic theory is developed. The key numerical tool that we use is the Gauss-Freud integration scheme that solves a computational problem that has previously been raised in several fields. Simulation exercises demonstrate the feasibility and robustness of the methods [Authors]
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Among the PAH class of compounds, high molecular weight PAH are now considered as relevant cancer inducers, but not all of them have the same biological activity. However, their analysis is difficult, mainly due to the presence of numerous isomers and due to their low volatility. Retention indices (Ri) for 13 dibenzopyrenes and homologues were determined by high-resolution capillary gas chromatography (GC) with four different stationary phases: a 5% phenyl-substituted methylpolysiloxane column (DB-5 ms), a 35% phenyl-substituted methylpolysiloxane column (BPX-35), a 50% phenyl-substituted methylpolysiloxane column (BPX-50), and a 35% trifluoropropylmethyl polysiloxane stationary phase (Rtx-200). Correlations for retention on each phase were investigated by using 8 independent molecular descriptors. Ri has been shown to be linearly correlated to PAH volume, polarisability alpha, Hückel-pi energy on the four examined columns. Ionisation potential Ip is a fourth variable which improves the regression model for DB-5ms, BPX-35, and BPX-50 column. Correlation coefficients ranging from r2 = 0.935 to r2 = 0.952 are then observed. Application of these indices to the identification and quantification of PAH with MW 302 in certified diesel particulate matter SRM 1650a is presented and discussed. [Authors]
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One of the major problems when using non-dedicated volunteer resources in adistributed network is the high volatility of these hosts since they can go offlineor become unavailable at any time without control. Furthermore, the use ofvolunteer resources implies some security issues due to the fact that they aregenerally anonymous entities which we know nothing about. So, how to trustin someone we do not know?.Over the last years an important number of reputation-based trust solutionshave been designed to evaluate the participants' behavior in a system.However, most of these solutions are addressed to P2P and ad-hoc mobilenetworks that may not fit well with other kinds of distributed systems thatcould take advantage of volunteer resources as recent cloud computinginfrastructures.In this paper we propose a first approach to design an anonymous reputationmechanism for CoDeS [1], a middleware for building fogs where deployingservices using volunteer resources. The participants are reputation clients(RC), a reputation authority (RA) and a certification authority (CA). Users needa valid public key certificate from the CA to register to the RA and obtain thedata needed to participate into the system, as now an opaque identifier thatwe call here pseudonym and an initial reputation value that users provide toother users when interacting together. The mechanism prevents not only themanipulation of the provided reputation values but also any disclosure of theusers' identities to any other users or authorities so the anonymity isguaranteed.
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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.
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This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that they observe (which may be distinct for different sets of agents) to form beliefs about unknown aspects of the true model of the economy, use their beliefs to decide on actions, and revise these beliefs through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of our model and derive its policy recommendations, particularly with respect to central bank communications. We demonstrate that two-sided learning can generate substantial increases in volatility and persistence, and alter the behavior of the variables in the model in a signifficant way. Our simulations do not converge to a symmetric rational expectations equilibrium and we highlight one source that invalidates the convergence results of Marcet and Sargent (1989). Finally, we identify a novel aspect of central bank communication in models of learning: communication can be harmful if the central bank's model is substantially mis-specified