1,720,977 research outputs found
Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives
Full text linkMany industries are exposed to weather risk which they can transfer on financial markets via weather derivatives. Equilibrium models based on partial market clearing became a useful tool for pricing such kind of financial instruments. In a multi-period equilibrium pricing model agents rebalance their portfolio of weather bonds and a risk free asset in each period such that they maximize the expected utility of their incomes constituted by possibly weather dependent profits and payoffs of portfolio positions. We extend the model to a multisite version and apply it to pricing rainfall derivatives for Chinese provinces. By simulating realistic market conditions with two agent types, farmers with profits highly exposed to weather risk and a financial investor diversifying her financial portfolio, we obtain equilibrium prices for weather derivatives on cumulative monthly rainfall. Dynamic portfolio optimization under market clearing and utility indifference of these representative agents determines equilibrium quantity and price for rainfall derivatives.rainfall derivatives, equilibrium pricing, space-time Markov model
Difference based Ridge and Liu type Estimators in Semiparametric Regression Models
Full text linkWe consider a difference based ridge regression estimator and a Liu type estimator of the regression parameters in the partial linear semiparametric regression model, y = Xβ + f + ε. Both estimators are analysed and compared in the sense of mean-squared error. We consider the case of independent errors with equal variance and give conditions under which the proposed estimators are superior to the unbiased difference based estimation technique. We extend the results to account for heteroscedasticity and autocovariance in the error terms. Finally, we illustrate the performance of these estimators with an application to the determinants of electricity consumption in Germany.Difference based estimator; Differencing estimator, Differencing matrix, Liu estimator, Liu type estimator, Multicollinearity, Ridge regression estimator, Semiparametric model
The Law of Attraction: Bilateral Search and Horizontal Heterogeneity
Full text linkWe study a matching model with heterogeneous agents, nontransferable utility and search frictions. Agents differ along a horizontal dimension (e.g. taste) and a vertical dimension (e.g. income). Agents’ preferences coincide only in the vertical dimension. This approach introduces individual preferences in this literature as seems suitable in applications like labor markets (e.g. regional preferences). We analyze how the notion of assortativeness generalizes to integration or segregation outcomes depending on search frictions. Contrary to results from the purely vertical analysis, here, agents continuously adjust their reservation utility strategies to changing search frictions. The model is easily generalizable in the utility specification, the distribution of taste-related payoffs and the number of vertical types. Extreme utility specifications can be treated as a case of horizontal heterogeneity only.Matching, Horizontal Differentiation , Marriage Markets
How Computational Statistics Became the Backbone of Modern Data Science
Full text linkThis first chapter serves as an introduction and overview for a collection of articles surveying the current state of the science of computational statistics. Earlier versions of most of these articles appeared in the first edition of Handbook of Computational Statistics: Concepts and Methods, published in 2004. There have been advances in all of the areas of computational statistics, so we feel that it is time to revise and update this Handbook. This introduction is a revision of the introductory chapter of the first edition.Discrete time series models, continuous time diffusion models, models with jumps, stochastic volatility, GARCH
Estimation of the characteristics of a Lévy process observed at arbitrary frequency
Full text linkA Lévy process is observed at time points of distance Δ until time T. We construct an estimator of the Lévy-Khinchine characteristics of the process and derive optimal rates of convergence simultaneously in T and Δ. Thereby, we encompass the usual low- and high-frequency assumptions and obtain also asymptotics in the mid-frequency regime.Jump process, Lévy measure, deconvolution problem, statistical inverse problem
Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data
Full text linkIn this paper, we provide new empirical evidence on order submission activity and price impacts of limit orders at NASDAQ. Employing NASDAQ TotalView-ITCH data, we find that market participants dominantly submit limit orders with sizes equal to a round lot. Most limit orders are canceled almost immediately after submission if not getting executed. Moreover, only very few market orders walk through the book, i.e., directly move the best ask or bid quote. Estimates of impulse-response functions on the basis of a cointegrated VAR model for quotes and market depth allow us to quantify the market impact of incoming limit orders. We propose a method to predict the optimal size of a limit order conditional on its position in the book and a given fixed level of expected market impact.price impact, limit order, impulse response function, cointegration, optimal order size
The economics of TARGET2 balances
Full text linkIt has recently been argued that intra-eurosystem claims and liabilities in the form of TARGET2 balances would raise fundamental issues within the European monetary union. This article provides a framework for the economic analysis of TARGET2 balances and discusses the key arguments behind this recent debate. The analysis is conducted within a system of financial accounts in which TARGET2 balances can arise either due to current account transactions or cross-border capital flows. It is argued that the recent volatility of TARGET2 balances reflects capital flow movements, while the previously prevailing current account positions did not find a strong reflection in TARGET2 balances. Some recent statements regarding TARGET2 appear to be due to a failure to distinguish between the monetary base (a central bank liability concept) and the liquidity deficit of the banking system vis-à-vis the central bank (a central bank asset concept). Furthermore, the article highlights the importance of TARGET2 for the stability of the euro area and points out that the proposal to limit the size of TARGET2 liabilities essentially contradicts the idea of a monetary union.TARGET2, central bank balance sheet, liquidity deficit, financial crisis
Asymptotics of Asynchronicity
Full text linkIn this article we focus on estimating the quadratic covariation of continuous semimartingales from discrete observations that take place at asynchronous observation times. The Hayashi-Yoshida estimator serves as synchronized realized covolatility for that we give our own distinct illustration based on an iterative synchronization algorithm. We consider high-frequency asymptotics and prove a feasible stable central limit theorem. The characteristics of non-synchronous observation schemes affecting the asymptotic variance are captured by a notion of asymptotic covariations of times. These are precisely illuminated and explicitly deduced for the important case of independent time-homogeneous Poisson sampling.non-synchronous observations, quadratic covariation, Hayashi-Yoshida estimator, stable limit theorem, asymptotic distribution
Pointwise adaptive estimation for quantile regression
Full text linkA nonparametric procedure for quantile regression, or more generally nonparametric M-estimation, is proposed which is completely data-driven and adapts locally to the regularity of the regression function. This is achieved by considering in each point M-estimators over different local neighbourhoods and by a local model selection procedure based on sequential testing. Non-asymptotic risk bounds are obtained, which yield rate-optimality for large sample asymptotics under weak conditions. Simulations for different univariate median regression models show good finite sample properties, also in comparison to traditional methods. The approach is the basis for denoising CT scans in cancer research.M-estimation, median regression, robust estimation, local model selection, unsupervised learning, local bandwidth selection, median filter, Lepski procedure, minimax rate, image denoising
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