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Forecasting credit migration matrices with business cycle effects—a model comparison
credit risk credit VaR forecasting transition matrices
2011/8/23
Migration matrices are considered a major determinant for credit risk management. They are widely used for credit value-at-risk determination, portfolio management or derivative pricing. It is well kn...
Modeling and forecasting volatility in global food commodity prices
volatility forecast fat-tail distribution food commodities
2014/2/27
To capture the volatility in the global food commodity prices, we employed two competing models, the thin tailed the normal distribution, and the fat-tailed Student t-distribution models. Results base...
Forecasting the Quantiles of Daily Equity Returns Using Realized Volatility: Evidence from the Czech Stock Market
Intraday data heterogeneous autoregressive model
2010/12/6
In this study, we evaluate the quantile forecasts of the daily equity returns on three of the most liquid stocks traded on the Prague Stock Exchange. We follow the recent findings that consider the po...
Revised capital assets pricing model: an improved model for forecasting risk and return
Revised Capital Assets Pricing Model Risk Return
2010/10/18
This study's aim is to examine a new version of capital assets pricing model which is
called Revised Capital Assets Pricing Model (R-CAPM) in Tehran Stock Exchange (TSE).
According to Markowitz theo...
A Dynamical Model for Forecasting Operational Losses
Operational Risk Dynamical Systems Value at Risk
2010/10/21
A novel dynamical model for the study of operational risk in banks and suitable for the calculation of the Value at Risk (VaR) is proposed. The equation of motion takes into account the interactions a...
A New Forecasting Model for USD/CNY Exchange Rate
Nonlinearity Functional-coefficient regression model GARCH model Index model Quantile regression
2011/4/2
his paper models the return series of USD/CNY exchange rate by considering the conditional mean and conditional volatility simultaneously. An index type functional-coefficient model is adopted to mode...
Term Structure Forecasting: No-arbitrage Restrictions Versus Large Information set
Yield curve terms tructure of interest rates forecasting large data set factor models
2011/4/1
This paper addresses the issue of forecasting the term structure.We provide a unified state-space modeling framework that encompasses different existing discrete-time yield curve models.
The International Journal of Forecasting is the leading journal in its field. It is the official publication of the International Institute of Forecasters (IIF) and shares its aims and scope. More inf...
Forecasting Model for Crude Oil Price Using Artificial Neural Networks and Commodity Futures Prices
Crude Oil Future Price ANN Prediction Models
2010/11/1
This paper presents a model based on multilayer feedforward neural network to forecast crude oil spot price direction in the short-term, up to three days ahead. A great deal
of attention was paid on ...
Forecasting with time-varying vector autoregressive models
time-varying vector autoregressive models
2010/12/13
The purpose of this paper is to propose a time-varying vector autoregressive model (TV-VAR) for forecasting multivariate time series. The model is casted into a state-space form that allows flexible ...
Forecasting volatility with the multifractal random walk model
Forecasting volatility the multifractal random walk model
2010/12/13
We study the problem of forecasting volatility for the multifractal random walk model. In order to avoid the ill posed problem of estimating the correlation length T of the model, we introduce a limit...
Demand forecasting for companies with many branches, low sales numbers per product, and non-recurring orderings
Demand forecasting companies branches low sales numbers product non-recurring orderings
2010/12/17
We propose the new Top-Dog-Index to quantify the historic deviation of the supply data of many small branches for a commodity group from sales data. On the one hand, the common parametric assumptions ...
A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series
Multistep forecasts Var forecasts Forecast comparisons
2014/3/18
‘‘Iterated’’ multiperiod-ahead time series forecasts are made using a one-period ahead model, iterated forward for the desired number of periods, whereas ‘‘direct’’ forecasts are made using a horizon-...
Forecasting Output and Inflation: The Role of Asset Prices
Forecasting Output Inflation Asset Prices
2014/3/18
Because asset prices are forward-looking, they constitute a class of potentially use-ful predictors of inflation and output growth. The premise that interest rates and asset prices contain usefu...
Forecasting Using Principal Components From a Large Number of Predictors
Factor models Forecasting Principal components
2014/3/18
This article considers forecasting a single time series when there are many predictors (N) and time series observations (T). When the data follow an approximate factor model, the predictors can be sum...