nep-rmg New Economics Papers
on Risk Management
Issue of 2005‒12‒20
five papers chosen by
Stan Miles
York University

  1. Do European Stock Markets Affect Latin American Stock Markets? By Andrés Rivas; Rahul Verma; Antonio Rodriguez; Pedro H. Albuquerque
  2. Business failure prediction: simple-intuitive models versus statistical models By Ooghe, H.; Spaenjers, C.; Pieter vandermoere
  3. Intraday Value at Risk (IVaR) Using Tick-by-Tick Data with Application to the Toronto Stock Exchange By Georges Dionne; Pierre Duchesne; Maria Pacurar
  4. The Myth of Long-Horizon Predictability By Jacob Boudoukh; Matthew Richardson; Robert Whitelaw
  5. Fuzzy Transfer Pricing World: On the Analysis of Transfer Pricing with Fuzzy Logic Techniques By Tucha Thomas; Brem Markus

  1. By: Andrés Rivas (Texas A&M International University); Rahul Verma (University of Houston, Downtown); Antonio Rodriguez (Texas A&M International University); Pedro H. Albuquerque (Texas A&M International University)
    Abstract: In this study, we examine the response of Latin American stock markets to movements in European stock market. Our results vary depending on the openness of the country in terms of international trade. We find evidence that Latin American stock markets are responsive to changes in the stock market from Spain. Additionally, during the second and third- periods, Spain has much stronger ties with Brazil, and this might explain why Brazil responds more to the shocks originating from the Spain than from those in France. In conclusion, this study uncovers two important findings. First, Spain influences Latin American markets but these responses are not homogeneous across markets. Second, the influence of Spain has different magnitude in the three sub-periods.
    Keywords: Emerging Markets, Latin America, Stock Markets Interdependence, VAR
    JEL: F30 G15 O54 C22
    Date: 2005–12–14
  2. By: Ooghe, H.; Spaenjers, C.; Pieter vandermoere
    Abstract: We give an overview of the shortcomings of the most frequently used statistical techniques in failure prediction modelling. The statistical procedures that underpin the selection of variables and the determination of coefficients often lead to ‘overfitting’. We also see that the ‘expected signs’ of variables are sometimes neglected and that an underlying theoretical framework mostly does not exist. Based on the current knowledge of failing firms, we construct a new type of failure prediction models, namely ‘simple-intuitive models’. In these models, eight variables are first logit-transformed and then equally weighted. These models are tested on two broad validation samples (1 year prior to failure and 3 years prior to failure) of Belgian companies. The performance results of the best simple-intuitive model are comparable to those of less transparent and more complex statistical models.
    Date: 2005–12–15
  3. By: Georges Dionne; Pierre Duchesne; Maria Pacurar
    Abstract: The objective of this paper is to investigate the use of tick-by-tick data for market risk measurement. We propose an Intraday Value at Risk (IVaR) at different horizons based on irregularly time-spaced high-frequency data by using an intraday Monte Carlo simulation. An UHF-GARCH model extending the framework of Engle (2000) is used to specify the joint density of the marked-point process of durations and high-frequency returns. We apply our methodology to transaction data for the Royal Bank and the Placer Dome stocks traded on the Toronto Stock Exchange. Results show that our approach constitutes reliable means of measuring intraday risk for traders who are very active on the market. The UHF-GARCH model performs well out-of-sample for almost all the time horizons and the confidence levles considered even when normality is assumed for the distribution of the error term, provided that intraday seasonality has been accounted for prior to the estimation.
    Keywords: Value at Risk, tick-by-tick data, UHF-GARCH models, intraday market risk, high-frequency models, intraday Monte Carlo simulation, Intraday Value at Risk
    JEL: C22 C41 C53 G15
    Date: 2005
  4. By: Jacob Boudoukh; Matthew Richardson; Robert Whitelaw
    Abstract: The prevailing view in finance is that the evidence for long-horizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perfectly correlated across horizons under the null hypothesis of no predictability. For example, for the persistence levels of dividend yields, the analytical correlation is 99% between the 1- and 2-year horizon estimators and 94% between the 1- and 5-year horizons, due to the combined effects of overlapping returns and the persistence of the predictive variable. Common sampling error across equations leads to ordinary least squares coefficient estimates and R2s that are roughly proportional to the horizon under the null hypothesis. This is the precise pattern found in the data. The asymptotic theory is corroborated, and the analysis extended by extensive simulation evidence. We perform joint tests across horizons for a variety of explanatory variables, and provide an alternative view of the existing evidence.
    JEL: G12 G10 C32
    Date: 2005–12
  5. By: Tucha Thomas; Brem Markus
    Abstract: The arm’s length analysis of international transfer prices of multinational firms lacks sound methodological approach of the so-called function and risk analysis. In practice, such analyses are descriptive. Derived from Zadeh’s mathematical theory of fuzzy sets, this paper investigates a quantitative approach to identify the function and risk pattern of related parties of multinational companies. We illustrate our fuzzy logic approach with a simple case.
    Keywords: Function and risk analysis, fuzzy logic theory, multinational company, transaction costs, transfer pricing.
    JEL: C69
    Date: 2005–12–08

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