Operational Risk Management and Implications for Bank’s Economic Capital – a Case Study

In this paper we review the actual operational data of an anonymous Central European Bank, using two approaches described in the literature: the loss distribution approach and the extreme value theory (“EVT”). Within the EVT analysis, two estimation methods were applied; the standard maximum likelihood estimation method and the probability weighted method (“PWM”). Our results proved a heavy-tailed pattern of operational risk data consistent with the results documented by other researchers in this field. Additionally, our research demonstrates that the PWM is quite consistent even when the data is limited since our results provide reasonable and consistent capital estimates. From a policy perspective, it should be noted that banks from emerging markets such as Central Europe are exposed to these operational risk events and that successful estimates of the likely distribution of these risk events can be derived from more mature markets.operational risk, economic capital, Basel II, extreme value theory, probability weighted method

A two-step approach to model precipitation extremes in California based on max-stable and marginal point processes

In modeling spatial extremes, the dependence structure is classically inferred by assuming that block maxima derive from max-stable processes. Weather stations provide daily records rather than just block maxima. The point process approach for univariate extreme value analysis, which uses more historical data and is preferred by some practitioners, does not adapt easily to the spatial setting. We propose a two-step approach with a composite likelihood that utilizes site-wise daily records in addition to block maxima. The procedure separates the estimation of marginal parameters and dependence parameters into two steps. The first step estimates the marginal parameters with an independence likelihood from the point process approach using daily records. Given the marginal parameter estimates, the second step estimates the dependence parameters with a pairwise likelihood using block maxima. In a simulation study, the two-step approach was found to be more efficient than the pairwise likelihood approach using only block maxima. The method was applied to study the effect of El Ni\~{n}o-Southern Oscillation on extreme precipitation in California with maximum daily winter precipitation from 35 sites over 55 years. Using site-specific generalized extreme value models, the two-step approach led to more sites detected with the El Ni\~{n}o effect, narrower confidence intervals for return levels and tighter confidence regions for risk measures of jointly defined events.Comment: Published at http://dx.doi.org/10.1214/14-AOAS804 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Untenable nonstationarity: An assessment of the fitness for purpose of trend tests in hydrology

The detection and attribution of long-term patterns in hydrological time series have been important research topics for decades. A significant portion of the literature regards such patterns as ‘deterministic components’ or ‘trends’ even though the complexity of hydrological systems does not allow easy deterministic explanations and attributions. Consequently, trend estimation techniques have been developed to make and justify statements about tendencies in the historical data, which are often used to predict future events. Testing trend hypothesis on observed time series is widespread in the hydro-meteorological literature mainly due to the interest in detecting consequences of human activities on the hydrological cycle. This analysis usually relies on the application of some null hypothesis significance tests (NHSTs) for slowly-varying and/or abrupt changes, such as Mann-Kendall, Pettitt, or similar, to summary statistics of hydrological time series (e.g., annual averages, maxima, minima, etc.). However, the reliability of this application has seldom been explored in detail. This paper discusses misuse, misinterpretation, and logical flaws of NHST for trends in the analysis of hydrological data from three different points of view: historic-logical, semantic-epistemological, and practical. Based on a review of NHST rationale, and basic statistical definitions of stationarity, nonstationarity, and ergodicity, we show that even if the empirical estimation of trends in hydrological time series is always feasible from a numerical point of view, it is uninformative and does not allow the inference of nonstationarity without assuming a priori additional information on the underlying stochastic process, according to deductive reasoning. This prevents the use of trend NHST outcomes to support nonstationary frequency analysis and modeling. We also show that the correlation structures characterizing hydrological time series might easily be underestimated, further compromising the attempt to draw conclusions about trends spanning the period of records. Moreover, even though adjusting procedures accounting for correlation have been developed, some of them are insufficient or are applied only to some tests, while some others are theoretically flawed but still widely applied. In particular, using 250 unimpacted stream flow time series across the conterminous United States (CONUS), we show that the test results can dramatically change if the sequences of annual values are reproduced starting from daily stream flow records, whose larger sizes enable a more reliable assessment of the correlation structures

Arbitrage pricing theory: evidence from an emerging stock market

The development of financial equilibrium asset pricing models has been the most important area of research in modern financial theory. These models are extensively tested for developed markets. This paper examines the validity of the Arbitrage Pricing Theory (APT) model on returns from 24 actively trading stocks in Karachi Stock Exchange using monthly data from January 1997 to December 2003. Explanatory factor analysis approach indicates two factors governing stock return. Pre-specified macro economic approach identifies these two factors as the anticipated and unanticipated inflation and market index and dividend yield. Some evidence of instability is found. The overall finding of two significant priced factors at least for a sub period supports APT for an emerging capital market.Asset Pricing, APT, Emerging Markets