Iceland illustrates why political ‘hectoring’ from foreign countries is bound to fail in Greece

Iceland entered a period of financial crisis in 2008, with the country subsequently involved in a prolonged dispute over losses generated in the Netherlands and the UK by an Icelandic bank. Jon Danielsson writes that the crisis in Iceland has much in common with the ongoing crisis in Greece, not least the heavy pressure exerted on both countries by foreign governments. He argues that just as in Iceland, this pressure has been counterproductive in Greece, hardening opposition to any potential settlement

Cryptocurrencies: policy, economics and fairness

Cryptocurrencies promise to replace fiat money with private money whose integrity is underpinned by algorithms, not government guarantees. While the technology is elegant, the success and failure of cryptocurrencies in the competition with fiat will not be determined by technology alone. What is more important is that any serious economic and social consequences be avoided. A cryptocurrency based monetary system would suffer from persistent deflation and higher systemic risk than existing fiat systems, and would exasperate inequality. If, however, cryptocurrencies cannot replace existing fiat money, their terminal value is zero

The case against aggressive government action on crypto

The financial regulators have recently taken an active interest in cryptocurrencies, more than a decade after their law enforcement counterparts did. So why are they doing this now, and what will the consequences be? Jón Danielsson writes that regulators feel compelled to respond due to political pressures and their actions may backfire

Why risk is so hard to measure

This paper analyzes the robustness of standard risk analysis techniques, with a special emphasis on the specifications in Basel III. We focus on the difference between Value– at–Risk and expected shortfall, the small sample properties of these risk measures and the impact of using an overlapping approach to construct data for longer holding periods. Overall, risk forecasts are extremely uncertain at low sample sizes. By comparing the estimation uncertainty, we find that Value–at–Risk is superior to expected shortfall and the time-scaling approach for risk forecasts with longer holding periods is preferable to using overlapping data

Why risk is so hard to measure

This paper analyzes the robustness of standard risk analysis techniques, with a special emphasis on the specifications in Basel III. We focus on the difference between Value– at–Risk and expected shortfall, the small sample properties of these risk measures and the impact of using an overlapping approach to construct data for longer holding periods. Overall, risk forecasts are extremely uncertain at low sample sizes. By comparing the estimation uncertainty, we find that Value–at–Risk is superior to expected shortfall and the time-scaling approach for risk forecasts with longer holding periods is preferable to using overlapping data

The fatal flaw in macropru: it ignores political risk

Political risk is a major cause of systemic financial risk. This column argues that both the integrity and the legitimacy of macroprudential policy, or ‘macropru’, depends on political risk being included with other risk factors. Yet it is usually excluded from macropru, and that could be a fatal flaw

Value-at-risk and extreme returns

Accurate prediction of extreme events are of primary importance in many financial applications. The properties of historical simulation and RiskMetrics techniques for computing Value-at-Risk (VaR) are compared with a method which involves modelling the tails of financial returns explicitly with a tail estimator. The methods are compared using a sample of U. S. stock returns. For predictions of low probability worst outcomes, RiskMetrics type analysis underpredicts while historical simulation overpredicts. However, the estimates obtained from applying the tail estimator are more accurate in the VaR prediction. This implies that capital requirements can be lower by doing VaR with the tail estimator

Beyond the sample: extreme quantile and probability estimation

Economic problems such as large claims analysis in insurance and value-at-risk in fi- nance, require assessment of the probability P of extreme realizations Q. This paper provides a semi-parametric method for estimation of extreme (P, Q) combinations for data with heavy tails. We solve the long standing problem of estimating the sample threshold of where the tail of the distribution starts. This is accomplished by the combination of a control variate type device and a subsample bootstrap technique. The sub- sample bootstrap attains convergence in probability, whereas the full sample bootstrap would only provide convergence in distribution. This permits a complete and comprehensive treatment of extreme (P, Q) estimation

Real trading patterns and prices in spot foreign exchange markets

Most of the existing empirical literature on FX market microstructure uses indicative quote data derived from Reuters EFX screens. This paper examines the adequacy of such data as proxies for firm, tradeable quotes. We present a comparison of prices (and volumes) derived from Reuters D2000-2 electronic inter-dealer broking system with contemporaneous data from EFX. Tick-by-tick data is available from both sources, covering October 6-10, 1997. Our main comparative results are as follows. EFX midquote returns are consistently more volatile than their D2000-2 counterparts and display strong moving average effects which are not present in the D2000-2 returns. EFX spreads bear little or no relation to the inside spreads derived from D2000-2. In terms of information flows, D2000-2 returns lead those on EFX by up to 3 minutes and, further, contribute around 90% of all information imp impounded in quotes. A bivariate GARCH analysis also indicates a dominant role for D2000-2 in price discovery. On the positive side, however, EFX quotation frequency correlates well with D2000-2 transaction frequency