Exogenous and endogenous crashes as phase transitions in complex financial systems

In this paper we provide a unifying framework for a set of seemingly disparate models for exogenous and endogenous shocks in complex financial systems. Markets operate by balancing intrinsic levels of risk and return. This remains true even in the midst of transitory external shocks. Changes in market regime (bearish to bullish and bullish to bearish) can be explicitly shown to represent a phase transition from random to deterministic behaviour in prices. The resulting models refine the empirical analysis in a number of previous papers.Exogenous; Endogenous; Financial Crashes; Bubbles; Econophysics

The Irish Rural Environmental Protection Scheme and lack of Strategic Environmental Assessment

working paperProposals specifically aimed at delivering environmental benefits are often exempt from assessment, despite evidence that they can be poorly thought-through and sometimes counterproductive. This is doubly true of agri-environmental schemes where local farm-scale actions are expected to generate large-area cumulative effects on soil and water quality, biodiversity or landscape. There is evidence that the benefits of such schemes have often been assumed rather than planned for, thus necessitating ex-post assessment to justify their continuance

Statistical modelling of financial crashes: Rapid growth, illusion of certainty and contagion

We develop a rational expectations model of financial bubbles and study ways in which a generic risk-return interplay is incorporated into prices. We retain the interpretation of the leading Johansen-Ledoit-Sornette model, namely, that the price must rise prior to a crash in order to compensate a representative investor for the level of risk. This is accompanied, in our stochastic model, by an illusion of certainty as described by a decreasing volatility function. The basic model is then extended to incorporate multivariate bubbles and contagion, non-Gaussian models and models based on stochastic volatility. Only in a stochastic volatility model where the mean of the log-returns is considered fixed does volatility increase prior to a crash.Financial crashes, super-exponential growth, illusion of certainty, contagion, housing-bubble.

Consideration of landscape in the framework documentation during the evolution of the Rural Environment Protection Scheme (REPS) in the Republic of Ireland.

working paperThis paper looks at the changing concept of landscape during the evolution of REPS. It reviews and groups definitions of landscape and identifies their agri-environmental relevance. Descriptions were devised to amplify each grouping with reference to an Irish context and were used as an analytical framework to categorise each landscape reference in REPS documentation. There was an increase in the use of the term landscape with each version of the scheme and expansion in the range of different landscape categories to which this apparently applied. However there has been no coherence in its use. This paper makes recommendations to improve the framework for the treatment of landscape issues in REPS and its future evolution

Revisiting Student Evaluation of Teaching during the pandemic

The pandemic has placed unprecedented pressures upon staff and students alike. Yet performance management of academics including Student Evaluation of Teaching (SET) persists. The American Association of University Professors (AAUP) has intervened on this issue. We develop new methods enabling better treatment of pandemic-era SET. Analysis of UK National Student Survey (NSS) data suggests 85% of institutions meet reasonable performance expectations during the pandemic. Results emphasize the need for a more sensitive treatment of pandemic-era SET

Booms, busts and heavy-tails: the story of Bitcoin and cryptocurrency markets?

YesWe develop bespoke rational bubble models for Bitcoin and cryptocurrencies that incorporate both heavy tails and the probability of a complete collapse in asset prices. Empirically, we present robustified evidence of bubbles in Bitcoin and Ethereum. Theoretically, we show that liquidity risks may generate heavy-tails in Bitcoin and cryptocurrency markets. Even in the absence of bubbles dramatic booms and busts can occur. We thus sound a timely note of caution

Stochastic modelling for financial bubbles and policy

In this paper, we draw upon the close relationship between statistical physics and mathematical finance to develop a suite of models for financial bubbles and crashes. By modifying previous approaches, we are able to derive novel analytical formulae for evaluation problems and for the expected timing of future change points. In particular, we help to explain why previous approaches have systematically overstated the timing of changes in market regime. The list of potential empirical applications is deep and wide ranging, and includes contemporary housing bubbles, the Eurozone crisis and the Crash of 2008