Book review: the militant muse: love, war and the women of surrealism by Whitney Chadwick

In The Militant Muse: Love, War and the Women of Surrealism, Whitney Chadwick explores how a number of women within the Surrealist movement fought to move beyond the confining role of muse to establish themselves as groundbreaking artists in their own right. Covering the lives of figures including Frida Kahlo, Claude Cahun and Valentine Penrose, this immersive and captivating account challenges the marginalisation of these women within the Surrealist movement and offers insight into the formative power of female friendship, determination and support, writes Vanessa Longden. The Militant Muse: Love, War and the Women of Surrealism. Whitney Chadwick. Thames & Hudson. 2017

Book review: how to write a thesis by Umberto Eco

Now in its twenty-third edition in Italy and translated into seventeen languages, How to Write a Thesis has become a classic. This is its first, long overdue publication in English. Vanessa Longden thinks that in addition to its witty one-liners, Eco’s book contains the bare bones on which to build research

The Biographical Dictionary of Iowa

Review of: "The Biographical Dictionary of Iowa," edited by David Hudson, Marvin Bergman, and Loren Horton

Book review: photography and the art market by Juliet Hacking

In Photography and the Art Market, Juliet Hacking combines business analysis of the art market with the historical emergence of the photograph as a collectable art object and a fundamental component of the international fine art scene. This is an essential handbook for students, curators and dealers, writes Vanessa Longden, as well as those wishing to enter the market as a private or institutional buyer

Measuring temperature-related mortality using endogenously determined thresholds

© 2018, Springer Nature B.V. Heat-related mortality tends to be associated with heatwaves that do not allow for sufficient acclimatisation to hot temperatures. In contrast, damage functions and most heatwave emergency response plans do not account for acclimatisation. Using an excess heat measure that accounts for acclimatisation, this paper produces estimates of temperature-related mortality for the five largest Australian capital cities. Fixed effects panel threshold regressions are applied to establish the thresholds that coincide with heightened mortality during extreme temperature events. The estimated parameters associated with these thresholds are then used to develop hindcast estimates for cold temperatures, moderate temperatures, hot temperatures and extreme heat. The estimated thresholds coincide with a notable impact of hot temperatures on mortality, but a limited cold temperature impact. This shows that the burden of risk associated with mortality related to future temperatures and climate change within Australia coincides with heatwaves rather than coldwaves. This is in contrast to recent studies that found that cold temperature-related mortality within Australian capital cities has and will continue to be notable. These studies also found a net benefit from climate change in Australia due to reduced cold temperature deaths

Predicting Nature of Default using Machine Learning Techniques

This paper presents machine learning techniques to help financial institutions model a loan’s nature of default and further incorporate nature of default in the prediction of loss given default models. Nature of default decribes the main reason why the lender puts the borrower in default. The comparison of different techniques show the decision tree approach as the best model, specifically the time it takes to default since a loan’s origination is the most important feature in distinguishing different default types. We find loans with longer time to default are more likely to emerge to bankruptcy; whereas loans defaulted shortly after origination are more likely to be sold at a discount, resulting in a material credit loss. We also find that trade finance loans are more likely to receive a specific provision or write-off from the lending bank when they default, possibly due to the significant decrease in collateral valuations when the company is in financial difficulty. The nature of default is also found to be a significant factor in predicting loss given default. The unique insight this paper provides, when compared to similar default and loss studies in the existing literature, lies with its specificity in the loan’s nature of default and its association with loss rates