Some New Models for Financial Distress Prediction in the UK

Abstract

In this paper we develop some new models for the prediction of failure in the UK that add to the literature by showing that "dynamic logit" models that incorporate market variables of the form developed by Chava and Jarrow (2004) and Campbell et al (2008) add considerable power to pure accounting-based models. Importantly, we extend the logic of Campbell et al (2008) by showing that incorporating macroeconomic variables adds predictive power, both in and out-of-sample, to market-based accounting models. Last, we show that adding industry controls gives a modest improvement to such models for UK firms in the case of a models based on accounting, market and economic variables, but a greater improvement in terms of a pure accounting based model.

Company Performance, Investment Decision, and Cyclical Sensitivity: A Dynamic Estimation on Company Microdata

“…The confirming empirical evidence demonstrating that the positive macroeconomic cycle lowers firm distress risk has been provided by Richardson et al (1998), Bhattacharjee et al (2009), and Christidis and Gregory (2010).…”

Constructing and Testing Alternative Versions of the Fama–French and Carhart Models in the UK

“…Our data come from various sources and cover the period from October 1980 to December 2010. The monthly stock returns and market capitalisations are from the London Business School Share Price Database (LSPD), The book‐values are primarily from Datastream, with missing values filled in with data from: Thomson One Banker; tailored Hemscott data (from the Gregory, Tharyan and Tonks, study of directors’ trading) obtained by subscription; and hand collected data on bankrupt firms from Christidis and Gregory (). By combining several data sources we are able to fill in any data gaps in the data available from Datastream.…”

Constructing and Testing Alternative Versions of the Fama-French and Carhart Models in the UK

“…Datastream; Thomson One Banker; tailored Hemscott data (from the Gregory, Tharyan and Tonks [2011] study of directors" trading) obtained by subscription; and hand collected data on bankrupt firms from Christidis and Gregory (2010), from which we obtain estimates of book value used in the computation of the BTM ratios used in portfolio formation. Combining these data sources means that we are able to infill any missing data on any one firm in either of the Hemscott or Datastream sources.…”

“…The smb and hml factor portfolios (see below) are then formed using the universe of UK main-market stocks for which market capitalisation, returns, and book values (to compute the BTM ratios) can be collected from any of Datastream, Hemscott, the LSPD or the hand-collected data from Christidis and Gregory (2010). Following Agarwal and Taffler (2008), who note that 22% of UK firms have March year ends, with only 37% of firms having December year ends, we match March year t accounting data with end of September year t market capitalisation data.…”