Vineet Agarwal

Twenty Five Years of the Taffler Z-score Model: Does it Really Have Predictive Ability?

Abstract Although copious statistical failure prediction models are described in the literature, appropriate tests of whether such methodologies really work in practice are lacking. Validation exercises typically use small samples of non‐failed firms and are not true tests of ex ante predictive ability, the key issue of relevance to model users. This paper provides the operating characteristics of the well‐known Taffler (1983) UK‐based z‐score model for the first time and evaluates its performance over the 25‐year period since it was originally developed. The model is shown to have clear predictive ability over this extended time period and dominates more naïve prediction approaches. This study also illustrates the economic value to a bank of using such methodologies for default risk assessment purposes. Prima facie, such results also demonstrate the predictive ability of the published accounting numbers and associated financial ratios used in the z‐score model calculation.

Is Management Quality Value Relevant

Using a unique database of management quality ratings over a 17 year period, we find that while good management appears to be associated with lower subsequent market returns, this is entirely consistent with an informationally efficient market. Quality of management is value relevant in that better managed firms have lower cost of equity, more stable earnings, higher profitability that persists over time, and higher market valuations using the Ohlson (1995 and 2001) method. Potentially endogenous relationships are unlikely to be driving our results. While well managed firms are good firms, contrary to the belief of many market participants their stocks perform no better than those of poorly managed firms.

Investor relations, information asymmetry and market value

Evidence to date on the market value of investor relations (IR) strategies is limited. We test the market relevance of IR activity directly employing a proprietary database measuring IR quality across all firms listed on NYSE, Amex and NASDAQ. Although, in theory, ‘repackaging’ and communicating existing information should have no market impact, we find that firms with higher quality IR strategies are rewarded with significantly higher valuation multiples. In addition, increase in IR quality is associated with increases in analyst following and liquidity. Overall, our findings are generally stronger for small firms which are more likely to be ‘neglected’. Our evidence is consistent with effective IR successfully raising firm visibility leading to enhanced recognition and reduced information asymmetry in line with Merton (1987) and thus ‘fairer’ firm valuation as argued by IR professionals.

The Impact of Effective Investor Relations on Market Value

In this first study to test formally the market value of investor relations (IR) activity, we employ the annual US Investor Relations Magazine Investor Relations Awards from 2000 to 2002 to proxy for the quality of firm investor relations. We find firms perceived to have the most effective IR strategies earn superior abnormal returns, both before and after the nominations. This shows that while the nominations themselves may be influenced by past performance to some extent, they are nonetheless also associated with subsequent positive abnormal returns. We also find that not surprisingly, higher analyst following is associated with more nominations suggesting analysts tend to favour the stocks they follow. Consistent with effective IR leading to lower information risk, liquidity of nominated firms increases in the year subsequent to the nominations. Overall, our evidence is consistent with effective IR successfully reducing risks associated with high information asymmetry, as predicted by information risk and agency theories.

Size and book-to-market anomalies and omitted leverage risk

Ferguson and Shockley (2003. Equilibrium ‘anomalies’. Journal of Finance 58: 2549–2580) develop a theoretical model and argue that size and book-to-market (B/M) effects in stock returns derive their cross-sectional explanatory power because they proxy for leverage and financial distress. Using UK data from 1979 to 2006, we provide evidence that the size factor of Fama and French (1993. Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33: 3–56) is indeed proxying for distress risk, while their distress factor is capturing leverage risk. However, anomalously low returns and higher exposure of small size and value stocks to the distress factor reduces the expected returns on these stocks and results in larger pricing errors. This leads to poor performance of the Ferguson and Shockley (2003. Equilibrium ‘anomalies’. Journal of Finance 58: 2549–2580) model in the time series. Underperformance of distressed stocks casts doubt on the hypothesis that the explanatory power of size and B/M factors is due to the omitted debt claims in equity only proxy for market portfolio.

The Performance of Structural Models in Pricing Credit Spreads

Although structural models have been used as a standard in credit risk modelling for the last thirty years, there is a lack of consensus in the literature regarding their performance. This paper tests the performance of three structural models, namely the Merton (1974) model, the Collin-Dufresne and Goldstein (2001) stationary leverage ratio model and the CreditGrades™ (2002) model against the credit default swap spread using data from 2003 to 2010. We find that, consistent with existing literature, while the structural models have significant explanatory power for the cross-section of CDS spreads, all three models underpredict the observed credit spreads. The underprediction of credit spreads is not driven by any ratings categories or sector. We also show that while the three models produce spreads that are highly correlated with each other, they carry information incremental to each other. However, our evidence demonstrates that other firm specific variables: CDS liquidity, and credit rating can explain a significant part of observed credit spreads. Finally, our results indicate that the observed underpricing is driven by actual spreads reflecting additional information such as liquidity and residual credit risk, and in fact, the actual spreads are lower than implied spreads once additional credit risk and CDS liquidity information is taken into consideration.

Does Investor Relations Add Value

IR professionals argue that good investor relations contributes to the “fair valuation of firms”. We test the proposition that effective communication of accounting and other firm-specific information enhances firm value directly employing a unique and large database of firms nominated for Investor Relations Magazine’s ‘best overall IR’ awards measuring investor relations quality. We find firms perceived by investment professionals as having superior IR have increased analyst following, and improved liquidity in the year after award nominations. Effective IR also leads to subsequent positive abnormal returns, and such firms are additionally rewarded with significantly higher valuation multiples within the Ohlson (1995) framework. Overall, our findings are strongest for smaller firms which are more likely to be ‘neglected’. Our evidence is consistent with good IR successfully reducing the risk to investors associated with high information asymmetry. We also find our results are unlikely to be driven by potential sample selection bias.