Robert W. Faff

An evaluation of volatility forecasting techniques

The existing literature contains conflicting evidence regarding the relative quality of stock market volatility forecasts. Evidence can be found supporting the superiority of relatively complex models (including ARCH class models), while there is also evidence supporting the superiority of more simple alternatives. These inconsistencies are of particular concern because of the use of, and reliance on, volatility forecasts in key economic decision-making and analysis, and in asset/option pricing. This paper employs daily Australian data to examine this issue. The results suggest that the ARCH class of models and a simple regression model provide superior forecasts of volatility. However, the various model rankings are shown to be sensitive to the error statistic used to assess the accuracy of the forecasts. Nevertheless, a clear message is that volatility forecasting is a notoriously difficult task.

Oil price risk and the Australian stock market

Abstract The primary aim of this paper is to investigate the sensitivity of Australian industry equity returns to an oil price factor over the period 1983–1996. The paper employs an augmented market model to establish the sensitivity. The key findings are as follows. First, a degree of pervasiveness of an oil price factor, beyond the influence of the market, is detected across some Australian industries. Second, we propose and find significant positive oil price sensitivity in the Oil and Gas and Diversified Resources industries. Similarly, we propose and find significant negative oil price sensitivity in the Paper and Packaging, and Transport industries. Generally, we find that long-term effects persist, although we hypothesize that some firms have been able to pass on oil price changes to customers or hedge the risk. The results have implications for management in these industries and policy makers and enhance our understanding of the “Dutch disease.”

Corporate sustainability performance and idiosyncratic risk: A global perspective

Does investing in sustainability leaders affect portfolio performance? Analyzing two mutually exclusive leading and lagging global corporate sustainability portfolios (Dow Jones) finds that (1) leading sustainability firms do not underperform the market portfolio, and (2) their lagging counterparts outperform the market portfolio and the leading portfolio. Notably, we find leading (lagging) corporate social performance (CSP) firms exhibit significantly lower (higher) idiosyncratic risk and that idiosyncratic risk might be priced by the broader global equity market. We develop an idiosyncratic risk factor and find that its inclusion significantly reduces the apparent difference in performance between leading and lagging CSP portfolios.

Time‐Varying Beta Risk of Australian Industry Portfolios: A Comparison of Modelling Techniques

This paper investigates three techniques for the estimation of conditional time‐dependent betas: (a) a multivariate generalised ARCH approach; (b) a time‐varying beta market model approach suggested by Schwert and Seguin (1990); and (c) the Kalman filter technique. These approaches are applied to a sample of returns on Australian industry portfolios over the period 1974–1996. The evidence found in this paper, based on in‐sample forecast errors, overwhelmingly supports the Kalman filter approach When out‐of‐sample forecasts are considered the evidence again finds in favour of the Kalman filter approach.

An Examination of the Fama and French Three-Factor Model Using Commercially Available Factors

In this paper we show that reasonable proxies for the FF factors can be readily constructed from ‘off the shelf’ style index data. We employ a GMM testing procedure in which the main focus of the tests is to assess the overriding validity of the restrictions placed on the empirical model framework. In addition, we augment the system of equations with a simple mean equation for each of the three FF risk factors, thereby permitting a direct estimate of the associated risk premia. The key findings are as follows. First, the proxy mimicking portfolios do represent pervasive sources of exposure across a sample of industry-sorted portfolios. Second, based on the outcome of all the GMM tests performed on our sample, the evidence seems to quite strongly support the three-factor Fama and French model. Third, when we take into account the estimated risk premia produced by our framework, the conclusion favouring the model has to be downweighted somewhat. Nevertheless, the estimated risk premia for the market and for the book-to-market factor are typically found to be significantly positive. Our main ‘perverse’ finding relates to the size risk premium which in our sample is typically significantly negative. This is consistent with other recent evidence of a ‘reversal’ in the size effect.

Time Varying Beta Risk: An Analysis of Alternative Modelling Techniques

This paper investigates the performance of three different approaches to modelling time-variation in conditional asset betas: GARCH models, the extended market model of Schwert and Seguin (1990) and the Kalman Filter algorithm. Using daily UK industry returns, we find the simple market model beta to be as efficient as the more complicated GARCH type models. However, the Kalman Filter algorithm incorporating a random walk parameterisation dominates all other models under the mean-square error criterion. Finally, we provide strong evidence that a combination of the methods under investigation may lead to considerably more powerful estimators of the time-variation in conditional beta. Copyright Blackwell Publishers Ltd 2000.

Does Simple Pairs Trading Still Work

Despite confirming the continuing downward trend in profitability of pairs trading, this study found that the strategy performs strongly during periods of prolonged turbulence, including the recent global financial crisis. Moreover, alternative algorithms combined with other measures enhance trading profits considerably, by 22 bps a month for bank stocks. Pairs trading is a relative value arbitrage in equity markets and is particularly attractive to hedge funds that seek to profit from temporary price deviations between stocks of close economic substitution. The scant research on this topic is mostly confined to seminal works that have documented economically and statistically significant, albeit declining, profits (on the order of 1 percent a month) from the use of a very simple pairs trading rule. This remarkable success has not been subjected to independent scrutiny, unlike other well-documented anomalies, such as momentum trading. We re-examined and expanded evidence on pairs trading in the U.S. market by using an extended dataset covering July 1962–June 2009. We confirmed a continuation of the declining trend in profitability over time, with the mean excess return for the portfolio of the top 20 pairs dropping precipitously, from 0.86 percent a month for 1962–1988 to 0.37 percent for 1989–2002 and to just 0.24 percent for 2003–2009. Although the literature suggests that this decline is the consequence of increased competition within the growing hedge fund industry, which competes away the same opportunities, careful analysis shows that not to be the case in pairs trading. We argued that pairs trading is essentially a risky arbitrage; thus, its performance depends on not only the state of market efficiency but also the degree of arbitrage risks facing arbitrageurs. These risks encompass fundamental risk, noise-trader risk, and synchronization risk, all of which work to prevent or delay arbitrage or to inflict losses on arbitrageurs. Using a simple attribution analysis, we were able to show that the “market efficiency” story, in which the hedge fund factor is just one component, is only partly to blame for the decline. Instead, we found that the worsening arbitrage risks facing pairs traders contribute up to 70 percent of the drop in profits. We also found that pairs trading performed particularly strongly during recent periods of prolonged turbulence, namely, the 2000–02 bear market and the 2007–09 global financial crisis. Although this finding seems counterintuitive, the increase in arbitrage risks during these periods of panic was outweighed by a corresponding decrease in market efficiency. Thus, some arbitrageurs have overcome worsening arbitrage risks to successfully exploit mispricings that appear to be abundant in such turbulent periods. We further proposed alternative algorithms that incorporate two additional pair-matching criteria: industry homogeneity and historical frequency of reversal in the price spread (in addition to the conventional price spread metric). Homogeneity involves matching securities within the same and narrowly defined industry groups to ensure close substitution by classification and lower divergence risk. To some extent, this metric can be viewed as a first step toward incorporating a fundamental aspect in pairs trading, which is traditionally a technical concept. Reversal frequency, computed as the number of zero crossings by the normalized price spread, measures how frequently two securities crossed each other in the past. A high number of zero crossings signifies a “track record” of frequent mispricings within a pair that were successfully corrected by market participants. When combined with the SSD and homogeneity metrics, this track record measure has been found to enhance trading profits considerably, by 22 bps a month for bank stocks.

An analysis of asymmetry in foreign currency exposure of the Australian equities market

Abstract Using both daily and monthly data, the authors: (a) analyse the extra-market component of foreign exchange exposure of the Australian equities market using the Australian/US exchange rate factor return in an augmented market model; and (b) use a dummy variable specification to model the potential asymmetric effect induced by non-linear hedging strategies, such as using currency options, for the period 1988–1996. Overall, the results are mixed. The following are found: (i) stronger evidence of foreign exchange exposure in the analysis employing daily data; (ii) when using daily data, a stronger lagged response than a contemporaneous response is observed; (iii) some evidence of asymmetry; and (iv) evidence of significant exchange rate exposures of the predicted sign in several industries. Further, the findings using monthly data are less significant than those using daily data.

Revisiting the Vexing Question: Does Superior Corporate Social Performance Lead to Improved Financial Performance?

The empirical evidence documenting the association between a firms level of corporate social performance (CSP) and corporate financial performance (CFP) remains divided. This paper reinvestigates the CSP/CFP association using a more rigorous methodology whilst taking advantage of a superior measure of CSP. In contrast to the findings of much of the prior research, the market-based tests suggest a negative association between CSP and CFP, while the accounting tests indicate no association exists. We suggest that the negative market CSP/CFP relation should not be interpreted as CSP having no value. Rather, our results may suggest that leading CSP firms trade at a price premium (i.e. returns discount) relative to lagging CSP firms, thereby indicating that financial markets value CSP and are prepared to realise lower returns. For firms, this signals an ability to obtain a lower cost of equity capital when they proactively manage their CSP profiles.

A multi-country study of power ARCH models and national stock market returns

The use of conditionally heteroscedastic models to model time varying volatility has become commonplace in the empirical finance literature. Ding, Granger and Engle (1993) suggested a model which extends the ARCH class of models to analysing a wider class of power transformations than simply taking the absolute value or squaring the data as in the conventional models. This class of models is called power ARCH (PARCH). This paper analyses the applicability of this model to national stock market returns for ten countries plus a world index. We find the model to be generally applicable once GARCH and leverage effects are taken into consideration. In addition, we also find that the optimal power transformation is remarkably similar across countries.