UK Stock Returns Research Articles

Are Regulatory Short Sale Data a Profitable Predictor of UK Stock Returns?

Are Regulatory Short Sale Data a Profitable Predictor of UK Stock Returns?

The Effect of Political Instability on the UK Stock Returns: Evidence from 2016 eferendum and the Major Events that Followed

This study examines the consequences of six events on the FTSE100 companies since the UK voted to leave the EU. These are the events that created political uncertainty leading to two General Elections within 30 months. The study examines the relationship between political instability and stock return abnormalities, using event study methodology and regression analysis to establish if such a link exists. Following each event, the UK stock market index declined except when Brexit was extended by six months (Event 5). The results of this study find a definite relationship between instability and return abnormalities, with the post-event abnormal returns proving to be the most significant over the event window. The industry variables were found to be most strongly linked with the CAR values out of all the independent variables, with the healthcare, utilities and basic materials industries exhibiting the most significant reactions. The findings of this study are an additional expectational tool for investors. It will be essential for investors during times of uncertainty.

Is Regulatory Short Sale Data a Profitable Predictor of UK Stock Returns?

Regulator-required public disclosures of net short positions do not provide a profitable investment signal for UK stocks. While long-short (zero initial outlay) portfolios based on this signal usually make a profit on average, it is rarely statistically significant in either gross or risk-adjusted terms. The issue is that the short sides of the portfolios make substantial losses. This is true even when using information in the trend in disclosures to form portfolios, rather than using the most recent disclosures, which is a more standard procedure. Unit initial outlay portfolios based on the disclosures that are allowed to take short positions do not reliably significantly outperform the market. Certain long-only unit initial outlay portfolios based on the disclosures do reliably significantly outperform the market. However, this out-performance is economically modest: about 1 percentage point a year in gross and risk-adjusted terms.

Sentiment versus liquidity pricing effects in the cross-section of UK stock returns

This study examines the asset pricing role of ‘sentiment risk’ in UK stock returns. We define sentiment risk as the sensitivity of stock returns to investor sentiment in financial markets. We incorporate a broad range of financial market variables in measuring financial conditions and use this as a proxy for market-wide investor sentiment. The paper distinguishes between rational and irrational (noisy) investor sentiment. Initial findings indicate a strong role for rational sentiment risk in the returns of FTSE All-Share stocks. However, further analysis reveals that this sentiment risk pricing is detected in the FTSE All-Share subgroup of FTSE small-cap stocks, while no evidence of sentiment risk pricing is found among the FTSE All-Share subgroups of FTSE 250 and FTSE 100 stocks. Our paper makes a key contribution by identifying that evidence of rational sentiment risk pricing disappears after controlling for the liquidity risk features of stocks. More generally, our findings point to a strong relation between sentiment risk and liquidity risk in stock returns and to the need for careful disentangling of sentiment versus liquidity effects.

Sentiment Versus Liquidity Pricing Effects in the Cross-Section of UK Stock Returns

This study examines the asset pricing role of ‘sentiment risk’ in stock returns in the case of the UK stock market. We define sentiment risk as the sensitivity of stock returns to investor sentiment in financial markets. We incorporate a broad range of financial market variables in measuring financial conditions and use this as a proxy for market-wide investor sentiment. The paper distinguishes between rational and irrational (noisy) investor sentiment. Initial findings indicate a strong role for rational sentiment risk in the returns of FTSE All Share stocks. However, our paper makes a key contribution by identifying that this evidence largely disappears after controlling for the liquidity risk features of stocks. No evidence of sentiment risk pricing is found among the subgroups of FTSE 250 and FTSE 100 stocks. More generally, our findings point to a strong relation between sentiment risk and liquidity risk in returns and the need for careful disentangling of sentiment versus liquidity effects.

The impact of downside risk on UK stock returns

PurposeThis paper aims to investigate patterns in UK stock returns related to downside risk, with particular focus on stock returns during financial crises.Design/methodology/approachFirst, stocks are sorted into five quintile portfolios based on the relevant beta values (classic beta, downside beta and upside beta, calculated by the moving window approach). Second, patterns of portfolio returns are examined during various sub-periods. Finally, predictive powers of beta and downside beta are examined.FindingsThe downside risk is observed to have a significant positive impact on contemporaneous stock returns and a negative impact on future returns in general. In contrast, an inverse relationship between risk and return is observed when stocks are sorted by beta, contrary to the classic literature. UK stock returns exhibit clear time sensitivity, especially during financial crises.Originality/valueThis paper focuses on the impact of the downside risk on UK stock returns, assessed via a comprehensive sub-period analysis. This paper fills the gap in the existing literature, in which very few studies examine the time sensitivity in relation to the downside risk and the risk-return anomaly in the UK stock market using a long sample period.

The Role of Economic Uncertainty in UK Stock Returns

We investigated the role of domestic and international economic uncertainty in the cross-sectional pricing of UK stocks. We considered a broad range of financial market variables in measuring financial conditions to obtain a better estimate of macroeconomic uncertainty compared to previous literature. In contrast to many earlier studies using conventional principal component analysis to estimate economic uncertainty, we constructed new economic activity and inflation uncertainty indices for the UK using a time-varying parameter factor-augmented vector autoregressive (TVP-FAVAR) model. We then estimated stock sensitivity to a range of macroeconomic uncertainty indices and economic policy uncertainty indices. The evidence suggests that economic activity uncertainty and UK economic policy uncertainty have power in explaining the cross-section of UK stock returns, while UK inflation, EU economic policy and US economic policy uncertainty factors are not priced in stock returns for the UK.

Predictable risks and returns: further evidence from the UK stock market

This paper examines whether the most cited performance models can explain variation in the UK stock returns. The dataset includes securities of the FTSE 100 from January 2000 to December 2016. Securities are classified based on their market capitalisation and their industry. Also, valuation ratios are put to the test so as to help us retrieve evidence of predictability. Finally, the January effect is included in our analysis as indicated particularly for the UK data. The authors find that during this short time period in which a financial crisis is also evident, all performance models are equally capable of assisting us interpreting UK predictability. Secondly, lagged market's excess returns capture most of the forecasting ability in returns, while the valuation ratios employed manage to partly predict returns in this specific sample. The paper's novelty lies in the fresh evidence presented in the case of the UK returns for the most recent dataset available.

The Role of Economic Uncertainty in UK Stock Returns

We investigate the role of domestic and international economic uncertainty in the cross-sectional pricing of UK stocks. We consider a broad range of financial market variables in measuring financial conditions in order to obtain a better estimate of macroeconomic uncertainty compared to previous literature. In contrast to many earlier studies using conventional principal component analysis to estimate economic uncertainty, we construct new economic activity and inflation uncertainty indices for the UK using a time-varying parameter factor-augmented vector autoregressive (TVP-FAVAR) model. We then estimate stock sensitivity to a range of macroeconomic uncertainty indices and economic policy uncertainty indices. The evidence suggests that economic activity uncertainty and UK economic policy uncertainty have power in explaining the cross-section of UK stock returns, while UK inflation, EU economic policy and US economic policy uncertainty factors are not priced in stock returns for the UK.

Industry concentration, stock returns and asset pricing: The UK evidence

How does competition in firms’ product markets influence stock returns? We examine this question using firms domiciled in the UK. We find that firms in less concentrated industries earn higher returns, even after controlling for the well-known determinants of the cross-section of UK stock returns. Furthermore, we suggest a novel asset pricing model that explicitly incorporates industry concentration as a distinguished risk factor capturing important features of product markets. Our results link the explanatory power of R&D activity of stock returns to product market structure. Also, we suggest an explanation for value premium on the basis of product market structure that favours barriers to entry interpretation for the higher returns obtained by less concentrated industries.

The effect of ambiguity on the UK stock market: evidence from a new empirical approach

This study developed a new ambiguity measure using the bid-ask spread. The results suggest that the degree of ambiguity has an impact on the daily UK stock market returns, but ambiguity does not cause changes in the returns. This implies that UK stock prices or returns cannot be predicted using variation in the degree of ambiguity through linear models, such as the VAR model, which was used in the study. The two sets of results in the study show that the degree of ambiguity from the previous two days might affect stock market returns. The authors observe that an increase in the degree of ambiguity two days ago is associated with a positive premium required by the investors. On the other hand, the degree of ambiguity tends to be affected by its past five-day values. Thus, the degree of ambiguity seems to persist for five days until investors update their priors. The intuition behind the result is that the degree of ambiguity can affect the returns of the UK stock market and UK stock market returns can in turn have an impact on the degree of ambiguity. The authors also observe that the degree of ambiguity does not seem to predict stock market returns in the UK when one applies linear models. However, this does not mean that there is no non-linear relationship between the degree of ambiguity and stock market returns or stock returns.

An Empirical Examination of the Incremental Contribution of Stock Characteristics in UK Stock Returns

This study uses the Bayesian approach to examine the incremental contribution of stock characteristics to the investment opportunity set in U.K. stock returns. The paper finds that size, book-to-market (BM) ratio, and momentum characteristics all make a significant incremental contribution to the investment opportunity set when there is unrestricted short selling. However, no short selling constraints eliminate the incremental contribution of the size and BM characteristics, but not the momentum characteristic. The use of additional stock characteristics such as stock issues, accruals, profitability, and asset growth leads to a significant incremental contribution beyond the size, BM, and momentum characteristics when there is unrestricted short selling, but no short selling constraints largely eliminates the incremental contribution of the additional characteristics.

Modelling the Dependence of the UK Stock Market on the US Stock Market: A Need for Multiple Regimes

Through the use of regime-switching models, recent empirical research has essentially shown that the dynamics of stock returns depend on the state of one stock market. The present paper extends this analytical framework by allowing the dynamics of returns to depend on the joint-states of two different stock markets. Such an extension is natural given the globalisation of financial markets and the rapid transmission of news from one international stock market to another. In an application involving the S&P500, the FTSE100 and the NIKKEI225 over the period January 1984 - October 2003, UK stock returns are found to depend on the joint-states of the US and UK stock markets three months back. Moreover the contemporaneous dependence of UK stock returns on US stock returns increases with a rising US market and a falling UK market but decreases with a falling US market and a rising UK market. This is consistent with a `rapport de force effect whereby the relative strengths of the US and UK stock markets matter in determining the degree of contemporaneous dependence of the UK stock market on the US stock market.

The impact of diverse measures of default risk on UK stock returns

A number of recent papers examine the relationship between default risk and equity returns, and the results are mixed. These studies employ different measures of default risk and we find that correlations between eight diverse measures of default risk tend to be less than 50%. Nonetheless, we find that the relationship between stock returns and diverse measures of default risk tends to be consistent; default risk is a significant determinant of stock returns and this relationship is “hump backed”, as predicted by Garlappi and Yan (2011).

Does the Macroeconomy Predict UK Asset Returns in a Nonlinear Fashion? Comprehensive Out-of-Sample Evidence

We perform a comprehensive examination of the recursive, comparative predictive performance of linear and nonlinear models for UK stock and bond returns. We estimate Markov switching, threshold autoregressive (TAR) and smooth transition autoregressive (STR) regime switching models and a range of linear specifications including models with GARCH type specifications. Results demonstrate UK asset returns require nonlinear dynamics to be modelled with strong evidence in favour of Markov switching frameworks. Our results appear robust to the choice of sample period, changes in loss functions and to the methodology employed to test for equal predictive accuracy. The key findings extend to a similar sample of US data.

Do the US trends drive the UK–French market linkages?: empirical evidence from a threshold intraday analysis

This article investigates the impact of US stock market openings on linkages between the UK and French markets. Using intraday data over the period December 2004 to March 2009, we find significant time-varying dependence between the UK and French stock returns, which alter according to the state of the US market. Indeed, not only does the opening of the US market itself significantly affect the UK stock dependency, but such linkages also seem to be closely dependent on bearish or bullish US market trends. Interestingly, the estimation of a two-regime Threshold Autoregressive (TAR) model indicates that the bearish US trends are a source of minor linkage (lower regime), whereas the bullish US trends involve higher interdependency (upper regime). This finding is particularly interesting as following the US trend expectations enables us to better forecast future European stock prices and to calculate the level of their potential contagion effects.

Are Monthly Seasonals Real? A Three Century Perspective

Over 300 years of UK stock returns reveal that well-known monthly seasonals are sample specific. For instance, the January effect only emerges around 1830. Most months have had their 50 years of fame, showing the importance of long time series to safeguard against sample selection bias, noise, and data snooping. The overall conclusion is that monthly seasonals might simply be in the eye of the beholder. Copyright 2013, Oxford University Press.

Does non-linearity help us understand, model and forecast UK stock and bond returns: evidence from the BEYR

The usefulness of non-linear models to provide accurate estimates and forecasts remains an open empirical debate. This paper examines the nature of the estimated relationships and forecasting power of smooth-transition models for UK stock and bond returns using a range of financial and macroeconomic variables as predictors. Notably, evidence of non-linearity is stronger when the bond-equity yield ratio is used as the transition variable. This ratio measures whether stocks are over (under)-valued relative to bonds and can act as a signal for portfolio managers. In-sample results reveal noticeable differences regarding the nature of relationships between the linear and non-linear setting, while results of a recursive forecasting exercise reveal both statistical and economic improvement over a linear model. Overall, these results support the view that non-linear estimates and forecasts can provide useful information for stock market traders, portfolio managers and policy-makers.

An Examination of Dynamic Trading Stategies in UK and US Stock Returns

Abstract: This paper examines the performance benefits of using conditioning information in mean‐variance strategies in UK and US stock returns. The paper finds that after adjusting for trading costs, there are no significant performance benefits in using conditioning information in mean‐variance strategies. This result stems from the high turnover that is required to implement dynamic trading strategies. The paper does find that after adjusting for costs, that the unconditional approach of Ferson and Siegel (2001) significantly outperforms alternative approaches of using conditioning information in mean‐variance strategies in UK stock returns.

Is There an Accruals or a Cash Flow Anomaly in UK Stock Returns?

In this paper, we apply a modified one-stage version of the Mishkin (1983) test to companies in the UK stock market in order to investigate the presence or otherwise of the accruals anomaly in UK firms’ annual returns. For the period of 1990-2007, we report that there is little evidence of a general accruals anomaly in the UK, in which accruals have a negative relationship with future returns, once risk and other potential forecasting variables have been accounted for. We also provide evidence that, after winsorising extreme observations, there is a cash flow anomaly in the UK stock market. We also find evidence in favour of an anomaly with respect to capital expenditure growth. Another interpretation is that the accruals anomaly is not distinct from other anomalies in the UK market, whereas the cash flow (and the capital expenditure growth) anomaly is.