The composition of CMBS risk

This paper identifies the put-option, liquidity availability proportion, and shadow liquidity risk premia embedded within commercial mortgage backed securities (CMBS) using reduced form and structural generalization models. These risk values are then interpreted as trading signals which are tested with automated trading strategies that buy undervalued and sell overvalued CMBS from November 2007 through June 2015. All three signals generate substantial positive trading profits in testing for the reduced form model but not for the structural generalization. The risk signals constructed independently of market pricing provide more profitable automated trading insights than those constructed from interactions between modeled risk measures and market spreads. In my tests of the information content of the risk signals with respect to future macroeconomic indicators, I find statistically significant evidence in keeping with recent studies. While I cannot reject CMBS efficiency, this paper’s disclosure of new risk measures, the profitability of automated strategies based on those risk measures, and the statistical significance of their forward guidance capabilities, together contributes to our understanding of CMBS risk and the credit spread puzzle debate.     

Direct Evidence of Non-trading on the London Stock Exchange

The extent of non-trading is shown to be much greater in the UK than in the more heavily researched US equity markets. Over the period 1975 to 1995 we find that almost 44% of all stocks in our sample failed to trade on the last day of a given month, a figure which is significantly higher than for stocks in the US (see Foerster and Keim, 1993). In this paper we investigate the relationship between the non-trading of UK stocks and the autoregressive and seasonal behaviour of UK stock returns. In addition, we find that stocks are much more likely to be recorded as not having traded on the last day of the month in the period prior to April 1981 than after this date. We trace this result to a reporting requirement change on the London Stock Exchange and investigate whether the change has any real implications for systematic risk estimates over this period. We also find that alternative methods for calculating betas, in the presence of thin trading, are very sensitive to stock size and to non-trading.     

THIN TRADING AND THE ESTIMATION OF BETAS: THE EFFICACY OF ALTERNATIVE TECHNIQUES

Infrequent trading induces biased estimates of the beta risk coefficient. This paper reports on the efficacy of approaches that seek to correct for this bias and documents the extent of thin trading among New Zealand securities. Parameter estimates free of the thin-trading bias are obtained. These are compared with estimates obtained using ordinary least squares (OLS) applied in the conventional manner to nonsynchronous data, with and without bias-correcting procedures. OLS beta estimates are found to be less biased, more efficient, and as consistent when compared with Dimson or Scholes-Williams estimators. Lower beta estimates are associated with lower trading frequencies.     

An unreliable canary: Insider trading,the cash flow hypothesis and the financial crisis

This paper investigates whether measures of aggregated insider trading could have predicted the wider economic change that occurred in the UK around the time of the financial crisis. Seyhun's (1988, 1992) cash flow hypothesis is the underpinning rationale driving the investigation. Within a vector auto-regressive framework, this study disentangles the relationship between returns and the activities of insiders in UK listed firms in order to validate Seyhun's assertions in this context. Findings suggest that, unlike the US, the relationship is not present. Instead, aggregate measures of trading decisions show that insiders are more likely driven by public perception than by private information.     

Alternative beta risk estimators and asset pricing tests in emerging markets: The case of Pakistan

This paper tests and compares the applicability of two asset pricing models specifically, the CAPM and the Fama–French three factor models for an emerging stock market namely, Pakistan. The paper analyses a number of beta risk estimators, including OLS, the Dimson thin trading estimator, a trade-to-trade estimator and a sample selectivity estimator. To uncover any possible influence of the return interval and the type of the market index, the analysis is carried out on three data frequencies namely daily, weekly and monthly as well as for a value and an equally weighted market index. The alternative beta estimators appear to correct thin trading bias but their effects on asset pricing tests are not visible. Moreover contrary to the expectations the test results for monthly and weekly frequencies are not promising. Instead for daily data the cross-section of returns are explained by a number of risk factors and trading volume.     

UK stock returns and robust tests of mean variance efficiency

We test both the unconditional and conditional Mean Variance Efficiency of the UK stockmarket, paying particular attention to choosing a suitable set of instruments for the conditional version of the model. By considering more carefully than previous authors the pricing of economic risk within the mean-variance framework we show that certain instruments can enhance the basic model structure. Given the tendency for financial market data to display non-constancy in variance and non-normality we employ the GMM procedure described in Hansen (1982), which requires much weaker distributional assumptions than the more traditional OLS techniques. We discuss forming portfolios of stocks using both size and dividend yield as a criterion to achieve a suitable spread of risk and return, and find that our conclusions are sensitive both to the method of portfolio formation and to the choice of estimator. This is an important finding given the problem of thin trading associated with the size ordering of UK stocks. We find some support for both the unconditional and conditional version of the CAPM, though we are cautious about our conclusions given the instability of the parameter estimates.     

An Adjustment Procedure for Predicting Betas When Thin Trading is Present: Canadian Evidence

We have incorporated effects of the process that generates true betas for TSE stocks, as well as thin trading effects, into the beta adjustment model. We note the Blume and Dimson and Marsh beta adjustment techniques aim at eliminating beta forecast error through regression tendency bias. Effects of other sources of forecast error have been ignored. We show the process generating security betas affects both cross-sectional correlation coefficient and order bias, while thin trading affects only cross-sectional correlation coefficient. We demonstrate that when OLS beta estimates are used to forecast their future risk levels, order bias accounts for 86% of forecast error, while thin trading effects account for 14% of forecast error. A beta regression tendency model which properly accounts for effects of cross-sectional correlation (which is a function of thin trading) and order bias completely abates forecast error. Our results have implications for the use of correlation coefficient to measure stability of betas across time, for beta adjustment models proposed in the literature, and for event study methodologies that rely on prediction errors.     

A note on the weak form efficiency of capital markets: The application of simple technical trading rules to UK stock prices - 1935 to 1994

Brock et al. (1992) found technical trading rules to have predictive ability with regards to the Dow Jones Index. The current paper considers whether this result can be replicated on UK data. The paper also considers whether investors could earn excess returns from technical analysis in a costly trading environment. The paper concludes that although the technical trading rules examined do have predictive ability in terms of UK data, their use would not allow investors to make excess returns in the presence of costly trading.     

Dividend Stability, Dividend Yield and Stock Returns: UK Evidence

This paper establishes an empirical role for two measures of dividend stability (as a proxy for dividend policy) in explaining UK stock returns. There is little systematic empirical evidence concerning the relation between dividend stability, dividend yield and stock returns despite the fact that a variety of theoretical models point to dividend policy as an important stock attribute. Here we construct two definitions of dividend stability, one of which involves dividend cuts, and use a sample of all listed UK firms from 1975 to 1997 to explore the relationship between stock returns and a variety of characteristics, including dividend stability. We find an inverse correlation between the stability of past dividend policy and systematic risk. Both stability measures have explanatory power over returns, but this is concentrated in January.     

Dividend Stability, Dividend Yield and Stock Returns: UK Evidence

This paper establishes an empirical role for two measures of dividend stability (as a proxy for dividend policy) in explaining UK stock returns. There is little systematic empirical evidence concerning the relation between dividend stability, dividend yield and stock returns despite the fact that a variety of theoretical models point to dividend policy as an important stock attribute. Here we construct two definitions of dividend stability, one of which involves dividend cuts, and use a sample of all listed UK firms from 1975 to 1997 to explore the relationship between stock returns and a variety of characteristics, including dividend stability. We find an inverse correlation between the stability of past dividend policy and systematic risk. Both stability measures have explanatory power over returns, but this is concentrated in January.     

Return sign forecasts based on conditional risk: Evidence from the UK stock market index

Recent theoretical works have found a link between return sign forecastability and conditional volatility. This paper compares the predictive performance of the conditional country risk and the conditional residual risk in forecasting the direction of change in the return on the UK stock market index. The conditional country risk and the conditional residual risk are estimated using the bivariate BEKK-GARCH technique and the direction of change in the UK stock market index is modelled using the binary logit approach. Both the in-sample and the out-of-sample predictions suggest that, as a predictor, the conditional residual risk is superior to the conditional country risk. Our findings support the residual risk model while contradicting the traditional capital asset pricing model (CAPM). Moreover, our tactical asset allocation simulations show that when the conditional residual risk is used in conjunction with multiple-threshold trading strategies to guide the investment decisions, the actively managed portfolio achieves greater returns than the return on a buy and hold portfolio.     

Discerning the Impact of Derivatives on Asset Risk: The Case of Canadian Banks

The Canadian banks have shown remarkable resilience to the financial crisis that intensified in the late 2008. The interesting question is whether this stability is due to their prudent lending practices to limit the original risk exposures or due to effective risk management through hedging by using financial derivatives. In this paper, we implement the option‐theoretic model of Merton to calculate the implied asset risk and discern the impact of these derivatives on the aggregate risk for Canadian banks over the period 1997–2008. An algorithm of iterative procedure is developed to impute asset value and risk from bank stock prices. Our estimates show that the risk for Canadian banks is low and even decreasing till the unfolding of the recent crises in 2008. Further analyses reveal that such low risks are not due to reliance on hedging, nor is it related to trading in derivatives, after disentangling the intertwined effects of hedging and trading. These results suggest that involvements in derivatives, in and of themselves, should not be blamed for causing the bank crises; rather, it is conservatism in controlling original risk exposures that remains fundamental for safeguarding a healthy financial system.     

Derivatives Clearing Mandates: Cure or Curse?

The Dodd-Frank Act mandates the widespread adoption of centralized clearing of OTC derivatives and also includes measures designed to move more derivatives trading onto exchanges. But, as the author points out, such a clearing mandate appears to be based on the premise that the recent experience in OTC derivatives represents a major market failure and that participants in what is now the world's largest financial market have been systematically choosing the wrong institutions for risk management and trading. In this article, the author begins by explaining why all derivatives are not cleared or exchange-traded, and why the attempt to mandate such practices (as opposed to encouraging voluntary adoption through differential capital requirements) could have serious unwanted consequences. Among such consequences is a possible increase in the very systemic risk that such mandates are supposed to prevent.     

Pairs trading in the UK equity market: risk and return

In this paper, we provide the first comprehensive UK evidence on the profitability of the pairs trading strategy. Evidence suggests that the strategy performs well in crisis periods, so we control for both risk and liquidity to assess performance. To evaluate the effect of market frictions on the strategy, we use several estimates of transaction costs. We also present evidence on the performance of the strategy in different economic and market states. Our results show that pairs trading portfolios typically have little exposure to known equity risk factors such as market, size, value, momentum and reversal. However, a model controlling for risk and liquidity explains a far larger proportion of returns. Incorporating different assumptions about bid-ask spreads leads to reductions in performance estimates. When we allow for time-varying risk exposures, conditioned on the contemporaneous equity market return, risk-adjusted returns are generally not significantly different from zero.     

The implication of discount rate changes for market timing

This study implements and tests a market timing trading rule using the public information contained in discount rate changes as signals to enter or exit the stock market. The trading rule entails entering the market on an initial discount rate cut and remaining fully invested through any subsequent cuts. Alternatively, an initial discount rate increase signals an exit from the market and remaining out of the market through any subsequent increases. It is presumed that short-term Treasury instruments are held in out-market periods. We test and report the results of this market timing strategy in comparison to a benchmark buy-and-hold strategy through the use of various investment performance measures. Analysis of ex-post returns indicates that the market timing trading rule produces higher risk-adjusted returns than a buy-and-hold-the-market strategy. Even without a risk adjustment, the returns of the strategy exceed those of the passive buy-and-hold strategy in the three subperiods analyzed. The strategy's predictive accuracy for timing the market clearly exceeds the minimum predictive accuracy suggested by earlier market timing literature. Finally, the results of the statistical analysis indicate that the strategy is successful in outguessing the market as defined in the classical Treynor and Mazuy illustration.     

市场摩擦对特质风险溢价的影响效应——基于A股主板市场的实证分析

与国外发达市场相比,我国A股主板市场的市场摩擦因素对市场微观结构和资产定价的影响更大。在防范和化解系统性风险的过程中,进一步分析市场摩擦如何作用于特质风险定价效应的问题具有重要的理论和现实意义。本文通过采用多维市场摩擦指标来代理信息不对称、交易成本、买卖限制、卖空限制、风险对冲和外部冲击,检验中国股市特质风险和预期收益率的关系,并判断出市场摩擦因素间的差异性影响机制。回归发现,市场摩擦和特质风险因子(特质波动率和特质偏度)都具有定价效应。各维度市场摩擦因素降低了股票流动性,进而增强了特质波动率的负向定价效应,部分解释了“特质波动率之谜”,但市场摩擦对特质偏度因子溢价的影响较为微弱。同时,基于特质波动率和特质偏度因子的投资策略能够产生超越CAPM、三因子和五因子模型的绝对收益,并印证了市场摩擦对特质风险因子绝对收益的影响作用。     

The Impact of Portfolio Diversification on Trading Rules Profits: Some Evidence for UK Share Portfolios

This paper demonstrates how the autocorrelation structure of UK portfolio returns is linked to dynamic interrelationships among the component securities of that portfolio. Moreover, portfolio return autocorrelation is shown to be an increasing function of the number of securities in the portfolio. Since the security interrelationships seemed to be more a product of their history of non-synchronous trading than of systematic industry-related phenomena, it should not be possible to exploit the high levels of return persistence using trading rules. We show that rules designed to exploit this portfolio autocorrelation structure do not produce economic profits.     

City goes dark: Dark trading and adverse selection in aggregate markets

We investigate the impact of dark trading on adverse selection in an aggregate market for trading UK stocks. Dark trading is linked to lower adverse selection risk and improved informational efficiency and liquidity in the aggregate market, even as liquidity declines in the lit market with dark trading. However, there is a trading value-based threshold when dark trading starts to induce adverse selection. We estimate that this threshold varies from around 9% for the most liquid stocks to 25% for the least liquid stocks. The overall average threshold for the 288 FTSE 350 stocks in our sample is 14%.     

Stress tests of capital requirements

This paper examines the performance of the leading methods for setting capital requirements for securities firms' trading books. Tests are conducted on a large sample of UK equity market makers' books over a substantial number of periods of equity market stress from 1985 to 1995. The comprehensive and building-block approaches, favoured by US and European regulators, fail to provide effective cover. Only portfolio-based, value-at-risk (VaR) type models are efficient in providing appropriate levels of capital to cover the position risk of equity trading books.     

Financial overconfidence over time: Foresight,hindsight, and insight of investors

Financial overconfidence leads to increased trading activity, higher risk taking, and less diversification. In a panel survey of online brokerage clients in the UK, we ask for stock market and portfolio expectations and derive several overconfidence measures from the responses. Overconfidence is identified in the sample in various forms. By matching survey data with participants’ transactions and portfolio holdings, we find an influence of overplacement on trading activity, of overprecision and overestimation on diversification, and of overprecision and overplacement on risk taking. We explore the evolution of overconfidence over time and identify a role of past success and hindsight on subsequent investor overconfidence in line with learning to be overconfident.