Correlation and return dispersion dynamics in Chinese markets

This paper studies the relation between firm-level return dispersions and correlations among Chinese stocks during periods of unusually large upward and downward swings. We analyze individual stock returns across 18 sectors and test if return dispersions and stock correlations show asymmetric patterns for extreme up and down markets. Evidence from studies on U.S. stocks suggests that equity return correlations tend to be much greater on the downside than on the upside and that the degree of comovement gets even stronger during extreme market states. However, in the case of Chinese stock market, we find that higher downside correlations apply to only stocks within the Financial sector. With the exception of Financial stocks, we find that stock correlations are significantly higher during up markets, rather than down markets. Regarding firm-level return dispersions, our findings are consistent with rational asset pricing model predictions. We find that equity return dispersions are significantly higher during periods of large price changes.     

Volatility and covariation of financial assets: A high-frequency analysis

Using high frequency data for the price dynamics of equities we measure the impact that market microstructure noise has on estimates of the: (i) volatility of returns; and (ii) variance–covariance matrix of n assets. We propose a Kalman-filter-based methodology that allows us to deconstruct price series into the true efficient price and the microstructure noise. This approach allows us to employ volatility estimators that achieve very low Root Mean Squared Errors (RMSEs) compared to other estimators that have been proposed to deal with market microstructure noise at high frequencies. Furthermore, this price series decomposition allows us to estimate the variance covariance matrix of n assets in a more efficient way than the methods so far proposed in the literature. We illustrate our results by calculating how microstructure noise affects portfolio decisions and calculations of the equity beta in a CAPM setting.     

The risk in hedge fund strategies: Theory and evidence from long/short equity hedge funds

Theory suggests that long/short equity hedge funds' returns come from directional as well as spread bets on the stock market. Empirical analysis finds persistent net exposures to the spread between small vs large cap stocks in addition to the overall market. Together, these factors account for more than 80% of return variation. Additional factors are price momentum and market activity. Combining two major branches of hedge fund research, our model is the first that explicitly incorporates the effect of funding (stock loan) on alpha. Using a comprehensive dataset compiled from three major database sources, we find that among the three thousand plus hedge funds with similar style classification, less than 20% of long/short equity hedge funds delivered significant, persistent, stable positive non-factor related returns. Consistent with the predictions of the Berk and Green (2004) model we find alpha producing funds decays to “beta-only” over time. However, we do not find evidence of a negative effect of fund size on managers' ability to deliver alpha. Finally, we show that non-factor related returns, or alpha, are positively correlated to market activity and negatively correlated to aggregate short interest. In contrast, equity mutual funds and long-bias equity hedge funds have no significant, persistent, non-factor related return. Expressed differently, L/S equity hedge funds, as the name suggests, do benefit from shorting. Besides differences in risk taking behavior, this is a key feature distinguishing L/S funds from long-bias funds.     

Trading frequency and asset pricing on the London Stock Exchange: Evidence from a new price impact ratio

This study proposes a new price impact ratio as an alternative to the widely used Amihud’s (2002) Return-to-Volume ratio. We demonstrate that the new price impact ratio, which is deemed Return-to-Turnover ratio, has a number of appealing features. Using daily data from all stocks listed on the London Stock Exchange over the period 1991–2008, we provide overwhelming evidence that this ratio, while being unequivocal to construct and interpret, is also free of a size bias. More importantly, it encapsulates the stocks’ cross-sectional variability in trading frequency, a relatively neglected but possibly important determinant of stock returns given the recently observed trends in financial markets. Overall, our findings argue against the conventional wisdom that there is a simple direct link between trading costs and stock returns by strongly suggesting that it is the compound effect of trading frequency and transaction costs that matters for asset pricing, not each aspect in isolation.     

Liquidity, analysts, and institutional ownership

In this paper, we investigate the empirical relationship between institutional ownership, number of analysts following and stock market liquidity. We find that firms with larger number of financial analysts following have wider spreads, lower market quality index, and larger price impact of trades. However, we find that firms with higher institutional ownership have narrower spreads, higher market quality index, and smaller price impact of trades. In addition, we show that changes in our liquidity measures are significantly related to changes in institutional ownership over time. These results suggest that firms may alleviate information asymmetry and improve stock market liquidity by increasing institutional ownership. Our results are remarkably robust to different measures of liquidity and measures of information asymmetry.     

Modeling default probabilities: The case of Brazil

Using disaggregated data from the Brazilian stock market, we calculate default probabilities for 30 different economic sectors. Empirical results suggest that domestic macroeconomic factors can explain these default probabilities. In addition, we construct the Minimum Spanning Tree (MST) and the ultrametric hierarchical tree with the MST based on default probabilities to disclose common trends, which reveals that some sectors form clusters. The results of this paper imply that macroeconomic variables have distinct effects on default probabilities, which is important to take into account in credit risk modeling and the generation of stress test scenarios.     

Control-ownership wedge and investment sensitivity to stock price

This study examines whether insiders’ incentives for private control benefits affect investment sensitivity to stock price. While Chen et al. (2007) link stock price informativeness to firms’ learning from the stock market, we offer an alternative agency-cost based explanation. Using a total of 2822 firms from 22 countries in East Asia and Western Europe, we document a strong negative association between control-ownership wedge and investment-q sensitivity, suggesting that insiders’ incentives for private control benefit reduce their propensity to listen to the market. Furthermore, the negative impact of wedge on investment-q sensitivity is primarily driven by sub-optimal investments. Overall, we provide evidence that agency problem is an important factor that determines the learning from the stock market in capital allocation.     

New evidence on oil price and firm returns

In this paper, we examine the relationship between oil price and firm returns for 560 US firms listed on the NYSE. First, we find that oil price affects returns of firms differently depending on their sectoral location. Second, we find strong evidence of lagged effect of oil price on firm returns. Third, we test whether oil price affects firm returns based on different regimes and find that in five out of the 14 sectors this is indeed the case. Finally, we unravel that oil price affects firm returns differently based on firm size, implying strong evidence of size effects.     

Cross hedging under multiplicative basis risk

Cross hedging price risk in an incomplete financial market creates basis risk. We propose a new way of modeling basis risk where price risk and basis risk are combined in a multiplicative way. Under this specification, positive prudence is a necessary and sufficient condition for underhedging in an unbiased market. Using the example of cross hedging jet fuel price risk with crude oil futures, we show that the new specification is superior in describing the price series and that optimal cross hedges differ significantly from those derived under the traditional additive cross hedging model.     

A computing bias in estimating the probability of informed trading

This study identifies a factor that leads to a bias in estimating the probability of informed trading (PIN), a widely-used microstructure measure. It is shown that, along with the numerical maximization of the likelihood function for PIN, the floating-point exception (i.e., overflow or underflow) may eliminate feasible solutions to the actual parameters in the optimization problem. Approximately 44% of PIN estimates for recent stock market data may have been subject to a downward bias that is more pronounced for active stocks than for inactive stocks. This study develops a remedy to mitigate the resulting bias.     

The impact of naked short selling on the securities lending and equity market

This paper examines the impact of naked short selling on equity markets where it is restricted to securities on an approved list. Consistent with Miller's (1977) intuition, stocks with the highest dispersion of opinions and short sale constraints are the only stocks to exhibit significant and negative abnormal returns in the post-event period. We also find slightly higher stock return volatility and a small reduction in liquidity when naked short sales are allowed. Overall, it impairs market quality (liquidity and volatility), although there appears to be some improvement in price efficiency in stocks with high short sale constraints.     

Is market fragmentation harming market quality?

We examine how fragmentation is affecting market quality in US equity markets. We use newly available trade reporting facilities (TRFs) data to measure fragmentation, and we use a variety of empirical approaches to compare execution quality and efficiency of stocks with more and less fragmented trading. We find that fragmentation affects all stocks; more fragmented stocks have lower transactions costs and faster execution speeds; and fragmentation is associated with higher short-term volatility but greater market efficiency, in that prices are closer to being a random walk. Our results that fragmentation does not appear to harm market quality are consistent with US markets being a single virtual market with multiple points of entry.     

Short sales and speed of price adjustment: Evidence from the Hong Kong stock market

We present empirical evidence that short sales contribute to market efficiency by increasing the speed of price adjustment to not only private/public firm-specific information but also market-wide information. Shortable stocks are characterized by weaker trade continuity and stronger quote reversals. They adjust faster to new information than non-shortable counterparts. These findings remain robust even in an “up” market condition in which short sales are not binding. The amount of information incorporated in each trade is also significantly higher for shortable than non-shortable stocks in both “up” and “down” market conditions. After controlling for firm size, trading volume, liquidity, price and option trading, short sales stand out as one of the significant factors that speed up the price adjustment.     

Universal features of price formation in financial markets: perspectives from deep learning

Using a large-scale Deep Learning approach applied to a high-frequency database containing billions of market quotes and transactions for US equities, we uncover nonparametric evidence for the existence of a universal and stationary relation between order flow history and the direction of price moves. The universal price formation model exhibits a remarkably stable out-of-sample accuracy across a wide range of stocks and time periods. Interestingly, these results also hold for stocks which are not part of the training sample, showing that the relations captured by the model are universal and not asset-specific.

The universal model—trained on data from all stocks—outperforms asset-specific models trained on time series of any given stock. This weighs in favor of pooling together financial data from various stocks, rather than designing asset- or sector-specific models, as is currently commonly done. Standard data normalizations based on volatility, price level or average spread, or partitioning the training data into sectors or categories such as large/small tick stocks, do not improve training results. On the other hand, inclusion of price and order flow history over many past observations improves forecast accuracy, indicating that there is path-dependence in price dynamics.     

Modeling and forecasting expected shortfall with the generalized asymmetric Student-t and asymmetric exponential power distributions

Financial returns typically display heavy tails and some degree of skewness, and conditional variance models with these features often outperform more limited models. The difference in performance may be especially important in estimating quantities that depend on tail features, including risk measures such as the expected shortfall. Here, using recent generalizations of the asymmetric Student-t and exponential power distributions to allow separate parameters to control skewness and the thickness of each tail, we fit daily financial return volatility and forecast expected shortfall for the S&P 500 index and a number of individual company stocks; the generalized distributions are used for the standardized innovations in a nonlinear, asymmetric GARCH-type model. The results provide evidence for the usefulness of the general distributions in improving fit and prediction of downside market risk of financial assets. Constrained versions, corresponding with distributions used in the previous literature, are also estimated in order to provide a comparison of the performance of different conditional distributions.     

Locals, foreigners, and multi-market trading of equities: Intraday evidence from Thailand

We study stock market orders and trades in a developing country, Thailand, where foreign ownership limits partially segment local and foreign investors into two distinct markets. Some foreigners forgo voting rights and distributions to trade on the “local board”, while some locals forgo such benefits and pay a price premium to trade on the “foreign board”. Regardless of nationality, these cross-market traders typically submit orders when liquidity is high, fill orders at relatively beneficial prices, exploit patterns in stock prices across markets, display profitable holding-period returns, and enhance price discovery. This suggests that skilled, informed trading that affects market quality does not depend on trader nationality.     

Do foreigners facilitate information transmission in emerging markets?

Using the degree of accessibility of foreign investors to emerging stock markets, or investibility, as a proxy for the extent of foreign investments, we assess whether investibility has a significant influence on the diffusion of global market information across stocks in emerging markets. We show that greater investibility reduces price delay to global market information. We also find that returns of highly investible stocks lead those of noninvestible stocks because they incorporate global information more quickly. These results are consistent with the idea that financial liberalization in the form of greater investibility yields informationally more efficient stock prices in emerging markets.     

Limit Order Adjustment Mechanisms and Ex-Dividend Day Stock Price Behavior

Unlike the NYSE, the Toronto Stock Exchange (TSX) does not adjust prices in the outstanding limit orders on ex-dividend days. We find that TSX ex-day stock price behavior differs from that on the NYSE in several key aspects. In each case, the TSX ex-day behavior is consistent with the lack of a limit order adjustment mechanism. Our findings confirm that market microstructure is an important factor that contributes to the observed Canadian ex-day price behavior. Our findings also resolve the puzzle of the relatively small ex-day price drop in Canada.     

Investor Attention and Time‐varying Comovements

This paper analyses the effect of an increase in market‐wide uncertainty on information flow and asset price comovements. We use the daily realised volatility of the 30‐year treasury bond futures to assess macroeconomic shocks that affect market‐wide uncertainty. We use the ratio of a stock's idiosyncratic realised volatility with respect to the S&P500 futures relative to its total realised volatility to capture the asset price comovement with the market. We find that market volatility and the comovement of individual stocks with the market increase contemporaneously with the arrival of market‐wide macroeconomic shocks, but decrease significantly in the following five trading days. This pattern supports the hypothesis that investors shift their (limited) attention to processing market‐level information following an increase in market‐wide uncertainty and then subsequently divert their attention back to asset‐specific information.     

Price discovery in currency markets

This paper examines the price discovery process in currency markets, basing its analysis on the pivotal distinction between the customer (end-user) market and the interdealer market. It first provides evidence that this price discovery process cannot be based on adverse selection between dealers and their customers, as postulated in standard models, because the spreads dealers quote to their customers are not positively related to a trade’s likely information content. The paper then highlights three factors familiar in the literature – fixed operating costs, market power, and strategic dealing – that may explain the cross-sectional variation in customers’ spreads. The paper finishes by proposing a price discovery process relevant to liquid two-tier markets and providing preliminary evidence that this process applies to currencies.