Kingsley Y. L. Fong

International Evidence on Algorithmic Trading

We study the effect of algorithmic trading (AT) on market quality between 2001 and 2011 in 42 equity markets around the world. We use exchange co-location service that increases AT as an exogenous instrument to draw causal inference of AT on market quality. On average, AT improves liquidity and informational efficiency but increases short-term volatility. AT also lowers execution shortfalls for buy-side institutional investors. Our results are surprisingly consistent across markets and thus across a wide range of AT environments. We further document that the beneficial effect of AT is stronger in large stocks than in small stocks.

What Are the Best Liquidity Proxies for Global Research

Liquidity plays an important role in global research. We identify high-quality liquidity proxies based on low-frequency (daily) data, which provide 1,000× to 10,000× computational savings compared to computing high-frequency (intraday) liquidity measures. We find that: (i) Closing Percent Quoted Spread is the best monthly percent-cost proxy when available, (ii) Amihud, Closing Percent Quoted Spread Impact, LOT Mixed Impact, High–Low Impact, and FHT Impact are tied as the best monthly cost-per-dollar-volume proxy, (iii) the daily version of Closing Percent Quoted Spread is the best daily percent-cost proxy, and (iv) the daily version of Amihud is the best daily cost-per-dollar-volume proxy.

Do Security Analysts Discipline Credit Rating Agencies

Earlier work exploiting brokerage house mergers identified that security analyst coverage leads to more competitive and less optimistically biased earnings forecasts. Since the earnings forecasts for a firm’s equity enter directly into the credit ratings of a firm’s debt, we test the hypothesis that security analyst coverage also disciplines credit rating agencies. We indeed find that a drop in analyst coverage due to these mergers leads to greater optimism-bias in credit ratings, especially for firms with little bond analyst coverage to begin with and for firms that are close to default. This coverage-induced shock leads to less informative ratings about future defaults and downgrades, and more subsequent bond security mispricings. Even though analysts do not directly compete with credit rating agencies, analyst reports about a firm’s equity nonetheless discipline what credit rating agencies can say about the firm’s debt.

Institutional Trading Around the Ex-Dividend Day

This study uses the trading records of institutional equity funds to examine their ex-dividend trading behaviour. We argue that trading is influenced by the tax incentives facing the fund, the characteristics of individual stocks and by changes in tax legislation. In aggregate, institutions trade to avoid the dividend and franking credit. Changes in tax incentives and the fund’s tax status also affect ex-dividend day trading, with unit trusts dominating the dividend avoidance trades. The results indicate that taxes, transactions costs and the cum-dividend price run-up influence the trading of institutional investors around the ex-dividend day.

Stock market closure and intraday stock index futures market volatility: “contagion”, bid–ask bias or both?

Abstract Chang et al. [Journal of Business 68 (1) (1995) 61] examine the impact of the closure of the New York Stock Exchange (NYSE) on S&P500 stock index futures traded on the Chicago Mercantile Exchange. They document a decline in futures market volatility immediately after the close of the NYSE, and an increase 15 minutes later when the futures market closes. They attribute this to contagion–i.e. a decline in information transfer from equities to futures markets following the closure of the underlying market. This paper examines the impact of the extension of trading hours in Hang Seng Index futures traded on the Hong Kong Futures Exchange on the 20 November, 1998 to 15 minutes after the close of the underlying market (the Stock Exchange of Hong Kong). Using the unique natural experiment provided by this change, a pattern similar to US markets is documented for the Hang Seng Index Futures following the change in trading hours. This provides strong evidence that the intraday pattern in volatility is caused by market closure. Unlike US futures exchanges, price reporters on the floor of the Hong Kong Futures Exchange collect quote data in addition to trade data. This data facilitates a test of another plausible microstructure explanation for the observed behaviour–bid–ask bounce associated with trading activity. This paper provides evidence that bid–ask bounce also explains part of the observed intraday behaviour in price volatility.

Overnight futures trading: now even Australia and US have common trading hours

Overnight futures trading is available in USA, France and Australia. The overnight prices can be used to compute 24 h returns for two international markets over exactly the same time interval, even though the countries in which these markets operate are in completely different time zones. These synchronous returns make it possible to compute accurate daily correlation measures, which can for example be used for daily value-at-risk (VaR). Using Australian overnight index futures prices we find the correlation between USA and Australia to be about 55%, in stark contrast to near-zero correlation measures obtained from non-synchronous closing prices.

Follow the leader: fund managers trading in signal‐strength sequence*

When fund managers trade sequentially in the same direction, the information confirmation hypothesis predicts the long‐term profitability of the leader trade to be increasing in the number of subsequent trades. The information cascade hypothesis predicts a non‐positive relationship. Using active equity funds’ daily trading data, we document a transition from information confirmation to information cascades as the number of followers increase. We find that highly disguised multiple‐broker packages exhibit higher market impact, higher long‐term returns and are associated with fewer followers. Our study also documents that lead fund managers face portfolio risk constraints in trading on private information.

Taxes, Order Imbalance and Abnormal Returns around the ex-Dividend day: Taxes, Order Imbalance and the Ex-Dividend Day

A costly arbitrage model, developed for the Australian imputation tax system, shows that stocks paying dividends with a tax credit are likely targets for ex-dividend arbitrage. We show that order imbalance, based on the direct observation of buyer and seller initiated trades, is a key factor in price movements around the ex-dividend day. Buying pressure before the ex-dividend day aimed at capturing the dividend and tax credit leads to an increase in prices that subsequently reverse in the ex-dividend period. This effect is concentrated in those stocks distributing a tax credit with their dividend payments. The price pressure resulting from order imbalance is substantially higher around the ex-dividend day relative to the effect observed outside this period. Our results reject the model of Frank and Jagannathan (1998) that bid-ask bounce is responsible for the ex-day premium and provide support for explanations based on taxes, transaction costs and incomplete price adjustment on the ex-day.

Are Volatility Over Volume Liquidity Proxies Useful For Global Or US Research

We examine a general class of volatility over volume liquidity proxies as computed from low frequency (daily) data. We start from the Kyle and Obizhaeva (2016) hypothesis of transaction cost invariance to identify a new volatility over volume liquidity proxy “VoV(%Spread)” for percent spread cost and a new volatility over volume liquidity proxy “VoV(λ)” for the slope of the transaction cost function “λ”. We test the monthly and daily versions of these new and existing liquidity proxies against liquidity benchmarks as estimated from high frequency (intraday) data on both a global and US basis. We find that both the monthly and daily versions of VoV(λ) dominate the equivalent versions of Amihud and other cost-per-dollar-volume proxies on both a global and US basis. We also find that both the monthly and daily versions of VoV(%Spread) dominate the equivalent versions of other percent-cost proxies for US studies that cover pre-1993 years. In a case study, we find that our new VoV liquidity proxies yield different research inferences than the best previous liquidity proxies from the prior literature. The success of our invariance-based liquidity proxies across exchanges and over time supports the prediction of Kyle and Obizhaeva of a specific functional form for transaction costs across exchanges and over time.

The Asymmetric Effect of Implied Volatility on Liquidity Provision

This paper examines how liquidity provision is affected by market sentiment prior to scheduled earnings announcements. We use different measures of volatility to proxy for market-wide sentiment and stock-specific uncertainty to examine how they affect traders’ liquidity provision in the lead-up to earnings announcements. Our results show that traders reduce their provision of liquidity as volatility increases before scheduled announcements. This result is asymmetric with more pronounced effects on the bid side. Changes in the market depth closer to the top of the limit order book are associated with market-wide sentiment (VIX), whereas stock-specific implied volatility drives liquidity provision of value traders on the order book further away from the best-bid-offer price.