James J. Angel

A Close Look at Short Selling on Nasdaq

We examine the frequency of short selling in stocks listed in the Nasdaq market. Using previously unavailable transaction data, we can report several findings: (1) overall, 1 of every 42 trades involves a short sale; (2) short selling is more common among stocks with high returns than stocks with weaker performance; (3) actively traded stocks experience more short sales than stocks of limited trading volume; (4) short selling varies directly with share price volatility; (5) short selling does not appear to be systematically different on various days of the week; and (6) days of high short selling precede days of unusually low returns. To examine the frequency of short selling, we used a unique data set that identifies all short-sale transactions reported to Nasdaq through its ACT trade-reporting system during the fall of 2000. Our study differs from most prior empirical studies in that our sample consists of day-by-day short selling of individual stocks by investors expecting price declines whereas most prior research relied on the once-a-month report of total short interest. To investigate the frequency of short selling, we used two complementary metrics. The first is the “percentage of short trades,” which is the ratio of short trades to the total number of trades in a stock within a day. This percentage addresses the likelihood that the seller in a transaction is shorting. The second is “percentage of shorted shares,” which is the ratio of the shares in the short trades to the total number of a companys shares traded in the day. This percentage concerns the probability that a traded share is being shorted. We found that, on average, the seller in 1 of every 42 trades is shorting and that 1 of every 35 traded shares is a shorted share. These results indicate that short sellers tend to transact in larger volume than the typical nonshorting investor. The second issue we examined is whether short selling varies with a stocks price performance in a manner that is consistent with either a momentum or contrarian investing style. After partitioning the sample into quintiles based on the within-sample percentage change in the stocks price, we found that both the percentage of short trades and the percentage of shorted shares were highest for the quintiles containing the stocks with the highest returns and lowest for those with the lowest returns. These results are most consistent with the proposition that short sellers tend to follow a contrarian strategy. Next, we addressed the link between short selling and trading volume. The liquidity offered by high-volume stocks potentially reduces the probability that the short seller will experience a “short squeeze” (when the shares that have been lent to the investor for the short sale are recalled). After partitioning the sample according to trading volume, we found that both the percentage of short trades and the percentage of shorted shares declined monotonically with trading volume. Therefore, as hypothesized, short sellers tend to be more interested in high-volume stocks. Fourth, we examined the relationship between short selling and stock price volatility. Specifically, we searched for any contemporaneous connection between the two. After partitioning the sample into quintiles according to the standard deviation of within-sample stock return, we found that short selling is highest for the most volatile stocks and lowest for low-volatility stocks. A number of prior studies documented a trend in which returns on certain days of the week tend to be significantly lower than returns on other days. Therefore, we considered whether any such day-of-the-week pattern is to be found in short selling. Somewhat surprisingly, our results indicate little day-to-day variation in short selling. Finally, we examined the potential short-term profitability of short selling by examining market- adjusted returns following days of significantly high short selling. We found statistically significant three-day excess returns of −1.23 percent following days of high short selling, implying that an investor who opens a short position on a day of high short selling in a stock and closes it three days later can obtain a positive net profit.

The rise and fall of the Amex Emerging Company Marketplace

In 1992, the AMEX launched the Emerging Company Marketplace (ECM) to trade the stocks of small but growing companies. After listing on the ECM, stocks experienced dramatic decreases in bid-ask spreads, but showed mixed results on price and trading volume. News coverage of the ECM stocks rose significantly. Yet few firms chose to list on the new ECM, and the AMEX closed it in 1995. What went wrong? A series of scandals tarred the image of the exchange. Furthermore, auction markets historically have not fared well against dealer markets for very small firms. For some companies, it is worthwhile to subsidize the distribution channel for their stock by listing in a higher transaction cost dealer market, which gives dealers incentive to publicize the firm.

Factors Affecting the Value of the Stock Voting Right: Evidence from the Swiss Equity Market

In Switzerland, voting share sell for 13% more than nonvoting shares. After allowing for differences in liquidity and transferability restrictions, the pure voting right itself is worth about 18%.

Short Selling and the Weekend Effect in Nasdaq Stock Returns

We examine daily short selling of Nasdaq stocks to explore whether speculative short selling causes a significant portion of the weekend effect in returns. We identify a weekend effect in speculative short selling whereby it constitutes a larger percentage of trading volume on Mondays versus Fridays. We find an opposite effect in dealer short selling, consistent with market makers adding liquidity and stability. Our main finding is that speculative short selling does not explain an economically meaningful portion of the weekend effect in returns, even among the firms most that are most actively shorted. This finding contradicts some prior studies.

When Finance Meets Physics: The Impact of the Speed of Light on Financial Markets and Their Regulation

Modern physics has demonstrated that matter behaves very differently as it approaches the speed of light. This paper explores the implications of modern physics to the operation and regulation of financial markets. Information cannot move faster than the speed of light. The geographic separation of market centers means that relativistic considerations need to be taken into account in the regulation of markets. Observers in different locations may simultaneously observe different “best” prices. Regulators may not be able to determine which transactions occurred first, leading to problems with best execution and trade-through rules. Catastrophic software glitches can tunnel through seemingly impregnable quality control procedures.

Should Owners of Nasdaq Stocks Fear Short-Selling?

It is interesting to look at the daily association between market-adjusted returns of Nasdaq stocks and the percentages of trading volume attributable to dealers and to their speculator customers. An unusually detailed and informative set of Nasdaq trading records reveals significantly negative average market-adjusted returns when speculative short-selling exceeds 10%. At the more common (lower) levels of speculative short-selling, average market-adjusted returns tend to be near zero. Even when there is considerable speculative short-selling, the associated negative market-adjusted return is, on average, only 4 to 6 basis points for each percentage point of short-selling. For many stocks, days of high speculative short-selling are not typically days of unusually low market-adjusted returns. Finally, high levels of short-selling by Nasdaq dealers are more common for stocks earning relatively higher market-adjusted returns.

Nonstandard-Settlement Transactions

While most trades settle in three business days, nonstandard-settlement trades often settle on the same business day. This article examines reasons behind nonstandard settlements and addresses situations that are useful to empirical database users in deciding whether or not to include these trades.

ETF Transaction Costs Are Often Higher Than Investors Realize

Exchange-traded funds (ETFs) and other exchange-traded products (ETPs) provide simple and efficient diversification and exposure to a wide range of investment asset classes. However, the apparently small bid–ask spreads for many ETFs can mask much higher transaction costs when ETF market prices deviate significantly from contemporaneous net asset values (NAVs). The deviations from NAV are often much greater than the bid–ask spreads suggest. The authors report that ETF closing prices are more than 90 basis points away from the NAV approximately 10% of the time. Investors’ market-on-close (MOC) orders are likely to be executed at prices below the NAV.

Practical Applications of ETF Transaction Costs Are Often Higher Than Investors Realize

The bid–ask spread alone does not tell the true cost of trading an exchange-traded fund (ETF). The market prices on most ETFs frequently deviate from their net asset value (NAV) because of fluctuations in market demand and supply. An investor needs to measure the true cost of an ETF trade as the difference between the funds current transaction price and its NAV at that point in time. Author James Angel , from Georgetown University , discusses his article, ETF Transaction Costs Are Often Higher Than Investors Realize , published in The Journal of Portfolio Management ’s Spring 2016 issue. In this article, Angel and co-authors Todd Broms of Broms Asset Management and Gary Gastineau of ETF Consultants.com offer their analysis of how and why ETF market prices deviate from their NAVs.

The Evolving Regulation of Financial Networks

It is no secret that financial markets are changing rapidly and that regulation needs to change to keep up with the changes in the industry. In order to understand the evolution of market regulation, it is important to understand not only the many trends affecting financial markets, but also the network economics that dominate the industrial organisation of the industry. This leads to many similarities between the stock exchange industry and other network industries such as telecommunications, transportation, and computer operating systems.