Brian Roseman

Retail option traders are typically net purchasers of short-dated options, especially out-of-the money contracts, whereas they frequently sell long-dated options. Using retail brokerage platform outages as shocks to trading, we find that outages are associated with commensurate demand shocks to implied volatility. Outages produce lower implied volatility on average, with stronger reductions for options that tend to be purchased by retail investors. In contrast, implied volatility increases for long-dated options during outages, consistent with reduced retail writing activity. The findings suggest that retail demand pressure can have important effects on the implied volatility term structure, moneyness curve, and call-put spread.

We show that secondary market activity impacts the cost of issuing new debt in the primary market. Specifically, firms with existing illiquid debt have higher costs when issuing new debt. We also find that with the improvement in the price discovery process brought about by introduction of TRACE reporting, firms that became TRACE listed subsequently had a lower cost of debt. The results indicate that the secondary market functions of liquidity and price discovery are important to the primary market. The results offer important implications for regulators and managers who are in a position to impact secondary market liquidity and price discovery. The results are also important for understanding the connection between the secondary market and the real economy.

We examine how political partisanship influences firm risk during live Monetary Policy Report to Congress (MPRC) hearings. Our research reveals that partisanship in Congress alleviates the negative impact of policy risk on firm risk. We attribute this risk mitigation to political gridlock inhibiting future policy changes. Consistent with this conjecture, we find that firms facing higher policy risk exhibit a more significant reduction in firm risk during MPRC hearings when Congress is divided between parties compared to when a single party controls both chambers. Additionally, we observe a decrease in lobbying expenditures when partisanship is high, and Congress is split.

We propose a new measure of price discovery, New Leadership Share (NLS), that attributes permanent information flow to individual markets using a uniquely identified structural moving average model. NLS quantifies each market's contribution to permanent price innovations as a proportion of total informational leadership and offers key technical advantages, including uniqueness and adherence to standard statistical asymptotics. We derive closed-form solutions and analytical standard errors for bivariate markets and provide a framework that extends naturally to multiple markets without the variable ordering problem. Simulation results show that NLS consistently outperforms three widely used benchmarks. Empirical analysis of 2023 data finds that exchange-traded funds and front-month futures markets share equal leadership relative to the S&P 500 spot index.

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.

We study brokerage platform outages to examine the impact of retail investors on financial markets. We contrast outages at Robinhood, which caters to inexperienced investors, with outages at traditional retail brokers. For stocks with high retail interest, we find that negative shocks to Robinhood investor participation are associated with reduced market order imbalances, increased market liquidity, and lower return volatility, whereas the opposite relations hold following outages at traditional retail brokerages. The findings suggest that herding by inexperienced investors can create inventory risks that harm liquidity in stocks with high retail interest, while other retail trading improves market quality.

We study the effects of exchange uplisting from the modern over-the-counter (OTC) markets on liquidity, volatility, and price discovery. In a series of difference-in-differences tests, we find that for a sample of OTC treatment firms that uplist to the NASDAQ, New York Stock Exchange (NYSE), or NYSE MKT, relative to matched control firms, liquidity improves dramatically after listing. We also show that price discovery improves for treatment firms vis-à-vis control firms after listing. The results contribute to the discussion surrounding the facilitation of capital formation and offer important insights to investors, managers, and exchange officials.

We examine the impact of the 2016 U.S. SEC Tick Size Pilot Program on transaction costs in both the equity and options markets. We find that an increase in the tick size from one-cent to five-cents increases percent bid-ask spreads for test stocks vis-à-vis control stocks; however, this increase is substantially reduced when the test stocks have actively traded options. We also find a spillover effect in transaction costs from the underlying stock market to the options market, as both percent bid-ask spreads and implied volatility spreads widen in options for test stocks versus control stocks. Lastly, we find reversal effects at the conclusion of the pilot program, as percent spreads in both the equity and options markets narrow when the tick size is reduced.

We use the 2016 U.S. SEC tick size pilot to examine the effects of an increase in the minimum price variation on limit order book liquidity in NASDAQ-listed stocks on the NASDAQ exchange. For treatment stocks with an average pre-pilot quoted spread less than $0.05, the tick size increase is binding and leads to a significant decrease in liquidity in the limit order book. Specifically, the implied cost to trade at and away from the best bid and offer prices increases and the limit order book becomes less resilient - the amount of time required for a deviation in liquidity to return to its long-run mean. For treatment stocks with an average pre-pilot quoted spread of at least $0.05, the tick size increase is non-binding and leads to either a slight decrease, or no change in limit order book liquidity.

We provide a novel test of information-based theories of price clustering by examining trade, order, and the National Best Bid and Offer (NBBO) quote price clustering during periods when information is removed from the market. We use a natural experiment of short-sale restrictions resulting from Securities and Exchange Commission (SEC) Rule 201 to more effectively determine the impact of information on price clustering. We find evidence of increased price clustering for trades, orders, and NBBO prices during short-sale restrictions. Overall, our findings indicate that short-sale restrictions harm the price discovery process and lead to a reduction in market efficiency.

We study odd-lot trades in U.S. Equities. NYSE- and NASDAQ-listed securities trade and report on various markets, and in this paper, we examine odd-lot activity in these venues. We also look at odd-lot trading on December 9, 2013, when odd-lot trades began reporting to the consolidated public tapes. We find a small increase in odd-lot trading occurring after odd-lot trades are reported to the consolidated tape, which is inconsistent with the belief that some odd-lot trades are larger trades broken up to avoid reporting to the consolidated tape. Odd-lot trades have disproportionately high cumulative price changes relative to the level of odd-lot trading. We also find a positive relation between odd-lot order imbalance and returns.

We investigate the degree to which orders are aggressively priced, paying particular attention to odd lot orders, and examine whether odd lot orders are being successfully used in stealth trading strategies. We find that odd lot orders execute at higher frequencies than larger orders, which is due to odd lot orders being aggressively priced. We find that microstructure changes have not altered the nature of price aggressiveness, but its determinants hold different explanatory power for odd lot orders. We find evidence that informed traders are shredding their orders into odd lot orders and stealth trading is permeating odd lot denominations.

We examine the cancellation of erroneous executions on equity exchanges in the United States. Self-regulatory organizations of the National Market System are able to cancel large numbers of trades that are deemed to be clearly erroneous. We explore the market response to cancellations by comparing erroneous trades against matched trades that are eligible to be deemed erroneous, but are never reported as erroneous. We analyze the relation between the cancellation of erroneous executions and the market environment, paying particular attention to the information dissemination process from exchange officials to market participants. We find that clearly erroneous executions have detrimental effects on market quality.

1-share trades are the most common odd lot trade size, accounting for 9.62% of all odd lot transactions and 3.65% of all trades on NASDAQ in 2012. While 50.41% of 1-share trades result from broken orders, 34.89% of 1-share trades are intentional. We provide substantial evidence that traders use 1-share trades to “ping” for hidden liquidity. In particular, our results indicate that 1-share trades are disproportionately aggressive and also execute against hidden liquidity more than any other odd lot trade size. We also find a relative increase in trading immediately following a 1-share trade. Our results are in line with Clark-Joseph (2014), who suggests that traders may use small, unprofitable trades to detect information from other traders. Specifically, 1-share trades represent the minimum cash outlay necessary to trade, while simultaneously producing the smallest possible effects on a market maker's inventory, and in turn, a security's price.

Using data consisting of Credit Default Swap (CDS) spreads, this study examines CDS spreads for nearly all European countries surrounding the August 5th, 2011 sovereign credit rating downgrade of the United States. While U.S. CDS spreads remained at relatively normal levels, we find a surge in European CDS spreads during the ten-day period surrounding the U.S. downgrade. At their highest level during this ten-day period, CDS spreads were nearly 25% higher than normal indicating that the CDS market perceived that the U.S. downgrade dramatically affected the likelihood of default in European countries. We show that European countries with the smallest GDP per capita and countries that had not recently been downgraded had the largest increase in CDS spreads. Our multivariate tests also show that countries that use the EURO also had the largest increases in CDS spreads.