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On May 18, 2014, AT&T Inc., the second-biggest U.S. mobile-phone carrier, agreed to acquire DirecTV, a satellite-television company, for $49 billion in cash and stock. However, the merger’s conditions and terms are complicated as the stock exchange ratio is contingent on the volume-weighted average AT&T stock price over a 30-day period that is three trading days prior to the date when the merger becomes effective.

Using a contingent claims pricing approach, we model DirecTV’s theoretical value based on the merger’s conditions and terms. It is shown that the theoretical DirecTV stock value is analogous to the sum of the present value of a cash offer, plus owning shares of the AT&T stock, and short volume-weighted average price (VWAP) call spreads. Using three different option-pricing models, DirecTV’s stock valuation model is tested with the market data. Empirical results show that on average, DirecTV’s stock was consistently priced at a discount during the sample period, and Funahashi and Kijima’s (2017) VWAP option model works better than Black and Scholes’ (1973) plain vanilla option model and Levy’s (1992) average-price option model.

The purpose of this paper is to conduct an empirical analysis of the trading performance of US corporate insiders.

Based on the volume weighted average price (VWAP), the authors propose a metric to measure the trading performance of US corporate insiders: trading alpha. This metric is clean of the contamination effect from insiders' own trades. The authors apply this metric to examine whether insiders can beat the market when they trade.

It is found that corporate insiders achieve positive trading alpha on both purchases and sales of stocks on average. The existence of a positive trading alpha is robust to controlling for firm, trading and insider characteristics. More importantly, evidence is found for the persistence in corporate insiders' trading performance. Those insiders who traded well in the past continue to trade well over time. Those who well execute in purchases of stocks also perform well in sales.

This paper extends the notion of beating the market from the investment profession to the trading profession. Skyrocketing corporate insider trades provide a natural setting under which to examine the trading performance. The findings that: insiders can beat the market on average when they trade; and there exists persistence in the insiders' trading performance over time and along trading directions are novel and new to the literature. This paper also has bearing on how to evaluate professional traders.

This paper conducts an empirical analysis for the estimations of volume-weighted price of the Korean stock market and provides the implications of the estimation errors regarding the characteristics of the market and the corresponding securities. We employ fast Fourier transformation strategy and traditional simple average strategy and compare the performances of the two methods using five minute interval intra-day data of KOSPI50 stocks. Estimations errors of the two methods from Ex Post real VWAP are computed and the relationships between the errors and other market variables are examined. We find that larger market value leads to smaller error whereas average trading in dollar has negative relationship with the estimation error. We also look at the behavior of institutional traders and the order execution mechanism to explain our statistical findings.

The purpose of this paper is to investigate how insiders’ trades are executed and whether and how outside investors can mimic outperforming insiders and reap substantial portfolio returns that withstand the erosion from adjustments for both the standard factors and stock characteristics in the asset pricing literature.

The authors design a metric for measuring insiders’ trade execution quality: the trading alpha. The authors run regression analysis to control for trade difficulty, insider reputations and the corporate role ranks of insiders and document the existence of the abnormal trading alpha. The authors further form portfolios based on the abnormal trading alpha and document a significant abnormal return that is robust to both standard asset pricing factors model and the stock characteristics adjustments.

Outperforming insiders at the aggregate level resemble value investors who trade on long-term fundamental information, trade patiently and earn rents from providing liquidity. Outside investors can mimic the outperforming insiders and reap significant abnormal portfolio returns.

Data limitations on insider trades and their association/interaction with their brokers prevent us from having a conclusive investigation of the trading skill hypothesis. The authors hope to further research along the lines of the trading skill hypothesis as compared to investment style hypothesis with more detailed data about the brokers used by insiders.

The findings can be applied for money management profession in that outsider investors can monitor the trading execution and construct portfolios based on the adjusted abnormal trading alpha. The resulting portfolio has been documented to be highly profitable after risk adjustments using standard asset pricing factors as well as stock characteristics.

Professional money managers and outsider investors should be able to benefit from the findings in this paper and use the proposed trading alpha metric to construct and rebalance real-time investment portfolios.

Outperforming insiders at the aggregate level resemble value investors who act on long-term fundamental information, trade patiently and earn rents from providing liquidity. From the perspective of investment implications, outside investors can mimic the outperforming insiders and reap substantial portfolio returns that withstand the erosion from adjustments for both the standard factors and stock characteristics in the asset pricing literature.

New regulatory initiatives, principally MiFID and RegNMS, challenge wholesale financial firms to prove that they can provide best execution for their clients. This article aims to outline the background to the problem and suggest that current research into SVM/DAPR applications may provide a practical approach.

The article presents a desk review of current issues in “best execution” based on work with European brokers and others, followed by initial, promising trial of SVM/DAPR.

The article finds that brokers need automated tools, e.g. “sifting engines” that help them to focus compliance efforts on anomalous trades.

Although brokers appear to need assistance in identifying anomalous trades, whether they place significant effort in compliance depends on regulatory enforcement.

MiFID and RegNMS will require changes in current practice. SVM/DAPR approaches appear to be worth further investigation.

The purpose of this paper is to explain the Securities and Exchange Commission's recently proposed amendments to Rule 10b‐18 under the Securities Exchange Act of 1934 that are intended to modernize Rule 10b‐18 to reflect changes in the market since the Rule's adoption.

The paper provides an overview of Rule 10b‐18, which provides an issuer that is buying its own stock a safe harbor from liability for market manipulation if the issuer satisfies the purchase, timing, price and volume conditions defined in Rule 10b‐18. It outlines the proposed amendments to the timing condition, price condition, limitation on disqualification, and the time in which the safe harbor is available in connection with an acquisition by a special purpose acquisition company.

The proposed amendments are intended to modernize Rule 10b‐18 to reflect changes in the market since the Rule's adoption.

The proposed amendments to the price condition and the disqualification provisions will likely be welcome by issuers and brokers who have been challenged by the evolution of market practices and technology, but the amendments to the timing condition and the restrictions on SPACs could result in fewer opportunities for issuers to purchase their own shares under the safe harbor.

The paper provides practical guidance from experienced securities lawyers.

Forthcoming requirements in MiFID and RegNMS mean that buy‐side and sell‐side firms need to find ways of showing regulators that they are sifting through their trading volumes in a justifiable, methodical manner looking for anomalous trades and investigating them, in order to prove “best execution”. The objective was to see if a SVM/DAPR approach could help identify equity trade anomalies for compliance investigation.

A major stock exchange, a computer systems supplier, four brokers and a statistical firm undertook a cooperative research project to determine whether automated statistical processing of trade and order information could provide a tighter focus on the most likely trades for best execution compliance investigation.

The support vector machine approach worked on UK equities and has significant potential for other markets such as foreign exchange, fixed income and commodities.

The research has implications for risk professionals as a generic approach to trading anomaly detection. The prototype compliance workstation can be trialed.

Automated anomaly detection could transform the role of compliance and risk in financial institutions.

While it has been claimed in many empirical studies that the political futures market can forecast better than the polls, it is unclear upon which our forecast should be based. Standard practice seems to suggest the use of the closing price of the market, as a reflection of the continuous process of information revealing and aggregation, but we are unsure that this practice applies to thin markets. In this chapter, we propose a number of reconstructions of the price series and use the closing price based on these reconstructed series as the forecast. We then test these ideas by comparing their forecasting performance with the closing price of the original series. It is found that forecasting accuracy can be gained if we use the closing price based on the smoothing series rather than the original series. However, there is no clear advantage by either using more sophisticated smoothing techniques, such as wavelets, or using external information, such as trading volume and duration time. The results show that the median, the simplest smoothing technique, performs rather well when compared with all complications.

This paper aims to explain the SEC's new Rule 201 and amended Rule 200(g), which are designed to improve the regulations that address harmful shortselling practices.

The paper summarizes Rule 201, discusses the reasoning behind the “alternative uptick rule”, defines “covered securities” to which Rule 201 applies, explains why the commission chose the national best bid as the basis of the execution of short sales during the circuit breaker period, discusses the SEC's policies and procedures approach, explains conditions under which a broker‐dealer submitting a short‐sale order after the circuit breaker is triggered submitting a short sale order after the circuit breaker is triggered may mark the order “short exempt,” explains the reason an exception for market making activities is not included in the rule, and discusses the implementation period and the need for broker‐dealers to develop new policies and procedures.

Broker‐dealers and other market centers will need to dedicate significant compliance and systems resources to develop the policies and procedures and systems enhancements necessary to comply with the rule.

The paper provides practical guidance from experienced securities lawyers.