Academic journal article The International Journal of Business and Finance Research

Market Efficiency around the Announcement Day of Self-Tender Offers

Academic journal article The International Journal of Business and Finance Research

Market Efficiency around the Announcement Day of Self-Tender Offers

Article excerpt

ABTRACT

We examine the dynamic relationship between self-tender returns, volatility and order imbalances. Since market makers care more about volatilities than inventory risk, they tend to lower the bid-ask spread to mitigate volatility. This result is different from the previous argument whereby market makers tend to raise the bid-ask spread to control inventory risk. A time-varying GARCH model also confirms the results that an order imbalance does not affect volatility during self-tender market convergency. We develop an imbalance-based trading strategy which is to buy (sell) according to whether order imbalances are positive (negative). The empirical findings support self-tender market efficiency.

JEL: G12, G14

KEYWORDS: Self Tender, Order Imbalance, Information Asymmetry, Volatility

(ProQuest: ... denotes formulae omitted.)

INTRODUCTION

An extensive body of literature has developed on stock buyback programs, which mainly take the form of open-market repurchases or self-tender offers (See Comment and Jarrell, 1991; Peyer and Vermaelen, 2009; Wang et al., 2009; Liang et al., 2013; and Chen et al., 2014). Nonetheless, few studies focus on the empirical patterns of the market microstructure. For example, Coke et al. (1995) investigate the bid-ask spread surrounding open-market repurchases. Ahn et al. (2001) examine the spread around self-tender offers. Therefore, we use intraday data for self-tender offer stocks on the announcement day to explore the market efficiency.

Compared with open-market repurchases, self-tender offers have the following characteristics. First, the timing, quality, and prices of shares acquired for self-tender offers are known because they are announced in company press releases. Besides, these offers occur over a relatively short period, typically 30 days, whereas open-market repurchases can span several years. Therefore, a shorter period can avoid more confounding informational events (See Nayar et al., 2008). Second, although self-tender offers occur less frequently than open-market repurchases, self-tender offers have a greater impact on the market since they involve a substantial offer volume and premium. Therefore, more risk arbitrageurs will be attracted to become involved in the trading activities during the self-tender offer period since they have strong incentives to buy stocks and tender them back to the firm to generate profits due to the large gaps between the pre-expiration market and offer prices (See Lakonishok and Vermaelen, 1990; Covrig and Melvin, 2005). In this study, we are particularly interested in the dynamic relationships between order imbalances, volatility and returns during the process of convergence to market efficiency. Admati and Pfleiderer (1988) point out that a concentrated-trading pattem arises endogenously as a result of the strategic behavior of liquidity traders and informed traders. Their results provide a partial explanation for some of the recent empirical findings concerning the patterns of volume and price variability in intraday transaction data. In order to perform a market efficiency test, we develop an order imbalance-based trading strategy to examine whether the strategy could earn a positive return and even beat the buy and hold return for different intervals during the convergence process.

We have several marginal contributions. First of all, in the self-tender offer literature on market efficiency, the time horizons are always long-term. We use the intraday data to explore the short-term speed of convergence to market efficiency on the announcement day for self-tender offer stocks to fill this gap in the literature. Secondly, on the announcement day of the self-tender, market maker behavior plays a very important role in mitigating volatility from discretionary trades through inventory adjustments. The remainder of our study is organized as follows. In data and methodology section, we describe the data and methods. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.