Pawan Jain

The Predictive Power of Limit Order Book for Future Volatility, Trade Price, and Speed of Trading

We investigate the information content of the limit order book (LOB) on the Tokyo Stock Exchange, the world’s second largest order-driven exchange1. Microstructure parameters, such as the current cost-to-trade 1% of average daily volume and order book slope, consistently and significantly predict future price volatility, trade prices, and speed of trading. The shape of the LOB on the bid side carries more predictive power than that on the ask side. We also document that the average trade size is the driving force in the standard volume-volatility relationship.

Stock price movement around the merger announcements: insider trading or market anticipation?

Purpose - – The purpose of this paper is to examine the stock price movements for existence of informed trading prior to a merger announcement for the companies listed on the emerging markets of India for the period from 1996 to 2010. Design/methodology/approach - – This study applies several event study methodologies and regression analyses to analyze the stock price movement surrounding a merger announcement. The paper divides mergers in two different types: industry merger cases and non-industry merger cases and in two different time periods: recession and boom. Findings - – The results show that the information held only by insiders’ works its way into prices. The paper finds strong evidence of insider trading in the case of industry mergers and mergers during recessions. Practical implications - – The results from this study have immediate policy implications for India and other developing markets as the paper provides the type of mergers and time periods when merger announcements are more susceptible to insider trading. Originality/value - – The paper extends the literature on mergers and insider trading by analyzing firms trading on a developing capital market, which, unlike the developed markets, is characterized by inadequate disclosure and a weaker enforcement of securities regulations. The results support this notion and recommend Indian securities market regulators to tighten the lax regulations. In addition, the author document the divergence in price reaction to the merger announcements for different types of mergers: industry mergers and non-industry mergers, as well as for mergers during different market conditions: recession vs booming capital markets.

Reits and Market Microstructure: A Comprehensive Analysis of Market Quality

This study analyzes the market quality differences, in terms of liquidity and volatility, between real estate investment trusts (REITs) and non-REIT common stocks. The 2008 financial crisis has significantly influenced the market quality for REITs. Our findings reveal intraday patterns indicating a lower liquidity, higher volatility, and greater price impact for REITs than non-REITs for the pre-crisis period. These relationships reverse during the post-crisis period with REITs becoming more liquid, less volatile, and cheaper to trade than non-REITs. Further, we document that post-crisis trading interest in REITs has increased significantly as reflected by increased volume, number of trades, and number of quotes.

Cancellation Latency: The Good, the Bad, and the Ugly

This paper provides several statistics concerning cancellation latency that would be helpful to regulators as they consider policies to establish a minimal quote life. We find that cancellation latency is related to market quality and is not constant. Rather, it varies depending upon the time of day, order price and size, market congestion, trader type, firm size, order imbalance, and technology used for submitting an order.

Machines, Memory and the Markov Property in Stock Returns: Deus Ex Machina?

This study seeks to understand whether and to what extent High Frequency Trading (HFT) affects the probabilistic properties of the stock returns in five markets. More specifically, it focuses on the impact of HFT/machine trading on five major stock indices, DAX, Nikkei 225, S&P 500, Russell 2000, and TOPIX. The empirical analysis demonstrates that while the introduction of machine trading and/or HFT appears to make the return series more “predictable” by reducing their Multiscale Entropy, it does not affect the Markov property, which does not hold for the return series under study.

A Global Investigation of Dividend Yields: Shareholder Demand, Agency Problems, and Market Quality

We compare cross-sectional variation of dividend yields of companies across 32 countries. Beyond the impact of firm-specific accounting and financial variables, this study investigates how the variations in country level variables affect dividend payout policies. The country level variables include shareholder demand due to demographic variations and consumption needs, agency problems manifested in the extent of minority shareholder protection and business disclosures, and market quality in terms of transparency and liquidity. We find that dividend yields are higher when diverse shareholder demands are strong, extents of business disclosures and legal protections are weak, and the market qualities are poor. The empirical evidence supports the demand-based theory in a global setting and the essence of bird-in-the-hand theory - the more the uncertainty the stronger the preference for dividend payout.