Efficiency and the trading system:The case of SETSmm

This paper studies the impact that a change from a dealer system to a market-maker supported auction system has on market quality. We study the impact that the introduction of SETSmm at the London Stock Exchange had on firm value, price efficiency and liquidity. We discover a small SETSmm return premium associated with the announcement that securities are to migrate to the new trading system. Moreover, securities that migrate to SETSmm are characterized by improvements to liquidity and pricing efficiency. We find that these changes are related to the return premium.

Stock repurchases and treasury share sales:do they stabilize price and enhance liquidity?

Can companies reduce the volatility and increase the liquidity of their stocks by trading them? In the context of the Italian stock market, where companies have far more leeway to sell as well as buy their own stocks than in the U.S., the answer is yes. We examine the effects of trading (open-market share repurchases and treasury shares sales) on liquidity (bid–ask spread) and volatility (return variance). Further, we examine the impact of shareholder approvals of repurchase programs on liquidity and volatility. We find clear evidence that trading increases liquidity and reduces volatility. These results are consistent with our analysis of the motives Italian companies give for making share repurchases.

Virtuális árhatás a Budapesti Értéktőzsdén = Virtual price effects on the Budapest stock exchange

Az árhatásfüggvények azt mutatják meg, hogy egy adott értékű megbízás mekkora relatív árváltozást okoz. Az árhatásfüggvény ismerete a piaci szereplők számára fontos szerepet játszik a jövőben benyújtandó ajánlataikhoz kapcsolódó árhatás előrejelzésében, a kereskedés árváltozásból eredő többletköltségének becslésében, illetve az optimális kereskedési algoritmus kialakításában. Az általunk kidolgozott módszer révén a piaci szereplők a teljes ajánlati könyv ismerete nélkül egyszerűen és gyorsan tudnak virtuális árhatásfüggvényt meghatározni, ugyanis bemutatjuk az árhatásfüggvény és a likviditási mértékek kapcsolatát, valamint azt, hogy miként lehet a Budapesti Likviditási Mérték (BLM) idősorából ár ha tás függ vényt becsülni. A kidolgozott módszertant az OTP-részvény idősorán szemléltetjük, és a részvény BLM-adatsorából a 2007. január 1-je és 2011. június 3-a közötti időszakra virtuális árhatás függvényt becsülünk. Empirikus elemzésünk során az árhatás függ vény időbeli alakulásának és alapvető statisztikai tulajdonságainak vizsgálatát végezzük el, ami révén képet kaphatunk a likviditás hiányában fellépő tranzakciós költségek múltbeli viselkedéséről. Az így kapott információk például a dinamikus portfólióoptimalizálás során lehetnek a kereskedők segítségére. / === / Price-effect equations show what relative price change a commission of a given value will have. Knowledge of price-effect equations plays an important part in enabling market players to predict the price effect of their future commissions and to develop an optimal trading algorithm. The method devised by the authors allows a virtual price-effect equation to be defined simply and rapidly without knowledge of the whole offer book, by presenting the relation between the price-effect equation and degree of liquidity, and how to estimate the price-effect equation from the time line of the Budapest Liquidity Measure (BLM). The methodology is shown using the time line for OTP shares and the virtual price-effect equation estimated for the 1 January 2007 to 3 June 2011 period from the shares BML data set. During the empirical analysis the authors conducted an examination of the tendency of the price-effect equation over time and for its basic statistical attributes, to yield a picture of the past behaviour of the transaction costs arising in the absence of liquidity. The information obtained may, for instance, help traders in dynamic portfolio optimization.

Stress events in the Hungarian stock market

Central clearing and the role of central counterparties (CCP) has gained on importance in the financial sector, since counterparty risk of the trading is to be managed by them. The regulation has turned towards them lately, by defining several processes, how CCPs should measure and manage their risk. Stress situation is an important term of the regulation, however it is not specified clearly, how stress should be identified. This paper provides a possible definition of stress event based on the existing risk management methodology: the usage of risk measure oversteps, and investigates the potential stress periods of the last years on the Hungarian stock market. According to the results the definition needs further calibration based on the magnitude of the cross-sectional data. The paper examines furthermore whether stress is to be predicted from market liquidity. The connection of liquidity and market turmoil proved to be contrary to the expectations; liquidity shortage was rather a consequence, than a forecaster phenomenon in the tested period.

Efficient Prices at Any Cost: Does Algorithmic Trading Deter Information Acquisition?

I demonstrate a powerful tension between acquiring information and incorporating it into asset prices, the two core elements of price discovery. As a salient case, I focus on the transformative rise of algorithmic trading (AT) typically associated with improved price efficiency. Using a measure of the relative information content of prices and a comprehensive panel of 37,325 stock-quarters of SEC market data, I establish instead that algorithmic trading strongly decreases the net amount of information in prices. The increase in price distortions associated with the AT “information gap” is roughly $42.6 billion/year for U.S. common stocks around earnings announcement events alone. Information losses are concentrated among stocks with high shares of algorithmic liquidity takers relative to algorithmic liquidity makers, suggesting that aggressive AT powerfully deters fundamental information acquisition despite its importance for translating available information into prices.

Short-term Trading in Long-term Funds: Implications for Financial Managers

Most hospitality firms do not consider managing stock portfolios to be a main part of their operations. They are in the service business, using their real assets and the services provided by employees to create valuable experiences for guests. However, the need to focus on stock investments arises through those employees. Employees consistently rank benefits, including retirement benefits, among the top five contributors to job satisfaction and as a key consideration in accepting a job.1 It is not surprising, then, that more than 90 percent of companies with 500 or more employees offer retirement plans. The five largest hotel companies in the U.S. have over $10 billion in assets under management in their retirement plans, making these plans a key component in retirement investment decisions.

Low-Volatility Anomaly in Helsinki Stock Exchange

International research shows that low-volatility stocks have beaten high-volatility stocks in terms of returns for decades on multiple markets. This abbreviation from traditional risk-return framework is known as low-volatility anomaly. This study focuses on explaining the anomaly and finding how strongly it appears in NASDAQ OMX Helsinki stock exchange. Data consists of all listed companies starting from 2001 and ending close to 2015. Methodology follows closely Baker and Haugen (2012) by sorting companies into deciles according to 3-month volatility and then calculating monthly returns for these different volatility groups. Annualized return for the lowest volatility decile is 8.85 %, while highest volatility decile destroys wealth at rate of -19.96 % per annum. Results are parallel also in quintiles that represent larger amount of companies and thus dilute outliers. Observation period captures financial crisis of 2007-2008 and European debt crisis, which embodies as low main index annual return of 1 %, but at the same time proves the success of low-volatility strategy. Low-volatility anomaly is driven by multiple reasons such as leverage constrained trading and managerial incentives which both prompt to invest in risky assets, but behavioral matters also have major weight in maintaining the anomaly.

Stock price and volume effects associated with changes in the composition of the FTSE Bursa Malaysian KLCI

We examine the stock price and volume effects associated with changes in the composition of the FTSE Bursa Malaysia Kuala Lumpur Composite Index (KLCI), over the time period of 2005–2012. We find evidence to support the price pressure hypothesis for both additions to and deletions from the KLCI. This is because significant stock price and trading volume effects in the pre index revision period are entirely reversed after the announcement of the news. Our empirical findings can be explained by the market microstructure literature. Significant changes in liquidity cause trading volume and stock prices to reverse back to their original level before the index revisions took place.