Similar Search Results

Liquidity, Volume and Dividend Yields in Stock Return Data : Evidence from London Stock Exchange

Vasilakis, Chrysovalantis - 2011

This paper investigates monthly liquidity in FTSE 100 equity index in London Stock Exchange over the period 1986 to …

Persistent link: https://www.econbiz.de/10013128842

Momentum, Echo and Predictability : Evidence from the London Stock Exchange (1820-1930)

Trigilia, Giulio - 2019

We study momentum and its predictability within equities listed at the London Stock Exchange (1820-1930). At the time …

Persistent link: https://www.econbiz.de/10012872210

Stock returns and calendar anomalies on the London Stock Exchange in the dynamic perspective of the Adaptive Market Hypothesis : a study of FTSE100 & FTSE250 indices over a ten yea...

Rosini, Lucrezia; Shenai, Vijay - In: Quantitative finance and economics 4 (2020) 1, pp. 121-147

Persistent link: https://www.econbiz.de/10012176735

Security price anomalies in the London International Stock Exchange : a 60 year perspective

Arsad, Zainudin - In: Applied financial economics 7 (1997) 5, pp. 455-464

Persistent link: https://www.econbiz.de/10001229848

Quantifying the high-frequency trading "arms race" : a simple new methodology and estimates

Aquilina, Matteo; Budish, Eric B.; O'Neill, Peter - 2020

Persistent link: https://www.econbiz.de/10013168017

Quantifying the High-Frequency Trading 'Arms Race' : A Simple New Methodology and Estimates

Aquilina, Matteo - 2020

We use stock exchange message data to quantify the negative aspect of high-frequency trading, known as “latency arbitrage.” The key difference between message data and widely-familiar limit order book data is that message data contain attempts to trade or cancel that fail. This allows the...

Persistent link: https://www.econbiz.de/10012829972

Quantifying the high-frequency trading "arms race" : a simple new methodology and estimates

Aquilina, Matteo; Budish, Eric B.; O'Neill, Peter - 2020

We use stock exchange message data to quantify the negative aspect of high-frequency trading, known as "latency arbitrage." The key difference between message data and widely-familiar limit order book data is that message data contain attempts to trade or cancel that fail. This allows the...

Persistent link: https://www.econbiz.de/10013346834