The volume traded daily for 17 stocks is followed over a period of about half a century. We look at the volume of stocks traded in a certain time interval (day, week, month) and analyze how long that traded volume keeps monotonically increasing or decreasing. On all three times scales we find that the sequence of traded volumes behaves neither like a sequence of independent and identically distributed variables, nor like a Markov sequence. A compressed exponential survival function with the same parameters at all timescales is firmly established. A day with an increase (decrease) of traded volume is most likely followed by a day with a decrease (increase) of traded volume...
A central problem of Quantitative Finance is that of formulating a probabilistic model of the time e...
The main goal of this paper is to gain insights into the dependence structure between the duration a...
A central problem of Quantitative Finance is that of formulating a probabilistic model of the time e...
The volume traded daily for 17 stocks is followed over a period of about half a century. We look at ...
AbstractWidely cited evidence for scaling (self-similarity) of the returns of stocks and other secur...
The scaling behaviour of both log-price and volume is analyzed for three stock indexes. The traditio...
Self-similarity is implicit in the standard modeling of financial markets, when a Brownian motion or...
This paper investigates the relationship between stock market trading volume and the autocorrelation...
Assuming that the variance of daily price changes and trading volume are both driven by the same lat...
Financial and seismic data, like many other high frequency data are known to exhibit memory effects....
Assuming that the variance of daily price changes and trading volume are both driven by the same lat...
none2noRelying on self-similarities and scale invariances, scientists have started to think about fi...
Financial and seismic data, like many other high frequency data are known to exhibit memory effects....
We investigate the random walk of prices by developing a simple model relating the properties of the...
We investigate the random walk of prices by developing a simple model relating the properties of the...
A central problem of Quantitative Finance is that of formulating a probabilistic model of the time e...
The main goal of this paper is to gain insights into the dependence structure between the duration a...
A central problem of Quantitative Finance is that of formulating a probabilistic model of the time e...
The volume traded daily for 17 stocks is followed over a period of about half a century. We look at ...
AbstractWidely cited evidence for scaling (self-similarity) of the returns of stocks and other secur...
The scaling behaviour of both log-price and volume is analyzed for three stock indexes. The traditio...
Self-similarity is implicit in the standard modeling of financial markets, when a Brownian motion or...
This paper investigates the relationship between stock market trading volume and the autocorrelation...
Assuming that the variance of daily price changes and trading volume are both driven by the same lat...
Financial and seismic data, like many other high frequency data are known to exhibit memory effects....
Assuming that the variance of daily price changes and trading volume are both driven by the same lat...
none2noRelying on self-similarities and scale invariances, scientists have started to think about fi...
Financial and seismic data, like many other high frequency data are known to exhibit memory effects....
We investigate the random walk of prices by developing a simple model relating the properties of the...
We investigate the random walk of prices by developing a simple model relating the properties of the...
A central problem of Quantitative Finance is that of formulating a probabilistic model of the time e...
The main goal of this paper is to gain insights into the dependence structure between the duration a...
A central problem of Quantitative Finance is that of formulating a probabilistic model of the time e...