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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The Geometric Phase of Stock Trading
|
|---|---|
| Published in |
PLOS ONE, August 2016
|
| DOI | 10.1371/journal.pone.0161538 |
| Pubmed ID | |
| Authors |
Claudio Altafini |
| Abstract |
Geometric phases describe how in a continuous-time dynamical system the displacement of a variable (called phase variable) can be related to other variables (shape variables) undergoing a cyclic motion, according to an area rule. The aim of this paper is to show that geometric phases can exist also for discrete-time systems, and even when the cycles in shape space have zero area. A context in which this principle can be applied is stock trading. A zero-area cycle in shape space represents the type of trading operations normally carried out by high-frequency traders (entering and exiting a position on a fast time-scale), while the phase variable represents the cash balance of a trader. Under the assumption that trading impacts stock prices, even zero-area cyclic trading operations can induce geometric phases, i.e., profits or losses, without affecting the stock quote. |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 11% |
| France | 1 | 11% |
| United States | 1 | 11% |
| Puerto Rico | 1 | 11% |
| Unknown | 5 | 56% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Luxembourg | 1 | 6% |
| Unknown | 17 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 33% |
| Researcher | 3 | 17% |
| Other | 2 | 11% |
| Student > Doctoral Student | 2 | 11% |
| Lecturer | 2 | 11% |
| Other | 2 | 11% |
| Unknown | 1 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Economics, Econometrics and Finance | 5 | 28% |
| Computer Science | 3 | 17% |
| Engineering | 2 | 11% |
| Business, Management and Accounting | 2 | 11% |
| Mathematics | 1 | 6% |
| Other | 2 | 11% |
| Unknown | 3 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 March 2016.
All research outputs
#6,879,606
of 25,183,822 outputs
Outputs from PLOS ONE
#94,568
of 218,436 outputs
Outputs of similar age
#100,776
of 350,009 outputs
Outputs of similar age from PLOS ONE
#1,376
of 4,269 outputs
Altmetric has tracked 25,183,822 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 218,436 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.7. This one has gotten more attention than average, scoring higher than 56% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 350,009 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 4,269 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.