There are 3 basic types of market efficiency: allocative, operational and informative. Assets per employee is one of many operational ratios to present bank efficiency.
Capital intensity focus contributes to:
1. capital deepening (increasing capital per worker, for better recent product)
2. capital widening (capital per worker remains constant or drop)
Basic Line Chart below is example to compare Total Assets per Employee ratio by Bank in years 2011 - 2020.
1. Long data libraries: Seaborn, Plotly Express, Altair
2. Wide data libraries: Matplotlib, Plotly, Bokeh, PyGal, Pandas
from pandas import read_csv
from matplotlib import pyplot
series = read_csv('Assets.csv', header=0, index_col=0, parse_dates=True, squeeze=True)
print(series.head(6))
series1=series.groupby(['Bank Name','Year' ])['Total Assets','Employees'].sum().reset_index()
print(series1.head())
series1["Assets per Employee"] = series1["Total Assets"]/series1["Employees"]
print(series1.head())
series1.info()
series1.plot(color = 'grey', x="Year", y="Assets per Employee")
# Convert long form to wide form by pivot function df.pivot().reset_index()
widened = series1.pivot(index='Year', columns='Bank Name', values='Assets per Employee').reset_index()
print(widened)
widened.plot(x="Year", y=['UBS', 'Credit Suisse'],color=['dimgrey', 'lightgrey'])
Since 2011 until 2020 there has been approximately 25% drop in Assets per Employee ratio, either for UBS or for CS both. Assets per employee in UBS in 2012 were 20.1 and in 2020 they dropped to 15.7. We can notice very low Assets per employee at UBS in 2019 as well.
References
https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/3235/imfi_en_2010_02_Becker.pdf
https://alphacution.com/tag/assets-per-employee/
https://communitybankingconnections.org/articles/2017/i2/banks-are-becoming-more-efficient
https://www.investopedia.com/investing/measuring-company-efficiency/
https://support.lumerical.com/hc/en-us/articles/360036107274-Optical-Hyperbolic-Secant-Pulse-Generator-SECH-INTERCONNECT-Element
https://experts.umn.edu/en/publications/full-analytical-solution-of-the-bloch-equation-when-using-a-hyper
https://en.wikipedia.org/wiki/Bloch_equations
https://www.investopedia.com/terms/c/capm.asp
https://www.investopedia.com/terms/c/capitaladequacyratio.asp
https://www.investopedia.com/ask/answers/040115/what-does-it-mean-when-company-has-high-capital-adequacy-ratio.asp
https://datacatalog.worldbank.org/bank-capital-assets-ratio-0
https://en.m.wikipedia.org/wiki/Capital_deepening
https://en.m.wikipedia.org/wiki/Capital_intensity
https://www.investopedia.com/terms/e/efficiencyratio.asp
http://www.bankregdata.com/allARmet.asp?met=APF
https://en.m.wikipedia.org/wiki/Solow–Swan_model
https://en.m.wikipedia.org/wiki/Capital_deepening
https://en.wikipedia.org/wiki/Efficient_frontier
https://www.nber.org/papers/w23075
https://www.nber.org
https://en.wikipedia.org/wiki/Markowitz_model
https://scholarcommons.usf.edu/ujmm/vol7/iss2/5/
https://www.youtube.com/watch?v=_B_24GUWdSM&list=PL8FB14A2200B87185&index=4
https://people.duke.edu/~charvey/Classes/ba350/control/opc.htm
https://web.stanford.edu/~wfsharpe/mia/mia.htm
https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=2309
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=349660
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3551218
https://www.datacamp.com/community/tutorials/finance-python-trading?utm_source=adwords_ppc&utm_campaignid=12492439676&utm_adgroupid=122563405561&utm_device=c&utm_keyword=python%20finance&utm_matchtype=b&utm_network=g&utm_adpostion=&utm_creative=504158801893&utm_targetid=aud-392016246653:kwd-301111479313&utm_loc_interest_ms=1002875&utm_loc_physical_ms=9062857&gclid=Cj0KCQjw6ZOIBhDdARIsAMf8YyFuzdFkl8GUioJy21c8xLmQO8BoVqD1foD-7bo_ahW4kZTqX1GcIkoaAqDiEALw_wcB
https://www.ukessays.com/essays/economics/economic-growth-models-standards-1975.php
https://economics.yale.edu/people/david-swensen
https://viking.som.yale.edu
https://som.yale.edu/faculty/roger-g-ibbotson
https://en.wikipedia.org/wiki/Karl_Pearson
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