Lakshmi
(Screenshot of the lak command in action)
Background
This project is inspired by Bogleheads forum. Bogleheads focus on a simple but powerful philosophy that allows investors to achieve above-average returns after costs. This tool is built around the same principles to help an average investor manage their investing portfolio.
Lakshmi (meaning "She who leads to one's goal") is one of the principal goddesses in Hinduism. She is the goddess of wealth, fortune, power, health, love, beauty, joy and prosperity.
Introduction
This project consists of a library module (lakshmi) and a command-line tool (lak) that exposes some of the functionality of the library. The library provides useful abstractions and tools to manage your investing portfolio.
Bogleheads wiki is a great resource for introduction to basic investing concepts like asset-allocation, asset-location, etc.
The following features are currently available:
- Specify and track asset allocation across accounts.
- Ability to add/edit/delete accounts and assets (funds, stocks, etc.) inside those accounts.
- Supports manual assets, assets with ticker, Vanguard funds (that don't have associated ticker symbols), EE Bonds and I Bonds.
- Automatic fetching of market value of various types of assets.
- Listing current values of assets, asset allocation and asset location.
- Tracking of tax-lot information for assets.
- Support for running what-if scenarios to see how it impacts the overall asset allocation.
- Analysis of portfolio to identify if there is need to rebalance or if there are losses that can be harvested.
Installation
This project can be installed via pip. To install the library and the lak command line tool, run:
pip install lakshmi
Command-line interface
(For detailed help, please see lak user guide)
The simplest way to use this project is via the lak command. To access the up to date help, run:
$ lak --help
Usage: lak [OPTIONS] COMMAND [ARGS]...
lak is a simple command line tool inspired by Bogleheads philosophy.
Detailed user guide is available at:
https://sarvjeets.github.io/lakshmi/docs/lak.html
Options:
--version Show the version and exit.
-r, --refresh Re-fetch all data instead of using previously cached
data. For large portfolios, this would be extremely slow.
-c, --config PATH The configuration file. [env var: LAK_CONFIG; default:
~/.lakrc]
--help Show this message and exit.
Commands:
add Add new accounts or assets to the portfolio.
analyze Analyze the portfolio.
delete Delete an account or asset.
edit Edit parts of the portfolio.
info Print detailed information about an asset or account.
init Initializes a new portfolio by adding asset classes.
list Command to list various parts of the portfolio.
whatif Run hypothetical what if scenarios by modifying the total...
A new portfolio can be created by either:
- Copying an existing portfolio file to ~/portfolio.yaml and editing it.
-- OR --
- Using the
lakcommands to create a new portfolio. The following command will open up an editor to input the desired asset allocation:
$ lak init
Accounts (His/Her 401(k), Roth IRAs, Taxable, etc.) can be added via the lak add account command:
$ lak add account
# Use the above command multiple times to add more accounts.
Assets can be added to an account via the lak add asset command. Different kinds of assets can be added to a portfolio. For a complete list, pull up the help for the command:
$ lak add asset --help
Usage: lak add asset [OPTIONS]
Edit assets in the portfolio.
Options:
-p, --asset-type [ManualAsset|TickerAsset|VanguardFund|IBonds|EEBonds]
Add this type of asset. [required]
-t, --account substr Add asset to this account (a sub-string that
matches the account name). [required]
--help Show this message and exit.
TickerAsset represents an asset with a ticker symbol. The value of these assets is updated automatically. To add a TickerAsset:
lak add asset -p TickerAsset -t account_str
where account_str is a sub-string that uniquely matches an account added previously.
That's it. To view all the assets, asset allocation and asset location, run:
lak list assets total aa al
For more detailed information about the tool, please see lak user guide.
Library
The lakshmi library can also be used directly. The modules and classes are well documented and there are numerous examples for using each method or class in the tests accompanying this package. For example, the example portfolio can be constructed and the asset allocation, etc. can be printed by the following piece of code:
from lakshmi import Account, AssetClass, Portfolio
from lakshmi.assets import TaxLot, TickerAsset
from lakshmi.table import Table
def main():
asset_class = (
AssetClass('All')
.add_subclass(0.6, AssetClass('Equity')
.add_subclass(0.6, AssetClass('US'))
.add_subclass(0.4, AssetClass('Intl')))
.add_subclass(0.4, AssetClass('Bonds')))
portfolio = Portfolio(asset_class)
(portfolio
.add_account(Account('Schwab Taxable', 'Taxable')
.add_asset(TickerAsset('VTI', 1, {'US': 1.0})
.set_lots([TaxLot('2021/07/31', 1, 226)]))
.add_asset(TickerAsset('VXUS', 1, {'Intl': 1.0})
.set_lots([TaxLot('2021/07/31', 1, 64.94)])))
.add_account(Account('Roth IRA', 'Tax-Exempt')
.add_asset(TickerAsset('VXUS', 1, {'Intl': 1.0})))
.add_account(Account('Vanguard 401(k)', 'Tax-Deferred')
.add_asset(TickerAsset('VBMFX', 20, {'Bonds': 1.0}))))
# Save the portfolio
# portfolio.Save('portfolio.yaml')
print('\n' + portfolio.asset_allocation_compact().string() + '\n')
print(Table(2, coltypes=['str', 'dollars'])
.add_row(['Total Assets', portfolio.total_value()]).string())
print('\n' + portfolio.asset_allocation(['US', 'Intl', 'Bonds']).string())
print('\n' + portfolio.assets().string() + '\n')
print(portfolio.asset_location().string())
if __name__ == "__main__":
main()
Contributing
I'm looking for contributors for this project. If you are interested, please contact me over email.
License
Distributed under the MIT License. See LICENSE for more information.
Acknowledgements
This project would not have been possible without my wife Niharika, who encouraged me to start working on this project and continued supporting me throughout the development.
In addition, I am indebted to the following folks whose wisdom has helped me tremendously in my investing journey: John Bogle, Taylor Larimore, Nisiprius, Livesoft, Mel Lindauer and LadyGeek.
The not-so-fine print
The author is not a financial adviser and you agree to treat this tool for informational purposes only. The author does not promise or guarantee that the information provided by this tool is correct, current, or complete, and it may contain technical inaccuracies or errors. The author is not liable for any losses that you might incur by acting on the information provided by this tool. Accordingly, you should confirm the accuracy and completeness of all content, and seek professional advice taking into account your own personal situation, before making any decision based on information from this tool.
In a nutshell:
- The information provided by this tool is not financial advice.
- The author is not an expert or financial adviser.
- Consult a financial and/or tax adviser before taking action.
16 Sep 25, 2022
21 Mar 25, 2022
3 Feb 13, 2022
17.1k Jan 4, 2023
5.1k Jan 5, 2023
12.4k Jan 8, 2023
13.3k Jan 7, 2023
131 Dec 25, 2022
3.4k Dec 30, 2022
14 Sep 11, 2022
14 Oct 18, 2022
23 Jun 29, 2022
3 Apr 4, 2022
4 Jan 19, 2022
64 Dec 28, 2022
140 Jan 3, 2023
16 Oct 15, 2022
58 Dec 6, 2022
5 Nov 19, 2021