Does Index Fund Investing Still Work in 2023?

Описание к видео Does Index Fund Investing Still Work in 2023?

Dollar Cost Averaging vs Lump Sum Investing!

If you had started investing anywhere between 1928-1997, and your retirement plan was either Dollar Cost Averaging or Lump Sum Investing in the S&P500 index over a 25 year period, which strategy would have been "better", and what are the differences?

The S&P500 Index has been around since 04 Mar 1957, but has been valued since 03 Jan 1928. Since the inception of the first market tracking ETF by State Street Global Advisors in 1993, S&P500 index funds have been extremely popularly investment vehicles for passive investors.

In this video we critically analyse the claims such as 'index investing always makes money' or 'if you dollar cost average into the S&P500 you can achieve 7% average market return'. By comparing investors with a 25 year holding period who start dollar cost averaging or lump sum investing at different months from Jan 1928 until today, we investigate whether these strategies have always worked out for the investor.

★ ★ Code Available on GitHub ★ ★
GitHub: https://github.com/TheQuantPy
Specific Tutorial Link: https://github.com/TheQuantPy/youtube...

★ ★ QuantPy GitHub ★ ★
Collection of resources used on QuantPy YouTube channel. https://github.com/thequantpy

★ ★ Discord Community ★ ★
Join a small niche community of like-minded quants on discord.   / discord  

★ ★ Support our Patreon Community ★ ★
Get access to Jupyter Notebooks that can run in the browser without downloading python.
  / quantpy  

★ ★ ThetaData API ★ ★
ThetaData's API provides both realtime and historical options data for end-of-day, and intraday trades and quotes. Use coupon 'QPY1' to receive 20% off on your first month.
https://www.thetadata.net/

★ ★ Online Quant Tutorials ★ ★
WEBSITE: https://quantpy.com.au

★ ★ Contact Us ★ ★
EMAIL: [email protected]

Disclaimer: All ideas, opinions, recommendations and/or forecasts, expressed or implied in this content, are for informational and educational purposes only and should not be construed as financial product advice or an inducement or instruction to invest, trade, and/or speculate in the markets. Any action or refraining from action; investments, trades, and/or speculations made in light of the ideas, opinions, and/or forecasts, expressed or implied in this content, are committed at your own risk an consequence, financial or otherwise. As an affiliate of ThetaData, QuantPy Pty Ltd is compensated for any purchases made through the link provided in this description.

Комментарии

Информация по комментариям в разработке