We are a boutique financial service firm specializing in quantitative analysis, derivatives valuation and risk management.
Harbourfront Technologies
Claim This Podcastby Harbourfront Technologies
55 episodes
Updated Daily
Accepts GuestsHas Sponsors
Podcast Overview
We are a boutique financial service firm specializing in quantitative analysis, derivatives valuation and risk management.
Language
🇺🇲
Publishing Since
4/4/2019
1 verified contact email on file for Harbourfront Technologies
Pitch yourself as a guest, propose sponsorships, or reach out directly to the host.
Recent Episodes
May 5, 2021
Trend-Following Trading System, Quantitative Trading In Python
In a previous post, we demonstrated the mean-reverting and trending properties of SP500. We subsequently developed a trading system based on the mean-reverting behavior of the index. In this installment, we will develop a trend-following trading strategy. http://tech.harbourfronts.com/trend-following-trading-system-quantitative-trading-in-python/
April 26, 2021
Mean - Reverting Trading System - Quantitative Trading In Python
We develop a simple trading system exploiting the mean-reverting behaviour of the SP500 market index. To generate buy and sell signals, we will use simple moving averages as noise filters. Since we know that the SP500 is mean-reverting in a short term, we will use short-term moving averages. http://tech.harbourfronts.com/mean-reverting-trading-system-quantitative-trading-in-python/
March 31, 2021
Autocorrelation Properties of SP500-Quantitative Trading in Python
We are going to examine the mean-reverting and trending properties of SP500 directly using the autocorrelation functions. We do so with the goal of designing quantitative trading systems on stock indices. http://tech.harbourfronts.com/autocorrelation-properties-of-sp500-quantitative-trading-in-python/
55 total episodes available
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Frequently asked questions
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- What is Harbourfront Technologies?
- How often does this podcast release new episodes?
This podcast updates daily.
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This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
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No, this podcast does not typically feature guests.
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