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Artwork for Papers With Backtest: An Algorithmic Trading Journey

Papers With Backtest: An Algorithmic Trading Journey

Papers With Backtest
Risk Management
Backtesting
Algorithmic Trading
Turn Of the Month Effect
Sector Momentum
Low Volatility Factor Effect
Relative Strength Strategy
Pairs Trading
Trend Following
Market Returns
Time Series Momentum
Trading Strategies
Faber's Research
Utilities Sector
Market Dynamics
Volatility
Investment Strategies
Stock Market
Discipline In Trading
Etfs

Welcome to Papers With Backtest, where data means profit in the world of algorithmic trading. Each episode dives into backtests, real-life trading applications, and groundbreaking research that every aspiring quant should know. Tune in to stay ahead in the algo trading game. Our website: paperswithbacktest.com/ Hosted on Ausha. See ausha.co/privacy-policy for more information.

PublishesWeeklyEpisodes71Foundeda year ago
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Artwork for Papers With Backtest: An Algorithmic Trading Journey

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Host

Ausha
Host of Papers With Backtest, focusing on insights into algorithmic trading and backtesting research.

Reviews

4.8 out of 5 stars from 5 ratings
  • “Too Conversational”

    The male and female voice change too frequently and far too much sudden and useless “hmm” “ok…” which are distracting. Otherwise nice content.

    Apple Podcasts
    4
    lscantab
    Hong Konga year ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

There are comments regarding distractions due to host transitions and vocal fillers, impacting the flow of discussions.
Listeners appreciate the in-depth analysis and relevance of the content to real-world trading scenarios.

Talking Points

Recent interactions between the hosts and their guests.

How Momentum Trading Strategies Adapt to Changing Conditions in Algorithmic Trading
Q: How do you reliably identify whether the market is in a UP or down end state?
The research paper does not provide all the answers, and it opens up a new area for exploration revealing that there's more to consider than just a simple approach to market classification.
The 60-40 Portfolio: Dynamic Hedging Strategies for Modern
Q: What is an important consideration when interpreting backtest results?
It is crucial to remain skeptical of backtest results due to the risk of overfitting, where a strategy may perform well on historical data but fail in live trading conditions.
The 60-40 Portfolio: Dynamic Hedging Strategies for Modern
Q: What was the average annual return of the dynamic strategy compared to the traditional approach?
The dynamic strategy achieved an average annual return of 9.44 percent, outperforming the traditional 60-40 portfolio which had an average return of 8.92 percent.
The 60-40 Portfolio: Dynamic Hedging Strategies for Modern
Q: How does the dynamic hedging strategy adjust allocations?
It shifts a small percentage of the portfolio from bonds to commodities based on the six-month rolling correlation between stocks and bonds, allowing for dynamic adjustments based on market conditions.
The 60-40 Portfolio: Dynamic Hedging Strategies for Modern
Q: What is the potential drawback of the traditional 60-40 portfolio in today's market?
The traditional 60-40 portfolio may not provide the reliable hedge it used to, especially as rising inflation can cause bonds to move in the same direction as stocks, amplifying losses rather than cushioning them.

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Frequently Asked Questions About This Podcast

What is This Podcast about and what kind of topics does it cover?

Focusing on algorithmic trading, the series explores various aspects of quantitative finance and trading strategies. Each episode typically analyzes academic research papers that provide insights into effective backtesting methods, market behavior, and innovative trading strategies. Topics discussed include investor sentiment, unusual trading volumes, seasonal effects, and the practical applications of machine learning in trading. By emphasizing data-backed insights, the content is designed to cater to both novice traders and experienced quants looking to refine their strategies and enhance their understanding of market mechanics. Unique to this series, the thorough breakdown of research findings paired with real-world applicability sets it... more

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this podcast launched a year ago and published 71 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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