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Quantopian Lectures Saved

Lecture 1: Introduction to Research β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 2: Introduction to Python β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 3: Introduction to NumPy β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 4: Introduction to pandas β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 5: Plotting Data β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 6: Means β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 7: Variance β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 8: Statistical Moments β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 9: Linear Correlation Analysis β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 10: Instability of Estimates β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 11: Random Variables β€” [πŸ“Lecture Notebooks]
Lecture 12: Linear Regression β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 13: Maximum Likelihood Estimation β€” [πŸ“Lecture Notebooks]
Lecture 14: Regression Model Instability β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 15: Multiple Linear Regression β€” [πŸ“Lecture Notebooks]
Lecture 16: Violations of Regression Models β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 17: Model Misspecification β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 18: Residual Analysis β€” [πŸ“Lecture Notebooks]
Lecture 19: The Dangers of Overfitting β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 20: Hypothesis Testing β€” [πŸ“Lecture Notebooks]
Lecture 21: Confidence Intervals β€” [πŸ“Lecture Notebooks]
Lecture 22: p-Hacking and Multiple Comparisons Bias β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 23: Spearman Rank Correlation β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 24: Leverage β€” [πŸ“Lecture Notebooks]
Lecture 25: Position Concentration Risk β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 26: Estimating Covariance Matrices β€” [πŸ“Lecture Notebooks]
Lecture 27: Introduction to Volume, Slippage, and Liquidity β€” [πŸ“Lecture Notebooks]
Lecture 28: Market Impact Models β€” [πŸ“Lecture Notebooks]
Lecture 29: Universe Selection β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 30: The Capital Asset Pricing Model and Arbitrage Pricing Theory β€” [πŸ“Lecture Notebooks]
Lecture 31: Beta Hedging β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 32: Fundamental Factor Models β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 33: Portfolio Analysis β€” [πŸ“Lecture Notebooks]
Lecture 34: Factor Risk Exposure β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 35: Risk-Constrained Portfolio Optimization β€” [πŸ“Lecture Notebooks]
Lecture 36: Principal Component Analysis β€” [πŸ“Lecture Notebooks]
Lecture 37: Long-Short Equity β€” [πŸ“Lecture Notebooks]
Lecture 38: Example: Long-Short Equity Algorithm β€” [πŸ“Lecture Notebooks]
Lecture 39: Factor Analysis with Alphalens β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 40: Why You Should Hedge Beta and Sector Exposures (Part I) β€” [πŸ“Lecture Notebooks]
Lecture 41: Why You Should Hedge Beta and Sector Exposures (Part II) β€” [πŸ“Lecture Notebooks]
Lecture 42: VaR and CVaR β€” [πŸ“Lecture Notebooks]
Lecture 43: Integration, Cointegration, and Stationarity β€” [πŸ“Lecture Notebooks] [Video]
Lecture 44: Introduction to Pairs Trading β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 45: Example: Basic Pairs Trading Algorithm β€” [πŸ“Lecture Notebooks]
Lecture 46: Example: Pairs Trading Algorithm β€” [πŸ“Lecture Notebooks]
Lecture 47: Autocorrelation and AR Models β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 48: ARCH, GARCH, and GMM β€” [πŸ“Lecture Notebooks]
Lecture 49: Kalman Filters β€” [πŸ“Lecture Notebooks] [▢️Video]
Lecture 50: Example: Kalman Filter Pairs Trade β€” [πŸ“Lecture Notebooks]
Lecture 51: Introduction to Futures β€” [πŸ“Lecture Notebooks]
Lecture 52: Futures Trading Considerations β€” [πŸ“Lecture Notebooks]
Lecture 53: Mean Reversion on Futures β€” [πŸ“Lecture Notebooks]
Lecture 54: Example: Pairs Trading on Futures β€” [πŸ“Lecture Notebooks]
Lecture 55: Case Study: Traditional Value Factor β€” [πŸ“Lecture Notebooks]
Lecture 56: Case Study: Comparing ETFs β€” [πŸ“Lecture Notebooks]

@BVodka
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BVodka commented Oct 30, 2020

Awesome @ih2502mk just started on learning and Quantopia went down. Thanks so much for this.

@jobquiroz
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jobquiroz commented Nov 1, 2020

Thank you for this

@ThieryLebeau
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ThieryLebeau commented Nov 2, 2020

Hi @ih2502mk and everyone!
How to download all these information at once ?

@mburke19
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mburke19 commented Nov 24, 2020

Thanks for this!!

@nfarsi
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nfarsi commented Jan 2, 2021

Many thanks for saving this information

@akshayrama3
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akshayrama3 commented Jan 12, 2021

lets get this moneyyy

@EigusBikeCo
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EigusBikeCo commented Apr 26, 2021

Thank you so much for this!!

@SimonKufeld
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SimonKufeld commented Jul 1, 2021

Thank god you saved those resources

@muehlegger
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muehlegger commented Jul 27, 2021

Thanks for saving and providing these great lectures!

@dallen101
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dallen101 commented Aug 22, 2021

Wow. I don't have the words to express how grateful and happy I am right now! Thank you!

@Big-al
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Big-al commented Aug 25, 2021

Awesome! Thank you!

@iveksl2
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iveksl2 commented Dec 24, 2021

Agree with @muehlegger . Thanks for saving and posting these

@Sanjaychegde
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Sanjaychegde commented Jan 6, 2022

Thanks

@pixyfox
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pixyfox commented Jan 19, 2022

Thank you !!

@clarisfinance
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clarisfinance commented Jan 29, 2022

thanks

@devinearr
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devinearr commented May 6, 2022

😀

@Raptor1121
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Raptor1121 commented May 15, 2022

Hi can anyone tell me how I can use this material? I dont have a programming background so I'm not sure how to start. Thanks!

@TheCodingSpiRiT
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TheCodingSpiRiT commented Jun 20, 2022

how can i use those notebooks now that the quantopian site is down?

@Heyymant
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Heyymant commented Jul 24, 2022

how can i use those notebooks now that the quantopian site is down?

Copy the raw file as text and then save its a ipynb file. :)

@Raptor1121
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Raptor1121 commented Jul 24, 2022

Heyymant

Thanks!

@QuantPhenomenon
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QuantPhenomenon commented Aug 27, 2022

This is very much appreciated. Thank you

@QuantPhenomenon
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QuantPhenomenon commented Aug 27, 2022

Just get the raw file and go from there.

@thatboredgirlie
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thatboredgirlie commented Sep 15, 2022

Verify Github on Galxe. gid:GFdyFLCMfgCpmFU7d4fcZD

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