- "Lighting Up Your Dark Data" by Lance Ransom

"Lighting Up Your Dark Data" by Lance Ransom

Talk by Lance Ransom, a Product Manager at Continuum Analytics and a former Partner and CTO of Schonfeld Group. From QuantCon NYC 2016.

Quants are faced with a complex data environment. Data is everywhere and it's increasingly challenging to analyze, explore and evaluate, all in one language and...
Talk by Lance Ransom, a Product Manager at Continuum Analytics and a former Partner and CTO of Schonfeld Group. From QuantCon NYC 2016.

Quants are faced with a complex data environment. Data is everywhere and it's increasingly challenging to analyze, explore and evaluate, all in one language and in one environment. Quants need a unified environment where they are able to write expressions and conduct pushdown processes, all without having to move the data and having the ability to deploy anywhere, anytime. Organizations need to better marshal the data and have visibility to conduct a clean transformation. This session will discuss how businesses gain a better understanding of their data, leading to better results. In the FinServ industry, fluidity in understanding the data will help create better risk models and trading strategies. Ransom will discuss how organizations address these challenges and future proof their work.

The slides for this presentation can be found at https://www.slideshare.net/Quantopian/light-up-your-dark-data-by-lance-ransom-at-quantcon-2016.

To learn more about Quantopian, visit us at https://www.quantopian.com.

Disclaimer
Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice.

More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian.

In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.

#finance #quantitative finance #risk #risk analysis #math #statistics #algorithms #algorithmic trading
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Quantopian provides free education, data, and tools so anyone anywhere can pursue their goals in quantitative finance. The Quantopian Channel is dedicated to serving up educational content on all things quant. Topics include: tools of the quant workflow, getting started in quant finance, using Ju...
Quantopian provides free education, data, and tools so anyone anywhere can pursue their goals in quantitative finance. The Quantopian Channel is dedicated to serving up educational content on all things quant. Topics include: tools of the quant workflow, getting started in quant finance, using Jupyter to streamline your research, using machine learning to build your strategies, and more. To learn more about Quantopian, visit: https://www.quantopian.com/.

Timetable

動画タイムテーブル

動画数:32件

Siri was triggered at , hahaha. Time to rethink about ML? - Reinforcement Learning for Trading Practical Examples and Lessons Learned by Dr. Tom Starke

Siri was triggered at , hahaha. Time to rethink about ML?

Reinforcement Learning for Trading Practical Examples and Lessons Learned by Dr. Tom Starke
2019年09月06日
00:01:40 - 00:43:34
guys please upload his talk too ! - Reinforcement Learning for Trading Practical Examples and Lessons Learned by Dr. Tom Starke

guys please upload his talk too !

Reinforcement Learning for Trading Practical Examples and Lessons Learned by Dr. Tom Starke
2019年09月06日
00:03:32 - 00:43:34
On  you mentions the Right Regime - 'does it end up choosing some training process ' It's easy to understand what is Mean Reversion process, but what does it mean 'training process' ? - Reinforcement Learning for Trading Practical Examples and Lessons Learned by Dr. Tom Starke

On you mentions the Right Regime - 'does it end up choosing some training process ' It's easy to understand what is Mean Reversion process, but what does it mean 'training process' ?

Reinforcement Learning for Trading Practical Examples and Lessons Learned by Dr. Tom Starke
2019年09月06日
00:19:53 - 00:43:34
when you said random walk most of the time I just realized you're not a real Quant my dear one. - Reinforcement Learning for Trading Practical Examples and Lessons Learned by Dr. Tom Starke

when you said random walk most of the time I just realized you're not a real Quant my dear one.

Reinforcement Learning for Trading Practical Examples and Lessons Learned by Dr. Tom Starke
2019年09月06日
00:23:55 - 00:43:34
you are updating state and applying the action. When we chose an action, first we need to apply than we need to update the state and get the reward. Let's say current price is 100.20. When agent decides to buy, it's has to buy from the price 100.20 (excluding spread/slippage and commission). In your example, it's buying with the next price. Am I wrong? - Reinforcement Learning for Trading Practical Examples and Lessons Learned by Dr. Tom Starke

you are updating state and applying the action. When we chose an action, first we need to apply than we need to update the state and get the reward. Let's say current price is 100.20. When agent decides to buy, it's has to buy from the price 100.20 (excluding spread/slippage and commission). In your example, it's buying with the next price. Am I wrong?

Reinforcement Learning for Trading Practical Examples and Lessons Learned by Dr. Tom Starke
2019年09月06日
00:30:14 - 00:43:34
true. - "How to Become a Quant? A Career in Quant Finance" Panel from QuantCon NYC 2018

true.

"How to Become a Quant? A Career in Quant Finance" Panel from QuantCon NYC 2018
2019年07月19日
00:12:20 - 01:00:46
time stamp - "How to Become a Quant? A Career in Quant Finance" Panel from QuantCon NYC 2018

time stamp

"How to Become a Quant? A Career in Quant Finance" Panel from QuantCon NYC 2018
2019年07月19日
00:30:00 - 01:00:46
Hey Quantopian, great explanatory video. At  you mention a link to the notebook, where can we find it? - Creating a Daily Fantasy Sports Algorithm Using Quantitative Finance, Pt. 3: Assembling a Team

Hey Quantopian, great explanatory video. At you mention a link to the notebook, where can we find it?

Creating a Daily Fantasy Sports Algorithm Using Quantitative Finance, Pt. 3: Assembling a Team
2019年07月13日
00:05:52 - 00:08:52
this final lineup would Not be allowed to enter in Draftkings. - Creating a Daily Fantasy Sports Algorithm Using Quantitative Finance, Pt. 3: Assembling a Team

this final lineup would Not be allowed to enter in Draftkings.

Creating a Daily Fantasy Sports Algorithm Using Quantitative Finance, Pt. 3: Assembling a Team
2019年07月13日
00:06:27 - 00:08:52
. Sisyphean Quants - The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018

. Sisyphean Quants

The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
2019年04月26日
00:06:53 - 00:15:26
. Integer Differentiation - The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018

. Integer Differentiation

The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
2019年04月26日
00:15:26 - 00:24:32
.  Inefficient Sampling - The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018

. Inefficient Sampling

The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
2019年04月26日
00:24:32 - 00:30:32
Pitfall #3: Inefficient Sampling - The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018

Pitfall #3: Inefficient Sampling

The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
2019年04月26日
00:24:33 - 01:13:36
. Wrong Labeling - The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018

. Wrong Labeling

The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
2019年04月26日
00:30:32 - 00:38:29
false breakout vol filtering - The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018

false breakout vol filtering

The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
2019年04月26日
00:38:00 - 01:13:36
. Weighting of non-IID samples - The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018

. Weighting of non-IID samples

The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
2019年04月26日
00:38:29 - 00:45:33
. Cross-Validation leakage - The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018

. Cross-Validation leakage

The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
2019年04月26日
00:45:33 - 00:48:31
. Backtest Overfitting - The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018

. Backtest Overfitting

The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
2019年04月26日
00:48:31 - 01:00:30
so he run many trials and got good results? Maybe he overfitted the results! - The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018

so he run many trials and got good results? Maybe he overfitted the results!

The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
2019年04月26日
00:59:00 - 01:13:36
. QnAGreat lecture. Very Insightful. Thank you for sharing :)I'm looking forward to reading the book. - The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018

. QnAGreat lecture. Very Insightful. Thank you for sharing :)I'm looking forward to reading the book.

The 7 Reasons Most Machine Learning Funds Fail Marcos Lopez de Prado from QuantCon 2018
2019年04月26日
01:00:30 - 01:13:36
I laughed :( - What to Look for and Look Out for in Quantitative Investing with Gary Antonacci

I laughed :(

What to Look for and Look Out for in Quantitative Investing with Gary Antonacci
2019年02月09日
00:06:44 - 00:53:54
he blinked at - Alpha and Beta in Finance

he blinked at

Alpha and Beta in Finance
2018年12月21日
00:00:44 - 00:03:22
he only blinked once, at - Alpha and Beta in Finance

he only blinked once, at

Alpha and Beta in Finance
2018年12月21日
00:02:40 - 00:03:22
If there's one thing traders should take away from this  "risk per trade" as in risking 1% of your account per trade... it's categorically incorrect. Ireedeemably wrong. Mathmatically stupid. - “The Five Reasons why most Traders Fail - and How to Avoid Them” with Andreas Clenow

If there's one thing traders should take away from this "risk per trade" as in risking 1% of your account per trade... it's categorically incorrect. Ireedeemably wrong. Mathmatically stupid.

“The Five Reasons why most Traders Fail - and How to Avoid Them” with Andreas Clenow
2018年12月11日
00:25:00 - 00:50:10
this & this 46:03 - “What To Do Before Machine Learning” with Dr. Ernie Chan

this & this 46:03

“What To Do Before Machine Learning” with Dr. Ernie Chan
2018年10月24日
00:42:36 - 00:58:44
TIME:Stock Ticker / ~Price(10.Aug.2018) / ~Price(16.AUG.2019) / Price RatioAABA / 68 / 69.90 / 1.03DBX / 30 / 17.26 / 0.58EQH / 22 / 19.85 / 0.9SPOT / 190 / 146 / 0.77BDX / 252 / 246 / 0.97CMG / 502 / 809 / 1.61CLX / 147 / 159 / 1.08SNAP / 12.17 / 16 / 1.08TSLA / 335 / 235 / 0.7SGEN / 74 / 76 / 1.02 - The Acquirer's Multiple: How to beat The Little Book that Beats the Market

TIME:Stock Ticker / ~Price(10.Aug.2018) / ~Price(16.AUG.2019) / Price RatioAABA / 68 / 69.90 / 1.03DBX / 30 / 17.26 / 0.58EQH / 22 / 19.85 / 0.9SPOT / 190 / 146 / 0.77BDX / 252 / 246 / 0.97CMG / 502 / 809 / 1.61CLX / 147 / 159 / 1.08SNAP / 12.17 / 16 / 1.08TSLA / 335 / 235 / 0.7SGEN / 74 / 76 / 1.02

The Acquirer's Multiple: How to beat The Little Book that Beats the Market
2018年08月11日
00:26:48 - 00:36:38
th at PM EDT. During this webinar, she assessed how your algorithm measures up against the Quantopian allocation process, provided feedback based on what we’re looking for, and offered general advice on how to improve your strategy. - Live Tearsheet Review with Dr. Jess Stauth

th at PM EDT. During this webinar, she assessed how your algorithm measures up against the Quantopian allocation process, provided feedback based on what we’re looking for, and offered general advice on how to improve your strategy.

Live Tearsheet Review with Dr. Jess Stauth
2018年07月28日
00:03:00 - 00:57:43