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pyquantnews
Open
There's enough here to keep you busy for a while! To keep it all handy, click the link below to hop to the top tweet. Then retweet it so you can keep it at the top of your timeline. Then come back when you're ready! https://t.co/S7xFDR3tPl
https://twitter.com/pyquantnews/status/1619867548824096768
Get started with Python now →
88945
https://twitter.com/pyquantnews/status/1619870589706985472
2023/01/30
2
0
pyquantnews
Open
I have 1 more thing for you: FREE 7-day masterclass that will get you up and running with Python for quant finance. Here's what you get: • Working code to trade with Python • Frameworks to get you started TODAY • Trading strategy formation framework https://t.co/oMuWK86JhR
https://pythonforquantfinancemasterclass.com
Get started with Python now →
88945
https://twitter.com/pyquantnews/status/1619870317505134592
2023/01/30
2
0
pyquantnews
Open
In this thread, I showed you how to decompose a time series of US unemployment data. Now you can: • Improve your time series forecasts • Inspect the trend and seasonality of a data series • Assess the goodness of fit by inspecting the noise There's one more thing for you!
Get started with Python now →
88944
https://twitter.com/pyquantnews/status/1619870095127314434
2023/01/30
0
0
pyquantnews
Open
The results are like the additive model. But, there are no missing values, and the seasonality component changes slowly over time. https://t.co/u9nEoOIvs3
Get started with Python now →
88944
https://twitter.com/pyquantnews/status/1619869815904116738
2023/01/30
0
0
pyquantnews
Open
STL uses locally estimated scatterplot smoothing (LOESS) to extract seasonality and trend from a time series. It improves on the basic additive model by handling any kind of seasonality and being more robust to outliers. Run the model and plot the results. https://t.co/Fy1c92YhU7
Get started with Python now →
88944
https://twitter.com/pyquantnews/status/1619869563042021376
2023/01/30
0
0
pyquantnews
Open
The additive model is basic and comes with caveats: • The model is not robust to outliers • There are missing data points at the beginning and end • The model assumes there’s the same seasonal pattern every year Time to try a more robust method. https://t.co/dOn5A9TTTe
Get started with Python now →
88944
https://twitter.com/pyquantnews/status/1619869311673180161
2023/01/30
0
0
pyquantnews
Open
Run the model and plot the results. The code extracts the trend, seasonal, and noise. Take a look at the noise component and inspect if it looks random. If there was a strong pattern, it would tell you the time series is serially auto-correlated and the model fit is suspect. https://t.co/ph2C24QdHL
Get started with Python now →
88944
https://twitter.com/pyquantnews/status/1619869058010161152
2023/01/30
1
0
pyquantnews
Open
There’s a clear downward trend in the unemployment rate. There also appears to be some consistent spikes. Time series decomposition should pick up these patterns. https://t.co/m3mmHO2kFe
Get started with Python now →
88944
https://twitter.com/pyquantnews/status/1619868807358455809
2023/01/30
1
0
pyquantnews
Open
Then, use the OpenBB SDK to get the unemployment data. Plot the data with a 12 month rolling mean and standard deviation to visualize the trend. https://t.co/YSbrmk6xWY
Get started with Python now →
88944
https://twitter.com/pyquantnews/status/1619868557273096192
2023/01/30
1
0
pyquantnews
Open
First, import pandas for data manipulation, statsmodels for time series analysis, and the OpenBB SDK for data. https://t.co/wGEOAeoAEJ
Get started with Python now →
88944
https://twitter.com/pyquantnews/status/1619868316050374657
2023/01/30
4
0
pyquantnews
Open
But first, a quick primer on time series decomposition if you’re unfamiliar: • Lets quants analyze and forecast each part and reassemble them • Breaks down a time series into trend, seasonality, and noise • Models are additive or multiplicative Let’s dive in!
Get started with Python now →
88944
https://twitter.com/pyquantnews/status/1619868054841696256
2023/01/30
1
0
QuantSymplectic
Open
Today's reading list: 1. https://t.co/OVsyeaAObM 2. https://t.co/7j9YqrQzg8 3. https://t.co/rjv4km7MVY 4. https://t.co/E8ZJZiuI5h 5. https://t.co/5qBLTjpPdH 6. https://t.co/ioFoubBSpX https://t.co/RKvIJisYDC
https://bit.ly/3Hlj2vo
13683
https://twitter.com/QuantSymplectic/status/1619867944879800320
2023/01/30
28
6
pyquantnews
Open
By reading this thread, you’ll be able to: • Get US unemployment data for free • Decompose the time series with an additive model • Decompose the time series with LOESS Here's how to do it in Python, step by step.
Get started with Python now →
88945
https://twitter.com/pyquantnews/status/1619867797978234880
2023/01/30
0
0
pyquantnews
Open
The most foundational time series analysis tool: Decomposition. Despite advances in machine learning, quants still use it. Unfortunately, most people forget about it. So instead of spending two months studying it, just use it. In a few lines of Python:
Get started with Python now →
88945
https://twitter.com/pyquantnews/status/1619867548824096768
2023/01/30
3
0
carlcarrie
Open
#MLOps via Automated Pipelines using Python, SQL and standard tools https://t.co/QxWm9ho1n8 Crypto example: 'phi wf run crypto/prices' Terminal and Jupyter integration: https://t.co/Ns8v7FLeaW
https://www.phidata.com/
New York
13301
https://twitter.com/carlcarrie/status/1619810977528287232
2023/01/29
7
0
carlcarrie
Open
Oxford scientists and theologians debate AI, the emergence of algocracy, and the path of AI /Human coexistence in the NYT Sunday edition https://t.co/MhTYdvHRhD https://t.co/1TuPoBzVw9
https://www.thetimes.co.uk/article/9d127dac-9731-11ed-ae85-8165ffa85053?shareToken=1f5ba82f303f7dc099dd0d2789f75ff5
New York
13301
https://twitter.com/carlcarrie/status/1619808757000851456
2023/01/29
3
0
IBKR_QB
Open
Elisabetta Basilico, PhD, CFA, reviews #SustainableInvesting research in this @alphaarchitect featured article: https://t.co/vwoyE5tbFB #ESG https://t.co/qADFMc7nsY
https://www.tradersinsight.news/swrb
Connecticut, USA
2691
https://twitter.com/IBKR_QB/status/1619711970634088450
2023/01/29
0
0
pyquantnews
Open
https://t.co/Bt6ld5oEne
https://pyquantnews.com/the-pyquant-newsletter/
Get started with Python now →
88867
https://twitter.com/pyquantnews/status/1619686375363674112
2023/01/29
0
0
pyquantnews
Open
There are 8 steps to building an algorithmic trading strategy: 1. Idea 2. Research 3. Signals 4. Assessment 5. Backtest setup 6. Backtest analysis 7. Performance analysis 8. Execution Yesterday, 11,836 people got the guide for free. Grab it below ↓
Get started with Python now →
88867
https://twitter.com/pyquantnews/status/1619686372515749892
2023/01/29
0
0
saeedamenfx
Open
The impact of risk cycles on business cycles: a historical view https://t.co/5HxRkayLf0 #QuantLinkADay https://t.co/8UPPD5ipsr
https://www.federalreserve.gov/econres/ifdp/the-impact-of-risk-cycles-on-business-cycles-a-historical-view.htm
London
9133
https://twitter.com/saeedamenfx/status/1619681901052137472
2023/01/29
0
0
carlcarrie
Open
The turbulent macroeconomic backdrop and historical perspectives on technical innovation... https://t.co/Vj5hnOahu4
https://chamathreads.substack.com/p/higher-rates-will-lead-to-the-next
New York
13293
https://twitter.com/carlcarrie/status/1619666683307909122
2023/01/29
5
0
lopezdeprado
Open
Thank you to the over 1,500 people who registered to ADIA Lab's inaugural seminar, titled "Can Factor Investing Become Scientific?" To learn more, visit: * Slides: https://t.co/wbY0h7H55J * Manuscript: https://t.co/5kDHBLna8i * Paper: https://t.co/kbF0ORWw0L https://t.co/Ipz9NKMozl
https://bit.ly/3HBenXz
New York, USA
20213
https://twitter.com/lopezdeprado/status/1619611869345648642
2023/01/29
17
4
carlcarrie
Open
GitHub Copilot Deconstruction https://t.co/xwSql2AlZh Co-Pilot Explorer - JavaScript and Python Code: https://t.co/N7QrdiB4Gd https://t.co/acPJFv0ich
https://thakkarparth007.github.io/copilot-explorer/posts/copilot-internals
New York
13292
https://twitter.com/carlcarrie/status/1619536098216271873
2023/01/29
7
3
carlcarrie
Open
Markets for Prompt Engineering | in FastCompany https://t.co/YF9GEWppNN
https://www.fastcompany.com/90825418/promptbase-generative-ai-prompt-marketplace
New York
13291
https://twitter.com/carlcarrie/status/1619534437271883781
2023/01/29
0
0
pyquantnews
Open
The FREE 7-day masterclass that will get you up and running with Python for quant finance. Here's what you get: • Working code to trade with Python • Frameworks to get you started TODAY • Trading strategy formation framework 7 days. Big results. https://t.co/oMuWK86JhR
https://pythonforquantfinancemasterclass.com
Get started with Python now →
88799
https://twitter.com/pyquantnews/status/1619512046818557952
2023/01/29
4
0
pyquantnews
Open
This thread is packed with information. If you can't get to it all now, click the link to hop to the top tweet. Then retweet it (with a comment!) so you can come back to it later. https://t.co/HzD6RVhNzv
https://twitter.com/3187132960/status/1619507701028982784
Get started with Python now →
88799
https://twitter.com/pyquantnews/status/1619511469195902978
2023/01/29
6
1
saeedamenfx
Open
28Jan23 / #365APoem / And told to stop, Johnson, advice of loan,
London
9132
https://twitter.com/saeedamenfx/status/1619511442990063616
2023/01/29
0
0
pyquantnews
Open
By reading the thread, you can backtest a real trading strategy with Backtrader. Now you can get data, backtest the strategy, and analyze the results to test the performance of your strategies.
Get started with Python now →
88799
https://twitter.com/pyquantnews/status/1619511229793304577
2023/01/29
4
1
pyquantnews
Open
The strategy underperforms the long-only strategy on an absolute basis. But, it has better risk-adjusted returns, lower drawdowns, and lower volatility. It also has a better profit factor—which is important for active strategies.
Get started with Python now →
88799
https://twitter.com/pyquantnews/status/1619510978437070848
2023/01/29
4
1
pyquantnews
Open
Running this code prints 70 different performance and risk metrics. https://t.co/JuZMM5hbdo
Get started with Python now →
88799
https://twitter.com/pyquantnews/status/1619510716116901891
2023/01/29
3
1
pyquantnews
Open
Trading takes time, money, and effort. To make sure you're better off not being long TLT, compare the strategy results to a long-only strategy. QuantStats makes it easy. Here’s how to use it. https://t.co/NenvTCphIA
Get started with Python now →
88799
https://twitter.com/pyquantnews/status/1619510474520887297
2023/01/29
6
1
pyquantnews
Open
The last step is to convert the results into a pandas DataFrame. https://t.co/YPMLuiPOMw
Get started with Python now →
88799
https://twitter.com/pyquantnews/status/1619510225840513024
2023/01/29
4
1
pyquantnews
Open
Now, run the backtest. The first step is to create a backtesting engine (Backtrader calls it Cerebro). Then add the data, initial cash, and strategy logic. https://t.co/yWflfpm0kO
Get started with Python now →
88793
https://twitter.com/pyquantnews/status/1619509983472762881
2023/01/29
2
0
pyquantnews
Open
Next, setup the BackTrader strategy. This code tests if there’s a position in the market. If not, it checks if the current day is within the first week of the month and creates a short position. Otherwise, if the current day is within the last week, it creates a long position. https://t.co/B3W4bXqiqu
Get started with Python now →
88793
https://twitter.com/pyquantnews/status/1619509715930677248
2023/01/29
3
0
pyquantnews
Open
Fund managers report their holdings monthly. They don’t want to tell investors they lost money on meme stocks. So they sell them and buy higher-quality assets, like bonds. Can you take advantage of this? Start with a simple helper function that gets the last day of the month. https://t.co/2UqTr6BUK9
Get started with Python now →
88793
https://twitter.com/pyquantnews/status/1619509463148367874
2023/01/29
3
0
pyquantnews
Open
There’s an unsolved issue with Backtrader that prevents it from downloading data. That’s why you need the OpenBB SDK. Here’s a simple workaround. This function downloads the data from the OpenBB SDK, converts it to a CSV, and reads it in the Backtrader’s `YahooFinanceCSVData`. https://t.co/CPkBwStEy1
Get started with Python now →
88793
https://twitter.com/pyquantnews/status/1619509214707073024
2023/01/29
3
0
pyquantnews
Open
Start by importing pandas, the OpenBB SDK, QuantStats, and Backtrader. https://t.co/twl63o8yjX
Get started with Python now →
88793
https://twitter.com/pyquantnews/status/1619508959580246016
2023/01/29
7
0
pyquantnews
Open
By reading this thread, you will be able to - Get data from OpenBB - Build a backtest using Backtrader - Assess the results using QuantStats Here's how to do it in Python, step by step.
Get started with Python now →
88793
https://twitter.com/pyquantnews/status/1619508708798599168
2023/01/29
4
1
pyquantnews
Open
Use the Backtrader backtest library. Backtrader is an event-driven backtesting framework designed to remove bias. It’s easy to build and test trading strategies in a reusable way. But it’s hard to get started. Fortunately, I lay it out step-by-step here.
Get started with Python now →
88793
https://twitter.com/pyquantnews/status/1619508508625436673
2023/01/29
3
0
pyquantnews
Open
Here's how: • Expect backtest results to be the same in real life • Build their own backtesting framework • Introduce bias into their backtest So, how do you avoid these problems?
Get started with Python now →
88793
https://twitter.com/pyquantnews/status/1619508272217690113
2023/01/29
2
0
pyquantnews
Open
But first, what’s a backtest? A backtest: • Tests trading ideas against historic market data • Is used to check the robustness of trading strategies • Is a simulation of how a strategy might have performed in the market And most beginners get it wrong...
Get started with Python now →
88793
https://twitter.com/pyquantnews/status/1619507953546952706
2023/01/29
3
0
pyquantnews
Open
Nobody taught me how to backtest a trading strategy. So I read all the books, documentation, and blogs. Then, I distilled what I learned into a simple step-by-step guide. But unlike a 300-page book, this won't take you a month to read. Here it is in 2 minutes:
Get started with Python now →
88793
https://twitter.com/pyquantnews/status/1619507701028982784
2023/01/29
97
15
pyquantnews
Open
The FREE 7-day masterclass that will get you up and running with Python for quant finance. Here's what you get: • Working code to trade with Python • Frameworks to get you started TODAY • Trading strategy formation framework 7 days. Big results. https://t.co/oMuWK86JhR
https://pythonforquantfinancemasterclass.com
Get started with Python now →
88788
https://twitter.com/pyquantnews/status/1619406393966043143
2023/01/28
0
0
carlcarrie
Open
Deep Generative Neural Net applied to sparse stock index portfolio optimization Python GitHub: https://t.co/RhzzBlZG2m https://t.co/UbRHkq3KS3
https://github.com/kayuksel/generative-opt
New York
13283
https://twitter.com/carlcarrie/status/1619402176660647936
2023/01/28
6
0
IBKR_QB
Open
This week on the IBKR Quant Blog, find stories on importing an ipynb file, the risks in the cryptocurrency market, volatility and measures of risk-adjusted return, and more: https://t.co/9o8WR1UsPG #Jupyter #DataAnalytics https://t.co/BzCxMNwMMt
http://ibkrquant.com
Connecticut, USA
2690
https://twitter.com/IBKR_QB/status/1619349589663809536
2023/01/28
0
1
erykml1
Open
A nice summary of the latest advances in deep learning for time series forecasting https://t.co/BxYS01ZoFV
https://towardsdatascience.com/advances-in-deep-learning-for-time-series-forecasting-and-classification-winter-2023-edition-6617c203c1d1?source=social.tw
The Netherlands
856
https://twitter.com/erykml1/status/1619341902951727104
2023/01/28
0
0
pyquantnews
Open
Some of the other skills that will help you along the way: • Statistics • Optimization • Linear algebra
Get started with Python now →
88779
https://twitter.com/pyquantnews/status/1619328004789772288
2023/01/28
4
0
pyquantnews
Open
6/ Practice Start by defining the outcomes you want and work backward from there. As you become more proficient, you can move on to more complex projects, such as building a trading algorithm.
Get started with Python now →
88779
https://twitter.com/pyquantnews/status/1619327766414983168
2023/01/28
1
0
pyquantnews
Open
5/ Get data There are many sources of financial data available, such as Quandl, Yahoo Finance, and FRED. The best? The OpenBB SDK
Get started with Python now →
88779
https://twitter.com/pyquantnews/status/1619327506145841154
2023/01/28
1
0
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