Algorithmic trading on Alpaca's Platform - Deep Dive

Focused View

Mayank Rasu,RASUQUANT LTD

13:28:01

6 View

1. Introduction to Alpaca & its API

1. API Trading Intro.mp4

07:51

2. Signing Up.mp4

04:52

3. What, How & Why of API Connections.mp4

07:47

4. Getting Anaconda Python Distribution.mp4

05:49

5. Connecting to Alpaca using API.mp4

10:13

6. Clarification on v1 API vs v2 API.mp4

04:15

7. V1 API Important Notice {Please Read}.html

2. Historical Data API

1. Historical Data API Intro.mp4

03:36

2.1 hist data basic.zip

2. Extracting BarCandle Data.mp4

09:40

3.1 hist data df.zip

3. Storing Bar Data in Dataframes.mp4

12:55

4.1 hist data function.zip

4. Reusable Function to Get Required Bar Data.mp4

08:27

5.1 hist data last trade v2.zip

5.2 hist data last trade.zip

5. Getting Last Traded Price.mp4

07:21

6.1 hist data last quote v2.zip

6.2 hist data last quote.zip

6. Getting Last Quote Information.mp4

02:55

7.1 hist data iterative.zip

7. Fetching Historical Data Iteratively.mp4

14:04

8. Historical Data v2 API Introduction.mp4

09:11

9.1 hist data v2.zip

9. Historical Data v2 API Implementation.mp4

15:48

10.1 hist data function v2.zip

10. Historical Data v2 API Homework.mp4

01:06

3. Orders API

1.1 order basic.zip

1. Placing Market & Limit Orders.mp4

13:45

2.1 order stop.zip

2. Placing Stop Loss Orders.mp4

08:49

3.1 order trail stop.zip

3. Placing Trailing Stop Loss Orders.mp4

06:45

4.1 order bracket.zip

4. Placing Bracket Orders.mp4

07:34

5.1 order list.zip

5. Extracting Orders Information.mp4

07:41

6.1 order cancel.zip

6. DeletingCancelling Open Orders.mp4

11:20

7.1 order replace.zip

7. ReplacingModifying Orders.mp4

05:21

4. Other Important API Calls

1.1 get positions.zip

1. Getting Position Information.mp4

10:42

2.1 delete positions.zip

2. DeletingClosing Positions.mp4

06:32

3.1 get account.zip

3. Getting Account Information.mp4

03:46

5. Alpaca Python Client

1. Alpaca Python API Library Intro.mp4

06:21

2.1 tradeapi intro.zip

2. Getting AccountPosition Info.mp4

07:57

3.1 tradeapi hist data.zip

3. Getting Historical Data.mp4

08:54

4.1 tradeapi hist data v2.zip

4. Getting Historical Data using V2 API.mp4

11:07

5.1 tradeapi orders.zip

5. Placing Orders.mp4

05:32

6. Streaming Market Data

1. Market Data Streaming Intro.mp4

07:54

2.1 streaming ticks.zip

2. Creating Market Data Streaming Client.mp4

12:36

3.1 streaming ticks v2.zip

3. Streaming Market Data using V2 API.mp4

10:50

4. Storing Tick Data in SQL DB - I.mp4

19:51

5.1 storing ticks sql v2.zip

5.2 storing ticks sql.zip

5. Storing Tick Data in SQL DB - II.mp4

13:00

6.1 storing ticks quotes sql v2.zip

6.2 storing ticks quotes sql.zip

6. Storing Tick Data in SQL DB - III.mp4

16:50

7.1 fetching ticks sql.zip

7. Fetching Data from DB.mp4

06:47

8.1 resample ticks.zip

8. Resampling Ticks Data to Candles.mp4

14:25

7. Implementing Trading Strategy Using Streaming Data

1. Handling Streaming Data Intro.mp4

04:22

2.1 threading code.zip

2. Python Multithreading Intro.mp4

14:27

3.1 threading daemon.zip

3. Daemon Threads.mp4

05:37

4.1 threading event.zip

4. Multithreading using Event object.mp4

06:40

5. Top Movers Strategy Intro.mp4

02:01

6. Implementing Top Movers Scanner - I.mp4

07:45

7.1 scanner top movers v2.zip

7.2 scanner top movers.zip

7. Implementing Top Movers Scanner - II.mp4

13:57

8. Additional Logistical Issues to Consider.mp4

06:40

9.1 top movers strategy v2.zip

9.2 top movers strategy.zip

9. Implementing Top Movers Strategy.mp4

11:47

10. Strategy Demo & Bug Fixing.mp4

04:59

8. Implementing Technical Indicators

1. Technical Indicators Intro.mp4

04:40

2. TradingView Charting Integration.mp4

09:40

3. MACD Intro.mp4

08:13

4.1 macd v2.zip

4.2 macd.zip

4. Implementing MACD.mp4

14:37

5. ATR & Bollinger Bands Intro.mp4

09:39

6.1 atr v2.zip

6.2 atr.zip

6. Implementing ATR.mp4

06:50

7.1 blngr bnd v2.zip

7.2 blngr bnd.zip

7. Implementing Bollinger Band.mp4

04:37

8. RSI Intro.mp4

10:27

9.1 rsi v2.zip

9.2 rsi.zip

9. Implementing RSI.mp4

10:02

10. ADX Intro.mp4

04:14

11. ADX in Excel.mp4

12:46

12.1 adx v2.zip

12.2 adx.zip

12. Implementing ADX.mp4

08:57

13. Stochastic Intro.mp4

06:21

14.1 stochastic v2.zip

14.2 stochastic.zip

14. Implementing Stochastic.mp4

05:44

9. Backtesting Strategies

1. Backtesting Intro.mp4

03:11

2.1 cagr v2.zip

2.2 cagr.zip

2. CAGR Implementation.mp4

16:01

3.1 vol sharpe v2.zip

3.2 vol sharpe.zip

3. Volatility & Sharpe Implementation.mp4

10:45

4.1 max dd v2.zip

4.2 max dd.zip

4. Maximum Drawdown Implementation.mp4

10:54

5. Intraday KPIs Intro.mp4

03:15

6.1 intraday kpi.zip

6. Intraday KPIs Implementation.mp4

12:34

7. Sample Technical Indicator Based Strategy Intro.mp4

04:36

8. Implementing Backtesting of Strategy - I.mp4

14:55

9. Implementing Backtesting of Strategy - II.mp4

20:58

10. Implementing Backtesting of Strategy - III.mp4

13:39

11.1 macd stoch bktest general kpi v2.zip

11.2 macd stoch bktest general kpi.zip

11. Implementing Backtesting of Strategy - General KPIs.mp4

11:00

12.1 macd stoch bktest intraday kpi v2.zip

12.2 macd stoch bktest intraday kpi.zip

12. Implementing Backtesting of Strategy - Intraday KPIs.mp4

14:11

13.1 macd stoch bktest long short v2.zip

13.2 macd stoch bktest long short.zip

13. Solution - Backtesting Long & Short Strategy.html

10. Designing & Deploying Strategies on Alpaca

1. Converting Backtested Strategy to Trading Strategy - I.mp4

09:53

2.1 macd stoch strat v2.zip

2.2 macd stoch strat.zip

2. Converting Backtested Strategy to Trading Strategy - II.mp4

15:02

3.1 macd stoch strat demo v2.zip

3.2 macd stoch strat demo.zip

3. Strategy Demo.mp4

05:22

11. Deploying Strategies in Cloud

1. Why Cloud.mp4

04:55

2. Launching AWS EC2 Instance.mp4

19:58

3.1 links and commands1.txt

3. Connecting To Instance - I.mp4

15:12

4.1 links and commands2.txt

4. Connecting To Instance - II.mp4

07:48

5.1 links and commands3.txt

5. Transferring Data Between Instance & Local Machine.mp4

05:41

6. Editing & Running Scripts.mp4

06:12

7.1 links and commands4.txt

7. Scheduling Scripts Using Crontab.mp4

14:59

8. Keeping Track of Running Processes using Screen.mp4

10:32

9. Using Screen Command with Crontab.mp4

07:35

10. Terminating Instance.mp4

03:42

Description

Advanced course on Implementing algorithmic trading strategies using Alpaca's API

What You'll Learn?

Algorithmic Trading
Alpaca's API
REST based API architecture
Handling Websocket based architecture
Multi threading application in algorithmic trading
Deploying strategies on cloud (AWS EC2)

Who is this for?

Traders looking to automate their strategies on Alpaca's platform

Anyone interested in Algorithmic trading

What You Need to Know?

Basic python skills (should be familiar with data types, data structures, loops, functions, installing and importing libraries etc.)

Basic familiarity with finance/trading

More details

Description
Alpaca has revolutionized trading by providing a commission free, API only stock trading platform. This course will help you gain thorough understanding about Alpaca's API and learn how to use it to implement trading strategy. The course will help you understand key concepts pertaining to API architecture (REST/HTTPS based API, Websocket connection etc.) and will prepare you well to build complex trading strategies on Alpaca's platform. You do not have to create a trading account with Alpaca to explore their API, as they also provide an excellent paper trading account which can help you test your strategies as well.
You can expect to gain the following skills from this course
What, Why & How of API trading
Alpaca's API fundamentals
Extracting historical data
Harnessing streaming tick level data
Incorporating technical indicators using python
Integrating Alpaca with TradingView charting
Backtesting strategies
End to End strategy design and deployment
Using multithreading to implement streaming data based strategies
Sqlite database management
Backtesting strategies
Deploying and running strategies on cloud (AWS EC2)

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Important note - Course prerequisites:

Please note that this course requires basic python proficiency. At the minimum, you should be comfortable with:
basic python data types and format
basic python data structures such as list, dictionary, tuple etc.
how to create python functions
how to implement loops in python
installing and importing librariesÂ
In addition, basic familiarity with finance/trading concepts is also required. Although, I have devoted reasonable time explaining concepts like technical indicators, strategy design, KPIs, risk management etc., some prior experience using these concepts would be very beneficial.
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Who this course is for:
Traders looking to automate their strategies on Alpaca's platform
Anyone interested in Algorithmic trading

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Algorithmic Trading

Mayank Rasu

Instructor's Courses

I have authored and published bestselling courses and books on finance and technology. I have a passion for simplifying seemingly complex topics such as algorithmic trading, machine learning, artificial intelligence and make them accessible to students with no technology/finance background.I have more than a decade of experience working with global investment banks in the quantitative analysis/risk management areas. My work experience has made me a firm believer in taking data driven decisions while always being mindful of the qualitative aspects of my job. I did my undergraduate education in engineering and earned MBA and MFE degrees. I see myself as a life long learner and I deeply cherish the opportunity of sharing my knowledge with others.

RASUQUANT LTD

Instructor's Courses

Learn how to implement algorithmic trading strategies on your platform of choice (Interactive Brokers, Zerodha, OANDA, FXCM, Alpaca, MT4 etc.). Start from scratch and gain expert level proficiency in qunatitative finance and algorithmic trading. More than 20000 satisfied students so far.I have authored and published bestselling courses and books on finance and technology. I have a passion for simplifying seemingly complex topics such as algorithmic trading, machine learning, artificial intelligence and make them accessible to students with minimal technology/finance background.

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