Do you want to create a tool that can help you with your real-world investments using Python? In this course, you will learn how to create an interactive web dashboard for financial data analysis for intermediate Python users and learn about pair trading strategies for in-depth quantitative work. We hope that you will be able to create your own useful analysis tools to help you analyze financial data more powerfully and make wise investment decisions.
Create an interactive web dashboard that lets you observe multiple function results simultaneously using Python
Long & Short Strategy: Introduction and Implementation of Pair Trading Strategy among Statistical Arbitrage Techniques
Financial and data background knowledge you must know when investing
How to use Plotly, a Python module that lets you visualize data on the web
Knowledge for analyzing financial data using Pandas
Create your own trading tools
Make financial data analysis smarter!
Don't miss out on the skills that will help you in your real-world investing.
When investing, you are bound to have various questions.
Which sectors should you invest in when interest rates rise?
When interest rates rise, does the banking sector necessarily rise as well?
How do actual sectors change as multiple macro data move?
I need a tool that can observe whether things are moving the way I think they are or the opposite.
It is inconvenient to observe this behavior by changing parameters and re-running it every time.
At this time, if there is a dashboard that allows me to observe complex and diverse indices and immediately check the results I want , it can play that role sufficiently.
Create interactive dashboards to help you make real-world investments!
I hope that this lecture will help you get closer to much more convenient and powerful financial data analysis.
Oh, is this perhaps your concern? 💡
I learned Python
I feel like I'm not using it properly.
Helpful for actual stock investment
Are there any data analysis tools?
For those who are familiar with Python programming and basic time series data analysis, we will create a tool that can be helpful for practical investment using Python .
In the previous 'Creating a Python Trading Room for Quant Investment' Part 1 , we learned how to create functions necessary for analyzing financial data. If you have learned simple programming and data analysis techniques, it is time to take a step closer to solving more complex problems in Part 2. Create a dashboard with your own hands that will help you with real-world investment!
Python Web Interactive Dashboard
(Data visualization library Plotly +
Dashboard building framework)
Using ETF data
Statistical Arbitrage - Pairs Trading
(Long & Short Investment Strategy)
Helpful for investment
With data and financial background knowledge
Understanding Financial Data Movements
Plotly Dash Dash Callback
“Can’t we create a tool that can observe the movements of stock indices and the sectors that make up them (semiconductors, construction, banking, consumer goods, chemicals, electric vehicles, etc.) according to the movements of macro variables such as the won/dollar exchange rate, copper, oil (WTI), interest rates (Rate), gold (Gold), VIX…?”
I will create a tool that allows me to observe how the sectors I am investing in or will invest in move according to the movement of macro variables that are issues in the current financial market. In order to create something that changes according to the movement of multiple variables, I need a tool that can change the variables of the function and run it multiple times and observe multiple functions at the same time. To create such a tool, I will use Python to output the results I want on a web page, input the variables of the function on the web page, and create a web dashboard that allows me to check the changing results of the function without having to re-run Python. Through this dashboard, you will be able to conveniently observe various data and the results of the function on a web page.
ETF?
In this lecture, we will use ETF Close Price Time Series Data to observe the movement of macro variables. ETF is a product that tracks the movement of each product, and it is data that shows the movement of each product well. As time passes, the financial market develops and various products are launched, and the types of ETFs are also diversifying. Although there are not many products yet, it is expected that domestic ETFs will gradually become as diverse as those in the United States. By using ETFs, you can reduce the effort of receiving data from various sites to use various macroeconomic data.
Stationary ADF (Augment Dicker-Fuller) Test Z-Score
“Can’t I learn a strategy that selects Long (buy) and Short (sell) targets through a statistical verification process and then receives signals to make investments?”
For the second project, we will learn about pair trading, one of the statistical arbitrage methods. We will set the statistical assumptions required to set up pairs (target stocks), select a pair that meets those assumptions, and then set up a long-short strategy.
If in the previous Part 1 lecture, we created an index for beginners, in this lecture, we chose a quantitative strategy that can only be attempted by intermediate users who have an understanding of financial data and an understanding of the phenomenon. This is widely used in algorithmic trading, and recently, it is being used to find patterns through machine learning. I wanted to let you know that this concept is a strategy that is widely used in financial algorithmic trading. Through pair trading, we will create a strategy that cannot be composed of a single asset.
Have you only invested to gain profits from the trend from the perspective of buying a single stock? Now, learn the strategy from the perspective of spread through pair trading. Spread trading is a strategy widely used in the financial sector, and the Long & Short strategy is representative. Since it is difficult for an individual to take a sell position, try pair trading using ETF data. By implementing your own various strategies and directly observing the phenomena occurring in financial data, it will be of great help in understanding the movement of financial data.
Top&Down Approach Interest Rate VIX Sales and Cost of Sales
“I want to improve my understanding of financial data, but can I learn more about the background knowledge related to data and finance , and why specific data is used?”
In data analysis, quantitative analysis methodology is important, but I think 'understanding data' is more important. In this lecture, the goal is not to create a financial data analysis tool and end it, but to create our own investment analysis tool. And the higher the understanding of financial data, the more useful the investment analysis tool can be. If you try to express the results with only numbers, you will inevitably get farther away from actual investment. Therefore, background knowledge that can understand the movement of financial data is essential.
In this lecture, we have prepared a separate Finance Background section. There is no right answer in finance, but we have prepared the lecturer's personal opinion that he has felt while working in investment. In this lecture, we will explain why and in what sense we used this data, and why we should use it.
Of course, finance is a complex world that moves, so it cannot be clearly explained in a dichotomous manner. However, I think there is a big difference between building your own logic and looking at and analyzing financial data and not. I want to convey and share these thoughts with you. I hope that you will also be able to create more useful financial analysis tools through your own views that can interpret financial phenomena.
Hello! This is ownCode.
I have spent a lot of time preparing this lecture with the hope that students will be able to analyze financial data more deeply and create their own useful investment tools. I hope that this lecture will help you create your own useful investment tools, make wise investment decisions, and understand financial data.
Q. Is there any prerequisite knowledge required to attend the lecture?
This course is an intermediate-level course aimed at analyzing financial data using Python. Therefore, it is intended for those who have some experience with basic Python programming, financial data, or time series data.
In order to take the course, you must have basic knowledge of the Python module Pandas. You must also be able to create functions in Python and be familiar with the basic grammar. The course was created on the assumption that you already know these contents.
If you don't know or are not familiar with Pandas, I recommend that you first take Pandas for financial data analysis and then take this course. Also, if you lack experience in financial data analysis using Python or are not familiar with functions and list comprehension, you can take Part 1 of Creating Your Own Trading Room for Quant Investment .
Q. Do I have to know the contents of Part 1 to take this lecture?
This lecture does not use the content of Part 1 of Creating My Own Trading Room for Quant Investment as the main content. I created the curriculum to deliver content that is as different from Part 1 as possible. However, when creating a project in the lecture, I used Draw Down, RSI, and MACD. Since this content is explained in Part 1, it is not explained separately in this lecture.
Q. How much mathematical knowledge is needed to understand Pair Trading?
In this lecture, I have excluded the mathematical explanation for Pair Trading. The important thing is to understand the concept of the strategy and what phenomenon occurred to learn such a strategy. To understand the mathematical part and academic content used in Pair Trading, you need academic knowledge of Time Series, and to understand this knowledge, you need knowledge of probability and statistics. Such content and concepts will be covered in detail in subsequent lectures.
This lecture focuses on the phenomenon itself and the background of using this strategy rather than the formula content. Therefore, no mathematical knowledge is required.
Who is this course right for?
Creating a Python Trading Room for Quantitative Investing - Part 1
For those who want to create a Web Dashboard using Python
For those who want to learn Pair Trading strategy during statistical arbitrage
For those who want to create an Interactive Dashboard for Top-Down Investing
Those who want to devise various strategies by understanding the background knowledge of financial data
Need to know before starting?
Python
Building a Python Trading Room for Quantitative Investing - Part 1
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