Blockchain Quantitative Investing series of courses ((1) - briefing

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NO.1

Blockchain is known as a decentralized distributed ledger technology, and its birth may have had a greater impact on humanity than any event in history. It has numerous application scenarios, and it can be said that everything can be carried on the basis of blockchain, for example: digital currency.

As an unprecedented cryptocurrency, Bitcoin is one of the most groundbreaking monetary experiments in human history, having endured countless market tests and technical attacks.

Due to its broad prospects and enormous imaginative space, the price has been rising steadily since its birth in 2009, reaching $1 in 2011 and peaking at over 1 oz of gold in 2013.

Today, Bitcoin has grown into a monetary system with tens of millions of users worldwide, tens of thousands of merchants accepting payments, and a market capitalization of up to $100 billion, a reference to the traditional financial system.

Blockchain technology has also attracted venture capital from thousands of well-known venture capital funds, companies, and individuals, including many traditional financial giants such as Visa, Nasdaq, Citigroup, MasterCard, Goldman Sachs, IDG Capital, PayPal, NYSE, and others.

As the number of digital currencies and exchanges increases, and the domestic economic environment becomes increasingly difficult, more and more people are realizing that using quantitative technology to invest in blockchain digital currencies is also becoming a trend in modern asset management. Quantitative trading in digital currencies is essentially the same as in futures and equities, and is based mostly on mathematical and statistical modeling, using computer technology to extract from the vast amount of historical data the most likely ways to generate stable returns. Whether it is stocks, futures, foreign exchange or digital currencies, speculative markets are the same in nature, because no matter what the trading market, the final participants are made up of people, but human nature is difficult to change.

Models, therefore, replace human subjective judgments and will greatly reduce the negative impact of irrational decisions caused by investor mood swings.

NO.2

Quantitative trading in digital currencies is essentially the same as in futures and equity, and is based mostly on mathematical and statistical modeling, using computer technology to extract from the vast amount of historical data the most likely ways to generate stable returns. Whether it is stocks, futures, foreign exchange or digital currencies, speculative markets are the same in nature, because no matter what type of trading market, the final participants are made up of people, but human nature is difficult to change.

Models, therefore, replace human subjective judgments and will greatly reduce the negative impact of irrational decisions caused by investor mood swings.

A qualified quantitative trading model must be based on clear economic meaning and trading concepts, systematized and programmatically abstracted, and presented in the form of a set of logically complete executable trading instruction processes and logical control schemes.

No.3

This series of courses will be driven by classic quantitative strategies and will integrate data, key codes, trading concepts, and trading methods into quantitative trading projects. It will teach you the end-to-end quantitative trading process, as well as each implementation link in the process. On the other hand, we will introduce how machine learning models are applied to quantitative modeling.

The content of the course will include a lot of programming, some mathematics, statistics and other knowledge, which is also the basic qualities that a Quant should have.

In addition, in order to ensure that you are ready to learn and build a quantified trading system that can work and run, we will show you the trading strategies mentioned in each lesson in detail.

Finally, we believe that strategy is more important than tactics, and whether you have the right trading concept determines your trading level. Or that only the right trading concept can steer the trading system to respond to different market conditions.

NO.4

By learning about this series of courses, you will gain the following:

• This is a great opportunity to learn more about the global digital currency market.
• To increase awareness and capacity to seize opportunities in the various digital currency markets.
• To advance the theory of quantitative investing and broaden the practical thinking and vision of quantitative investing.
• How to build modules in a quantitative trading system.
• It is important to capture the market's leverage by building a quantitative investment strategy.
• Learn how to implement trading models such as risk models, cost models, and portfolio building models.
• Big data and AI in quantitative trading systems.
• Quantify the pitfalls that the trading system may encounter in the course of a real-world war.
• It helps to empower strategic investment decisions and increase the capacity for quantitative product design and R&D.

To sum up, the real-world analysis and case studies of different digital currency markets will not only help you gain a deeper understanding of quantitative investment ideas, quickly familiarize you with the cutting edge technologies of quantitative investing and global market conditions, improve your ability to use language tools to process data, efficiently build quantitative investment strategies, but also help you broaden the real-world thinking and vision of quantitative investing, improving the theoretical foundation and the real-world capability at the same time.

NO.5

The purpose of this series of courses is not to sell any trading strategy, but rather to show the ideas of the research and development strategy, so that people can write a system that suits them and can adjust it at any time.

Unlike other quantitative trading classes, we don't teach you the secrets to getting rich overnight. In fact, quantitative trading is a serious data science and project-based practice course, so we are firmly against the packaging and demonization of quantitative trading.

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