Index arbitrage. Introduction.

Introduction to a series of posts on trading, where robots rely on the index when making decisions.

We have a great data source in OsEngine that generates an auto-index using an auto-formula. In this series, we will discuss:

1. Possible robot algorithms. Why is this necessary in trading?

2. How to collect the index?

3. Volatility, Correlation, Cointegration, and volumes in trading from the index.

4. Why it's important to also look at the broader market and how to do it.

5. How it's done in OsEngine?

6. Let's look at examples of several robots using this type of data source in OsEngine. We will analyze it line by line.

1. Index in the context of algo trading.

An index is a combination of price series of exchange-traded assets, combined (added, weighted, normalized, etc.) together into a series that should reflect the overall dynamics of the original price series.

Or, moving away from mathematics towards trading:

An index is an indicator of the dynamics of several (or many) assets, which can be used to compare with the traded instrument to make trading decisions.

Or, getting closer to programming:

An index is merged data on trades (arrays of Close or OHLC) of many instruments together using a certain formula.

2. Why do we need an index?

The index shows us, as traders, where the market is heading in a particular part of the market.

There are many classifications of indices. The following are highlighted:

1. Sectoral indices. Reflect the dynamics of price movements within a specific economic sphere. Example: gas industry. Creating an index from companies involved in gas production. Or the Financial sector, then creating an index of banks traded on the exchange. Or services providing blockchain services in Crypto, then creating an index from ETHUSDT, ADAUSDT, etc.

2. Geographical indices. Reflect the dynamics of exchange movements in a particular region of the planet. Example: Brics / G7. Russia / America / Europe / Asia. And so on.

3. According to the calculation methodology. We will talk about this below.

Looking at one of these indices, we can understand how traders are currently positioned by sector, region, etc., and make trading decisions based on this data.

There are many trading strategies that trade from the index. In this series of articles, we will discuss the following:

1. Index one-legged arbitrage on mean reversion.

2. Trending index one-legged arbitrage.

3. Index two-legged arbitrage.

4. Inter-exchange index two-legged arbitrage.

5. Index arbitrage.

3. Weighing securities in the index.

Equal weighted index - the weight of each component security is determined to be equal to the others.

Volume weighted index - the weight of each component security is determined by identifying trades for each security over a certain period and determining its share in the total volume of all securities in the index. The identified share will be the weight of this security in the index.

Price weighted index - the weight of each component security is determined by dividing its price by the sum of all prices in the index.

Market capitalization weighted index - the weight of each component security is determined by dividing its market capitalization by the total market capitalization of all securities in the index. This information is reference, and will not be used in the calculations within the series of articles.

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