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Jacob IsenbergA Negative FED: The Domino of the TradFi Crisis - Florence Finance - Medium
Find out about the ideal bridge that could hold the key to a new financial future With the central pillar of TradFi now operating at a financial loss, there are significant implications on what the future holds for the entire realm of finance. Yet there are likely several semi-interdependent paths, which could occur and we will logically dissect the strengths and weaknesses, of these various outcomes. For reference, we’ll build off of some information discussed in Lyn Alden’s recent piece on ...
Jacob IsenbergReal World Asset Lending: The Next Big Trend in Crypto?
Find out how this $150 million investment in Real World Asset Lending is supporting our vision at Florence Finance Our friends over at MakerDAO have put their money where their mouth is, and together with Centrifuge, have made one of the most significant on-chain investments ($150m) into real-world assets to date. Not only does this show how seriously they are taking their real world assets (RWA) initiative, but it also displays some vital insight as to where the market is headed. We at Flore...
Jacob IsenbergLearn with Autonio: The Essentials of DeFi — Hive
621780d85f519840bf559689\_b73b71ba-p-1080.jpegIn the world of fiat currency there is an obscure yet firmly established hierarchy that controls the creation, circulation, and management of all matters in the financial domain. For ordinary consumers, the main way that we interact with this incomprehensible system is with banks, which have been thought of as the trusted intermediaries for millennia, and will gladly take our funds in exchange for a bank slip that supposedly ensures our money is s...
Jacob IsenbergA Negative FED: The Domino of the TradFi Crisis - Florence Finance - Medium
Find out about the ideal bridge that could hold the key to a new financial future With the central pillar of TradFi now operating at a financial loss, there are significant implications on what the future holds for the entire realm of finance. Yet there are likely several semi-interdependent paths, which could occur and we will logically dissect the strengths and weaknesses, of these various outcomes. For reference, we’ll build off of some information discussed in Lyn Alden’s recent piece on ...
Jacob IsenbergReal World Asset Lending: The Next Big Trend in Crypto?
Find out how this $150 million investment in Real World Asset Lending is supporting our vision at Florence Finance Our friends over at MakerDAO have put their money where their mouth is, and together with Centrifuge, have made one of the most significant on-chain investments ($150m) into real-world assets to date. Not only does this show how seriously they are taking their real world assets (RWA) initiative, but it also displays some vital insight as to where the market is headed. We at Flore...
Jacob IsenbergLearn with Autonio: The Essentials of DeFi — Hive
621780d85f519840bf559689\_b73b71ba-p-1080.jpegIn the world of fiat currency there is an obscure yet firmly established hierarchy that controls the creation, circulation, and management of all matters in the financial domain. For ordinary consumers, the main way that we interact with this incomprehensible system is with banks, which have been thought of as the trusted intermediaries for millennia, and will gladly take our funds in exchange for a bank slip that supposedly ensures our money is s...
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The Emergence of Algorithmic Trading and Its Importance
The overarching aim of algorithmic trading is about obtaining information quicker and executing a trade order faster, thereby leveraging speed and computational resources. Electronic communication in the 1990’s improved this capability, where smaller differences in the bid and ask offer were realized than previously before.
An ongoing evolution of the digital age brought with it the ability to effectively and efficiently replace the mundane trading processes with automated programs (algorithms) which performed the same repetitive tasks. These algorithms determined the price, quantity, and routing of orders. With this data, algorithms were able to make trading decisions as well as submit and manage orders.
Fast forward to the 21st century and algorithmic trading has been adopted by countless investment banks, mutual funds, hedge funds, and pension funds. Its impact varies across different markets where the percentage of its utilization can range over 90%, as is the case in the foreign exchange market.
Its widespread adoption can be attributed to the numerous benefits it offers. Slippage is kept low when liquidity is provided, making trading cheaper for the customer. Overall liquidity improves as well with algorithmic trading, as spreads become tighter. All in all, algorithmic trading has proven to enable faster and easier orders, which are then executed out of the back-end of the broker.
In the current crypto algorithmic trading landscape, software programs are the mechanisms that run sets of algorithms which determine what asset to buy or sell and when to buy or sell it. This is done in an incredibly efficient manner as automated software programs can communicate directly with an exchange through its API.
Overview of Market Making as a Business
Market makers account for the efficiency with which market transactions can take place while the difference between the bid price and ask price is known as the market-maker spread, which is how market makers make money. By providing liquidity on both buy and sell orders they form an integral role in a marketplace while continually placing new orders based on the supply and demand of the asset.
Without overthinking their function, these entities literally make markets with high-volume trading by placing orders on the books to buy or sell an asset to other traders or retail investors. However their role is a passive one as they wait for the orders they’ve set to get filled. Applying the fundamentals of algorithmic trading to market making means that it is now able to actively participate in these processes.
Personalizing Strategy with Parameter Configuration
The main purpose of parameter configuration is to input various strategies into your market making algorithm. The ability to personalize your own unique strategy while also removing the element of human emotion, which has been documented to cause significant losses for traders. More importantly, this helps your risk management by automating the trading process, removing the element of emotion.
Hummingbot’s Role in Algorithmic Trading for Market Making
With a mission of democratizing high frequency (algorithmic) trading with open source technology, Hummingbot offers terminal-based algorithmic trading tools to help capitalize on a large number of orders across multiple markets and multiple decision parameters.
Built on the foundational strategies, Hummingbot provides a mix of trend-following strategies, arbitrage opportunities, and others entirely dedicated to market making.
Market Making Strategies on Hummingbot
The following examples are a few algorithmic trading strategies that can be used for market making:
perpetual_market_making- which allows single trading pairs to run on a perpetual swap in an order book exchange.
avellaneda_market_making- implements the strategy high-frequency trading in a limit order book.
cross_exchange_market_making- lets you make markets by creating buy and sell orders on the maker exchange while hedging filled trades on another taker exchange.
How NIOX Maker 2.0 is Ramping Up Market Making
Maker is contributing the UI to Humminbot’s already robust architecture along with an inclusion of a cloud based service, AI integrations, and an ongoing collaboration in their open source software.
With a beta-release in early November for DAO members, followed by a public launch in December, users of NIOX Maker 2.0 will soon get to experience one of the most up-to-date market making tools within the algorithmic crypto trading space.
Have fun making markets and trading with Autonio!
Originally published on: https://www.autonio.foundation/posts/maker-2-0-the-role-of-algorithmic-trading-in-market-making
Written by: Jacob Isenberg
Edited by: Matthew Breeden
The Emergence of Algorithmic Trading and Its Importance
The overarching aim of algorithmic trading is about obtaining information quicker and executing a trade order faster, thereby leveraging speed and computational resources. Electronic communication in the 1990’s improved this capability, where smaller differences in the bid and ask offer were realized than previously before.
An ongoing evolution of the digital age brought with it the ability to effectively and efficiently replace the mundane trading processes with automated programs (algorithms) which performed the same repetitive tasks. These algorithms determined the price, quantity, and routing of orders. With this data, algorithms were able to make trading decisions as well as submit and manage orders.
Fast forward to the 21st century and algorithmic trading has been adopted by countless investment banks, mutual funds, hedge funds, and pension funds. Its impact varies across different markets where the percentage of its utilization can range over 90%, as is the case in the foreign exchange market.
Its widespread adoption can be attributed to the numerous benefits it offers. Slippage is kept low when liquidity is provided, making trading cheaper for the customer. Overall liquidity improves as well with algorithmic trading, as spreads become tighter. All in all, algorithmic trading has proven to enable faster and easier orders, which are then executed out of the back-end of the broker.
In the current crypto algorithmic trading landscape, software programs are the mechanisms that run sets of algorithms which determine what asset to buy or sell and when to buy or sell it. This is done in an incredibly efficient manner as automated software programs can communicate directly with an exchange through its API.
Overview of Market Making as a Business
Market makers account for the efficiency with which market transactions can take place while the difference between the bid price and ask price is known as the market-maker spread, which is how market makers make money. By providing liquidity on both buy and sell orders they form an integral role in a marketplace while continually placing new orders based on the supply and demand of the asset.
Without overthinking their function, these entities literally make markets with high-volume trading by placing orders on the books to buy or sell an asset to other traders or retail investors. However their role is a passive one as they wait for the orders they’ve set to get filled. Applying the fundamentals of algorithmic trading to market making means that it is now able to actively participate in these processes.
Personalizing Strategy with Parameter Configuration
The main purpose of parameter configuration is to input various strategies into your market making algorithm. The ability to personalize your own unique strategy while also removing the element of human emotion, which has been documented to cause significant losses for traders. More importantly, this helps your risk management by automating the trading process, removing the element of emotion.
Hummingbot’s Role in Algorithmic Trading for Market Making
With a mission of democratizing high frequency (algorithmic) trading with open source technology, Hummingbot offers terminal-based algorithmic trading tools to help capitalize on a large number of orders across multiple markets and multiple decision parameters.
Built on the foundational strategies, Hummingbot provides a mix of trend-following strategies, arbitrage opportunities, and others entirely dedicated to market making.
Market Making Strategies on Hummingbot
The following examples are a few algorithmic trading strategies that can be used for market making:
perpetual_market_making- which allows single trading pairs to run on a perpetual swap in an order book exchange.
avellaneda_market_making- implements the strategy high-frequency trading in a limit order book.
cross_exchange_market_making- lets you make markets by creating buy and sell orders on the maker exchange while hedging filled trades on another taker exchange.
How NIOX Maker 2.0 is Ramping Up Market Making
Maker is contributing the UI to Humminbot’s already robust architecture along with an inclusion of a cloud based service, AI integrations, and an ongoing collaboration in their open source software.
With a beta-release in early November for DAO members, followed by a public launch in December, users of NIOX Maker 2.0 will soon get to experience one of the most up-to-date market making tools within the algorithmic crypto trading space.
Have fun making markets and trading with Autonio!
Originally published on: https://www.autonio.foundation/posts/maker-2-0-the-role-of-algorithmic-trading-in-market-making
Written by: Jacob Isenberg
Edited by: Matthew Breeden
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