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Trading

Overview

Trading products to service digital asset trading include delivery by spot and derivatives orders/contracts.

Utilizing institutional grade trading and compliance solutions to execute trades based on comprehensive analysis. Orderblock™ builds trading algorithms, bots, and scripts to reveal edges within competitive markets. The company is well-postured to stay ahead of the competition in the fast-paced digital asset trading sector.

Market Competence

Algorithmic

Automation with machine learning

Target Forecasting

Predictive analysis decision making

Custom Metrics

Research crafted trading software

Custom Metrics

Research crafted trading software

Data Filters

Depth of granularity in market data

Market Intelligence

Research crafted trading software

Strategies

Backtesting strategies to examine ex-post data
Base strategies are a combination of advanced data collection and analysis, sophisticated technology, and traders who make discretionary decisions. Proprietary systems paired with human invention is the largest fundamental driver to our success.

Market Opportunities

Mean reversion and range-bound market making conditions are driven by substantially automated systems and provide consistent revenue streams for the business. Discretionary trading based on market events and sentiment, and is independent of automation.

Systematic ideologies, planning, and management in regards to capital allocation are all taken into account in every business process. The trading desk's sole operational task is to stay ahead of the competition and to make informed trades based on trusted, timely market information.

machine-learning
high-frequency-trading
volatility-trading
quantitative-trading

Mean Reversion

Return of price to certain historical averages

Range Bound

Price fluctuations within an accepted range

Event Based

Price momentum based on fintech events

Sentiment Driven

Price adaptability driven by social conditions

Calendar Events
Positioning markret-neutral, long, and short during calendar events. Trading decisions focus on interest rate decisions, critical data reports, and other accompanying statements. Metrics conceived from crowd-sourced data can detect changes statement language usage, and determine if there is a hawkish or dovish bias. Web-scraping python scripts can fetch rate decisions in milliseconds.
Protocol Upgrades
Protocol and network research provides insight to understand what is changing, and its potential impact on the network and the value of a digital asset. Market sentiment for invoked upgrades can have both long and short term effects on price. EIP 1559 fundamentally changed the supply of the Ethereum network, meanwhile a DAO protocol layer proposal may bear less significance on price & supply.
Token Economics
Use case, product market fit, and the team's ability to orchestrate their vision. Tokenomics are a viable tool to forecast future price action based on; changes in the total supply, circulating supply, and any mechanisms that affect the token's supply such as burn or buyback. We also look at analytics concerning the token's float as well as unlock and vesting schedules. High floats generally create an environment of liquidity.
Supply and Demand
Supply and demand factors have an effect the pricing correlations of digital assets. Events that dictate supply and demand changes are catalysts for future pricing of an asset. Token issuance, burn events, and mining estimates can be helpful indications of on the move liquidity. Gauging market sentiment and following the course of the majority of market participants is imperative to making strong forecasting decisions.

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