Go Summarize

HFT Trading Bot Strategy 2023

Jacob Amaral2022-11-27
trading bot#crypto trading bot#best crypto trading bot#trading bots#bitcoin trading bot#best trading bot#crypto bot trading#trading#crypto trading#crypto trading bots#cryptocurrency trading bot#crypto trading bot tutorial#trading robot#day trading#day trading bot#bybit trading bot#forex trading#make money crypto trading bot#how to setup crypto trading bot#bot trading#trading robot forex#forex trading robot#stock trading bot#pionex trading bot
37K views|1 years ago
💫 Short Summary

The video segments discuss high frequency trading strategies using cumulative Delta of an order book to predict market movements based on buyer and seller activity. The importance of statistical analysis, backtesting, factoring in slippage and commissions, and parameter optimization is emphasized. The speaker demonstrates coding systems for trading decisions and highlights the significance of using math to find an edge in trading strategies, applicable to various trading styles. Overall, the video promotes building profitable systems through mathematical approaches in high frequency trading and other trading systems.

✨ Highlights
📊 Transcript
The segment explains high frequency trading (HFT) and a strategy using cumulative Delta of an order book.
Cumulative Delta is the difference between bid and ask prices, reflecting buyer and seller activity.
Traders can forecast market movements by measuring Delta over time.
The strategy involves tracking market buys and sells at each price within different time frames.
Positive Delta indicates more buyers, while negative Delta shows more sellers, helping traders predict price movements and gain an edge in the market.
The significance of Delta in trading and how platforms like NinjaTrader use the Cumulative Delta indicator to measure the difference between bid and ask prices.
Explanation of how Delta is calculated and examples of code used to track Delta crossings above and below specific thresholds.
Importance of understanding Delta variations in forecasting market movements based on buyer and seller activity.
Trading strategy based on analyzing Delta crosses in the market.
Determining whether to go long or short based on specific conditions related to the last close and Delta values.
Variables such as long continuation, long reversal, short continuation, and short reversal are used to make trading decisions.
Calculating the percentage chance of a successful trade using historical data.
Focus on oil trading and suggestion to test the strategy with different bar sizes for potentially higher success rates.
Importance of building a strategy based on statistical analysis.
Demonstrates coding a system to enter short on a Delta cross above 100 and back testing for profitability.
Goal of achieving a 54% win rate by going short after a Delta cross above 100.
Process involves checking current positions, entering or exiting short positions based on specific criteria, and analyzing bar close data.
Emphasis on thorough testing and monitoring to identify and resolve calculation bugs.
The impact of slippage and commissions on trading returns.
Importance of factoring in slippage and commissions during backtesting for accurate results.
Need for accuracy in calculations to account for negative effects on net returns due to numerous trades.
Applying slippage and commission adjustments for more accurate results when building a trading system.
Significance of using a mathematical approach to find an edge in high-frequency trading systems.
The video discusses high frequency trading systems using order flow cumulative Delta.
The speaker emphasizes the importance of mathematical aspects and parameter testing for optimization.
Personal experience with two versions of the system in the live portfolio is shared, highlighting the need to test different values and time frames for accuracy.
Math can be applied to swing trading or longer hold time systems, not just high frequency trading.
The video promotes using math to find an edge in trading strategies and encourages building profitable systems for portfolios.