From the inception of the Wealth Forge institute,Robovis Prof. William Decker tried to create a "lazy investment system", and he realized early on the significance of quantitative trading in the future, which will be applicable to all kinds of investment markets and types of investment, such as the securities market, various types of futures market trading, cryptocurrency market trading, foreign exchange market trading, and so on.

Compared to subjective trading, quantitative trading can help investors/traders deal with many problems:

1. Avoiding Emotional Trading: Quantitative trading can help investors eliminate the influence of emotional factors on trading decisions and thus trade more objectively and rationally.

2. Automated Trade Execution: Quantitative trading can automate the execution of trading strategies and quickly respond to market changes, reducing human errors and delays.

3. Big Data Analysis: Quantitative trading can utilize large-scale data and analytical tools to mine and analyze market patterns and trends to identify potential trading opportunities.

4. Risk Control: Quantitative trading allows for the application of strict risk management and stop-loss strategies to protect portfolios from significant losses.

5. Statistical Advantage: Through quantitative trading, investors can utilize statistical principles and mathematical models to improve portfolio returns and risk management.

6. Market Arbitrage: By quickly reacting to market price differences and potential conflicts of interest, quantitative trading allows for market arbitrage and thus profits.

7. Transaction cost optimization: Quantitative trading can reduce transaction costs through algorithms and execution strategies, such as low latency trading and high frequency trading.

8. Diversified investment: Through quantitative trading, diversified investment strategies can be easily implemented, including trading in stocks, futures, foreign exchange and other asset classes.

Overall, quantitative trading can help investors improve trading efficiency and profitability in terms of decision-making, execution and risk management.