Quantitative Supply and Demand Trading

Quantitative Trading: All models are wrong, some are useful

Quantitative trading is the practice of using data to drive decision making in making trades and participating in financial markets. This approach encompasses a range of strategies, from fully automated algorithms to structured manual systems, offering various alternatives to purely discretionary trading.

Quantitative vs Discretionary Trading

Decision-making Process: Quantitative trading relies on systematic rules and data analysis. We may develop these methods based on market observations, historical data, and specific hypotheses. We may use hard coded algorithms, or stick with simpler, manually executed rule sets. Discretionary trading, in contrast, depends on a trader's judgment and real-time market interpretation. This human intuition is immensely powerful, but comes with potential risks, like fast paced markets and high stress volatility. Quantitative methods aim take the load of decision making out of the real time execution, while discretionary approaches leverage human intuition.

Analysis and Execution: Quantitative trading excels in processing market data systematically, whether through computer algorithms or structured manual analysis. This approach allows for consistent evaluation across multiple instruments and timeframes. Discretionary traders may also be able to do this, but struggle to maintain the same level of consistency, especially during high-stress market periods.

Strategy Application: A key strength of quantitative trading lies in its consistent application of strategies. Whether automated or manual, the system follows defined rules regardless of market noise or our current emotions. Discretionary trading may see variations based on the trader's current perspective or recent experiences, which can be both a strength and a weakness.

Emotions can be a traders worst nightmare. Quantitative trading aims to mitigate this risk. By executing trades based on predefined rules, quantitative systems minimize the influence of fear, greed, and other emotions that may throw us off. This objectivity helps us from making irrational decisions when we find ourself in uncomfortable positions in markets. Quantitative approaches maintain strategy integrity even in markets that seem crazy or unpredictable. Whether through automated systems or disciplined manual execution, these methods continue to follow their rules regardless of market conditions. This consistency can be crucial in capitalizing on opportunities during high risk, high reward, volatile moments in markets.

Today, I'm going to share my SUPPLY AND DEMAND trading systems rules. This system aims to identify high-probability areas where I expect price to bounce or reject using a simple candlestick pattern and set of rules. Also included is a Custom ThinkOrSwim script: Auto-plots levels from our quant analysis

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