Making many market observations is key to finding trading opportunities in the markets. Studying live data and historical static data are part of the process. Developing a relationship with the market and placing live trades with real risk in a test account is the best way to learn how the market works. Using short term discretionary techniques as well as scalping strategies, reveal more patterns than static data and SIM trading. The cost of developing fully automated trading strategies is typically much greater than optimizing a few indicator based strategies.
Learning to code takes time. Even experienced coders have to learn market dynamics in order to code a trading strategy for backtesting and live trading. Finding quick ways to backtest a long list of trading ideas is the best way to determine the direction of trading systems research. The ideas that are coded are based on market observations. Since the markets change frequently, coding new trading ideas can become a part of the daily process in keeping a trading systems portfolio relevant. More advanced languages can be used once the basic ideas have been developed.
Backtesting strategy ideas after market observations have been observed and the strategy has been coded is the last step before a strategy can be traded in live trading. The three most important factors that are considered in a strategy backtest is the equity curve, average trade profit, and net profit as a percent of drawdown. During the backtest, we have to consider realistic market conditions. For example, making sure there are no limit order rejects and the path inside the bar based on the parameters used represents an accurate backtest that can be repeated in live trading.