The article explores how different techniques, including the discrete wavelet transform, can be used to study global stock market behavior. The researchers found that stock markets show long-term memory effects in volatility measures, with mature markets recovering faster from crises than emerging markets. They also discovered that stock markets can be classified into more than just emerging and mature categories, with international co-movements and volatility increasing since the mid-20th century. The goal is to anticipate these impacts to make better investment decisions.