This section, we will identify some of the key strengths and weaknesses of quantitative strategies.

    Markets are often driven as much by emotions as by fundamentals. While it is sometimes important to factor in market sentiment, it is usually not a good idea to let your own emotions color your trading decisions（市场通常受基本面因素影响，也受情绪影响。）. In my experience, trader sentiment swing wildly between greed and fear, blinding them to what is really going on in the market. Greed and its enabler egomania often cause a trader to refuse to take profits and rides huge winners all the way down to huge losses. Fear and its enabler self-doubt often cause traders to liquidate positions due to short-term losses that would have eventually turned into big winners.

    Once a strategy is agreed and the rules are in place to control changes to that strategy is more likely that the careful reasoning used to construct the strategy will prevail over the short-term desires to tweak or modify it.（一旦策略达成了一致而且制定了控制策略变更的规则，那么用于构建策略的谨慎推理将更有可能战胜短期内对策略进行调整和修改的愿望） This makes risk management clear and also keeps the emotion out（避免情绪化）.

    Correctly formulated strategies are always optimal from a mathematical perspective（从数学角度看。制定的策略总是最佳的）. This optimality may prove illusory, but it still represents the collective wisdom of a strategy as developers and is a big improvement over the strategies based on sentiment（这种优化可能被证明是虚幻的，但它仍然代表了作为开发人员的策略的集体智慧，是对基于情绪的策略的一大改进。）. Quant trading despite being rules-based, emotion free, mathematically optimal is still quite risky.

    Small firms blow up all the time and see even some of the biggest firms like Knight Capital have flamed out in less than an hour of trading. Knight was the largest trader in US equities with a market share of around 17% on both the New York Stock Exchange and the NASDAQ. Knight’s Electronic Trading Group managed an average daily volume of 3.3 billion trades trading over 21 billion daily and yet due to a computer glitch, Knight accidentally bought 7 billion dollars of equities in 45 minutes with no customer orders or funds to pay for them（购买了70亿美元的股票）. They tried to cancel the orders but failed and was forced to sell the stocks at a $478 million loss. With this loss of trading capital, it had to accept a capital infusion from a rival firm who eventually ended up taking it over.

    Quant trading already dominates the market, it’s extremely competitive（主导市场，竞争非常激烈）. That said, it is the only area of trading that is growing and anyone who wants to develop or trade strategies should invest some of their time and effort on their coding and statistical skills. Quant strategies are only optimal within the context of their assumptions, made during their construction（在假设范围内才是最佳的）.

    This is a weakness, but it is also true of any strategy that attempts to predict a random variable such as equity prices. Profits are never certain in a risky strategy（利润永远不确定）. If you want a guaranteed return, you should be a Buy and Hold investor in government bonds, most of which yielded negative real return.

    Lastly, markets are always changing, uptrending markets and assets suddenly reverse to downtrend which can cause correlations to reverse and volatility to spike upward.

    Overall though, the rapid expansion of quantitative trading shows that the opportunities outweigh the challenges. I hope as we work our way through this course, you will gain a functional understanding of the real world applications of Quant trading techniques. And also how machine learning and AI can help you leverage your development efforts and make your strategies more effective and profitable.