The perception that one has for quantitative trading might not accurately showcase its bounds, and out of all, this branch of trading hinges on one\u2019s psyche, be it in conjunction or tearing down an algorithm. Such algorithms by being low or high performing need decision making and emotional un-attachment from the assets that allow and break down various quantitative trading strategies. Due to the nature of trading, there are psychological barriers that need crossing in order to perform at optimal efficiency.
<\/p>\n\n\n\n
While attempting to make a rational decision, there often exists such mental emotion hurdles that refrain one from performing, these are known as psychological barriers and consist of the following:<\/p>\n\n\n\n
Fear of Loss: Overconfidence: Confirmation Bias: Loss Aversion: Performance Anxiety: One:<\/strong> For some self reinforcing of action is needed by bypassing it, and for that one motive is to place faith in the algorithms in relation to system interfaces.<\/p>\n\n\n\n Challenge:<\/strong> Letting go and not aiming for manually handling the entire trade.<\/p>\n\n\n\n Solution: <\/strong>Analyze and comprehend backtesting and the rationale that goes into using quantitative models. A solid faith in the legitimacy of algorithm can prevent the traders from getting emotional.<\/p>\n\n\n\n Example:<\/strong> If in the case of a model sells, then execute a trade without considering market gossip.<\/p>\n\n\n\n Challenge:<\/strong> Making Emotional Decisions in lots of Volatility.<\/p>\n\n\n\n Solution:<\/strong> Focus centrally on adopting clear cut systems, such that it is easy to determine a clear entry, exit, position sizing and risk management plan.<\/p>\n\n\n\n Example: <\/strong>Targets are based on strategy parameters rather than personal emotions, therefore stop-loss and take-profit levels can be utilized.<\/p>\n\n\n\n Challenge:<\/strong> Overcoming being emotional over possible loss as well as gain.<\/p>\n\n\n\n Solution:<\/strong> Persuade clients to understand that trading is a probabilities game and it is only natural to loose at times.<\/p>\n\n\n\n Example: <\/strong>The main focus should be on 100 trades as a whole, and not concentrate on what happens on a trade to trade basis.<\/p>\n\n\n\n Challenge: The propensity to make models that are impulsively out of touch with the system.<\/p>\n\n\n\n Solution: Eliminate centrally framed decisions by automating trade execution.<\/p>\n\n\n\n Example: Employ algorithms that make trading automatic depending on the signals received as opposed to manual intervention.<\/p>\n\n\n\n Challenge: <\/strong>Being Unaware of their own psychological trends towards emotional trading.<\/p>\n\n\n\n Solution: <\/strong>Keep a record of all trades in a notebook to appraise each individual decision and to detect triggers of emotions.<\/p>\n\n\n\n Example:<\/strong> If there is a repeated sign that certain trades are slower than normal during the times that the market is experiencing high volatility, then that is the signal to make those strategies then.<\/p>\n\n\n\n Managing Expectations Challenge: <\/strong>The goal set by management may not be realistic and it may lead to either frustration or being overly aggressive in taking risk. <\/p>\n\n\n\n Solution:<\/strong> Based on past performance records and an individual\u2019s willingness to take risk, feasible targets are set. <\/p>\n\n\n\n Example:<\/strong> Rather than seeking a 50% return in a year, look to set an objective of something like 12-15%, which is more in line with reality.<\/p>\n\n\n\n 7. Growth Mindset: <\/strong><\/p>\n\n\n\n How to Develop Christine Amanpour\u2019s Growth Mindset Challenge: Having a loss and relating it back to failure. <\/p>\n\n\n\n Solution:<\/strong> Use these losses to learn more and then improve and change the model in the future. <\/p>\n\n\n\n Example: <\/strong>Suppose, a model has been persistently poor at turning a profit during earning seasons. A little adjustment to the model would be to consider these days as seasons.<\/p>\n\n\n\n 8. Must Shift Focus From \u2018Me\u2019 to \u2018We\u2019 Challenge: <\/strong><\/p>\n\n\n\n Over-emotional ownership in specific trades or an asset class. <\/p>\n\n\n\n Solution: <\/strong>Apply multi-strategy, multi-assets across multi-time frames to minimize reliance on any one trade. <\/p>\n\n\n\n Example: <\/strong>Use momentum and mean-reversion strategies in combination in stocks and commodities in order to spread and lower the risks.<\/p>\n\n\n\n 9. Factor E: <\/strong><\/p>\n\n\n\n Innovation is Visionary and the introduced marginalized growth did not make significant impacts Challenge: <\/p>\n\n\n\n Too much stress due to inability to control drawdowns or due to market volatility. Solution: Imagining such techniques where traders calmly and rationally speculate and trade through a set of organized parameters. <\/p>\n\n\n\n Example:<\/strong> Anticipate moments during trading sessions when market fall may happen.<\/p>\n\n\n\n 10. Get Some Fresh Air: <\/strong><\/p>\n\n\n\n Taking breaks Ensure that Hard Work does not Result in Poor Decision-Making Challenge: Over-emotional exhaustion which might come off as poor judgment on the managements or decision makers part. <\/p>\n\n\n\n Solution:<\/strong> Keep putting in breaks on a scheduled basis or cut trading after specific set hours. <\/p>\n\n\n\n Example:<\/strong> Stop trading after high volatility for a period reaching between 2to 5 trades.<\/p>\n\n\n\n The Role of Technology in Overcoming Psychological Barriers<\/strong><\/p>\n\n\n\n Tools for Backtesting<\/p>\n\n\n\n Get confidence in the strategy by analyzing its past performance.<\/p>\n\n\n\n Software for Managing Risk<\/p>\n\n\n\n Automatically determine the size of a position and the stop-loss orders.<\/p>\n\n\n\n Tools for Analyzing Sentiment<\/p>\n\n\n\n Cut the market noise and match market activity with strategy in terms of insights.<\/p>\n\n\n\n Dashboards Tracking Performance<\/p>\n\n\n\n Analyze the win rate, drawdowns, or Sharpe ratios, among others, and optimize the parameters based on the results obtained. Traders who break the psychological barriers usually achieve such goals as<\/p>\n\n\n\n Increased Stability: <\/strong>There are fewer distortions due to rules interrupting a trader, so there is a discipline that grows.<\/p>\n\n\n\n Greater Returns While Taking on Below-Normal Risk:<\/strong> Decisions made are more impartial and there are no unnecessary risks assumed.<\/p>\n\n\n\n Greater Self-Faith: <\/strong>Systems offer clear guidance on market fluctuations and systems can be used with no- or low- emotion.<\/p>\n\n\n\n Reduced Levels of Anxiety: <\/strong>The need to conform to a range of rules and systems eliminates the emotional aspects associated with trading. While driven by algorithms quantitative trading is not without its own psychological challenges. Knowing the psychological barriers that most people have for example fear, overconfidence and loss aversion and how these can be dealt with for example by following rules, automating or suppressing emotions improves the effectiveness of traders. The important thing to remember about quantitative trading is that it is not sufficient to possess the best models; you also have to possess the psychological self-discipline not to deviate from following the models.<\/p>\n\n\n\n
<\/strong>Even when models indicate good conditions for trading, contracts are not traded as the trader is afraid their capital would be lost in the process.<\/p>\n\n\n\n
<\/strong>When a certain trade is successful, confidence boosts to overextents where risks are taken unnecessarily or strategies are ignored.<\/p>\n\n\n\n
<\/strong>Information matching the beliefs of a trader are the only ones sought, data contradicting those beliefs is ignored.<\/p>\n\n\n\n
<\/strong>Once a position is taken and the assets in that position begin to lose their value, there is a trader\u2019s correction which if too much pain is attached then such position is held on to for too long.<\/p>\n\n\n\n
<\/strong>Due to certain assets having targets and benchmarks, there is the worry to meet those metrics, and this worry leads to irrational behavior.
<\/p>\n\n\n\nCountering Psychological Hurdles<\/h5>\n\n\n\n
\n
\n
\n
\n
\n
<\/ol>\n\n\n\n
<\/ol>\n\n\n\n
<\/ol>\n\n\n\n
<\/ol>\n\n\n\n
<\/p>\n\n\n\nThe Effects of Breaking out of the Psychological Barriers<\/h5>\n\n\n\n
<\/p>\n\n\n\nTo Conclude<\/h5>\n\n\n\n