Behavioral finance and how robo-advisors are customizing solutions.

Behavioral finance is essentially the study of how psychological influences affect the decision-making processes of investors, resulting in some irrational financial behaviors in the process. Traditional finance involves the following: traditional finance essentially deals with the notion that the investor always acts rationally to create just the optimal outcome, or maximizing returns and at the same time minimizing risks. But behavioral finance is well aware of this-isn't-perfect information: cognitive biases, emotions, or other psychological influences normally steer investors away from the ideal. Overconfidence, loss aversion, or herd behavior-are all poor financial decisions, and robo-advisors, automated platforms using algorithms to provide financial advice, increasingly use principles of behavioral finance to create customized solutions to overcome these biases and guide investors toward better choices.

Probably one of the most significant advantages of robo-advisors is that they can offer a disciplined, emotion-free approach to investing. Humans inevitably struggle to make rational investment decisions when markets become extremely volatile and investors are very likely to sell in fear when they fall or buy impulsively in rising markets. This emotional response hurts them in terms of bad timing both at entry and exit points. Whereas, robo-advisors operate based on fixed algorithms and investment strategies that do not deviate from their course of duty and ignore short-term fluctuations in the market and do not respond to immediate responses in the face of emotions. By gelling out human emotions from the equation, robo-advisors make it easier for the investors to keep up the long-term focus rather than sticking by their plans no matter what.
Behavioral finance has brought out numerous biases on the side of the investors, and robo advisers have devised techniques to improve on them. One such bias is loss aversion, which occurs when investors feel the pain of losses more than the pleasure of gains. These investors can therefore be overly prudent by predominantly choosing low-risk investments to avoid loss but miss out on significant growth in the long term.

Yet another bias robo-advisors help mitigate is overconfidence. Overconfident investors overestimate their knowledge or their ability to predict the movements of markets. This can lead to excessive trading on an assumption that they can successfully time the market or pick winning stocks. This ultimately means higher transaction costs and a lower overall return. Overconfidence is overcome by the low cost, passive investment strategies offered by robo-advisors, including exchange traded funds tracking market indices rather than attempting to beat them. In this approach, robo-advisors are typically more disciplined, long-term, and normally avoid frequent trading speculations.

Moreover, robo-advisors help fight herd behavior: investors always tend to imitate the others, which sometimes turns into a disastrous asset bubble or crash. According to behavioral finance theories, people have a tendency to herd: they think that if many others are buying a certain stock or asset, it is probably a correct decision. This can lead to speculative bubbles that exploded in instances such as the dot-com boom wherein individuals continued to pour money into overvalued technology stocks based on the fact that it became accepted by the masses. Robo-advisors, however, base their selection of portfolios on objective data and financial models following factual undercurrents instead of tendencies or fancies of the market. By being data-driven, robo-advisors, therefore, prevent investors from acting irrationally with market behavior and help them to avoid the evils of chasing hot stocks or speculative bubbles.

In addition to dealing with the cognitive bias, robo-advisors provide personalized investment advice as they analyze enormous amounts of data related to each investor. Most robo-advisors start by requiring a client to fill out a questionnaire that makes an evaluation of their financial goals, their tolerance levels for risk, investment time horizon, and income requirements. This data is then used to produce a tailored portfolio based on distinctive personal considerations. For instance, a young investor that has no objection to taking on a higher level of risk and the time horizon of many years, so the portfolio allocated here would be significantly weighted in equities; an older investor nearing retirement may receive a much more risk-averse portfolio with a higher allocation to bonds. This again makes sure that the portfolio is tailored to each investor's personal profile and investment strategies drive in accordance with long-term financial goals and risk preferences.

Robo-advisors also increasingly use behavioral nudges to assist investors in remaining on track or avoiding common financial mistakes. It draws features directly from much behavioral finance research by allowing users, for example, automatic rebalancing, so it gets the portfolio back to the original asset allocation should that drift away due to market movements. It allows the investor to have his intended risk level and also stops him from becoming overexposed in a particular asset class, like stocks during a period of bull run in the stock market. Some also offer goal-based investing where, through reminders of long-term financial goals-to save for retirement or a home, for example-investors do not get sidetracked by a fluctuating market.