the more fair & crystal is the sky, the uglier seem the clouds that in it fly
Henry Bolingbroke, Duke of Hereford
King Richard Ⅱ by W Shakespeare

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the more fair & crystal is the sky, the uglier seem the clouds that in it fly
Henry Bolingbroke, Duke of Hereford
King Richard Ⅱ by W Shakespeare
How can artificial intelligence (AI) impact our understanding of behavioural finance and marketing?
In recent years, research in machine learning has made dramatic advances. Perhaps the most famous example is the AI Go player AlphaGo created at Google Deepmind. Although Go is overall a more popular game than Chess, it is not as well known here in the west owing to its Asian origins.
The scientific paper outlining Google’s approach, published in the journal Nature in January 2016 this year, leads with the sentence “the game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves”.
The possibility of AI to beat the top human players was considered to be at least a decade away. The authors then describe the machine-learning algorithm that beat the European champion in five out of five professional games and later also beat the legendary South Korean player Lee Sedol, considered by many to be the top player over the past decade, in four out of five games. All games were broadcast on live TV across Asia and live streamed over the web to the rest of the world.
But it is not only in the area of games that machine learning has recently made significant progress. Another paper, also published in the journal Nature this year, shows how machine learning can be used to predict the synthesis of new inorganic-organic hybrid materials. The production of new materials is a complex process not fully understood and relies primarily on trial and error. A machine-learning algorithm trained on data from failed experiments was used to predict the successful synthesis of new materials. It greatly outperformed traditional human strategies. New hypotheses on the formation of materials, not previously understood, were revealed. These are only two out of many recent examples of where machine learning has supplemented human intelligence.
Practitioners in the areas of both behavioural finance and marketing are typically familiar with, now fairly standard, econometric techniques such as linear regression and controlled trials. These methods clearly have a firm place in the practitioner’s toolkit due to easy-to-understand properties and results that are easy to explain to clients.
But there is now scope for machine learning to make similar massive advances in our understanding of behavioural finance and marketing. .
Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G.,& Dieleman, S. (2016). Mastering the game of Go with deep neural networks and tree search. Nature,529(7587), 484-489.
Raccuglia, P., Elbert, K. C., Adler, P. D., Falk, C., Wenny, M. B., Mollo, A., ... & Norquist, A. J. (2016). Machine-learning-assisted materials discovery using failed experiments. Nature,533(7601), 73-76.
Premium Bonds vs Cash ISAs: Behavioural Tips for UK Savers
Ever caught yourself daydreaming about a massive Premium Bonds jackpot while your Cash ISA quietly ticks over? Me too — choosing between a flutter and guaranteed interest is as much about feelings as it is about numbers.
Would a saver trade predictable interest for the thrill of a tax-free prize? UK residents weighing ISAs and Premium Bonds, often with £1k–£50k, worry about odds, tax and access. Arithmetic and behavioural insight exposes common traps such as probability weighting and loss aversion. Thrill value also plays a role. Expected-value comparisons and a basic calculator can turn uncertainty into a clear personal choice.
Behavioural finance: prize versus guaranteed interest choices. Deciding between Premium Bonds' prize draw and guaranteed interest savings comes down to maths. Behaviour affects how savers value odds and certainty. Premium Bonds give uncertain, prize-based returns. Behavioural finance shows people often overweight tiny odds and value the thrill of draws. That can make Premium Bonds feel more attractive than their arithmetic expected value.
ISAs offer predictable compound interest and tax-free shelter within the annual ISA allowance. Compare expected value, odds at your balance and liquidity. Also assess how much uncertainty you enjoy.
Key factors to compare
Compare expected value, variance, liquidity and psychological appeal to decide which product fits a saver. Draw a clear line between arithmetic and behaviour. Arithmetic covers expected returns. Behaviour covers how people feel about odds. Match the product to the goal: emergency access, steady growth or entertainment.
Probability weighting
Time to smack those instincts against the maths and find out which side wins...
Read the full analysis about premium bonds vs cash isas behavioural in the original article.
Why everything is turning into betting
Everything is turning into betting because structural economic pressure, financial disillusionment and digital platform design have made high-risk speculation feel rational to a generation that sees traditional wealth-building as unattainable. Wage growth has lagged inflation across developed economies, housing affordability has deteriorated, and the mathematics of compounding appears too slow to…
How Past Performance Can Mislead Investors? Let’s explore how anchoring bias affects mutual fund selection and how to make better investment
Behavioural finance is the study of the way in which psychology influences the behavior of market participants both at the individual
Behavioural finance is the study of the way in which psychology influences the behavior of market participants both at the individual and group level and the subsequent effects on financial markets.
It is a part of behavioural economics which deals with biases and cognitive errors affecting investors’ investing behavior. It makes an attempt to explain the gaps and market anomalies. Standard finance theories and framework does not explain this. Standard finance theories and models are based on certain assumptions
investors are rational
investors are risk averse
investors are self interested utility maximizers
investors update their belief, as new information comes in
investors have access to all available information
Real life behaviour of investors is different from what traditional finance models assume. Some of the example in daily life are
investors hold concentrated portfolio instead of diversifying
investors show greed and fear instead of making rationale choice of risk return
instead of accepting randomness with winning investments, investor attribute it to their skill
investors getting confused between a good company and a good stock
investors perceive domestic companies because they perceive the risk is low due to familiarity of the company
So real life investors are very different from those in standard finance theory.
Nobel laureates Daniel kahneman and Richard Thaler brought behavioural finance to forefront and attempt to integrate it with standard finance.
Bounded rationality
Most investors have limited 1.time Or 2.information or 3.ability to comprehend complex information at the time of decision making. Similarly when selecting one of many options requires meticulous analysis incorporating all the available information, people get confused.
They settle with an option possibly suboptimal which seems to be satisfactory and sufficient based on quick analysis governed by ‘thumb rules’. In other words, instead of optimizing as suggested by theories in finance, investors “satisfice” (seemingly satisfactory and sufficient).
How Past Performance Can Mislead Investors? Let’s explore how anchoring bias affects mutual fund selection and how to make better investment
Behavioural Finance Meaning, Types, Benefits | Bajaj Finserv Mutual Fund
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