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Discerning Behavioural Finance

  1. DICERNING BEHAVIORAL FINANCE Dr. Shikta Singh Associate Professor, Finance & Economics KSOM KIIT UNIVERSITY, IoE A Glimpse into the Non CONVENTIONAL Approach of Finance- An Eye through the Behavioral Finance
  2. 2 ABOUT KIIT o Founder- Dr. Achyuta Samanta, M.P Lok sabha o The Ministry of Education Govt. of India has granted ‘Institution of Eminence’ (IoE) Tag to KIIT Deemed to be University. o In 2020, KIIT was placed 21st rank among Indian Universities ranked by National Institution Ranking Framework (NIRF), Govt. of India. o KIIT School of Management, a constituent school of KIIT secured 30th rank in the same year. Though very young, it is moving up the ladder of rankings and recognition with an increased acceleration with its focus on academics. o The Institute has received “A” ranking by the National Assessment & Accreditation Council (NAAC). o Globally in 2021, the institute was placed in the 101-200 range given by the QS University Rankings of Times Higher Education. In World o As per ARIIA (Atal Ranking of Institutions on Innovation Achievements) Ranking its No. 1 o Won Prestigious Mac Jannet Award for “Art of Giving”
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  7. SO THESE TWO SYSTEM WORKS- • System 1 operates automatically and rapidly. It requires little or no effort and is not amenable to voluntary control. • System 2 is effortful, deliberate, and slow. It requires mental activities that may be demanding, including complex calculation. 7
  8. SYSTEM-1 • Here are some examples of the automatic activities attributable to System 1, in rough order of complexity.  Detect that one object is nearer than another.  Discern friendliness in a voice.  Answer 2+1=?  Drive a bicycle on an empty road.  Comprehend simple sentences. • All these mental events occur automatically and require practically no effort. 8
  9. SYSTEM-2 • While the activities of System 1 normally run on an automatic pilot and are involuntary, the operations of System 2 require attention and voluntary effort. Here are some examples of the operations of system 2.  Identify the no. of blinking arrows in the circus.  Discern the voice of a friend in a crowded and noisy room.  Walk at a speed faster than is natural for you.  Control your behaviour in a social situation, even if you are in pain.  Count the number of times the letter “a” occurs in a paragraph.  Compare two Companies analysis report for overall value.  Calculate the value of product of 11113x 737990.  Pick holes in a complex argument. 9
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  15. BEHAVIORAL FINANCE, INTRODUCTION “The investor’s chief problem, and even his worst enemy, is likely to be himself”- Benjamin Graham “There are three factors that influence the market: Fear, Greed, and Greed.”- Market folklore • Sooner or later, you are going to make an investment decision that winds up costing you a lot of money. • Why is this going to happen? • You made a sound decision, but you are “unlucky”. • You made a bad decision-one that could have been avoided. • The beginning of investment wisdom: • Learn to recognize circumstances leading to poor decisions • Then, you will reduce the damage from investment blunder 15
  16. WHAT IS BEHAVIORAL FINANCE? It is the study of the influence of psychology on the behavior of investors or financial analysts. It also includes the subsequent effects on the markets. 16 It focuses on the fact that investors are not always rational, have limits to their self-control, and are influenced by their own biases.
  17. WHAT IS BEHAVIORAL FINANCE? A field of finance that proposes psychology- based theories to explain stock market anomalies. Within behavioral finance, it is assumed that the information structure and the characteristics of market participants systematically influence individuals' investment decisions as well as market outcomes. 17
  18. WHAT IS IT?  Study that seeks to combine psychology, sociology and traditional finance.  Helps explain why people make irrational financial decision. 18 WHAT IS IT IMPORTANT?  It is necessary because technical “analysis assume” that people act rationally. Psychology Behavioral finance Sociology Finance
  19. TRADITIONAL FINANCIAL THEORY Traditional finance includes: • Both the market and investors are perfectly rational • Investors truly care about utilitarian characteristics • Investors have perfect self-control • They are not confused by cognitive errors or information processing errors
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  21. BEHAVIORAL FINANCE THEORY Traits of behavioral finance are: • Investors are treated as “normal” not “rational” • They actually have limits to their self-control • Investors are influenced by their own biases • Investors make cognitive errors that can lead to wrong decisions
  22. CONVENTIONAL VS BEHAVIORAL Traditional Financial Theory In order to better understand behavioral finance, let’s first look at traditional financial theory. Traditional finance includes the following beliefs: • Both the market and investor are perfectly rational • Investors truly care about utilitarian characteristics • Investors have perfect self-control • They are not confused by cognitive errors or information processing errors Behavioral Finance Theory Traits of behavioral finance are: • Investors are treated as “normal” not “rational” • They actually have limits to their self-control • Investors are influenced by their own biases • Investors make cognitive errors that can lead to wrong decisions 22
  23. WHY BEHAVIORAL FINANCE? • Conventional or modern finance is based on rational and logical theories, such as the capital asset pricing model (CAPM) and the efficient market hypothesis (EMH). • These theories assume that people, for the most part, behave rationally and predictably. • One of the most rudimentary assumptions that conventional economics and finance makes is that people are rational “wealth maximizers” who seek to increase their own well-being. • Behavioral finance seeks to explain our actions, whereas modern finance seeks to explain the actions of the “economic man” 23
  24. BEHAVIORAL FINANCE – MICRO & MACRO 24 Micro-behavioral finance Macro-behavioral finance • Analyzes behavioral biases which distinguish individual investors from totally rational economic beings – homo economicus – from neoclassical economics • Questions totally rational decision-making • States that behavioral biases have a profound impact on decision-making and can drive suboptimal decision- making and errors that directly contradict with traditional finance • Analyzes market anomalies that distinguish financial markets from efficient markets assumed by traditional finance • At the same time questions this informational efficiency of markets • States that financial markets are impacted by behavioral influences (market anomalies, bubbles, excess volatility, limited arbitrage)
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  27. BEHAVIORAL FINANCE MAY ALSO BE DEFINED BY THE MODIFICATIONS IT HAS MADE TO A STANDARD FINANCE FRAMEWORK Here is a catch-all description given by Statman (2014): Behavioral finance substitutes normal people for the rational people in standard finance. It substitutes behavioral portfolio theory for mean-variance portfolio theory, and behavioral asset pricing models for the CAPM and other models where expected returns are determined only by risk. Behavioral finance expands the domain of finance beyond portfolios, asset pricing, and market efficiency. It explores the behavior of investors and managers in direct and indirect ways, whether by examining brains in fMRIs or examining wants, errors, preferences, and behavior in questionnaires, experiments, and the field. Behavioral finance explores saving and spending behavior and it explores financial choices affected by culture, fairness, social responsibility, and other expressive and emotional wants. 27
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  30. EVOLUTION OF BEHAVIORAL FINANCE The case (Reading) ARTICLE ON BF- CONCEPT.pdf Standard finance theory is accepted world-wide from market level perspective. But in1960s and 1970s, new wave in field of finance has been started by psychologist, study of heuristics found many biases and limit to cognitive resources, through examining economic decisions. It was started by study of Slovic (1969,1972) studied stock brokers and investors. Slovic (1972) states the money Game: “You are—face it—a bunch of emotions, prejudices, and twitches, and this is all very well as long as you know it. Successful speculators do not necessarily have a complete portrait of themselves, warts and all, in their own mind, but they do have the ability to stop abruptly when their intuition and what is happening out there are suddenly out of kilter. If you don’t know who you are, this is an expensive place to find out.” Recognition of the contribution that behavioural analysis is now significant in financial economics was reflected in 2002 with Awards of the Nobel Prize in economics to professor of psychology, Daniel Kahneman, where he detailed the heuristics and biases that occur when making decisions under uncertainty.
  31. • Fast and successful development of behavioral finance (economics) from 1970s • Daniel Kahneman and Amos Tverky (academic psychologists) – The most famous paper Prospect Theory: An Analysis of Decision under Risk – Econometrica, 1979 • Prospect theory is cornerstone of behavioral finance, behavioral economics overall – Descriptive alternative to mainstream expected utility theory • Framing – Form versus substance, risk-seeking versus risk-aversion depending on losses or gains • In 2002, Kahneman received the Nobel Memorial Prize in Economics, despite being a research psychologist, for his work in prospect theory, decision making and judgment under risk, i.e. in real world conditions. (Amos Tversky prem. died in 1996) PROSPECT THEORY – CORNERSTONE OF BEHAVIORAL FINANCE (KAHNEMAN, TVERSKY – 1979) 3 1 Daniel Kahneman (1934) Amos Tversky (1937-1996)
  32. A REASONING 32
  34. THE BOOK- BY THALER • Those 3 ideas developed by Richard Thaler, that change the way we think and behave: • 1. Bounded rationality- mental accounting • 2. lack of self-control – dilemma/mental illusion • 3. nudges- push or a positive reinforcement 34
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  36. Behavioral finance views investors as “normal” but being subject to decision-making biases and errors. We can break down the decision making biases and errors into four buckets. 37 DECISION-MAKING ERRORS AND BIASES
  37. SELF DECEPTION • It limits to the way we learn. • We mistakenly think we know more than we actually do, and we tend to miss information that we need to make an informed decision. 38
  38. HEURISTIC SIMPLIFICATION We can also scope out a bucket that is often called heuristic simplification. Heuristic simplification refers to information-processing errors.
  39. EMOTION • Emotion in behavioral finance refers to the decisions based on our current emotional state. • Our current mood may take our decision making off track from rational thinking. 40
  40. SOCIAL INFLUENCE Here social influence is how our decision making is influenced by others.
  41. BIASES IN BEHAVIORAL FINANCE- ONE SHOULD REALISE Loss Aversion Framing Bias Anchoring Bias Herding Bias Mental Accounting Disposition Effect Prospect & Regret Media Response Overconfidence & illusion of control Self Attribution Bias Hindsight Bias Confirmation Bias
  42. 43 Situation 1: While you are walking, you find a Rs. 100 note lying on the ground. You pocket it and feel happy about it Situation 2: While you are walking, you find a Rs. 200 note lying on the ground. You pocket it and subsequently, someone picks your pocket and you lose Rs. 100. Which situation do you think will make you happier? The answer would be in Situation 1. Although you gained Rs. 100 in both cases, the emotional outcomes are different. A loss of Rs.100 gave you more pain than the gain of Rs. 200. LOSS AVERSION-
  43. 44 We experience the same thing while investing. Consider the below scenarios You invested Rs. 1,000 and sold at a value of Rs. 2,000. The same investment has touched a high of say Rs. 3,000 and is now trading at say Rs. 2,000. The pain from the notional loss of Rs 1,000 will be much more compared to the overall gain on the investment. This behaviour is also evident from the fact that most people prefer Fixed Deposits even for long- term goals even though instruments like Mutual Funds although don’t have guaranteed returns, have a better ability to beat inflation over the long run.
  44. HOW TO DEAL WITH LOSS AVERSION BIAS: • One of the easiest ways to avoid this bias is to adopt an overall portfolio perspective and not look at investments individually. Different asset classes perform differently at a time, so if you have a well-diversified portfolio spread across asset classes, you will have some investments underperforming while others performing well. And hence on an overall portfolio level, you will not see extreme losses or volatility. ( Ex. Of trons) • Also, it is important to remain aware of loss aversion as a potential weakness in your investing decisions. 45
  46. AVERSION TO AMBIGUITY In decision theory and economics, ambiguity aversion also known as uncertainty aversion describes a preference for known risks over unknown risks. 47
  47. MENTAL ACCOUNTING An economic concept established by economist Richard Thaler, which contends that individuals divide their current and future assets into separate, non-transferable portions. The theory purports individuals assign different levels of utility to each asset group, which affects their consumption decisions and other behaviors. 48
  48. FRAMING Framing is a cognitive heuristic in which people tend to reach conclusions based on the 'framework' within which a situation was presented. BF Framing.pptx 49
  49. AVAILABILITY BIAS The giving of preference by decision makers to information and events that are more recent, that were observed personally, and were more memorable. This is because memorable events tend to be more magnified and are likely to cause an emotional reaction. 50
  50. CONFIRMATION BIAS In psychology and cognitive science, confirmation bias (or confirmatory bias) is a tendency to search for or interpret information in a way that confirms one's preconceptions, leading to statistical errors. 51
  51. ANCHORING In psychology and cognitive science, confirmation bias (or confirmatory bias) is a tendency to search for or interpret information in a way that confirms one's preconceptions, leading to statistical errors. 52
  52. ANCHORING • It’s a tendency to attach or anchor our thought to a reference point even if its not logical or supported by underlying facts. • For instance- • If NALCO’s share was at 75 when the Sensex stood at 33000. In the meantime post-budget , Sensex has gone down to 30000 and so do the share price of NALCO around 60. • So one will start thinking since post budget market and Sensex had start rallying, NALCO will also regain and invest. • But in the meantime there might be some fundamental change affecting NALCO as a PSU, which will keep the price to be depressed • That’s called anchoring bias in investment.
  53. INNUMERACY BIAS  Natural inability to cognitively process and evaluate probability and ratios is called innumeracy bias.  Difficulty in evaluation of ratios and probabilities. 54
  54. GAMBLERS FALLACY  When an individual erroneously believes that the onset of a certain random event is less likely to happen following an event or a series of events.  This line of thinking is incorrect because past events do not change the probability that certain events will occur in the future. 55
  55. HINDSIGHT BIAS  A psychological phenomenon in which past events seem to be more prominent than they appeared while they were occurring.  A tendency to think that one would have known actual events were coming before they happened. 56
  56. SELF ATTRIBUTION BIAS  Self-attribution bias occurs when people attribute successful outcomes to their own skill but blame unsuccessful outcomes on bad luck. 57
  57. HERD BEHAVIOR  It is the tendency for individuals to mimic the actions of a larger group. Individually, most people would not necessarily make the same choice. This is called herd behavior 58
  58. REPRESENTATIVE BIAS  A Representativeness Bias is a cognitive bias in which an individual categorizes a situation based on a pattern of previous experiences or beliefs about the scenario. It can be useful when trying to make a quick decision but it can also be limiting because it leads to close-mindedness. 59
  59. 60 BEHAVIORAL CONSTRUCTS MEASUREMENT VARIABLES Heuristics Representativeness Availability Anchoring and adjustment Herd bias Cognitive bias Confirmation bias Framing effect Mental Accounting Gambler’s Fallacy Overreaction and Under- reaction Emotional bias Loss- aversion Endowment effect Overconfidence Regret aversion Home bias
  61. BOBBY MITTAL  Illusion of control  Anchoring 62
  62. MANISH SWAIN  Herd Behavior 63
  63. JACK & KELLY  Self attribution bias Self protecting bias 64
  64. HARISH AND BARDAAN  Gamblers Fallacy 65
  65. CLIENT PROFILES 66 Client Age Investmen t horizon Objective Risk profile Portfolio Bobby 42 23 Retire comfortably at 65 Teacher Growth 70 %equity 30% bonds Manish 60+ 30 Stable income Retired professor 60 %equity 40%bonds $1million 5%gold 5%real estate Jack & Kelly 35 30 Save for retirement Do not have lot of assets 85%equity 15%bonds Harish & Bardaa n 50 10 Grow money Have short term liquidity needs $100000 75%equity 25%bonds Advice No changes Transfer Buy more at market low & CHANGE A BIT No stock can fall to zero. Risk seeker
  66. CAN QUANTITATIVE TRADING FACTOR IN BEHAVIOURAL BIASES - THE CASE • In recent history use of data science and quantitative research and modelling has failed to factor in investor behaviour and response to events like Covid pandemic and flaring up of tension in Middle East due to killing of Iranian General Quassem Soleimani by America in Baghdad airport. • In case of Soleimani killing while crude surged by 4%, US and Germany Treasury yield nosedived and US stock indexes were up as a knee jerk reaction. In the absence of any such even factored into the models used by Quant traders their investor lost wealth. • Similar was the fate of most of the quant fund managers when most of them had to loose wealth in the aftermath of Covid pandemic outbreak. 67
  67. WHAT IS QUANT TRADING • Quantitative trading is a type of market strategy that relies on mathematical and statistical models to identify – and often execute – opportunities. The models are driven by quantitative analysis, which is where the strategy gets its name from. It's frequently referred to as ‘quant trading’, or sometimes just 'quant'. • Quantitative analysis uses research and measurement to strip complex patterns of behaviour into numerical values. It ignores qualitative analysis, which evaluates opportunities based on subjective factors such as management expertise or brand name. • Quantitative trading works by using data-based models to determine the probability of a certain outcome happening. • Unlike other forms of trading, it relies solely on statistical methods and programming to do this. 68
  68. • You may, for example, spot that volume spikes on Apple stock are quickly followed by significant price moves. • So, you build a program that looks for this pattern across Apple’s entire market history. • If it finds that the pattern has resulted in a move upwards 95% of the time in the past, your model will predict a 95% probability that similar patterns will occur in the future. 69
  69. QUANTITATIVE VS ALGORITHMIC TRADING • Algorithmic (algo) traders use automated systems that analyse chart patterns then open and close positions on their behalf. Quant traders use statistical methods to identify, but not necessarily execute, opportunities. While they overlap each other, these are two separate techniques that shouldn’t be confused. • Here are a few important distinctions between the two: • Algorithmic systems will always execute on your behalf. Some quant traders use models to identify opportunities, but then open the position manually • Quantitative trading uses advanced mathematical methods. Algorithmic tends to rely on more traditional technical analysis • Algorithmic trading only uses chart analysis and data from exchanges to find new positions. Quant traders use lots of different datasets • What data might a quant trader look at? • The two most common data points examined by quant traders are price and volume. But any parameter that can be distilled into a numerical value can be incorporated into a strategy. Some traders, for example, might build tools to monitor investor sentiment across social media. • There are lots of publicly available databases that quant traders use to inform and build their statistical models. These alternative datasets are used to identify patterns outside of traditional financial sources, such as fundamentals. 70
  70. QUANTITATIVE TRADING -CASE • Let's say, for example, that you hypothesize that the NIFTY/SENSEX is more likely to move in a certain direction at a particular point in the trading day. So you build a program that examines a large set of market data on the NIFTY and breaks down its price moves by every second of every day. That's a simple example of a quant trading strategy using just one data parameter: price action. Most quantitative traders pull on several different sources at once to build far more intricate models with a better probability of identifying profitable opportunities. • What is a quant trader and what do they do? • A quant trader is usually very different from a traditional investor, and they take a very different approach to trading. Instead of relying on their expertise in the financial markets, quant traders (quants) are mathematicians through and through. Most firms hiring quants will look for a degree in maths, engineering or financial modelling. They’ll want experience in data mining and creating automated systems. • As well as building their own strategies, quant traders will often customize an existing one with a proven success rate. But instead of using the model to identify opportunities manually, a quant trader builds a program to do it for themselves. 71
  71. OVERCOMING BEHAVIORAL FINANCE ISSUES #1 Focus on the Process • Reflexive – going with guts • Reflective – Logical and methodical #2 Prepare, Plan and Pre-Commit • Behavioral finance teaches us to invest by preparing, by planning, and by making sure we pre-commit. 72
  72. FEW OF MY WORKS- Singh-Das/ffabe2857d7e10828ac8f39acfbf2f3a20406e2b?p2df Behavioural-Finance-Perspective.pdf FOR SURVEY- 73
  73. PROSPECT THEORY According to Prospect Theory, these are two stages of decision making- 1. Editing Stage 2. Evaluation Stage In Editing Stage, decision makers frame the choice in terms of potential gain or loss in reference to a fixed reference point. In Evaluation Stage, the decision maker employ on S-shaped value curve.
  74. To understand how the disposition effect works:- To sell winners & ride losers emerges in prospect theory Eg. Consider an investor who bought a stock a month ago for Rs 100, but the stock is currently selling for Rs 80. Let us assume that the investor expects the stock to go back to Rs 100 or fall further to Rs 60, both outcomes being equi-probable. The possibilities are displayed- 0.5 Rs 60 Rs 100 Rs 80 0.5
  75. According to Prospect Theory, the investor frames his choices as choice between two lotteries:- A. Sell the stock now & realize what had been a “paper loss” of Rs.20 B. Hold the stock for one more period with equal odds of “breakeven” & losing additional Rs. 20. The choice between those lotteries falls in the loss region as in Figure . So, it is associated with the common portion of the S-shaped value.
  76. B will be preferred over A Change in Wealth Value 0
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  79. PROPOSITION 1 The decision whether to moderate or adapt to a client’s behavioral biases during the asset allocation process depends fundamentally on the client's level of wealth. Specifically, the wealthier the client, the more the practitioner should adopt to the client’s behavioral biases. The less wealthy, the more the practitioner should moderate a client’s biases. 80
  80. PROPOSITION 2 The decision whether to moderate or adapt to a client’s behavioral biases during the asset allocation process depends fundamentally on the type of behavioral bias the client exhibits. Specifically, clients exhibiting cognitive biases should be moderated, while those exhibiting emotional biases should be adapted to. 81
  81. VISUAL DEPICTION OF PROPOSITION 1 AND PROPOSITION 2 82 High Level of Wealth (Adapt) Moderate and Adapt Moderate Adapt Moderate and Adapt Cognitive Biases (Moderate) Emotional Biases (Adapt) Low Level of Wealth (Moderate)
  82. CASE A Ms. Samaira is a single 65-year-old with a modest lifestyle and no income beyond what her investment portfolio of $1 million generates. Her primary investment goal is to not outlive her assets; she does not, under any circumstances, want to lose money becoz she recalls that her relative lost money in the crash of 1929, Ms. Samaira exhibits these behavioral biases: • Loss aversion- the tendency to feel the pain of losses more than the pleasure of gain. • Anchoring and adjustment-the tendency to believe that current market levels are “right” by unevenly weighting recent experience. • Selective memory- the tendency to recall only events consistent with one’s understanding of the past. 83
  83. CASE B Mr. Jones is a single 50-year-old pharmaceutical executive earning $250,000 a year. He lives extravagantly, occasionally spending more than his income, but has saved approximately $1.5 million. His primary investment goal is to donate $3 million to his alma mater, but he cannot obtain life insurance. Mr. Jones exhibits the following biases: • Loss aversion • Overconfidence- the tendency to over-estimate one’s investment savvy • Lack of self-control- the tendency to spend today rather than save for tomorrow. 84
  84. CASE C The Roy family includes a financially well-informed couple, both aged 36, and two children aged 4 and 6. They are financially sound, but were not invested during the bull market of the 1900s as many of their neighbor's were. The couple’s total income $120,000, is, like the family itself, not expected to grow significantly. They have saved $150,000 which they hope will be the financial foundation from which they will send their children to college and retire comfortably. The Roys suffer from: • Loss aversion • Regret- the tendency to feel deep disappointed for having made incorrect decisions • Availability bias- the tendency to believe that what is easily recalled is more likely 85
  85. APART FROM THAT, FOLLOWING WERE THE ALLOCATIONS FOR EACH OF THE THREE INVESTORS- • Samaira:75% bonds,15% stocks, 10% cash • Jones- 85% stocks,10% cash, 5% cash • Roy Family- 70% stocks,25% bonds, 5% cash 86
  86. THREE FUNDAMENTAL QUESTIONS WHICH ARISES- • 1. What effect do a client’s biases have on the asset allocation decision? • 2. Should you moderate or adapt to these biases if you were in their position? • 3.What is the best practical allocation for each investor? 87
  87. GUIDELINES FOR OVERCOMING PSYCHOLOGICAL BIASES  Understand the Biases  Focus on the Big Picture  Rely on Words and Numbers, not Sights and Sounds  Follow a Set of Quantitative Investment Criteria  Diversify  Take Care of the Downside  Control Your Investment Environment  Strive to Earn Market Returns  Track Your Feelings  Review Your Biases Periodically  Rebalance
  88. CAN THERE BE AN END TO BEHAVIOURIAL BIASES? 89 While we cannot cure the behavioral biases we’re born with, we can certainly try to mitigate their effects. Whether you’re a personal investor, an investment manager, a financial planner, or a broker, you can benefit from understanding the driving forces behind investment decisions. In “The End of Behavioral Finance,” we believe that one day behavioral finance will no longer be as controversial as it once was; That one day, its ideas will become part of the mainstream. Eventually, individuals might wonder, “what kind of other finance is there?”
  89. THANK YOU Dr. Shikta Singh 9437414777 ASSOCIATE PROFESSOR