Agent-based models of financial markets

Financial Markets and ABM

September 26, 2016

Seminar Overview

• September 19: Introduction and basic concepts

• September 26: Financial markets and ABM

• October 3: Examples of different models

• October 10: Introduction to the development framework

• October 17: Scenario analysis and simulation

• October 24: The agents’ behavior (Guest speaker Faten Ben Bouheni)

• October 31: Implementation of agents’ behavior

• November 7: Evolution and Learning

• November 14: Optimization and overfitting

• November 21: Commercialization of models / How to pitch (Guest speaker Roger Hilty)

• November 28: Pitch of the Models

• December 5: Pitch of the Models

• December 12: Pitch of the Models

• December 19: General Feedback to the Pitch Sessions and some conclusions

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Slides

The slides will be available online on Friday before the seminar on:

http://www.business.uzh.ch/professorships/qba/teaching/operationsResearch/lectures/ABMFM.html

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Puppies! Now that I've got your attention, complexity theory

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https://www.ted.com/talks/nicolas_perony_puppies_now_that_i_ve_got_your_attention_complexity_theory#

Content

• Discussion of the reading

• What is a market?

• Market prediction

• Elements of Agent-Based Models

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What is a market?

• Place

• Participants

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Markets

• A market is the place where supply (sellers) meets demand (buyers). They determine the price of a good.

• Rational behavior, competition and transparency are three axioms for perfect markets.

• Financial markets: Abstraction of the real world to tradable instruments. It makes the allocation of capital more efficient.

• Market participants make decisions based on heterogeneous investment objectives. They have different time horizons, risk profiles and knowledge/information. Each individual’s analyses lead to different valuations of the investment and hence different decisions.

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Economics and Markets

• Economics is a social science dealing with the interactions of human beings.

• Need to abstract from reality reduce complexity.

• Macroeconomics and microeconomics are the two main parts of economics. Macroeconomics studies the economy as a whole. Microeconomics analyses individual behavior (agents).

• Economic processes are complex: It is difficult to decompose them into separate parts that can be studied separately and then be aggregated to yield a complete picture.

• Markets at the core of the economy the exchange of goods and services.

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Market Environment

• Assets

• Market structure• Order processing

• Price calculation

• Clearing and settlement

• Evolution and social learning

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Assets

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Market Structure

• Auction

• Order book

• Market maker

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www.six-swiss-exchange.com/orderbook_en.html?SecurityId=CH0024899483CHF1

Agents

• Methods, Behavior (Processing)• Decision and trading rules• Individual learning or adaptation

• Attributes (Memory)• Portfolio, wealth• Genes (parameters)

• Two types of strategies exist, labeled technical and fundamental. The relative number or wealth of the two types depends on the market details.

• Make realistic assumptions about the behavior of the agents (bounded rationality (Simon, 1982), behavioral finance)

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Market Prediction

• The efficient market theory is invalid because its assumptions do not hold:• Rational behavior of market participants.

• Availability of information

• Perfect knowledge

• Unlimited computing power for real time decisions

• Different market participants

• The cause of unpredictability or randomness is often ignorance. The source of randomness disappears for the smartest market participant.

• There exist qualitative and quantitative models. We generally distinguish between fundamental and technical analysis.

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How the Economy works

http://www.youtube.com/watch?v=PHe0bXAIuk0

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Technical analysis

• The analysis of the development of the price and not the value.

• Reflects the psychology of the markets.

• Most univariate.

• For all markets possible.

• Used in Japan since 17th century.

• Examples: Trend follower, contrarians, put/call indicators, point and figure charts, Elliott Waves theory, …

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Chart analysis

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Some thoughts about forecasting

• Experts do little better than random chance at forecasting such political events as revolutions and regime changes. (Tetlock, 2005)

• Simple predictive models outperform human experts’ ability to make predictions by avoid common cognitive traps. (Guszcza, 2016)

• What does it need to predict (Hyndman, 2015)• We understand and can measure the causal factors.• There are a lot of historical data available.• The forecasts do not affect the things we are trying to forecast.• The future will somewhat resemble the past in a relevant way.

• Reasons that make it hard to predict (www.santafe.edu)• The dynamics may be in some sense inherently unpredictable.• The financial or energetic cost of measuring the system may be prohibitive.• The computational problem of prediction may be difficult.• The state space itself may be unknown.

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Financial Markets as Complex Systems

• Deterministic system

• Stochastic shocks

• Drift component

𝑿(𝒕 + 𝟏) = 𝒇(𝑿 𝒕 ,𝒘 𝒕 )

• X(t) is a vector with a number of components xi. The external variables are subsumed in w(t). The decision is arbitrary to put the different variables in X(t) or w(t).

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Deterministic System

• Non linear

• Multivariate• Interconnected markets

• Arbitrage

• Bounded rational agents

• Applications• Fundamental and technical analysis

• Economics

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Stochastic System

• Random walk: The actual price is the best prediction. The markets are efficient.

• External shocks

• Distribution

• Applications• Risk Management

• Value at Risk

• Black & Scholes

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Drift Component

• Change of the deterministic system

• Learning• Change of capital allocation• Individual Learning• Social learning

• Innovation

• Change of regulations/ market structures

• Responsible for non stationary

• Reduce market efficiency

• Difference to physical dynamic systems• Responsible for the decreasing quality of traditional forecasting models over

time

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Economic versus Financial Market Models• What are the advantages of financial market models over economic

models?

• What are the disadvantages of financial market models over economic models?

Please take 5 minutes to think about this question.

Briefly prepare for a discussion in class - discuss it with your neighbors.

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Why Agent-Based Models

• Given financial markets are multivariate, non linear, deterministic systems with stochastic shocks and a drift component ABMs are a promising modeling solution.

• The complex behavior of financial markets emerges as the result of the collective actions of many “simple” agents in mutual action.

• Financial markets are social systems, built on buying and selling decisions of human beings.

• In an ABM the agents don’t need to be profitable or rational The real world market’s results stem from the interaction of real world market participants!

• Understanding the behavior of market participants enables us to correctly forecast market behavior.

• ABMs are a very powerful framework but with many degrees of freedom.

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Elements of Agent-Based Models

Agents

• Market participants• Behavioral disposition

• Microeconomics

• Explicit knowledge in the form of agents’ behavioral structures

• Individual basic decision structures with bounded rationality

• Decentralized, heterogeneous and local

• Adaptive, individual learning• Analytical

Environment

• Market• Market structure

• Macroeconomics

• Implicit knowledge in the form of time series analysis

• Complex, non-linear, path-dependent

• Collective behavior leads to a self-organizing system

• Social learning and changing market structures (regulation,…)

• Computational

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Readings

Kostadinov, F., Ankenbrand, T. (2013): Agent-based modelling and the Swiss real estate market. Working paper (available www.avaco.ch).

Tetlock, P.E., Expert Political Judgement: How Good Is It? How Can We Know. Princeton, 2005.

Guszcza, J., Maddirala, N., Minds and Machines. Deloitte Review, 2016.

Hyndman, R., Exploring the boundaries of predictability: What can we forecast, and when should we give up? http://robjhyndman.com/seminars/yahoo2015/

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