Online Financial Intermediation

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Online Financial Intermediation
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Types of Intermediaries

• Brokers
• Match buyers and sellers
• Retailers
• Buy products from sellers and resell to buyers
• Transformers
• Buy products and resell them after modifications
• Information brokers
• Sell information only

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Size of the Financial Sector
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Transactional Efficiencies

• Phases of Transaction
• Search
• Automation efficiencies
• Fewer constraints on search with wider scope
• Negotiation
• Online price discovery
• Settlement
• Efficiencies associated with electronic clearing
  of transactions
• Automation and expansion will increase
  competition among intermediaries reducing the
  impact of existing gatekeepers

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Value-Added Intermediation

• Transformation functions
• Continuing role for intermediaries (such as
  banks) that allow transformation of asset
  structures
• Changes in maturity (short-term versus long-term
  borrowing and lending activities)
• Volume transformation (aggregation of savings for
  provision of large loans)
• Information Brokerage
• Importance of information in evaluation of risk
  and uncertainty
• Enhancements on the internet EDGAR (Electronic
  Data Gathering Analysis and Retrieval)
• Online database with all SEC filings and analysis
  of publicly available information

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Asset Pricing

• Risk and Return
• Stock prices move randomly

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Asset Pricing

• Diversification and the law of large number
• Model returns as a stochastic process
• N assets j12N
• Simple model with AR(1) returns
• Special case with 0 IID returns

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Asset Pricing

• Construct a portfolio consisting of 1/N shares of
  each stock
• Payoff to the portfolio is the average return
• We measure the risk associated with the portfolio
  as simply the variance (or standard deviation of
  the returns).
• Risk of any given asset will be 2
• What is the risk of the average portfolio

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Asset Pricing
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Asset Pricing

• It now follows that for independent random
  processes the variance of the average goes to
  zero as the number of stocks in the portfolio
  goes to infinity
• Law of Large Numbers
• Result depends critically on the independence
  assumption
• Example with correlated returns
• Extreme case occurs when all returns are
  identical ex ante as well as ex post

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Asset Pricing
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Asset Pricing
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Asset Pricing

• Law of large numbers holds when 0
• Independent returns
• Uncorrelated returns
• Hedging portfolios

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CAPM

• Capital Asset Pricing Model
• Approximation assumption returns are roughly
  normally distributed

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CAPM

• Normal distribution characterized by two
  parameters mean and variance (i.e. return and
  risk)
• Holding different combinations (portfolios) of
  assets affects the possible combinations of
  return and risk an investor can obtain
• 2 asset model
• proportion of stock 1 held in portfolio
• 1-proportion of stock 2 held in portfolio
• Joint distribution of the returns on the two
  stocks

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CAPM

• Return to a portfolio is denoted by z with
• Average return to the portfolio is
• Variance of the portfolio is

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CAPM

• We can derive the relationship between the mean
  of the portfolio and its variance by noting that
• Substituting for in the expression for the
  variance of the portfolio we find
• To portfolio spreadsheet

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CAPM

• Multi-asset specification
• Choose portfolio which minimizes the variance of
  the portfolio subject to generating a specified
  average return
• Have to perform the optimization since you can no
  longer solve for the weights from the
  specification of the relationship between the
  averages

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CAPM

• As with the two asset case yields a quadratic
  relationship between average return to the
  portfolio and its variance which is called the
  mean-variance frontier
• Frontier indicates possible combinations of risk
  and return available to investors when they hold
  efficient portfolios (i.e. those that minimize
  the risk associated with getting a specific
  return
• Optimal portfolio choice can be determined by
  confronting investor preferences for risk versus
  return with possibilities

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CAPM
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CAPM

• Two fund theorem
• Introduce possibility of borrowing or lending
  without risk
• Example T-bills
• Let rf denote the risk-free rate of return
• Historically around 1.5
• The two fund theorem then states that there
  exists a portfolio of risky assets (which we will
  denote by S) such that all efficient combinations
  or risk and return (i.e. those which minimize
  risk for a given rate of return) can be obtained
  by putting some fraction of wealth in S while
  borrowing or lending at the risk-free rate. The
  portfolio S is called the market portfolio.

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CAPM
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CAPM

• Implications of the two fund theorem for asset
  prices
• In equilibrium asset prices will adjust until
  all portfolios lie on the security market line

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CAPM

• Implications for asset market equilibrium
• Risk-averse investors require higher returns to
  compensate for bearing increased risk
• Idiosyncratic risk versus market risk
• Equilibrium risk vs. return relationships
• Market risk of asset i is defined as the ratio of
  the covariance between asset i and the market
  portfolio to the variance of the market portfolio

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CAPM

• Since iSiS i S (where iS is the
  correlation coefficient between asset i and the
  market portfolio S) we can write
• Finally since the returns on all assets must be
  perfectly correlated with those on the market
  portfolio (in equilibrium) we know that iS1
  so that

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CAPM

• Since the equation for the market line is
• it follows that the predicted equilibrium
  return on a given asset i will be
• The term rS-rf is called the market risk premium
  since it measures the additional return over the
  risk-free rate required to get investors to hold
  the riskier market portfolio.
• Determining rS
• Applications