MONASH
BUSINESS
SCHOOL
BFC3241
Investments
Lecture 1: How Markets Work
How are weekly topics related?
Weekly Topic
W1: How Markets Work
W3: Asset Pricing Models
Basics of investments:
• Trading mechanics
• Risk & return
• Constructing investment portfolios
W4-5: Equity Analysis I-II
Choosing between individual equities
W2: Portfolio Theory
Does equity analysis always work?
W6: Market Efficiency
Typical investment mistakes
W7: Behavioral Finance
W8-9: Investment Vehicles I-II
W10: Portfolio Management
W11-12: CFA Code of Ethics & Prof Standards
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Choosing between investment portfolios
• Passive and active investments
• Estimate portfolio performance
Rules & standards governing investments
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Reading list
▪ BKM Ch.3 “Securities Markets”
▪ BKM Ch.5.1-5.3 “Risk, Return, and the Historical Record”
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Agenda
▪ The Mechanics of Trading
▪ Risk and Return: Relation and Measurement
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THE MECHANICS OF TRADING
▪ Primary market
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–
–
–
New issue is created and sold
Exchange of cash between investors and issuers
Public offering
Private offering
▪ Secondary market
– Existing owner sells to a different investor
– Exchange of cash between one investor and another
▪ Valuation matters in both primary and secondary markets!
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The Mechanics of Trading
▪ Most equity markets are organized as centralized limit order books
– Record of outstanding orders to buy and sell securities
▪ Exchanges provide the electronic platform for matching orders
▪ Brokers connect to this platform and trade on behalf of their clients
▪ Clearing houses maintain the record of securities’ owners
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The Mechanics of Trading
▪ A structure of a typical limit order book
– Orders specify the #stocks & price at which these stocks are to be bought/sold
The difference between the
best bid and ask prices is
called the bid-ask spread
• $404.73-$404.65=$0.08
Orders to sell @ ask prices
The price that we normally refer Orders to buy @ bid prices
to is the average between the
best bid and ask prices
• ($404.73+$404.65)/2=$404.69
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#Stocks
Price
22
$404.75
17
$404.74
3
$404.73
5
$404.65
12
$404.64
18
$404.63
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The Mechanics of Trading
▪ All orders can be classified into market and limit orders
▪ Market orders
#Stocks
– A request to buy/sell stocks immediately at the best
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available price
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– E.g., a market order to buy 1 stock would be executed
@ $404.73 – best price at which someone wants to sell 3 2
– Execution is guaranteed, but the price isn’t
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8
Price
$404.75
$404.74
$404.73
$404.65
12
$404.64
18
$404.63
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The Mechanics of Trading
▪ Limit orders
– A request to buy/sell stocks at a certain price
– E.g., a limit order to buy 1 stock @ 404.70 would be
placed in the limit order book as a bid order
– But it will not be executed immediately since no one is
interested to sell at this price
#Stocks
Price
22
$404.75
17
$404.74
3
$404.73
15
$404.70
$404.65
512
$404.65
$404.64
12
18
$404.64
$404.63
18
$404.63
▪ $404.73 is the best price at which someone wants to sell
– The price is guaranteed, but the execution isn’t
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The Mechanics of Trading
▪ Other important types of orders: stop loss and take profit orders
– Both are created to close the position once the price reaches a certain level
▪ Stop loss orders are created to limit losses on
the existing position
– Usually market orders, but could be limit orders, too
▪ Take profit orders are created to lock in profits
on the existing position
– Usually limit orders, but could be market orders, too
#Stocks
Price
22
$404.75
17
$404.74
3
$404.73
5
$404.65
12
$404.64
18
$404.63
▪ Which one of the above would be limit or market orders?
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The Mechanics of Trading
▪ Right now, all equity trading is essentially done remotely through the
electronic communication networks (ECNs)
▪ This innovation changed the market and allowed new trading
strategies to proliferate (algo trading, high-frequency trading)
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The Mechanics of Trading
▪ While trading we incur transaction costs
– Commission fees paid to broker for making a transaction
– Bid-ask spread – an implicit transaction cost. Why?
#Stocks
– Price impact – price changes caused by large trades
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Price
$404.75
17
$404.74
3
$404.73
5
$404.65
12
$404.64
▪ Dark pools are trading systems allowing their participants 18
to trade large blocks of stocks without showing their hand
$404.63
▪ Price impact is very important for large investors
– To minimize it, they would use algorithms to split their
big orders into smaller chunks and execute them over
a long time period
– They would trade their large orders in dark pools
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The Mechanics of Trading
▪ Buying on margin
– Borrow money from the broker to purchase securities
– Margin is the % of trade value contributed by the investor, the rest is the loan
▪ Two types of margin
– Initial margin is the difference between the initial investment and loan values
▪ Reflects initial investor equity value
– Maintenance margin is the min investor equity value that must be maintained
▪ If investor equity < maintenance margin, the investor will receive a margin call,
notification from the broker to put more money into account to keep position open
▪ If an investor doesn’t do that, the position is liquidated by the broker
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The Mechanics of Trading
▪ Buying on margin: Example
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–
–
–
Stock price: $70
#Shares bought: 1,000
Initial margin 50%
Maintenance margin (MMR): 40%
▪ Investor balance sheet
Assets
Liabilities
Value of stock $70,000
Loan
$35,000
Equity
$35,000
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The Mechanics of Trading
▪ Buying on margin: Example
– New share price: $60. What happens with the balance sheet?
Assets
Liabilities
Value of stock $60,000
Loan
$35,000
Equity
$25,000
▪ New margin = $25,000/$60,000 = 41.57%
– The margin has dropped from 50% to 41.57% > 40% MMR
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The Mechanics of Trading
▪ Buying on margin: Example
– How far must the share price drop to receive a margin call?
– MMR = 40% → when the new margin is 40% we get a margin call
– 0.40 = equity / 1,000*new_price
0.40 = (1,000*new_price - $35,000) / 1,000*new_price
0.40 = 1 - $35,000 / 1,000*new_price
0.60 = $35 / new_price
new_price = $35 / 0.60 = $58.33
▪ What happens when an investor receives a margin call?
– They have to restore their margin back to 50% (initial margin) of the new total
position value (by putting more money or selling off part of their position)
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The Mechanics of Trading
▪ Short sales: selling securities that one doesn’t own
– Borrow stocks from a lender (broker) for a fee
– Sell stocks in the open market expecting to profit from decreasing stock price
– Buy stocks back later to close your position and return them back to the lender
▪ Short sales require margin
– Essentially the proceeds from the sell trade are kept by the broker as a pledge
– These proceeds earn a small interest rate to short seller
▪ Note however, that a short seller also pays the stock borrowing fee to the broker
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The Mechanics of Trading
▪ Example: short selling on margin
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–
–
–
–
Stock price: $60
#Shares sold short: 100
Initial margin 50%
Maintenance margin (MMR): 30%
Assume that there is no stock borrowing fee
▪ Investor balance sheet
Assets
Liabilities
Cash
$6,000
Short position $6,000
T-bills
$3,000
Equity
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$3,000
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The Mechanics of Trading
▪ Example: short selling on margin
– New share price: $65. What happens with the balance sheet?
Assets
Liabilities
Cash
$6,000
Short position $6,500
T-bills
$3,000
Equity
$2,500
▪ New margin = $2,500/$6,500 = 38.46%
– The margin has dropped from 50% to 38.46% > 30% MMR
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The Mechanics of Trading
▪ Short selling on margin: Example
– How far must the share price rise to receive a margin call?
– MMR = 30% → when the new margin is 30% we get a margin call
– 0.30 = equity / 100*new_price
0.30 = ($9,000 - 100*new_price) / 100*new_price
0.30 = $9,000 / 100*new_price - 1
1.30 = $90 / new_price
new_price = $90 / 1.30 = $69.23
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Agenda
▪ The Mechanics of Trading
▪ Risk and Return: Relation and Measurement
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RISK AND RETURN: RELATION AND MEASUREMENT
▪ Risk-return tradeoff is a fundamental principle behind investments
– Securities with higher returns have higher risks (“no pain, no gain”)
▪ Expected (ex-ante) vs. historical (ex-post) risk & return
– Expected over some future period
– Historical (ex-post) = past, something already happened (realized)
▪ Holding period return (HPR) measures historical/realized returns
– HPR = (Ending Price – Beginning Price + Div) / Beginning Price
HPR = (Ending Price – Beginning Price) / Beginning Price + Div / Beginning Price
HPR = Capital Gain Yield + Dividend Yield
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Risk and Return: Relation and Measurement
▪ Basic math behind HPR
– HPR is usually annualized, i.e., is expressed in % per annum
– E.g., if HPR for the last 2 years was 20%, an annualized HPR, HPRann, can be
expressed from the following equation: (1 + HPRann)2 = 1.20
1+ HPRann = 1.201/2 → HPRann = 1.201/2 - 1 = 9.5445%
▪ The above calculation assumes compounding of returns over 2 years
– We call it geometric average return (GAR):
▪ We can also calculate a return without compounding
– We call it arithmetic average return (AAR):
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Risk and Return: Relation and Measurement
▪ HPR for a portfolio of N securities can be calculated as follows
– Take HPR of each security i, HPRi
– Multiply it by the weight of this security in the portfolio, wi
– Sum up all these products to get the portfolio HPR: 𝐻𝑃𝑅𝑝 = σ𝑁
𝑖=1 𝐻𝑃𝑅𝑖 𝑤𝑖
where wi = [$ invested in security i] / [$ value of the entire portfolio]
▪ Realized (ex-post) risk is measured as standard deviation of past returns
– Ex-post variance: 𝜎 2 =
1
σ𝑛𝑗=1
𝑛−1
𝑟𝑖 − 𝑟ҧ
2
▪ n is #observations, 𝑟𝑖 is HPR for year T, 𝑟ҧ is AAR
– Ex-post standard deviation (StDev): σ = 𝜎 2
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Risk and Return: Relation and Measurement
▪ Expected (ex-ante) risk & return use future returns & their probabilities
– Expected return: 𝐸 𝑟 = σ𝑆𝑠=1 𝑝 𝑠 𝑟(𝑠)
▪ r(s) is the return in state (scenario) s, p(s) is the probability of observing state s
– Expected variance: 𝜎 2 = σ𝑆𝑠=1 𝑝(𝑠) 𝑟 𝑠 − 𝐸(𝑟)
2
▪ Why do we care so much about means and StDev?
– Stock returns are approx.
normally distributed
– Expected return = mean
– Possibility of getting returns
other than expected = StDev
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Risk and Return: Relation and Measurement
▪ We might also be interested in other measures of risk, e.g., tail risk
– StDev measures dispersion of possible asset returns
– Instead, we might be interested in large losses we might incur
– E.g., how much would we lose in an extreme case, say, 5th percentile of the
return distribution?
▪ Value-at-Risk (VaR) asks exactly this question for different percentiles
– E.g., VaR(5%) = E(r) - 1.645σ
– Say annual E(r) =12%, σ = 35%, then VaR(5%) = 12% - 1.645*35% = -45.57%
– I.e., there is 5% chance to get a return of -45.57% in a given year
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Summary
▪ The Mechanics of Trading
– Types of trading orders
– Transaction costs associated with trading
– Trading on margin
▪ Risk and Return
– Risk-return trade-off
– Realized & expected returns & risks
– Holding period returns: conventions & different calculation methods
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