Lecture 1
Dominant types of markets
1. Dealer markets
a. Fixed income markets, FX markets, some derivative markets
2. Agency markets / limit order book
a. Most stock markets, some derivative markets
Market liquidity: ‘the ability to trade large quantities of a financial asset quickly, at low cost,
and with little impact on the price.’
● Transaction costs (fixed, variable)
● Depth
● Price impact
100 basis points = 1 percentage point
1. Dealer markets
a. Buyers and sellers do not trade directly with each other, but with ‘dealers’
(usually banks) who act as intermediary and stabilize the market by supplying
immediacy
b. They charge bid-ask spread as compensation
i. Sell to dealers bid, buy from dealers ask price
1. Fixed costs: admin, operation, technology
2. Cost of bearing inventory risk
3. Cost of trading against better informed (asymmetric info)
4. Potentially also counterparty risk
c. Competition among different dealers helps to keep bid-ask spreads low
AmeriTrade = platform for forex trading
Bid Quote = sell price
Ask Quote = buy price
2. Agency markets
a. Order flow meets at a central place (e.g. the stock exchange), so buyers and
sellers directly trade with each other.
b. In most agency or auction markets there is one market maker or specialist for
each stock
i. “Specialists handle much of the order flow for stocks assigned to them
by the exchange and have the affirmative obligation … “ (see slide)
c. An investment bank / party could also act as a market maker → appear on
the bid and ask price on the order book.
Inside spread: the difference between the best bid and ask quotes
Inside debt: the closest order to go through the books
,As a specialist it is better to start trading the stock at a high inventory for the stock.
1. Maybe there is inside information that the specialist doesnt know → price increases
→ profit when you have a big inventory
2. If there is a very big imbalance between bid and ask side, then the specialist may
have to act as an intermediary. That is why a high inventory is better (less imbalance)
3 recent trends
1. Institutionalization
2. Computerized / high-frequency trading
3. Sustainable investing
1. Institutionalization
a. During 1945 over 90% of all stocks were held by households, nowadays it's
around 36% (incl. hedge funds).
b. Passive and active mutual funds are gaining popularity (institutions)
c. As well as foreign investors (institutions)
Advantages:
● Diversification
● Specialization / professionalism
● Economies of scale / cost reduction
● Better monitoring of firms through block holdings
Disadvantages:
● Agency problems
● Herd behaviour / risks of concentrated holdings
● Additional costs (marketing)
* there are more mutual funds that invest in US stocks, then US stocks themselves!
2. Automated trading
a. High frequency trading revolution (HFT), see example of glass cable and 15
millisecond mis timing of information release.
b. HFT is blamed for increasing excess volatility (e.g. flash crash) and for
exploiting small retail investors.
c. Other evidence showed that HFT can help liquidity and price discovery
3. Sustainable investing
a. Investors start caring more about just risk and return, but also takes in the
potential impact (ESG scores)
i. 30 trillion is involved in ESG investing at this moment (2018)
ii. However, be careful for greenwashing
iii. Climate change
b. Primum non nocere - first do no harm
, i.
Reason to reflect on your investments, such as; harmful products
(weapons, tabacco), harmful production processes (deforestation,
poor agricultural processes) and human right violations (child labor,
slavery).
c. Three key roles finances play:
i. Capital allocation
ii. Influence on business
iii. Risk management / insurance
Prerequisites for Portfolio Theory (pre-lecture 2)
Key assumptions of the Modern Portfolio Theory (MPT) by Markowitz
1. Investors are risk averse
a. Investors only accept risky securities if they provide compensation via a risk
premium.
b. Investors want to maximize the expected return of their portfolio for a given
level of risk .
2. Security returns are normally distributed
a. The normal distribution is characterized by the mean and the standard
deviation (breadth).
b. 95% of returns fall within that interval
c. Parameters are called, the moments of the distribution (mean, variance,
skewness and kurtosis)
* Kurtosis: the thickness of the tails of the distribution. The tails of actual stock returns are
fatter than in the case of a normal distributions (extreme returns - and +)
● If securities are normally distributed, the shape of the entire distribution of portfolio
returns can be described using 2 variables: E(R) and σ(𝑅).
● Investment analysis can be performed within mean-variance space.
○ Investors like E(R)
○ Investors dislike σ(𝑅) → a.k.a. risk
○ In other words, investors are mean-variance optimizers in MPT!
1 2
Utility function: 𝑈 = 𝐸(𝑅) − 2
* 𝐴σ
A = particular investor’s risk
When the risk-free rate (also, risk-free investment) is 5% then the utility function will be:
1 2
𝑈 = 𝐸(𝑅) − 2
* 𝐴σ = 0, 05
In practice it is not possible to compute the expected return from all securities. Therefore we
use historical returns with a reasonable estimate of the E(R).
Dominant types of markets
1. Dealer markets
a. Fixed income markets, FX markets, some derivative markets
2. Agency markets / limit order book
a. Most stock markets, some derivative markets
Market liquidity: ‘the ability to trade large quantities of a financial asset quickly, at low cost,
and with little impact on the price.’
● Transaction costs (fixed, variable)
● Depth
● Price impact
100 basis points = 1 percentage point
1. Dealer markets
a. Buyers and sellers do not trade directly with each other, but with ‘dealers’
(usually banks) who act as intermediary and stabilize the market by supplying
immediacy
b. They charge bid-ask spread as compensation
i. Sell to dealers bid, buy from dealers ask price
1. Fixed costs: admin, operation, technology
2. Cost of bearing inventory risk
3. Cost of trading against better informed (asymmetric info)
4. Potentially also counterparty risk
c. Competition among different dealers helps to keep bid-ask spreads low
AmeriTrade = platform for forex trading
Bid Quote = sell price
Ask Quote = buy price
2. Agency markets
a. Order flow meets at a central place (e.g. the stock exchange), so buyers and
sellers directly trade with each other.
b. In most agency or auction markets there is one market maker or specialist for
each stock
i. “Specialists handle much of the order flow for stocks assigned to them
by the exchange and have the affirmative obligation … “ (see slide)
c. An investment bank / party could also act as a market maker → appear on
the bid and ask price on the order book.
Inside spread: the difference between the best bid and ask quotes
Inside debt: the closest order to go through the books
,As a specialist it is better to start trading the stock at a high inventory for the stock.
1. Maybe there is inside information that the specialist doesnt know → price increases
→ profit when you have a big inventory
2. If there is a very big imbalance between bid and ask side, then the specialist may
have to act as an intermediary. That is why a high inventory is better (less imbalance)
3 recent trends
1. Institutionalization
2. Computerized / high-frequency trading
3. Sustainable investing
1. Institutionalization
a. During 1945 over 90% of all stocks were held by households, nowadays it's
around 36% (incl. hedge funds).
b. Passive and active mutual funds are gaining popularity (institutions)
c. As well as foreign investors (institutions)
Advantages:
● Diversification
● Specialization / professionalism
● Economies of scale / cost reduction
● Better monitoring of firms through block holdings
Disadvantages:
● Agency problems
● Herd behaviour / risks of concentrated holdings
● Additional costs (marketing)
* there are more mutual funds that invest in US stocks, then US stocks themselves!
2. Automated trading
a. High frequency trading revolution (HFT), see example of glass cable and 15
millisecond mis timing of information release.
b. HFT is blamed for increasing excess volatility (e.g. flash crash) and for
exploiting small retail investors.
c. Other evidence showed that HFT can help liquidity and price discovery
3. Sustainable investing
a. Investors start caring more about just risk and return, but also takes in the
potential impact (ESG scores)
i. 30 trillion is involved in ESG investing at this moment (2018)
ii. However, be careful for greenwashing
iii. Climate change
b. Primum non nocere - first do no harm
, i.
Reason to reflect on your investments, such as; harmful products
(weapons, tabacco), harmful production processes (deforestation,
poor agricultural processes) and human right violations (child labor,
slavery).
c. Three key roles finances play:
i. Capital allocation
ii. Influence on business
iii. Risk management / insurance
Prerequisites for Portfolio Theory (pre-lecture 2)
Key assumptions of the Modern Portfolio Theory (MPT) by Markowitz
1. Investors are risk averse
a. Investors only accept risky securities if they provide compensation via a risk
premium.
b. Investors want to maximize the expected return of their portfolio for a given
level of risk .
2. Security returns are normally distributed
a. The normal distribution is characterized by the mean and the standard
deviation (breadth).
b. 95% of returns fall within that interval
c. Parameters are called, the moments of the distribution (mean, variance,
skewness and kurtosis)
* Kurtosis: the thickness of the tails of the distribution. The tails of actual stock returns are
fatter than in the case of a normal distributions (extreme returns - and +)
● If securities are normally distributed, the shape of the entire distribution of portfolio
returns can be described using 2 variables: E(R) and σ(𝑅).
● Investment analysis can be performed within mean-variance space.
○ Investors like E(R)
○ Investors dislike σ(𝑅) → a.k.a. risk
○ In other words, investors are mean-variance optimizers in MPT!
1 2
Utility function: 𝑈 = 𝐸(𝑅) − 2
* 𝐴σ
A = particular investor’s risk
When the risk-free rate (also, risk-free investment) is 5% then the utility function will be:
1 2
𝑈 = 𝐸(𝑅) − 2
* 𝐴σ = 0, 05
In practice it is not possible to compute the expected return from all securities. Therefore we
use historical returns with a reasonable estimate of the E(R).
