Investment Banking and Capital Markets

Investment Banking and Capital Markets – Universit¨ at Hohenheim Investment Banking and Capital Markets Prof. Dr. Hans-Peter Burghof, Arne Breuer, Ul...
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Investment Banking and Capital Markets – Universit¨ at Hohenheim

Investment Banking and Capital Markets Prof. Dr. Hans-Peter Burghof, Arne Breuer, Ulli F.P. Spankowski Universit¨ at Hohenheim Chair for Banking and Financial Services

Winter 2009/10

Chair for Banking and Finance

Winter term 2009

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

Investment Banking and Capital Markets

Who’s that guy in front of me? I

Ulli F.P. Spankowski

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Studied at the University of Ulm, Universidad Politecnica de Valencia, and the University of Hohenheim

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PhD studies since May 2008 - Research Focus: Market Microstructure, Credit Ratings, Credit Derivatives

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Project Manger at Stuttgart Financial/Boerse Stuttgart Group since May 2008

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Associate Director of Stuttgart Financial/Boerse Stuttgart Group since July 2009

Chair for Banking and Finance

Winter term 2009

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

Investment Banking and Capital Markets Stuttgart Financial I

Joint initiative of the Ministry of Economics of Baden-Wuerttemberg, Boerse Stuttgart Group and Stiftung Kreditwirtschaft/University of Hohenheim which started in 2007

Goal I

Fostering and promoting the financial centre of Stuttgart

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Providing a platform to connect the members of the financial centre

Why should I care about that? I

Interesting events

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Networking

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Job-Portal (Internships, Trainee-programs, etc.)

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Check it out: www.stuttgart-financial.de

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Or Xing-Group: Stuttgart Financial

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Winter term 2009

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

Investment Banking and Capital Markets

Contact Details I

Email: [email protected]

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Phone: 0711-222 985 752

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Office hours: on request only

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Winter term 2009

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

Investment Banking and Capital Markets

Outline for this lecture 1. Market Micro... what? 2. Key concepts 3. Market characteristics 4. Theory of Market Microstructure (Glosten/Milgrom 1985) 5. Literature

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Winter term 2009

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

Investment Banking and Capital Markets

Definition I

Market microstructure deals with the purest of financial intermediation the trading of a financial asset

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The field of market microstructure deals with the costs of providing transaction services (trading) and with the impact of such costs on the short run behavior of security prices

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Market microstructure analyzes the manner in which the process by which securities are traded affects prices and volumes of the securities, as well as behaviour of traders

⇒ Traditional economic theory often assumes that markets operate without costs and without friction (e.g. see standard rational expectations models) whereas the essence of market microstructure is the analysis of trading costs and market frictions

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

2. Key Concepts

Efficiency and Liquidity The aim of market microstructure research is to evaluate and compare the operation of financial markets. For the evaluation and comparison of market performance some measurements are necessary. Therefore the following two concepts will be crucial: I

Market efficiency

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Market liquidity

Most of you have probably come across the former in some context. However, the latter is a more complex and opaque feature of markets.

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Winter term 2009

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

2. Key Concepts

Market efficiency Definition: A market is said to be efficient with respect to a given set of information Ω if no agent can make economic profit by trading on Ω. Economic profit is defined as the level of return after costs adjusted appropriately for risk. Weak form efficiency: if we define Ω to contain past and current price/return information only then the market is said to be weak-form efficient. An implication of weak-form efficiency is that past/current returns cannot be used to predict future prices/returns. Hence the best guess for a future prices/returns is the current one. Semi-strong from efficiency: Ω is defined to contain weak-form information & all publicly available information. Strong from efficiency: Ω is defined to contain weak-form & all publicly available & insider information.

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

2. Key Concepts

Weak-form efficiency and random walks The idea of weak-form efficiency led to the formulation of the random walk model of stock prices (RWM). Prices follow a random walk if: Pt = Pt−1 + t ,  ∼ IID(0, σ 2 )

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The difference between successive prices is an unforecastable, random error term. Therefore, returns (i.e. price changes) are also unforecastable.

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Hence, if the EMH holds security price changes (returns) are not serially correlated Ri,t 6= f (Ri,t−1 )

Problem: if we look at data on a transaction-by transaction basis, the microstructure effects which we want to measure will always lead to deviations of prices from the random walk paths - hence, this model is invalid.

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

2. Key Concepts Market liquidity Partial definition: Markets are often termed liquid if trading costs are low and if volumes are high. From a practitioner’s view this implies that altering my portfolio’s composition is not likely to be expensive and also not likely to be difficult (which means finding a trading partner is relatively easy). A more precise definition of liquidity is Kyle (1985), Pagano/Peng/Schwartz (2008): 1. Tight: Which means that costs of trading small amounts are themselves small (i.e. bid-ask spreads are small.) 2. Deep and Broad: Costs of trading large amounts are small too - big trades do not cause large price movements. 3. Resilient: Discrepancies between prices and ”true” values for the asset in question are small and corrected very quickly. 4. Accentuated Intra-Day Volatility: The more liquid a market, the less volatile it is due to the amount of information in the market.

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

2. Key Concepts Accentuated Intra-Day Volatility at NYSE

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

2. Key Concepts Accentuated Intra-Day Volatility at LSE

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

2. Key Concepts

Market liquidity I

Liquidity is one of the most important key features of a market

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Most empirical microstructure research has concentrated on measuring liquidity through the bid-ask spread

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Liquidity is a key factor in the competition between markets. Hence, market officials care about their liquidity since ”liquidity leads to liquidity”

⇒ A highly liquid market, reflects low trading costs which in return leads to an increased number of trades executed in this market, which again boosts liquidity.

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

3. Market Characteristics Before we talk about market types, we first have to clarify which orders can be placed in a market and particularly focus on the bid-ask spread.

Bids, Asks, and Spreads I

Bid: price one would receive for an immediate sale of a unit of asset i

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Ask: price charged for immediate purchase of a unit of asset i

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Bid-Ask spread: is defined as the difference between the ask and bid price

Obviously the ask price should exeed the bid price. Otherwise one could buy a unit of the asset (paying the ask) and immediately resell it (at the bid) to make profit. ⇒ There are various reasons for the existence of the Bid-Ask spread, as for instance transaction costs, inventory costs, or asymmetric information. Some of them we will discuss into detail later on during this lecture.

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

3. Market Characteristics Type of orders In general, a trader can submit two type of orders to markets in order to complete his buying/selling desires: I

Market orders: Are straightforward requests to buy/sell immediately at the best price available. Hence, a market order to buy 100 shares of Daimler AG would execute with certainty at the best (ask) price available. Note that this implies that there is price risk.

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Limit orders: Are price contigent. A limit order to buy sets a maximum price that will be paid, and a limit order to sell sets a minimum price that will be accepted. A limit order to buy 100 shares of Daimler AG at (max.) 35 Euro/share then the order will only execute if a seller exists who’s willing to give you his shares for 35 Euro/share or less. The major problem with limit orders is that sometimes the counterpart is not present. Hence, there is execution risk. ⇒ The basic trade-off when determining the order type is between price and execution risk. Patient traders tend to choose limit orders while impatient traders are more likely to pay a premium for instant execution and use market orders.

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

3. Market Characteristics

Types of markets It is useful to distinguish major types of market structures, although most real-world markets are a mixture of market types. The main distinction between market types can be broken down into I

Auction markets (order-driven markets) and

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Dealer markets (quote-driven markets)

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

3. Market Characteristics Auction markets A pure auction market is one in which investors (usually represented by a broker) trade directly with each other without the intervention of dealers. I

Call auction market: Takes place at specific times when the security is called for trading. Investors place (limit) orders - prices and quantities which are traded at a specific time according to specific rules, usually at a single market clearing price. Example: When do you think a call auction is necessary?

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Continuous auction market: Investors trade continuously against resting orders placed earlier by other investors. Continuous auction markets have two sides. On the one side, investors, who wish to sell, trade at the bid price established by resting buy orders. On the other side, investors who wish to buy, trade at the asking price established by resting sell orders

⇒ Most continuous auction markets nowadays are almost entirely electronic.

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

3. Market Characteristics Dealer markets A pure dealer market is one in which dealers (also know as market makers) post quotes (bid and ask) at which public investors can trade. The investors cannot trade directly with one another but must buy and sell at the dealers ask and bid. I

Liquidity provider: The dealer is obliged (trading rules and regulations) to trade at the quotes which he provides.

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Inventory risk: The dealer holds an inventory of the security, which fluctuates as he trades.

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Dealers/Market Makers and Brokers: By the way, where is the difference???

⇒ Empirical research has shown that spreads in continuous auction markets tend to be smaller compared to spreads in dealer markets. So why are dealer markets still in use? Chair for Banking and Finance

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

3. Market Characteristics Trading rules and regulations In most market places, sets of rules exist which regulate the process by which transactions take place. The most important of these rules are called priority rules. These rules determine the sequence in which existing (limit) orders execute against incoming (market) orders. I

Price priority: The best priced orders execute first. Hence, the buyer willing to pay the most (or the seller willing to accept the least) is satisfied first.

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Time priority: The order entered first (in terms of calendar time) is satisfied first - colloquially know as ”first come, first served”.

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Size priority: The order for the largest amount of shares/units is satisfied first. Hence, a limit sell for 1000 shares would be ahead of another limit sell for 750 shares in the execution queue.

⇒ In reality, these rules are employed simultaneously with a hierarchy imposed. Generally, price priority overrules time priority which comes before size priority.

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

4. Theory of Market Microstructure

The Model of Glosten/Milgrom (1985) I

One of the most famous sequential trade models

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Market Maker quotes a bid B and a ask A

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Security has value V = V or V , V < V

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At time t = 0, informed traders (only) know V

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Time is discretized

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Trades are for one unit, occur at each time step

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MM has infinite capital: no inventory/bankruptcy concerns

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4. Theory of Market Microstructure

The Model of Glosten/Milgrom (1985): Setup 

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I I I

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w.p. 1 − δ w.p. δ  Informed Trader type T ∼ Uninformed V ∼

V V

w.p. µ w.p. 1 − µ

Trader take action S (buy/sell from MM), one at a time  buy if V = V Informed traders: S ∼ sell if V = V  buy w.p. 1/2 Uninformed traders: S ∼ sell w.p. 1/2

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

4. Theory of Market Microstructure The Model of Glosten/Milgrom (1985): Event Trees

µ

V = V ;T = ?

1− δ

1− µ

V

U;S = ?

buy

0

sell

1/2 buy 1/2 sell

V =? δ

1

I; S = ?

V

µ

I; S = ?

0 1

V = V ;T = ?

buy

sell

1/2 buy

1− µ

U;S = ? 1/2

t=0

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t=1,2,…

sell

V = security value (V , V ); T = trader type (Informed / Uninformed); S = trader’s side (buy / sell)

Chair for Banking and Finance

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

4. Theory of Market Microstructure

The Model of Glosten/Milgrom (1985): Likelihood of Buys and Sells I

What is P(buy), P(sell) after one trade? P(buy )

P(sell)

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=

P(buy |V )P(V ) + P(buy |V )P(V )

(1)

=

1 + µ(1 − 2δ) (1 − µ)δ + (1 + µ)(1 − δ) = 2 2

(2)

=

P(sell|V )P(V ) + P(sell|V )P(V )

(3)

=

(1 + µ)δ + (1 − µ)(1 − δ) 1 − µ(1 − 2δ) = 2 2

(4)

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

4. Theory of Market Microstructure

The Model of Glosten/Milgrom (1985): Likelihood of V , V I

After one trade, we have information via Bayes’ Theorem:

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P(buy |V ) =

P(buy |V )P(V ) (1 − δ)(1 + µ) = P(buy ) 1 + µ(1 − 2δ)

(5)

P(buy |V ) =

P(buy |V )P(V ) δ(1 − µ) = P(buy ) 1 + µ(1 − 2δ)

(6)

P(sell|V ) =

P(sell|V )P(V ) (1 − δ)(1 − µ) = P(sell) 1 − µ(1 − 2δ)

(7)

P(sell|V ) =

P(sell|V )P(V ) δ(1 + µ) = P(sell) 1 − µ(1 − 2δ)

(8)

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

4. Theory of Market Microstructure

The Model of Glosten/Milgrom (1985): Bid, Ask, Spread I

If competition narrows profit 0, before trading we have...

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A = E (V |buy ) and B = E (V |sell). A = V P(V |buy ) + V P(V |buy ) =V

(1 − δ)(1 + µ) δ(1 − µ) +V 1 + µ(1 − 2δ) 1 + µ(1 − 2δ)

B = V P(V |sell) + V P(V |sell) =V

δ(1 + µ) (1 − δ)(1 − µ) +V 1 − µ(1 − 2δ) 1 − µ(1 − 2δ) A−B =

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4(1 − δ)δµ(V − V ) 1 − µ2 (1 − 2δ)2

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(9) (10) (11) (12) (13)

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

4. Theory of Market Microstructure

The Model of Glosten/Milgrom (1985): Updating Bids and Asks I

After each trade, Baysian update of beliefs about V

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Idea: How often would we see these trades if V = V vs.V ?

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With these ideas, we can update the bid and ask prices

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Expected bid and ask after k buys and s sells: Ak+s = V P(V |k + 1 buys, s sells) + V P(V |k + 1 buys, s sells) k+1

=

s

k+1

V δ(1 − µ) (1 + µ) + V (1 − δ)(1 + µ) (1 − µ) (1 − δ)(1 + µ)k+1 (1 − µ)s + δ(1 − µ)k+1 (1 + µ)s

Bk+s = V P(V |k buys, s + 1 sells) + V P(V |k buys, s + 1 sells) =

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V δ(1 − µ)k (1 + µ)s+1 + V (1 − δ)(1 + µ)k (1 − µ)s+1 (1 − δ)(1 + µ)k (1 − µ)s+1 + δ(1 − µ)k (1 + µ)s+1

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(14)

s

(15) (16) (17)

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

4. Theory of Market Microstructure

The Model of Glosten/Milgrom (1985): Example I

Given: µ = 0, 3 and δ = 0, 5; V = 1; V = 2

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Calculate the bids and asks for 10 buys and 10 sells

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Calculate the bids and asks for 15 buys and 7 sells

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Calculate the bids and asks for 7 buys and 15 sells

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

4. Theory of Market Microstructure

The Model of Glosten/Milgrom (1985): Results I

Basic idea: Spreads exist due to adverse selection

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Orders are serially correlated, i.e. buys tend to follow buys

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Trades have price impact: a buy increases bid and ask

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Spreads tend to decline over time as MMs figure out V

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Bid-ask may be such that market effectively shuts down

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Investment Banking and Capital Markets – Universit¨ at Hohenheim

5. Literature

Basic Literature I

O’Hara, M. (1997): Market Microstructure Theory

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Stoll, H.R. (2003): Market Microstructure

Detailed Literature I

Glosten, L.R./Milgrom, P.R. (1985): Bid, ask and transaction prices in a specialist market with heterogeneously informed traders, Journal of Financial Econometrics, Vol. 14, pp. 71-100.

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