Readings2

Question 1

Moore’s Law versus Murphy’s Law: Algorithmic
Trading and Its Discontents

What is Moore’s and Murphy’s law?

Answer 1

▪ Moore’s law in financial markets: from 1929 to 2009 the total market capitalization of the US stock market has been doubling every decade
▪ Murphy’s law: “whatever can go wrong will go wrong” (faster and with worse consequences when computers are involved)

Question 2

Moore’s Law versus Murphy’s Law: Algorithmic
Trading and Its Discontents

What is algorithmic trading? What are the benefits of AT?

Answer 2

Algorithmic trading (AT): the use of mathematical models, computers, and
telecommunications networks to automate the buying and selling of financial
securities (benefits: cost savings, operational efficiency, and scalability)
▪ Cheaper, enhances operational efficiency and promotes economies of scale, but
creates tighter interconnections in the financial system
▪ Regulation is outdated and its philosophy is ripe for an overhaul
▪ AT is not bad per se, but it needs to be appropriately monitored to benefit the
society at large

Question 3

Moore’s Law versus Murphy’s Law: Algorithmic
Trading and Its Discontents

What encouraged the rise of AT?

Answer 3

▪ The financial industry is becoming more complex over time (not less) – marginal product of more sophisticated financial technology is increasing
▪ A number of breakthroughs in quantitative modelling of financial markets: Black, Cox, Fama, Lintner, Markowitz, Merton, Miller, Modigliani, Ross, Samuelson,
Scholes, Sharpe, and others
▪ Parallel breakthroughs in computer technology – Moore’s law in technology. Storage and processing speeds have changed the way financial technology
operates

Question 4

Moore’s Law versus Murphy’s Law: Algorithmic
Trading and Its Discontents

What 5 developments fueled the popularity of AT?

Answer 4

1) Quantitative models in finance:
▪ Markowitz portfolio theory. The CAPM. Factor models for return estimation. The BMS options pricing model. Dynamically complete markets
2) The emergence of index funds:
▪ “passive” investing: value-weighted portfolio need not be adjusted as it automatically does so as Mcap changes; Samsonite’s pension fund: rebalancing
weights to keep the $1 investment in each stock
3) Arbitrage trading (incl. statistical arbitrage)- one human cannot monitor all possible possibilities, AT can.
▪ Even if most arbitrage opportunities are not riskless, if you can manage and quantify their risks, they become an attractive investment opportunity. Statistical
arbitrage: large arbitrage portfolios are formed to maximize expected returns while minimizing volatility
4) Automated order execution and market making:
▪ Slicing and dicing orders to execute them in the optimal (cost-efficient) manner
without moving the price too much (despite a downward-sloping demand curve)
▪ Market-making: continuously quoting prices and standing ready to buy and sell
securities at those prices so as to gain on bid–ask spreads. AT allows for more
sophisticated dynamic risk management (specify how an bid/ask should be
adjusted following bid/ask orders)
5) High-frequency trading (HFT):
▪ Trade at incredibly high frequencies and short time intervals. HFTs’ impact on
liquidity and market quality remains ambiguous: more trading can promote
liquidity, but HFTs are often accused of predatory trading that consummates
liquidity

Question 5

Moore’s Law versus Murphy’s Law: Algorithmic
Trading and Its Discontents

What are some examples of AT failure?

Answer 5

1. Facebook IPO glitch–> too high demand, the AT had to recompute price with every new order–> created a 30 min delay
2. The perfect financial storm- in the source of 33 minutes, prices os most actively traded companies crashed and recovered (Apple traded only $100,000 per share).
3. BATS IPO- software bug made symbols of stock from A to BFZZ inaccessible –> IPO was canceled
4. Knight Capital Group- because of a technology issue sent out erroneous orders into the market–> the company had to liquidate the position–> huge losses
5. High-frequency manipulation- spoofing and layering- placing orders to create a false impression of demand/supply and later trade in the opposite direction.

Question 6

Moore’s Law versus Murphy’s Law: Algorithmic
Trading and Its Discontents

What is spoofing? Layering?

Answer 6

Spoofing- placing an order in a certain direction (buy/sell) to create a false impression of demand/supply for a particular security and to later trade in the
opposite direction of the initial order, profiting from the imbalance
Layering- the same but or a series of orders at different prices (?)

Question 7

Moore’s Law versus Murphy’s Law: Algorithmic
Trading and Its Discontents

What are the regulation proposals for AT?

Answer 7

–> Do nothing: will result in cost reductions for intermediaries, but will not address
the issue of fair and orderly markets
–> Ban AT altogether: will yield a more “fair” and orderly market, but also reduce
liquidity, efficiency, and capital formation
–> Change the definition and requirements of market makers to include HFT: will
lead to a more fair and orderly market, but will also increase the costs for
intermediaries
–> Fix time intervals between trades (market continuity): leads to reduced
immediacy. Need more analysis to evaluate the effects connected with demand for
immediacy
–> Introduce a “Tobin tax” on all transactions: will reduce trading activity, liquidity
and make hedging more costly (think option dynamic replication) and remove HFT

Question 8

Moore’s Law versus Murphy’s Law: Algorithmic
Trading and Its Discontents

What are financial regulations 2.0 for the AT?

Answer 8

• -> Systems-engineered: should approach financial markets as complex systems composed of multiple software applications, hardware devices and human personnel
• -> Safeguards-heavy: both human and machine safeguards are necessary to ensure the safe functioning of the system
• -> Transparency-rich: should aim to make the design of financial products more transparent and accessible to regular automated audits
• -> Platform-neutral: should be designed to encourage innovation in technology and finance and should be neutral with respect to the specifics of how core computing technologies work

Question 9

Deciphering the Liquidity and Credit Crunch 2007-
2008

What were the factors leading up to the housing bubble?

Answer 9

i) A low interest rate environment:
▪ The Fed reluctant to raise interest rates fearful of deflation after the dot-com bubble
▪ Large capital inflows from abroad, especially Asia (bought American assets to
maintain favorable exchange rate and hedge against currency depreciation)
ii) A new “originate and distribute” banking model:
▪ Banks pooled, tranched, and resold loans via securitization instead of holding on to
them
▪ CDOs became extremely popular. Offloading balance-sheet risk (pipeline risk) led to
moral hazard – little incentive in monitoring the loan and performing initial due
diligence, because it will be sold later to someone else → NINJA loans
▪ Banks could lower their capital charges by securitizing (because of inadequate
calculations of risk-weighted assets and flawed ratings systems) and providing
contractual credit lines and liquidity backstops to the investment vehicles they
owned that held CDOs
iii) Lax regulation led to a dramatic fell in lending standards
iv) Banks relied on short-term financing and repo financing –> refinancing risk (if liquidity in the market dries up, it will be difficult to roll over short-term loans)

Question 10

Deciphering the Liquidity and Credit Crunch 2007-
2008

What were the reasons for optimistic CDO ratings?

Answer 10

1) Rating models were based on historically low mortgage default and delinquency rates
2) Past downturns in housing prices were primarily regional phenomena (diversification due to low cross-regional correlation)
3) Rating agencies collected higher fees for structured products (+ an issuer could resort to another rating agency if not satisfied with a product’s rating)
4) “Rating at the edge”: bank made sure that tranches were slides in such a way that they just barely crossed the dividing line to reach a certain rating (AAA, AA,…)

Question 11

Deciphering the Liquidity and Credit Crunch 2007-
2008

What is the funding liquidity risk? Market liquidity risk?

Answer 11

–> Funding liquidity risk: funding liquidity reflects the ease with which an institution
can obtain funding from financiers. Funding liquidity risk takes 3 forms
▪ Margin/haircut funding risk (margins/haircuts could change);
▪ Rollover risk (costly or impossible to roll over short-term borrowing);
▪ Redemption risk (depositors may choose to withdraw their money)

–> Market liquidity risk: market liquidity refers to the ease of quickly selling an asset without significantly depressing its price. Measured by:
▪ The bid-ask spread
▪ Market depth (selling without moving the price)
▪ Market resiliency (time it takes for prices to bounce back)

Question 12

Deciphering the Liquidity and Credit Crunch 2007-
2008

Borrower’s balance sheet effect: to what two spirals does a trader that uses leverage (margin trader) gets exposed to?

Answer 12

▪ A loss spiral: as the borrower’s equity evaporates, he needs to sell some of his assets to maintain constant leverage. Rapid sale of illiquid assets may lead to
significant losses (the trader moves the price significantly when selling)
▪ A margin spiral: the level of leverage that the borrower has to maintain doesn’t stay constant during market shocks, margin requirements typically rise and the borrower needs to sell even more assets (reinforcing loss spiral)

Question 13

Deciphering the Liquidity and Credit Crunch 2007-
2008

What were the effect catalysts (what increased the effect of/ caused the financial crisis) ?

Answer 13

–> The lending channel dry up:
▪ Moral hazard in monitoring: intermediaries have less “skin in the game” and will
thus invest less effort in proper monitoring
▪ Precautionary hoarding: the likelihood of interim shocks and tighter funding
increases
–> Runs on financial institutions:
▪ First-mover advantages make many financial institutions, not just banks,
vulnerable to runs (e.g. hedge fund client runs)
–> Network effects:
▪ Counterparty credit risk (financial institutions are lenders and borrowers at the
same time)
▪ Gridlock risk (holding additional funds due to counterparty risk). Makes risks
materialize

Question 14

Towards a Political Theory of the Firm

What is Medici vicious cycle?

Answer 14

The ability to influence the political power increase with economic power, so does the need to do so (fear of expropriation by politics)
“Medici vicious cycle” risk: money is used to gain political power and political power is them used to make more money

Question 15

Towards a Political Theory of the Firm

What are the reasons behind why the size of the average publicly listed company has tripled in the market capitalization?

Answer 15

▪ The size and market share of companies has increased reducing competition across conflicting interests in the same sector (more powerful vis-à-vis
consumers)
▪ The complexity of regulation has increased (easier to tilt the playing field)
▪ Demise of the antibusiness ideology that prevailed among Democrats took place
▪ The ideal state of affairs is the “goldilocks” balance between the power of the state and power of firms (otherwise, one entity will exploit the other)
▪ Network externalities (an increase in usage leads to a direct increase in the value for others)
▪ Proliferation of information-intensive goods (high fixed and low variable costs with increasing returns to scale) [winner-take-all industries]
▪ Reduced antitrust enforcement

Question 16

Towards a Political Theory of the Firm

What is the goldilocks balance?

Answer 16

The ideal state of affairs is the “goldilocks” balance between the power of the state and power of firms (otherwise, one entity will exploit the other)

Question 17

Towards a Political Theory of the Firm

On what does the Medici vicious cycle depend on?

Answer 17

▪ The main source of political power:(democratic or autocratic)
▪ The conditions of the media market: key mechanism in formation of social consensus; [i.e. censorship and concentration of media ownership in the hands of few make Medici vicious cycle more likely]
▪ Electoral process (incl. electoral law and campaign financing laws): [Electoral law – who can vote, who can hold the office, how political parties can be organized]; [campaign financing – private or public?]
▪ The dominant ideology; political legitimacy (how a given jurisdiction selects a person(s) whom they entrust the passage of new laws – think formal election process vs. inheriting political power)
▪ Prosecutorial and judiciary powers: how independent these powers are from the the political and the economic powers?

Question 18

Towards a Political Theory of the Firm

On what does a company’s ability depend to obtain what it wants from the political system?

Answer 18

1) Its ability to make credible long-term promises (future employment opportunities for politicians and regulators – think Citigroup example). Depends on the company’s longterm survival probability
2) The grip a company has on the market for specific human capital (the only game in the town – being the only employer in a town gives you a lot of lobbying power)
3) A company’s ability to wrap its self-interest in a bigger, noble idea (Fannie Mae and
the goal that every American should be able to borrow to purchase a house)
4) The control that a company has through its imagine in society by way of employment,
data ownership, media ownership, research funding, other methods

Question 19

The Economic Consequences of Legal Origins

What is a legal origin? What are the possible reasons for divergance?

Answer 19

Legal origin (LO) is a style of social control of economic (and not only) life (English common law vs. French civil law)
▪ English law puts a greater emphasis on judicial independence and the enforcement of
property rights, in part through the active use of case law (precedents)
▪ French law sets maintaining social order as its top priority and attempts to write laws and
statutes that require strict enforcement rather than interpretation

Possible historical reasons for the divergence:
▪ Common law – developed because the side of lawyers and property owners wanted to limit the
crown’s ability to interfere in the markets;
▪ Civil law – rediscovered in the Middle Ages and adopted by the Catholic church. Policyimplementing, state-desired allocations. Written during the 19th century French Revolution in
Napoleon’s codes to deprive judges, who were on the losing side with royalty, of law-making
power (i.e. create a legislation that can foresee all future circumstances)

Question 20

The Economic Consequences of Legal Origins

Compare the investor/ creditor protection between the common and civil law? Regulations? Judicial institutions?

Answer 20

LO → investor/creditor protection → economic/financial development
▪ Common law is associated with significantly better protection of creditors and outside investors,
both through rules and enforcement
LO → regulation → economic/financial development
▪ Common law is associated with less intervention in the markets/societal organization
LO → judicial institutions → contract enforcement/property rights
▪ Common law is associated with more judicial independence

Common law appears to be associated with better rules and in turn stronger financial development that leads to better economic outcomes (e.g. [arguably] faster economic growth). (Arguably because there are other confounding variables, such as human
capital)

Question 21

The Economic Consequences of Legal Origins

Why does common law lead to better economic outcomes on average?

Answer 21

▪ Common law is more respective of private property and contracts than civil law
▪ Common law puts more emphasis on unconditioned private contracting rather than
centrally-directed regulation (“dispute-resolving” vs. “policy-implementing”)
▪ Common law features a more adaptive framework and evolves over time thanks to
greater judicial independence

Question 22

The Economic Consequences of Legal Origins

When does common law works worse for the economy?

Answer 22

▪ When there’s disorder, civil law solutions will cope better (the example of Nigeria)
▪ Other country-specific variables have to be considered in evaluating the suitability of a legal
system
▪ All countries mix both systems and can implement solutions from both (neither of the two
systems is perfect)

Question 23

The Economic Consequences of Legal Origins

What impacts and what does not impact legal rules and outcomes?

Answer 23

Legal origins do impact

Culture (religion) and politics (political alliances writing rules to benefit themselves) do not impact.

Question 24

The Economic Consequences of Legal Origins

What were the findings supporting the Legal origin theory?

Answer 24

▪ Common law countries appear to have moved sharply ahead of the civil law ones in
financial development over the course of the 20th century
▪ Investor protection improved sharply in the common law countries over the same period

Shall the world remain peaceful and orderly, globalization will likely drive the world
towards more common law-type solutions in the future

Question 25

Bitcoin: Economics, Technology, and Governance

What are the Bitcoin intermediaries?

Answer 25

▪ Currency exchanges: designated institutions that convert traditional
currencies into bitcoins. CEs are in the purview of many regulators and are
often the targets of perpetrators
▪ Digital wallets: applications for managing a user’s account in a more
convenient way (less space, more mobility, better interface), but prone to
hackers
▪ Mixers: sending orders from multiple accounts to one and then from that
account to destination accounts. All transaction traces are lost in this way
(actually, not really..)
▪ Mining pools: miners can join their (computational) efforts and split the
rewards

Question 26

Bitcoin: Economics, Technology, and Governance

What are the uses of Bitcoin?

Answer 26

▪ Illicit activities (e.g. drugs trading through the Silk Road). Gambling
services. Evading international capital controls
▪ Consumer payments: very low cost for retailers compared to credit card
charges, mixed effects for consumers (no rebated or bonuses; currency
exchange charges; block chain processing time and storage burdens)
▪ Buy-and-hold (for price appreciation)
▪ Possible future: general purpose payments, mainstream store of value,
and enabling technology (international remittances, transfers of digital
property, and other services besides payments)

Question 27

Bitcoin: Economics, Technology, and Governance

What are the risks associated with Bitcoin?

Answer 27

▪ Market risk: the value of bitcoins is highly volatile (fluctuations in the
exchange rate between bitcoin and other currencies)
▪ Liquidity risk: (the shallow market problem) – a person seeking to trade a
large amount of bitcoins typically cannot do so quickly without affecting
the market price
▪ Counterparty risk: currency exchanges may cease operations (45%)
without reimbursing their consumers (46%), while digital wallet services
are lucrative targets for cybercriminals
▪ Transaction risk: i) no built-in mechanism to cancel a transaction if bitcoins
are sent due to error or fraud (irreversible transactions); ii) possibility to
cancel the payment or double-spend during the 10-minute interval of
block processing (miner collusion); iii) blacklisting stolen bitcoin transfers
losses to those who accepted them and gives abuse power to list managers
▪ Operational risk: operator errors, security flaws, and malware (miner “51
percent attack”, denial-of-service attack – swamping a target firm with
messages and requests so that it becomes unusable or very slow)
▪ Privacy-related risks: transactions could be linked back to people who
made them (real names are often revealed at currency exchanges or in
purchase details)
▪ Legal and regulatory risks: a law-abiding user could lose funds in an
exchange frozen or seized due to criminal activity

Question 28

Prone to Fail: The Pre-Crisis Financial System

Dealer / market maker function

Answer 28

Make markets by buying securities from investors who want to sell, then selling them to investors who want to buy.

Dealers hold securities on their balance sheets in order to provide immediacy to sellers and to have a stock on hand for buyers

Question 29

Prone to Fail: The Pre-Crisis Financial System

Repos (repurchase agreements) mechanism

Answer 29

on each repo, a dealer transfers securities as collateral to its creditor, and in turn receives cash. When an overnight repo matures the next morning, the dealer is responsible for returning the cash with interest, and is given back its securities collateral

Question 30

Prone to Fail: The Pre-Crisis Financial System

Tri-party repos mechanism

Answer 30

cash investors in repos (e.g. money market mutual funds, securities lending firms) often
held the collateral securities provided to them by dealers in accounts at two “tri-party” agent banks,
J.P. Morgan Chase and Bank of New York Mellon (only 2 in the pre-crisis period). Likewise, these repo
investors transferred their cash to the dealers’ deposit accounts at the same two tri-party banks.

Question 31

Prone to Fail: The Pre-Crisis Financial System

What is a Credit crunch

Answer 31

a decrease in lending by financial institutions —> reduced availability of loans/credit
irrespective of interest rates, frequently an outcome of ‘flight to safety’

Question 32

Prone to Fail: The Pre-Crisis Financial System

The key sources of fragility

Answer 32

1. Weakly supervised balance sheets of the largest banks and investment banks /ONE OF THE MOST POPULAR FACTORS/
2. The run-prone designs
3. Weak regulation of the markets for securities financing and over-the-counter derivatives
4. The undue reliance of regulators on “market discipline.”

Question 33

Prone to Fail: The Pre-Crisis Financial System

Explain “Too big to fail” concept

Answer 33

creditors apparently assumed
that the biggest banks were too important to be allowed by the government to fail and thus creditors would not take losses
if any of the largest banks or investment banks were to approach insolvency.

Question 34

Prone to Fail: The Pre-Crisis Financial System

Why was the pre-crisis supervision so ineffective?

Answer 34

1. The SEC’s original mission is to protect the customers of financial firms, which crowded out a parallel
   focus on financial stability —> a financial regulator with inappropriate goals
2. It was simply too difficult for regulators to detect the excessive buildup of risk and flight-prone shortrun debt and derivatives in the core of the pre-crisis financial system, especially given significant financial
   innovation and complexity
3. Investors and policymakers assigned irrationally low probabilities to disaster outcomes, especially with
   respect to the performance of the housing market
   —> Gennaioli and Shleifer: “put inaccurate beliefs at the center of the analysis of financial fragility.” =
   underestimated risks
4. Regulators placed undue reliance on market discipline
5. The historical US emphasis on a decentralised banking system —> “financial crises occur when
   banking systems are made vulnerable by construction, as the result of political choices.”

Question 35

Prone to Fail: The Pre-Crisis Financial System

What was the biggest reason firms opted not to be
supervised by the Fed?

Answer 35

the biggest reason firms opted not to be
supervised by the Fed was the “comprehensiveness” of the Fed’s supervisory approach, “particuarly
when compared to alternatives such as Office of Thrift Supervision (OTS) or Securities & Exchange
Commission (SEC) holding company supervision”

Question 36

Prone to Fail: The Pre-Crisis Financial System

Core Meltdown Risks

Answer 36

Risks: (1) creditor runs and (2) fire-sale losses

Question 37

Prone to Fail: The Pre-Crisis Financial System

Regulatory response since the crisis:

Answer 37

• The largest US dealer banks are all now under the supervision of the Federal Reserve.
• Improvements in the capitalisation of the largest financial institutions
• A reduction of unsafe practices and infrastructure in the markets for securities financing and derivatives
• New failure resolution methods now prevent derivatives and other critical financial contracts from suddenly terminating at
insolvency —> general creditors to these firms no longer presume that they will be bailed out —> much higher costs of
debt financing for these firms, which has discouraged their leverage and has knocked down the rapid pre-crisis growth of
their balance sheets

Question 38

Prone to Fail: The Pre-Crisis Financial System

Remaining concerns

Answer 38

• There is still no known operational planning for US government failure resolution of derivatives clearinghouses
• Regulations have forced the majority of derivatives risk into these clearinghouses, which are the new “too big to fail”
financial firms
• A threat that fading memories of the costs of the last crisis will lower the resolve and vigilance of legislatures and financial
regulators to monitor changes in practice and to take steps to control socially excessive risk-taking

Question 39

Prone to Fail: The Pre-Crisis Financial System

Too-Big-to-Fail Eviscerates Market Discipline - > Two basic assumptions that are wrong:

Answer 39

1. ’Banks can be relied upon to provide rigorous risk control.’
   In reality banks’ internal risk management and control functions were often ineffective in the run-up to the crisis and were usually trumped by the
   pressure to do profitable business.
2. ‘Markets will always self-correct.’
   A deference to the self-correcting property of markets inhibited supervisors from imposing prescriptive views on banks.