Questions & explanations
1. What is the difference between a credit default swap (CDS) and bond insurance?
A CDS and bond insurance both protect against default, but they differ in structure and regulation. Bond insurance is a traditional insurance policy bought by a bond issuer to guarantee payments to investors. The insurer evaluates the bond's risk and charges a premium. A CDS is a derivative contract that can be bought by anyone, even someone who doesn't own the bond. Bond insurance covers the actual bondholders, while CDS can be used for speculation. Also, bond insurers are regulated as insurance companies, while CDS sellers often are not. The payout methods may also differ: CDS usually pays the difference between face value and recovery, bond insurance pays the missed payments.
2. Compare IFRS 9 and CECL approaches to loan loss provisioning.
IFRS 9 (International Financial Reporting Standard 9) and CECL (Current Expected Credit Loss) both use expected loss models, but they differ in scope and timing. IFRS 9 is used in many countries outside the US, while CECL is for US banks. IFRS 9 uses a three-stage model: only lifetime losses for loans with significantly increased risk. CECL requires a lifetime expected loss for all loans from the start. CECL also does not have a staging approach – it's a single measurement. In practice, CECL usually leads to higher provisions at origination because it includes all future losses from day one. Both models require economic forecasts, but CECL allows more flexibility in methods.
3. What role do taxes play in credit spread decomposition?
Taxes affect credit spread because different bonds have different tax treatment. For example, in many countries, interest from government bonds is tax-exempt at the local level, while corporate bond interest is taxable. Investors in high tax brackets prefer tax-free bonds, which lowers their yield. The credit spread between taxable and tax-free bonds includes a tax premium. The tax portion of the spread is the extra yield needed to make taxable bonds comparable after tax. For example, if a corporate bond yields 5% and a municipal bond yields 3.5% (tax-free), the 1.5% difference includes a tax effect. analysts adjust for tax to isolate default and liquidity risks.
4. Compare a credit default swap (CDS) with an interest rate swap in terms of purpose and risk.
A CDS and an interest rate swap (IRS) are both derivatives, but they hedge different risks. A CDS hedges credit risk – the risk that a borrower defaults. An IRS hedges interest rate risk – the risk that market interest rates change. In a CDS, the buyer pays a fixed premium and receives a payment on default. In an IRS, parties exchange fixed and floating interest payments based on a notional amount. The main risk in a CDS is counterparty default; in an IRS, the risk is also counterparty, but market movements cause mark-to-market changes. Both are used by banks to manage their risk exposures, but CDS is more about credit events, while IRS is about rate movements.
5. How do both types of models incorporate recovery rate (how much lenders get back if default happens)?
In structural models, recovery rate is often assumed to be a fraction of the debt, sometimes based on asset value at default. For example, in Merton model, recovery equals assets minus bankruptcy costs. Reduced-form models treat recovery as a separate input, often as a percentage of face value (e.g., 40% for senior unsecured debt). In practice, recovery is estimated from historical data. Both types need recovery to convert default probability into credit spreads. Higher expected recovery lowers the required spread for a given default probability. Models differ in how recovery is determined: structural links to assets, reduced-form uses an exogenous assumption.
6. What design choices do central banks face when creating a CBDC?
They must decide whether the CBDC should be a token-based or account-based system. Token-based works like digital cash – you hold it in a digital wallet, and transfer is private. Account-based requires identity verification and works like a bank account. Another choice is whether to pay interest on CBDC holdings, which could affect bank deposits. They also set limits on how much an individual can hold to avoid bank runs. Privacy vs. traceability is a key trade-off – too much privacy could aid crime, too little might scare users. Some designs allow offline transactions using near-field communication (NFC). Each choice has big impacts on the financial system.
7. What is yield farming in DeFi and how does it work?
Yield farming means users lend or stake their crypto assets to earn rewards, often in the form of additional tokens. For instance, you can deposit your coins into a lending protocol like Aave and earn interest plus extra governance tokens. Some protocols offer very high yields by distributing their native tokens to attract liquidity. The returns come from trading fees, borrowing interest, or token inflation. But these high yields are risky: the token price can drop sharply, or a smart contract bug can steal funds. Yield farming often involves complex strategies across multiple protocols. It is not passive – users must monitor positions and risks constantly.
8. How are gains and losses from derivatives taxed differently for hedgers versus speculators?
Hedgers use derivatives to manage business risk, so their gains and losses are usually taxed as ordinary income, matching the underlying business transaction. For example, a farmer hedging crop prices pays ordinary tax on futures gains, offsetting higher crop sale income. Speculators are traders who seek profit from price changes. Their gains are often treated as capital gains, which may have lower tax rates if held long-term. But in some countries, frequent trading makes gains ordinary income. The key difference is that hedgers get ordinary treatment to mirror their business, while speculators may get capital treatment if holding period rules are met.
9. How do CAR and leverage ratio differ?
CAR uses risk-weighted assets, while the leverage ratio uses total assets without risk weights. CAR gives less weight to safe assets, so a bank with many government bonds can have a high CAR even if its total assets are large. The leverage ratio is stricter because it does not consider risk. For example, a bank with $10 capital and $100 in safe bonds has CAR = 10% (if bonds have low risk weight), but leverage ratio = 10% (same). If the same bank has $100 in risky loans, CAR might be 5% (if high risk weight), but leverage ratio stays 10%. So both are used together: CAR ensures capital matches risk, leverage ratio ensures a minimum overall capital base.
10. What role does liquidity transformation play in the Diamond-Dybvig model?
Liquidity transformation means the bank takes liquid deposits (which can be withdrawn anytime) and invests in illiquid loans (which cannot be sold quickly without loss). This is the core of the Diamond-Dybvig model. It allows the economy to fund long-term projects using short-term savings, which is valuable. But it also creates fragility: if too many depositors demand their money at once, the bank cannot meet all withdrawals without selling loans at a loss. The model shows that this liquidity transformation makes banks useful but also run-prone. Deposit insurance helps keep the system stable while preserving the benefits of liquidity transformation.
11. What are some common use cases of smart contracts in finance?
Smart contracts are used for decentralized exchanges where trades happen automatically via liquidity pools. They power lending platforms where users earn interest from pooled assets. Insurance contracts can automatically pay out when certain triggers occur, like a flight delay verified by an oracle. Smart contracts also enable tokenization – creating digital tokens that represent real-world assets like stocks or real estate. Another use is in supply chain finance, where payments release when goods arrive. The key benefit is removing intermediaries and reducing costs. However, adoption is still limited by legal uncertainty and technical risks.
12. Compare global macro and event-driven hedge fund strategies.
Global macro funds bet on big economic changes in countries and markets, using top-down analysis. Event-driven funds focus on specific corporate events like mergers, bankruptcies, or spin-offs. Macro is about predicting trends in interest rates, currencies, etc., while event-driven is about analyzing individual deals or distressed companies. Macro strategies often use derivatives and can be very liquid, while event-driven may involve less liquid securities and longer time horizons. Both can profit in different market conditions, but macro is more dependent on global news, and event-driven on corporate actions. They require different skills.