Foreign exchange risk begins with a measurement currency

A foreign asset can make every promised payment and still produce a loss when measured in the institution’s home currency. Foreign exchange risk is the possibility that exchange-rate changes reduce the home-currency value of assets relative to liabilities. Before calculating, state the currency in which the institution measures performance, the foreign currency, and the direction of the exchange-rate quote.

The source begins with the attraction of global investment. Domestic and foreign returns are not perfectly correlated because economies, asset markets and currencies do not move in lockstep. Foreign assets may therefore improve diversification or offer attractive expected returns. This is not a guarantee: exchange-rate changes can offset or overwhelm a foreign asset’s local-currency gain.

The slide cites roughly 10% foreign assets for US pension funds, compared with more than 30% foreign securities plus 10% foreign-currency deposits for Japanese funds. These are the lecture’s historical allocation context, not a current market survey or recommended allocation. The point is that foreign-currency exposures are material enough to require deliberate management.

The key question is the net position in each currency. Holding a foreign asset alone does not tell the whole story if a matching foreign liability or derivative offsets it. Matching assets and liabilities in that currency can reduce translation exposure, but the relevant amounts and cash-flow timing must match too. Equal foreign principal today does not automatically eliminate later funding or interest-rate risk.

A US financial institution buys Turkish bonds

The source’s institution measures its result in dollars. It starts with $100 million, converts at 5 TL per dollar, and buys a one-year lira bond paying 10%. Assume the bond repays in full, with no taxes, transaction fees or currency hedge. The first conversion gives $100 million × 5 TL/$ = TL 500 million. After one year, the local investment pays 500 × 1.10 = TL 550 million.

If the ending exchange rate remains 5 TL/$, divide the lira proceeds by 5: 550/5 = $110 million. The dollar profit is 110 − 100 = $10 million, and the dollar return is 110/100 − 1 = 10%. The reciprocal quote, 0.20 $/TL, gives the same conversion by multiplication: 550 × 0.20 = 110.

If the lira depreciates and the ending quote becomes 10 TL/$, the same TL 550 million converts to only 550/10 = $55 million. Dollar profit is 55 − 100 = −$45 million, giving a −45% dollar return. The bond still earned +10% in lira. The loss arises in conversion back to the measurement currency, not from a missed bond payment.

The quote change from 5 to 10 TL/$ means a dollar buys twice as many lira. In the reciprocal quote, each lira falls from $0.20 to $0.10—a 50% decline in its dollar value, not 100%. The combined return is multiplicative: 1.10 × 0.50 = 0.55. Adding +10% and −50% would incorrectly produce −40%, because it ignores that the interest earned in lira also converts at the weaker exchange rate.

For a general calculation, let W be the starting dollars, S₀ and S₁ the starting and ending TL/$ quotes, and r the lira return. The chain is W → WS₀ lira → WS₀(1+r) lira → WS₀(1+r)/S₁ dollars. Dividing by W gives 1+R_$=(1+r)S₀/S₁. Unit cancellation is safer than memorizing whether to multiply or divide.

The break-even exchange rate

The source asks how much depreciation the local interest can absorb before the dollar investment loses money. At break-even, the ending dollar amount must equal the original $100 million. Since the bond pays TL 550 million, solve 550/S₁ = 100. The threshold is S₁ = 5.5 TL/$.

An ending quote below 5.5 leaves more than $100 million; an ending quote above 5.5 leaves less. The lira can weaken relative to the initial 5 TL/$ quote, but only until the currency loss exactly consumes the interest cushion. In reciprocal terms, the threshold is 1/5.5 = 0.181818… $/TL.

The general break-even condition is S* = S₀(1+r). In this example the TL/$ quote can rise 10%, but the lira’s dollar value falls from 0.20 to 0.181818…, a decline of about 9.09%. There is no contradiction: the two percentages use different denominators. Always state the quote convention when saying that a currency appreciated or depreciated by a percentage.

This break-even calculation concerns the investment’s dollar return before fees, taxes, funding costs and default. It is not automatically the financial institution’s total profit. If the initial dollars were borrowed, their funding cost would also have to be covered.

Net long versus net short: which currency move hurts?

For a particular foreign currency, subtract foreign-currency liabilities from foreign-currency assets, including relevant contractual positions. A positive net amount is net long; a negative amount is net short. If q is home-currency units per foreign-currency unit and the fixed net foreign amount is N, its home-currency value is qN, so a translation change is ΔV = NΔq.

If N is positive, foreign-currency depreciation lowers q and hurts the institution. The source’s US bank net long pounds is a clean example: if sterling falls against the dollar, the net sterling assets translate into fewer dollars. If N is negative, foreign-currency appreciation raises the home-currency cost of net debt, making the position more negative.

The source’s short-position illustration says a “US bank net short $” loses if the dollar rises. The direction rule is valid only after specifying a different reporting currency. For a bank measuring purely in dollars, a dollar amount has no dollar-versus-dollar exchange-rate movement. A clear version is a lira-reporting bank that owes more dollars than it holds: dollar appreciation raises the lira value of its net dollar debt.

For example, a lira-based institution with $20 million of assets and $30 million of liabilities is net short $10 million. If the quote rises from 30 to 33 TL/$, its net translated value changes by −10 × (33−30) = −TL 30 million, holding the dollar quantities fixed. This is an original numerical illustration of the source sign rule.

The hedge footer requires matching both size and maturity in each currency. Otherwise equal currency totals can still leave a payment-timing or foreign-interest-rate mismatch. A derivative hedge can reduce the intended exchange exposure while introducing counterparty, margin or basis risk. Matching one dimension does not mean every risk disappears.

Market risk, VaR and daily earnings at risk

Market risk concerns losses on traded assets, liabilities and derivatives when market prices change. Interest rates, exchange rates and equity prices are named in the source; commodity and derivative values appear in the next page’s inventory. This overlaps with the risks already studied. A rise in rates can affect both the long-term loan in the banking book and the bond held for trading.

The active trading strategy changes the management horizon. Positions may be bought and sold quickly, valued frequently and used to generate trading income. Greater reliance on that income can increase sensitivity to price movements, other things equal. A long position generally benefits from a price rise; a simple short position generally benefits from a fall. The risk is the opposite move against the actual position.

The source names Value at Risk (VaR) and Daily Earnings at Risk (DEAR) as day-to-day measures. VaR is a model-based loss threshold at a stated confidence level over a stated horizon. For example, a one-day 99% VaR of 2 million means the model assigns roughly a 1% chance to losses exceeding 2 million over that day. It does not mean 2 million is the largest possible loss.

DEAR emphasizes a daily earnings/value-risk horizon. The source gives the names but no confidence level, distributional assumption or estimation formula, so none should be presented as if supplied by this lecture. A meaningful risk number needs its horizon and assumptions. It also needs complementary analysis of tail losses, market liquidity, model error and operational controls.

The page contrasts a relatively liquid trading book with longer-held, less liquid investment or banking positions. This is a useful business-model distinction, not a promise that trading assets can always be sold quickly. In a stressed market, an instrument normally traded each day can become difficult to sell without a large price concession.

Banking book versus trading book

The source’s complete banking-book list is cash, loans, premises and equipment, and other illiquid assets. Its funding list is deposits, other illiquid borrowed funds, and capital. These are held in the longer-term banking relationship rather than primarily for short-term price trading. Capital is included as funding in this teaching table, but it is equity, not an ordinary borrowed liability.

The trading-book list contains bonds, commodities, foreign exchange, equities and derivatives on both the long and short sides. These positions are monitored at current market values, often daily. The table calls the long side assets and the short side liabilities as a simplified exposure presentation; not every economic short position has identical accounting treatment.

Two qualifications prevent overreading the table. Cash is obviously liquid even though it appears in the banking list, so “banking book” does not mean every item is illiquid. The derivatives footnote calls them off-balance-sheet items, but this refers to the contingent/notional nature of the exposure; derivative fair values may be recognized on the balance sheet. The classification is not a complete accounting standard.

The final line introduces securitization: loan cash flows can be packaged into securities that are traded. This can make previously less tradable claims more marketable and bring daily price changes into view. It does not remove their underlying credit risk. When credit concerns rise, trading prices and market liquidity can deteriorate together—precisely the connection illustrated next by the 2008 crisis.

When trading risk is unmanaged: Barings and the 2008 comparison

The first case concerns Barings Bank and Nick Leeson in 1995. The source describes unauthorized speculative derivatives positions exposed to a decline in Japan’s Nikkei index. An open, unhedged position allowed an adverse market move to create a large loss; weak controls allowed the exposure to grow or remain concealed. This is market risk interacting with operational risk, not a market-price story alone.

The lecture reports losses of about £827 million, also quoted as approximately US $1.4 billion, and describes the amount as twice the bank’s available trading capital. Using that comparison, 827/2 implies about £413.5 million of available trading capital. This is a derived comparison amount, not a new independently measured regulatory-capital statistic. The key economic fact is that the reported loss exceeded the available cushion.

The second box uses 2008 as a system-scale extreme. It links troubled subprime mortgage-backed securities, frozen markets and Lehman’s failure on 15 September 2008. Borrower-credit problems impaired the securities’ expected cash flows; falling prices damaged capital; difficulty trading and funding positions magnified the pressure. Calling the episode market risk does not exclude credit, liquidity and systemic transmission.

The concluding rule is conditional on exposure: greater price volatility creates greater market-risk potential for an open position. But volatility alone is not the whole loss estimate. Position size, direction, hedges, leverage, liquidity and controls determine whether a shock remains manageable or overwhelms the institution.

Example: Barings Bank, Nick Leeson and the Nikkei

The illustrated page repeats the loss and capital figures and specifies 26 February 1995 as the insolvency date after an unsuccessful rescue attempt. The source emphasizes the collapse of a merchant bank more than 200 years old. Age and reputation did not substitute for exposure control or sufficient loss-absorbing resources.

Use the case as a causal sequence: unauthorized speculative trading creates an inadequately controlled position → an adverse Nikkei movement produces losses → losses exceed the available trading-capital cushion → a failed rescue leaves the bank insolvent. The sequence explains why independent verification, limits and separation of trading from control functions matter. Producing a risk statistic while the true positions remain hidden would not solve the problem.

The biographical material identifies Nicholas William “Nick” Leeson, born 25 February 1967, and mentions his prison sentence, release in 1999, later Galway United role and speaking activities. These details are source background, not claims about his current employment. The lecture also points to the film Rogue Trader, a video reference and nickleeson. com for further viewing. They are optional context; the examinable financial reasoning is the interaction of an open market position, failed controls and inadequate capital.