Explore the complexities of bond secondary market structures, including over-the-counter (OTC) networks and exchange platforms, and learn key pricing conventions such as clean versus dirty pricing and yield-based quotes.
Secondary bond markets provide a venue where investors buy and sell existing debt securities. If you ever bought a used car and then resold it later, you might understand this idea right away: The car is the same car—only ownership changes. In secondary markets, the original issuer doesn’t receive additional funds from these subsequent trades; instead, the trades happen among investors themselves. Despite that, the vitality of these markets is crucial for the overall health of the fixed-income landscape. A bond that’s easy to buy or sell (i.e., it’s liquid) is a bond that many investors feel comfortable holding. That comfort contributes to efficient price discovery, lower transaction costs, and, ultimately, a more attractive investment environment.
Anyway, from a CFA® perspective, we want to see how trades are arranged, how prices are quoted, and which market structures can exist. Secondary market transactions can look very different depending on whether you’re dealing with highly liquid government bonds or specialized private placements. The knowledge you gain here will help you navigate trading mechanics, figure out how prices are formed and discovered, and appreciate the complexities of bond liquidity.
Most of the world’s bond volume trades over the counter. You could say OTC bond markets have their own unique energy, a lot like a bustling bazaar—except it’s largely electronic these days. The “bazaar” analogy holds because participants negotiate directly (or via intermediaries such as dealers) rather than through a centralized exchange order book. Here’s a brief rundown of some of the key players that animate the OTC scene:
Because OTC trading is decentralized, transparent pricing data is sometimes less readily available than in exchange-traded markets. For instance, if you’re used to equity markets (with readily visible quotes on an order book), bond markets can feel more opaque, as the trading often happens bilaterally. Despite efforts from regulators and market participants to increase transparency, you still might not always see an official “last traded price” as easily as you could for a stock. Instead, you rely on indicated quotes from multiple dealers, electronic platforms, or third-party data sources.
Here’s an illustrative diagram of a typical OTC transaction flow:
graph LR
A["Investor A <br/>(Seller)"] -- "Wants to Sell Bond" --> B["Dealer/Broker"]
B["Dealer/Broker"] -- "Facilitates/Executes Trade" --> C["Investor B <br/>(Buyer)"]
In practice, the broker or dealer stands in the middle, quoting a price to Investor A and a price to Investor B, then matching or warehousing the bond. This arrangement means transaction costs can vary, especially if the bond in question is illiquid or rarely traded.
Although OTC markets dominate bond trading, a portion of certain government bonds, corporate bonds, or specialized debt instruments can trade on organized exchanges. Think of how equity shares commonly trade on the NYSE or LSE. An exchange-traded bond market has a central location (physical or electronic), with standardized listing requirements, real-time public quotes, and typically stricter regulatory oversight (e.g., listing rules, reporting requirements, etc.).
Still, let’s be honest, exchange trading for corporate bonds is quite small compared to OTC. One reason is that bonds often have unique features—coupon structures, maturities, embedded options—and may not fit standardized exchange-traded contracts well. That’s partially why government bonds, especially short-term Treasury bills or notes from certain developed markets, are more likely to be exchange-traded than specialized corporates or emerging-market issues.
Pricing in the bond world can get complicated pretty fast. That said, there are some general frameworks that help keep things coherent. In many major markets, bond prices are quoted as a percentage of par value (face value). For instance, you might see a quote of 99.75 or 105.50. Occasionally, you’ll see fractional quotes in increments of 1/32 (especially in U.S. Treasury markets) or decimalized quotes in a more modern format.
The most common confusion for new entrants into the bond market is, “Why is the final settlement price different from the quote on my screen?” The short answer is accrued interest. The quoted price (often called the clean price) doesn’t include accrued interest. But when you settle the trade, you pay or receive the dirty price (also known as the full price), which includes accrued interest.
Mathematically, the relationship is often expressed as:
The accrued interest typically accumulates daily from the last coupon payment date up to (but not including) the settlement date. Day count conventions vary by market—some use Actual/Actual, others might use 30/360 or Actual/365—but the principle remains that the buyer compensates the seller for the interest the seller earned up to the transaction date.
In a typical environment, if you see a corporate bond quote at 102.00, that might just be its clean price. The actual price you pay could be 102.18 or 102.23 once accrued interest is added. Over the life of a trade, you’ll see that clean price remain stable following coupon payments, while accrued interest builds up between coupon dates. The dirty price is used for actual trade settlement because it represents the total amount of money changing hands.
Sometimes, especially for government securities, you’ll see trades expressed directly in yield terms. For example, a U.S. Treasury might be quoted at a yield to maturity of 3.20%. Market participants then use yield-price conversions to figure out the actual transaction price. This approach is common for money market instruments as well (like T-bills, commercial paper, or certificates of deposit), where discount yield or bond equivalent yield might be used instead of a direct price quote.
Regardless, you should be comfortable flipping back and forth between price and yield quotes. A bond’s yield moves inversely to its price, so as yields go up, prices go down, and vice versa. If you’ve done any equity-level finance, you’re sure to remember that key inverse relationship. The big difference in bond markets is that the yield measure typically accounts for coupon payments, reinvestment assumptions, maturity, and potential embedded options. For exam and real-world practice, you should be able to apply standard yield conversion formulas and verify that a given yield quote translates to the correct bond price.
Here’s a tiny snippet of Python code that might give a sense of how yield to price conversions can be automated (a simplistic approach, ignoring day count specifics and compounding frequencies beyond annual):
1def bond_price(face_value, coupon_rate, yield_rate, years_to_maturity):
2 """
3 Calculate approximate bond price using a simplistic discounting approach.
4 :param face_value: e.g., 1000
5 :param coupon_rate: e.g., 0.05 means 5% annual coupon
6 :param yield_rate: e.g., 0.04 means 4% YTM
7 :param years_to_maturity: integer or float
8 :return: approximate bond price
9 """
10 coupon_payment = face_value * coupon_rate
11 present_value_coupons = 0
12 for t in range(1, int(years_to_maturity)+1):
13 pv_coupon = coupon_payment / ((1 + yield_rate)**t)
14 present_value_coupons += pv_coupon
15
16 present_value_maturity = face_value / ((1 + yield_rate)**years_to_maturity)
17 return present_value_coupons + present_value_maturity
In a real trading system, you’d need more precise day count conventions, coupon frequency, settlement date adjustments, yield compounding assumptions, possible embedded options, and more. But hopefully this snippet shows how straightforward yield-based price calculations can be when you abstract away the numerous real-world wrinkles.
Many bond markets around the world operate as quote-driven venues—particularly the OTC ones. In quote-driven systems, dealers post bid-ask quotes. Investors wanting to execute a trade must accept a dealer’s quote (or negotiate). The advantage here is immediacy: if a dealer can manage the inventory risk, you might get filled quickly.
One caveat: The bid-ask spreads can be wide, especially for less liquid issues. But hey, that’s the cost of participating in a market where the dealer is taking on risk of holding that bond until they find another buyer or seller at an acceptable price.
In an order-driven market, all buy and sell orders funnel into a central limit order book, matching trades when a buy price meets (or betters) a sell price. You’ve seen this in equity markets—like the big electronic boards. Certain exchange-traded bond markets also adopt this mechanism for specific issues, typically the most liquid government securities. The appeal here is transparency: you see orders in real time, so you can gauge supply and demand directly.
However, order-driven systems in bond markets can suffer from limited liquidity if the order flow is sparse. For that reason, many corporate bond markets stay primarily quote-driven, reliant on dealers that can provide liquidity, especially for large institutional trades.
Think of a big pension fund that wants to offload $50 million worth of a certain corporate bond with 15 years remaining to maturity. This is a large trade—too big to “chip away at” on a public order book (lest the fund risk pushing the price down on itself). Instead, the fund’s portfolio manager typically calls or messages multiple dealers, obtains quotes, and might then negotiate with the dealer who offers the best price. That negotiation might take minutes or hours, depending on the market’s liquidity, the size of the block, and the overall environment.
Or imagine a scenario where a retail investor in Europe is looking to buy a small lot (say, €5,000) of a local government bond. The investor might be directed to a local exchange platform, see published bid-ask quotes, and place a limit order. That order then sits in the order book until matched with a seller’s asking price or the inverse.
The important thing to remember is that these structures (OTC vs. exchange, quote-driven vs. order-driven) can coexist, often for the very same bonds. As a result, you may see slightly different quotes in different venues, but usually not enough difference that you could easily “arbitrage” to profit risk-free—dealers and high-frequency traders keep the markets fairly tight.
No discussion of bond market microstructure is complete without mentioning the bid-ask spread. Essentially, the spread is the dealer’s compensation for providing liquidity and bearing inventory risk. Less liquid bonds, or those with uncertain credit prospects, typically exhibit wider spreads. So do complicated structured instruments. Meanwhile, highly liquid government bonds or large, actively traded investment-grade credits can have narrower spreads.
Sure, it might look like a fraction of a percentage at times, but the spread can be a huge factor in large trades. Even a 0.10% difference (10 basis points) on a $10 million trade can translate into a $10,000 cost. Over time, that cost can add up, which is why institutional traders might shop around with multiple dealers or attempt to trade on the more transparent portion of the market if possible—particularly for large blocks.
Especially since the 2008 financial crisis, global regulators have stepped up efforts to bring transparency and stability to bond trading. Regulatory initiatives, such as the EU’s Markets in Financial Instruments Directive II (MiFID II) or the U.S. FINRA Trade Reporting and Compliance Engine (TRACE) system, have increased post-trade reporting requirements. This means trades get reported and released to the public within a short time window, allowing participants to see recent transaction prices.
For IFRS or US GAAP reporting, you’d classify bonds on the balance sheet at fair value through profit or loss (FVTPL), amortized cost, or fair value through other comprehensive income (FVOCI), depending on the entity’s business model and the characteristics of the instrument. This classification can influence how frequently you mark these bonds to market, which in turn compels you to care about the day-to-day or even intraday changes in secondary market quotes.
From an ethical standpoint (and as guided by the CFA Institute Code and Standards), practitioners must deal fairly and objectively with clients, especially when offering bond quotes or executing trades on their behalf. A portfolio manager or an investment adviser must aim for best execution, diligently seeking the best price while balancing other relevant factors like order size, speed, and market conditions.
If you’re preparing for the CFA exam, especially at advanced levels, expect to see scenario-based questions. Be ready to:
A typical exam question might read: “A pension fund needs to liquidate $10 million of a thinly traded corporate bond in 48 hours. Describe the likely secondary market execution method and the considerations affecting price.” You’d want to highlight that an OTC approach with multiple dealers is the typical route due to the bond’s illiquidity, that the portfolio manager might have to accept a wider spread, and that regulation or post-trade reporting could influence the eventual price discovery.
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