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The FixedRateBondHelper class in python has the following constructor: ql.FixedRateBondHelper( price, settlementDays, faceAmount, schedule, coupons, dayCounter, paymentConv=Following, redemption=100.0, issueDate=Date(), paymentCalendar=Calendar(), exCouponPeriod=Period(), exCouponCalendar=Calendar(), exCouponConvention=Unadjusted, exCouponEndOfMonth=...

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A floating rate bond is typically referencing to some interest rate curve (3m LIBOR, 6m EURIBOR etc.) You can also consider other periods, you just need to know the forward rate for that period, which is first derived from the interest rate curve and second discounted by that interest rate curve. This doesn't assume any embedded options. Only for the first ...

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According to Monika Piazzesi: The word “affine term structure model” is often used in different ways. I will use the word to describe any arbitrage-free model in which [zero coupon] bond yields are affine (constant plus-linear) functions of some state vector x. Affine models are thus a special class of term structure models, which write the yield y(τ) of ...

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In an Affine Term Structure model, zero coupon bond prices can be written as $P\left(t, T\right) = e^{A\left(t, T\right) - B\left(t, T\right) r_t}$. The zero coupon rate $R\left(t, T\right) = -\frac{\ln \left(P\left(t, T\right) \right)}{T - t}$ is thus an affine function in the short rate $r_t$. Many textbooks have some dedicated paragraphs to these models; ...

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Note: In this text, I will not touch on the topic of dirty vs. clean price. Neither on business day adjustments for the curve construction. Definition The present value of a bond, or its clean price, can be defined is $$P(t) = \sum_i^ncD(t,T_i)+D(T_n)$$ Where $c$ is the coupon on the bond (potentially scaled to correct payment frequency), $D(t,T)$ is ...

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When you use $E[r(t)]$, you need to include an additional term to ensure the no-arbitrage condition. Try to use simulated $r(t)$ and calculate the expectation of $P(t,T)$ because $P(t,T)$ is a random variable. ($N$ = number of simulation) $$P^1 (t,T) = \exp(A(t,T) - B(t,T)r^1(t))$$ $$P^2 (t,T) = \exp(A(t,T) - B(t,T)r^2(t))$$ $$...$$  P^N (t,T) = \...

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As part of your analysis, it is always a good idea to do something simple before pulling out the big guns. So, OLS by country with perhaps a handful of controls would be a good benchmark, if only to tell later if your complicated ideas don't amount to squashing a fly with a sledge hammer. As for the panel idea, you have to think about how you'd be pooling ...

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