如果未做特别说明,文中的程序都是 C++11 代码。
QuantLib 金融计算——收益率曲线之构建曲线(4)
本文代码对应的 QuantLib 版本是 1.15。相关源代码可以在 QuantLibEx 找到。
概述
QuantLib 中提供了用三次 B 样条函数拟合期限结构的功能,但是,并未提供使用三次样条函数拟合期限结构的功能。本文展示了如何在 QuantLib 的框架内实现三次样条函数,并拟合期限结构。
示例所用的样本券交易数据来自专门进行期限结构分析的 R 包——termstrc。具体来说是数据集 govbonds
中的 GERMANY
部分,包含 2008-01-30 这一天德国市场上 52 只固息债的成交数据。
注意:为了适配 QuantLib,实际计算中删除了两只债券的数据,以保证所有样本券的到期时间均不相同。样本券数据在《收益率曲线之构建曲线(3)》的附录中列出。
三次样条函数与期限结构
用三次样条函数拟合期限结构,实质上是用若干三次样条函数的组合近似贴现因子曲线的形状,
\[ d(t,\beta) = 1 + \sum_{l=1}^n \beta_l c_l(t) \]
贴现因子 \(d(t,\beta)\) 表示为三次样条函数的线性组合,\(\beta_l\) 是最优化计算需要估计出的参数。
三次样条函数 \(c_l(t)\) 的形式基于文献 (Ferstl and Hayden, 2010),
\[ \begin{cases} & \text{ if } l=n, c_l(t)=t\\ & \text{ else }, c_{l}\left(t\right)= \left\{\begin{array}{ll} 0 & {t<k_{l-1}} \\ {\frac{\left(t-k_{l-1}\right)^{3}}{6\left(k_{l}-k_{l-1}\right)}} & {k_{l-1} \leq t<k_{l}} \\ {\frac{\left(k_{l}-k_{l-1}\right)^{2}}{6}+\frac{\left(k_{l}-k_{l-1}\right)\left(t-k_{l}\right)}{6}+\frac{\left(t-k_{l}\right)^{2}}{6\left(k_{l+1}-k_{l}\right)}} & {k_{l} \leq t<k_{l+1}} \\ {\left(k_{l+1}-k_{l-1}\right)\left[\frac{2 k_{l+1}-k_{l}-k_{l-1}}{6}+\frac{t-k_{l+1}}{2}\right]} & {k_{l+1} \leq t} \end{array}\right. \end{cases} \]
对于有 \(n\) 个参数的贴现因子曲线,用户需要提供 \(n-1\) 个 knots \(k_i(1\le i\lt n)\),并令 \(k_0 = 0\) 以及 \(k_n = k_{n-1}\)。
knots 的选择
knots 的选择基于文献 (McCulloch, 1975),也可以参考文献 (Ferstl and Hayden, 2010),
\[ \begin{cases} & \text{ if } l=1, k_l = 0\\ & \text{ else if } l=n-1,k_l=m_N \\ & \text{ else }, k_l = m_h + \theta(m_{h+1} - m_h) \end{cases} \]
其中,\(h=\left\lceil\frac{(l-1) k}{n-2}\right\rceil\),\(\theta=\frac{(l-1) k}{n-2}-h\),\(m_i(1 \le i\le N)\) 是升序排列后样本券的剩余期限。
实现三次样条函数
三次样条函数类 CubicSpline
的实现仿照已存在的 BSpline
类,
CubicSpline.hpp
class CubicSpline { public: CubicSpline(const std::vector<Real>& knots); ~CubicSpline(); Real operator()(Natural i, Real x) const; private: Size n_; std::vector<Real> knots_ex_; };
CubicSpline.cpp
CubicSpline::CubicSpline(const std::vector<Real>& knots) : n_(knots.size() + 1), knots_ex_(knots) { knots_ex_.insert(knots_ex_.begin(), 0.0); knots_ex_.insert(knots_ex_.end(), knots.back()); } CubicSpline::~CubicSpline() { } Real CubicSpline::operator()(Natural i, Real x) const { using namespace std; if (i < n_) { Real q = knots_ex_[i], q_minus = knots_ex_[i - 1], q_plus = knots_ex_[i + 1]; if (x < q_minus) { return 0.0; } else if (q_minus <= x and x < q) { return pow(x - q_minus, 3) / (6.0 * (q - q_minus)); } else if (q <= x and x < q_plus) { return pow(q - q_minus, 2) / 6.0 + (q - q_minus) * (x - q) / 2.0 + pow(x - q, 2) / 2.0 - pow(x - q, 3) / (6.0 * (q_plus - q)); } else { return (q_plus - q_minus) * ((2.0 * q_plus - q - q_minus) / 6.0 + (x - q_plus) / 2.0); } } else { return x; } }
实现拟合方法
拟合方法 CubicSplinesFitting
的实现仿照已存在的 CubicBSplinesFitting
类,两者均是 FittedBondDiscountCurve::FittingMethod
的派生类,
CubicSplinesFitting.hpp
class CubicSplinesFitting : public FittedBondDiscountCurve::FittingMethod { public: CubicSplinesFitting(const std::vector<Time>& knotVector, const Array& weights = Array(), ext::shared_ptr<OptimizationMethod> optimizationMethod = ext::shared_ptr<OptimizationMethod>(), const Array& l2 = Array()); CubicSplinesFitting(const std::vector<Time>& knotVector, const Array& weights, const Array& l2); //! cubic spline basis functions Real basisFunction(Integer i, Time t) const; static std::vector<Time> autoKnots(const std::vector<Time>& maturities); #if defined(QL_USE_STD_UNIQUE_PTR) std::unique_ptr<FittedBondDiscountCurve::FittingMethod> clone() const; #else std::auto_ptr<FittedBondDiscountCurve::FittingMethod> clone() const; #endif private: Size size() const; DiscountFactor discountFunction(const Array& x, Time t) const; CubicSpline splines_; Size size_; //! N_th basis function coefficient to solve for when d(0)=1 Natural N_; };
CubicSplinesFitting.cpp
CubicSplinesFitting::CubicSplinesFitting(const std::vector<Time>& knots, const Array& weights, ext::shared_ptr<OptimizationMethod> optimizationMethod, const Array& l2) : FittedBondDiscountCurve::FittingMethod( false, weights, optimizationMethod, l2), splines_(knots) { Size basisFunctions = knots.size() + 1; size_ = basisFunctions; N_ = 0; } CubicSplinesFitting::CubicSplinesFitting(const std::vector<Time>& knots, const Array& weights, const Array& l2) : FittedBondDiscountCurve::FittingMethod( false, weights, ext::shared_ptr<OptimizationMethod>(), l2), splines_(knots) { Size basisFunctions = knots.size() + 1; size_ = basisFunctions; N_ = 0; } Real CubicSplinesFitting::basisFunction(Integer i, Time t) const { return splines_(i, t); } QL_UNIQUE_OR_AUTO_PTR<FittedBondDiscountCurve::FittingMethod> CubicSplinesFitting::clone() const { return QL_UNIQUE_OR_AUTO_PTR<FittedBondDiscountCurve::FittingMethod>( new CubicSplinesFitting(*this)); } Size CubicSplinesFitting::size() const { return size_; } DiscountFactor CubicSplinesFitting::discountFunction(const Array& x, Time t) const { DiscountFactor d = 1.0; for (Size i = 0; i < size_; ++i) { d += x[i] * splines_(i + 1, t); } return d; } std::vector<Time> CubicSplinesFitting::autoKnots(const std::vector<Time>& maturities) { using namespace std; vector<Time> m(maturities); sort(m.begin(), m.end()); Size k = m.size(); Size n(floor(sqrt(k) + 0.5)); vector<Time> knots(n - 1); knots[0] = 0.0; knots[n - 1] = m.back(); for (Size l = 1; l < n - 1; ++l) { Size h(ceil(Real(l * k) / Real(n - 2))); Real theta = Real(l * k) / Real(n - 2) - h; knots[l] = m[h - 1] + theta * (m[h] - m[h - 1]); } return knots; }
测试
用上述两个类拟合样本券的期限结构,并和 termstrc
的结果做比较。
辅助函数 CubicSplineSpotRate
用于将样条函数表示的贴现因子转换成即期利率。
QuantLib::Real CubicSplineSpotRate(const std::vector<QuantLib::Real>& knots, const QuantLib::Array& weights, const QuantLib::Time& t) { using namespace std; using namespace QuantLib; CubicSpline spline(knots); Size s = weights.size(); Real d = 1.0, r; for (Size i = 0; i < s; ++i) { d += weights[i] * spline(i + 1, t); } r = -std::log(d) / t; return r; }
测试函数
void TestCubicSplineFitting() { using namespace std; using namespace QuantLib; // 样本券数据,以及相关配置 Size bondNum = 50; vector<Real> cleanPrice = { 100.002, 99.92, 99.805, 99.75, 100.305, 99.76, 99.75, 99.975, 100.0416, 100.0574, 99.5049, 101.0971, 101.137, 100.7199, 99.8883, 100.908, 103.3553, 99.5034, 103.913, 97.4229, 104.5636, 99.7527, 104.3708, 99.6051, 104.8603, 101.3415, 105.29, 102.4969, 103.7602, 100.2803, 102.6046, 102.5291, 99.4748, 95.9702, 97.1815, 114.2849, 100.2847, 112.23, 98.397, 102.0235, 99.8483, 121.2711, 125.9157, 114.5791, 103.2202, 123.4668, 113.4694, 103.1873, 91.5603, 95.4441}; vector<Handle<Quote>> priceHandle(bondNum); for (Size i = 0; i < bondNum; ++i) { ext::shared_ptr<Quote> q( new SimpleQuote(cleanPrice[i])); Handle<Quote> hq(q); priceHandle[i] = hq; } vector<Year> issueYear = { 2002, 2006, 2003, 2006, 1998, 2006, 2003, 2006, 1999, 2007, 2004, 2007, 1999, 2007, 2004, 2007, 1999, 2005, 2000, 2005, 2000, 2006, 2001, 2006, 2001, 2007, 2002, 2007, 2002, 2003, 2003, 2004, 2004, 2005, 2005, 1986, 2006, 1986, 2006, 2007, 2007, 1993, 1997, 1998, 1998, 2000, 2000, 2003, 2004, 2006}; vector<Month> issueMonth = { Aug, Mar, Apr, May, Jul, Aug, Sep, Nov, Jan, Feb, Feb, May, Jul, Aug, Aug, Sep, Oct, Feb, May, Aug, Sep, Feb, May, Aug, Dec, Feb, Jun, Aug, Dec, Jun, Oct, Apr, Oct, Apr, Oct, Jun, Apr, Sep, Oct, Apr, Sep, Dec, Jul, Jan, Oct, Jan, Oct, Jan, Dec, Dec}; vector<Day> issueDay = { 14, 8, 11, 30, 4, 30, 25, 30, 4, 28, 2, 30, 4, 24, 25, 21, 22, 24, 5, 26, 29, 26, 23, 30, 28, 28, 26, 24, 31, 24, 21, 25, 27, 28, 30, 20, 26, 20, 31, 27, 21, 29, 3, 4, 7, 4, 27, 22, 24, 28}; vector<Year> maturityYear = { 2008, 2008, 2008, 2008, 2008, 2008, 2008, 2008, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2010, 2010, 2010, 2010, 2011, 2011, 2011, 2011, 2012, 2012, 2012, 2012, 2013, 2013, 2014, 2014, 2015, 2015, 2016, 2016, 2016, 2016, 2017, 2017, 2018, 2024, 2027, 2028, 2028, 2030, 2031, 2034, 2037, 2039}; vector<Month> maturityMonth = { Feb, Mar, Apr, Jun, Jul, Sep, Oct, Dec, Jan, Mar, Apr, Jun, Jul, Sep, Oct, Dec, Jan, Apr, Jul, Oct, Jan, Apr, Jul, Oct, Jan, Apr, Jul, Oct, Jan, Jul, Jan, Jul, Jan, Jul, Jan, Jun, Jul, Sep, Jan, Jul, Jan, Jan, Jul, Jan, Jul, Jan, Jan, Jul, Jan, Jul}; vector<Day> maturityDay = { 15, 14, 11, 13, 4, 12, 10, 12, 4, 13, 17, 12, 4, 11, 9, 11, 4, 9, 4, 8, 4, 8, 4, 14, 4, 13, 4, 12, 4, 4, 4, 4, 4, 4, 4, 20, 4, 20, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4}; vector<Date> issueDate(bondNum), maturityDate(bondNum); for (Size i = 0; i < bondNum; ++i) { Date idate(issueDay[i], issueMonth[i], issueYear[i]); Date mdate(maturityDay[i], maturityMonth[i], maturityYear[i]); issueDate[i] = idate; maturityDate[i] = mdate; } vector<Real> couponRate = { 0.0425, 0.03, 0.03, 0.0325, 0.0475, 0.035, 0.035, 0.0375, 0.0375, 0.0375, 0.0325, 0.045, 0.045, 0.04, 0.035, 0.04, 0.05375, 0.0325, 0.0525, 0.025, 0.0525, 0.035, 0.05, 0.035, 0.05, 0.04, 0.05, 0.0425, 0.045, 0.0375, 0.0425, 0.0425, 0.0375, 0.0325, 0.035, 0.06, 0.04, 0.05625, 0.0375, 0.0425, 0.04, 0.0625, 0.065, 0.05625, 0.0475, 0.0625, 0.055, 0.0475, 0.04, 0.0425}; Frequency frequency = Annual; Actual365Fixed dayCounter(Actual365Fixed::Standard); BusinessDayConvention paymentConv = Unadjusted; BusinessDayConvention terminationDateConv = Unadjusted; BusinessDayConvention convention = Unadjusted; Real redemption = 100.0; Real faceAmount = 100.0; Germany calendar(Germany::Eurex); Date today = calendar.adjust(Date(30, Jan, 2008)); Settings::instance().evaluationDate() = today; Natural bondSettlementDays = 0; Date bondSettlementDate = calendar.advance( today, Period(bondSettlementDays, Days)); vector<ext::shared_ptr<BondHelper>> instruments(bondNum); vector<Time> maturity(bondNum); // 配置 helper for (Size i = 0; i < bondNum; ++i) { vector<Real> bondCoupon = {couponRate[i]}; Schedule schedule( issueDate[i], maturityDate[i], Period(frequency), calendar, convention, terminationDateConv, DateGeneration::Backward, false); ext::shared_ptr<FixedRateBondHelper> helper( new FixedRateBondHelper( priceHandle[i], bondSettlementDays, faceAmount, schedule, bondCoupon, dayCounter, paymentConv, redemption)); maturity[i] = dayCounter.yearFraction( bondSettlementDate, helper->maturityDate()); instruments[i] = helper; } Real tolerance = 1.0e-6; Natural max = 5000; ext::shared_ptr<OptimizationMethod> optMethod( new LevenbergMarquardt()); vector<Real> knots = CubicSplinesFitting::autoKnots(maturity); vector<Real> termstrcKnotes = { 0.000000, 1.006027, 2.380274, 5.033425, 9.234521, 31.446575}; cout << "QuantLib knots:\t"; for (auto v : knots) { cout << setprecision(6) << fixed << v << ", "; } cout << endl; cout << "termstrc knots:\t"; for (auto v : termstrcKnotes) { cout << setprecision(6) << fixed << v << ", "; } cout << endl; cout << endl; CubicSplinesFitting csf( knots, Array(), optMethod); FittedBondDiscountCurve tsCubicSplines( bondSettlementDate, instruments, dayCounter, csf, tolerance, max); Array weights = tsCubicSplines.fitResults().solution(); Array termstrcWeights(7); termstrcWeights[0] = 1.9320e-02, termstrcWeights[1] = -8.4936e-05, termstrcWeights[2] = -3.2009e-04, termstrcWeights[3] = -3.7101e-04, termstrcWeights[4] = 7.2921e-04, termstrcWeights[5] = 2.0159e-03, termstrcWeights[6] = -4.1632e-02; cout << "QuantLib weights: \t" << weights << endl; cout << "termstrc weights: \t" << termstrcWeights << endl; cout << endl; cout << "QuantLib final cost value:\t" << tsCubicSplines.fitResults().minimumCostValue() << endl; cout << endl; // 比较 QuantLib 和 termstrc 的结果 Real spotRate, termstrcSpot; for (Size i = 0; i < bondNum; ++i) { Time t = dayCounter.yearFraction( bondSettlementDate, maturityDate[i]); spotRate = tsCubicSplines.zeroRate(t, Compounding::Continuous, frequency).rate() * 100.0; termstrcSpot = CubicSplineSpotRate(termstrcKnotes, termstrcWeights, t) * 100.0; cout << setprecision(3) << fixed << t << ",\t" << spotRate << ",\t" << termstrcSpot << ",\t" << spotRate - termstrcSpot << endl; } }
部分结果:
QuantLib knots: 0.000000, 1.117808, 2.690411, 5.430137, 9.432877, 31.446575, termstrc knots: 0.000000, 1.006027, 2.380274, 5.033425, 9.234521, 31.446575, QuantLib weights: [ 0.005281; 0.004565; -0.002934; 0.000804; 0.000652; 0.001886; -0.038316 ] termstrc weights: [ 0.019320; -0.000085; -0.000320; -0.000371; 0.000729; 0.002016; -0.041632 ] QuantLib final cost value: 0.000338 0.044, 3.823, 4.125, -0.302 0.121, 3.809, 4.061, -0.253 0.197, 3.794, 4.001, -0.207 0.370, 3.761, 3.878, -0.116 ... .. .
图 1:结果对比
注意:尽管以 termstrc 的结果作为基准,并不意味着基准就是正确答案。
由于样本券的数量不同(termstrc
使用了 52 只券),两者的 knots 差异较大。同时,因为优化方法的不同(termstrc
使用 OLS,QuantLib 使用 Levenberg-Marquardt 算法),估计出的参数也有差异。最终导致两个期限结构在两端差异较大。
不过,考虑到最终的 cost value,QuantLib 的结果可能更好一些。
参考文献
- Ferstl.R, Hayden.J (2010). "Zero-Coupon Yield Curve Estimation with the Package
termstrc
." Journal of Statistical Software, Volume 36, Issue 1. - McCulloch JH (1975). "The Tax-Adjusted Yield Curve." The Journal of Finance, 30(3), 811–830.