Robotizing bond portfolio selection on the Russian debt market on the basis of a modified strategy of riding the yield curve

The modern global debt market features historically low average interest rates, convergence of yields on bonds with different maturities, an increase of yield curve inversion emergence frequency and a large-scale trend to automate financial decision making. The researchers’ attention in these fields is mainly focused on designing models that describe the state of the debt market as whole or its individual instruments in particular, as well as on risk management methods. At the same time, the specialized literature offers very few works concerning the topic of computer algorithms for bond portfolio selection based on traditional or advanced investment strategies. The aim of the present research is to create a modification of the existing algorithm of riding the yield curve strategy application, employing, first, average bond yield over the holding period instead of traditional bond yield to maturity; second, a developed algorithm for calculating the market spread on bonds; and, third, alternative risk evaluation indicators (compensation coefficients), which allow us to measure objectively price risk, liquidity risk, transaction costs risk and a general risk. The modification and the development of the algorithm for calculating the market spread were carried out using the direct measurement of the result technique, which entails application of the strategy to the data on bond issues received through the Moscow Exchange API. The selection of financial instruments was conducted in all sectors of the Russian debt market: public bonds, sub-federal and municipal bonds, corporate bonds. The modified algorithm enabled us to get extra yield for each selected bond issue, thereby proving the high effectiveness of the technique compared to the traditional strategy. Software implementation of the algorithm can be integrated into any robotized or semi-robotized stock exchange trading application.

FOREIGN FINANCING, EXCHANGE RATE EXPOSURES AND CORPORATE INVESTMENT IN SINGAPORE

We study the effect of exchange rate fluctuations on foreign corporate investment flows to Singaporean firms using a linear reduced-form empirical specification on data from the past decade. Overall, we find that the cost of debt capital falls on average when the Singapore dollar depreciates. Isolating the effect of exchange rates on US-denominated debt vis-a-vis interest rates and yield curve variables shows that an increase in the cost of foreign debt capital through exchange rate changes leads to lower investment, albeit only slightly and an order of magnitude less important than short-term government bond yields.

Extrapolating Long-Maturity Bond Yields for Financial Risk Measurement

Insurance companies and pension funds have liabilities far into the future and typically well beyond the longest maturity bonds trading in fixed-income markets. Such long-lived liabilities still need to be discounted, and yield curve extrapolations based on the information in observed yields can be used. We use dynamic Nelson-Siegel (DNS) yield curve models to extrapolate risk-free yield curves for Switzerland and several countries. We find slight biases in extrapolated long bond yields of just a few basis points. In addition, the DNS model allows the generation of useful financial risk metrics, such as ranges of possible yield outcomes over projection horizons commonly used for stress-testing purposes. Therefore, we recommend using DNS models as a simple tool for generating extrapolated yields for long-term interest rate risk management. This paper was accepted by Kay Giesecke, finance.

Testing the Dimensionality of Policy Shocks

This paper provides a nonparametric test for deciding the dimensionality of a policy shock as manifest in the abnormal change in asset returns' stochastic covariance matrix, following the release of a macroeconomic announcement. We use high-frequency data in local windows before and after the event to estimate the covariance jump matrix, and then test its rank. We find a one-factor structure in the covariance jump matrix of the yield curve resulting from the Federal Reserve's monetary policy shocks prior to the 2007-2009 financial crisis. The dimensionality of policy shocks increased afterwards due to the use of unconventional monetary policy tools.

A generalized stress correction scheme for the Maxwell elasto-brittle rheology: impact on the fracture angles and deformations

The Maxwell elasto-brittle (MEB) rheology uses a damage parameterization to represent the brittle fracture of sea ice without involving plastic laws to constrain the sea ice deformations. The conventional MEB damage parameterization is based on a correction of super-critical stresses that binds the simulated stress to the yield criterion but leads to a growth of errors in the stress field. A generalized damage parameterization is developed to reduce this error growth and to investigate the influence of the super-critical stress correction scheme on the simulated sea ice fractures, deformations and orientation of linear kinematic features (LKFs). A decohesive stress tensor is used to correct the super-critical stresses towards different points on the yield curve. The sensitivity of the simulated sea ice fractures and deformations to the decohesive stress tensor is investigated in uniaxial compression experiments. Results show that the decohesive stress tensor influences the growth of residual errors associated with the correction of super-critical stresses, the orientation of the lines of fracture and the short-term deformation associated with the damage, but it does not influence the long-term post-fracture sea ice deformations. We show that when ice fractures, divergence first occurs while the elastic response is dominant, and convergence develops post-fracture in the long term when the viscous response dominates – contrary to laboratory experiments of granular flow and satellite imagery in the Arctic. The post-fracture deformations are shown to be dissociated from the fracture process itself, an important difference with classical viscous plastic (VP) models in which large deformations are governed by associative plastic laws. Using the generalized damage parameterization together with a stress correction path normal to the yield curve reduces the growth of errors sufficiently for the production of longer-term simulations, with the added benefit of bringing the simulated LKF intersection half-angles closer to observations (from 40–50 to 35–45∘, compared to 15–25∘ in observations).

Forecasting Commodity Prices Using the Term Structure

The aim of this study is to test the ability of the yield curve on US government bonds to forecast the future evolution in the prices of commodities often used in as raw materials. We consider the monthly prices of nine commodities for more than 30 years. Our findings, confirmed by several parametric and non-parametric tests, are robust and indicate that the ability to forecast future performance changes over time. Specifically, between 1986 and the early 2000s the yield curve was quite successful in forecasting monthly changes in commodity prices, but that success diminished in the period following. One possible explanation for this outcome is the increased flow of capital into the commodity market resulting in stronger correlations with the equity markets and a breakdown of the obvious relationship between commodities and business cycle. Our findings are important for asset pricing, commodity traders and policy makers.

Geopolitical uncertainty and sovereign bond yields of BRICS economies

Purpose The politically unstable economies have high and volatile sovereign spread. The purpose of this paper is to investigate the impact of geopolitical uncertainty on sovereign bond yields. Design/methodology/approach The sovereign yields at various maturities were decomposed into three factors, namely, level, slope and curvature, using the Dynamic Nelson Siegel model. The relationship between geopolitical uncertainty and the yield curve factors was examined using a quantile causality test. Findings The study found that at the extreme high-rate regime, geopolitical uncertainty causes the yield curve factors positively, indicating bond investors demand a higher return for geopolitical uncertainty. On the other hand, during extreme low-rate regime geopolitical causes the short- and medium-term factors negatively. The extreme low-rate regime indicates the period of economic slowdown. During this regime, the central banks try to reduce the short-term rates to stimulate growth. Originality/value This is one of the few papers that investigates the relationship between the geopolitical risk and sovereign bond yields at the various maturities and interest rate regimes. Understanding the relationship between the geopolitical risk and short-term rates would help the central banks the efficacy of their policy actions. The long-term rates are influenced by the global investor preferences; examining the relationship with the long-term rates would help the investors frame the trading strategies.

Forecasting with Macro-Finance Models: Applications to United States and New Zealand

<p>In this thesis, I use macro-finance models to explore the inter-relationships between the macroeconomy and the yield curve in a forecasting setting. Using the arbitrage-free Nelson-Siegel approach to model the yield curve combined with Vector Autoregression (VAR), I jointly model macroeconomic variables and the yield curve factors to produce forecasts of inflation, activity, and interest rates. In line with earlier literature I compare whether the macro-finance model is able to better capture the dynamics of the macro variables and the yield curve factors compared with a macro-only model and a yields-only model respectively. However, a key difference is I use a full real-time forecasting setting, whereas the recent literature focuses on quasi real-time forecasting. I find there is benefit from using macro-finance models for forecasting macroeconomic variables in real-time but the gain is more significant at longer-term horizons. Indeed, the macro-finance models do not outperform traditional macroeconomic models for forecasting activity at short-term horizons. The forecasting gain is more robust for inflation and the policy rate. The theoretically motivated restrictions on the yield curve dynamics improve the forecast performance of yield curve components and generally macroeconomic variables. Using a quasi real-time environment to assess the forecast performance can overstate the usefulness of macro-finance models and understate the usefulness of placing restrictions on the yield curve dynamics.</p>