Narrow Results

Constant maturity swaps (CMS) and CMS spread options are analysed in the multi-factor HJM framework. For Gaussian models, which include a version of the Libor Market Models and the G2++ model, explicit approximated pricing formulae are provided. Two approximating approaches are proposed: an exact solution to an approximated equation and an approximated solution to the exact equation. The first approach borrows from previous literature on other models; the second approach is new. For the latter, the price approximation errors are smaller than in the previous literature and negligible in practice. These approaches are being used here to price standard CMS and CMS spreads and can be used for other European exotic products.

This work evaluates some changes proposed by the Basel Committee on Banking Supervision in regulating capital allocation in the trading book for equities following a company default. In the last decade, the committee designed some measures to account for the risk of a company default that the ten-day value-at-risk measure does not capture. The first and more conservative measure designed to capture the effect of defaults was the incremental risk charge. With time, this measure evolved into the default risk charge. We use a Merton model to compute the probability of default and compare this probability to simulated asset returns in order to compute the one-year value-at-risk and capture the risk of a company default. The analysis compares portfolios of Ibovespa companies and S&P 500 companies. Additionally, we propose a method to account for the correlation in the companies and compare the effects of the standard method of capital allocation to those of our models.

This paper investigates the underlying factors that determine share returns on the Dhaka Stock Exchange. The empirical analysis does not support the critical condition of the Capital Asset Pricing Model of a positive relationship between share return and beta. However, it shows that variables such as size, price to book, volume of shares traded, earnings yield and cash flow yield have a significant influence on share returns. The degree and direction of relationship among the variables are similar to other emerging markets, but are not always consistent with developed markets perhaps due to lack of homogeneous expectations regarding risk return characteristics and different market microstructure.

In time series modeling, one problem is to identify a small number of influential factors to explain variations in the variable of interest. With a vast number of possible factors available, suitable features need to be identified to yield multi-factor models with good explanatory power. In this paper, we propose a novel subset selection method which makes use of the properties in the frequency domain environment. The proposed system ensures key patterns in the target variable be sought and suitable factors be selected based on frequency peaks in common. It can perform well even when the number of factors is significantly greater than the sample size. Moreover, a very important feature of the proposed system is the capability of handling factors with different timeframes, which is lacking in existing methods. We demonstrate the system via several examples with dataset from finance, economic, road traffic and air pollution.

The study on the multiple-curve interest rate models becomes increasingly active since the 2007 credit crunch, for which one curve, typically the OIS curve, is used for discounting purpose, while the LIBOR curves (associated with various market tenors) are used for projecting the future cash flows. In this work, we extend the standard LIBOR market model to accommodate such multiple-curve setting by means of a multiplicative basis. The multiplicative basis is modeled as an exponential function of multi-factor square-root processes. Under the multiplicative basis setup, the OIS forward rates are correlated with the implied (additive) LIBOR-OIS spreads. We then derive closed-form pricing formulas for caplet, swaption, and interest rate futures in the multiplicative basis framework. In particular, we show that the valuation of caplet and swaption can be easily computed by a proper integral of real-valued functions, which facilitates the calibration of our model. Finally, we discuss a slight modification of our model to allow for negative interest rates.

In Zhong (2018), LIBOR market model with multiplicative basis, International Journal of Financial Engineering, 5(2), we proposed a LIBOR market model with multiplicative basis, namely, the LMM-MB model, to model the joint evolution of the LIBOR rates and the OIS forward rates. This model leads to tractable pricing formulas for the standard interest rate derivatives such as the (vanilla) caplet, swaption and futures. In this paper, we study the pricing of some non-standard interest rate derivatives under the LMM-MB model, specifically the in-arrears (IA) cap and the ratchet cap. Similar to the vanilla caplet, we show that the pricing of the IA caplet can be readily computed by a proper integral of real-valued functions. We then derive an analytical approximation for the ratchet cap. In the case of non-zero spread, the ratchet cap can be approximated by using a two-dimensional fast Fourier transform method. In the case of zero spread, the ratchet cap can be computed from a proper integral of a single variable function. Numerical results reveal a good match of our close-form formulas with the Monte Carlo simulation method.