Ken Nyholm

Estimating the Probability of Informed Trading

Using a new empirical model, I estimate the probability of trades being generated by privately informed traders. Inference is drawn on a trade-by-trade basis using data samples from the New York Stock Exchange (NYSE). The modeling setup facilitates in-depth analysis of the estimated probability of informed trading at the intraday level and for stocks with different levels of trading activity. The most important empirical results are: (a) the intradaily pattern of the inferred probability of informed trading is highly correlated with the intradaily pattern of observed quoted spreads, (b) differences in the magnitude of quoted spreads across volume categories are not exclusively related to differences in the level of informed trading, and (c) private information is incorporated faster in the quotes for high-volume stocks than in the quotes for low-volume stocks.

Long-horizon yield curve projections: comparison of semi-parametric and parametric approaches

Two methods for evolving forward the yield curve are evaluated and contrasted within a Monte Carlo experiment: one is originally presented by Rebonato et al. (2005) and the other by Bernadell et al. (2005). A detailed account for how to implement the models is also presented. Results suggest that the two techniques are complementary and able to capture important cross-sectional and time-series properties of observed yield curve data. Our results are of interest to practitioners in the financial markets as well as central banks who need accountable and history consistent procedures for generating long-term yield curve forecasts.

Central bank reserves and sovereign wealth management

List of Illustrations Preface Introduction About the Editors Notes on Contributors Dinner Speech: Asset Allocation in a General Equilibrium Framework B.Litterman PART I: CENTRAL BANK RESERVES MANAGEMENT Global Reserves Management K.Rybinski & U.Krynska Conceptual Issues in Central Bank Strategic Asset Allocation A.Joia & J.Coche Strategic Asset Allocation: Balancing Short-Term Liquidity Needs and Real Capital Preservation J.Bonza, N.Gomez & R.Pabon Asset Liability Management for Central Banks U.Kisoen Combating Intervention Risks S.Fisher Reserves Adequacy and Diversification V.Sahakyan & J.Coche PART II: SOVEREIGN WEALTH MANAGEMENT Asset Allocation and Portfolio Construction for Sovereign Wealth Managers F.Weinberger, B.Lee & D.Rogal A Note on Portfolio Choice for Sovereign Wealth Funds B.Scherer Portfolio Choice for Oil Based Sovereign Wealth Funds B.Scherer Strategic Investment and Risk Management for Sovereign Wealth Funds S.Claessens & J.Kreuser Optimal Scale and Asset Allocation for SWF: Chinas Case Y.Zhang, X.Wei& Y.Hou The Impact of Sovereign Wealth Funds on Global Financial Markets M.Fidora & R.Beck Public Investment Funds and Value-Based Generational Accounting R.Molenaar, R.Hoevenaars & E.Ponds Notes Bibliography Appendix Index

Risk Management for Central Banks and Other Public Investors: Strategic asset allocation for fixed-income investors

Introduction The goal of strategic asset allocation (SAA) is to find an optimal allocation of funds across different asset classes subject to a relatively long investment horizon. The optimal allocation of funds should always reflect the risk–return preferences of an institution and the machinery underlying the strategic asset allocation decisions should be based on a transparent and accountable process with which such allocations can be determined and reviewed at regular intervals. Often ‘modern portfolio theory’ is presented following Markowitz (1959) and Sharpe (1964) in the context of the Capital Asset Pricing Model (CAPM) and mean-variance portfolio analysis as the basic theory for how equity markets behave in equilibrium and how investors should position themselves on the efficient frontier, depending on their risk aversion. This theory is central to the understanding of modern finance and thus important for students and market practitioners alike. However, when it comes to actual portfolio allocation decisions and the practical implementation of portfolio allocation decisions in public and private investment organizations the CAPM leaves, quite understandably, many questions unanswered. It is some of these missing answers that the present chapter aims at addressing. In doing so, the viewpoint of a strategic investor is taken; however, elements relevant for tactical asset allocation and portfolio managers are also touched upon. In particular, the focal point of the exposition is that of a central banks reserves management. This perspective naturally narrows the investment universe considerably.

A Rotated Dynamic Nelson-Siegel Model: A Rotated Dynamic Nelson-Siegel Model

I show how to rotate the factor structure of the well†known Dynamic Nelson†Siegel yield†curve model to enable direct parametrization of the short rate process. This makes it easy to calculate model†implied term premia and to integrate macroeconomic variables into the model in a Taylor†rule†type fashion.

A Spread-Risk Model for Strategic Fixed-Income Investors

Surprisingly little attention has been paid in the academic literature to the forecasting of credit spreads1. Although this is understandable, and in line with traditional academic progression where one aims to fully understand the in-sample behaviour of a phenomenon before starting to develop theories and models for how this phenomenon could behave out-of-sample, it leaves the financial practitioner in an unpleasant vacuum.