The CFO’s Information Challenge in Managing Macroeconomic Risk

In this chapter we examine the role of the CFO in setting risk management strategy with respect to macroeconomic risk, in particular, and we consider the information requirements for setting a strategy that is consistent with corporate objectives. We argue that macroeconomic risk management requires a broad approach encompassing financial, operational and strategic considerations. Furthermore, several interdependent sources of risk in the macroeconomic environment must be taken into account. Once this interdependence among, for example, exchange rates, interest rates and inflation are taken into account macroeconomic risk management can be considered a relatively self-contained aspect of Integrated Risk Management (IRM) provided relevant information is available to management. Financial risk management cannot be considered a self-contained part of macroeconomic risk management, however, since value increasing investments in flexibility of business operations affect corporate exposure and make it uncertain.Risk Management Strategy; Macroeconomic Risk; Integrated Risk Management; Chief Financial Officer; Information Needs; Corporate Strategy; Financial Risk; Real Options

Forecasting UK real estate cycle phases with leading indicators: a probit approach

This paper examines the significance of widely used leading indicators of the UK economy for predicting the cyclical pattern of commercial real estate performance. The analysis uses monthly capital value data for UK industrials, offices and retail from the Investment Property Databank (IPD). Prospective economic indicators are drawn from three sources namely, the series used by the US Conference Board to construct their UK leading indicator and the series deployed by two private organisations, Lombard Street Research and NTC Research, to predict UK economic activity. We first identify turning points in the capital value series adopting techniques employed in the classical business cycle literature. We then estimate probit models using the leading economic indicators as independent variables and forecast the probability of different phases of capital values, that is, periods of declining and rising capital values. The forecast performance of the models is tested and found to be satisfactory. The predictability of lasting directional changes in property performance represents a useful tool for real estate investment decision-making

Forecasting UK Real Estate Cycle Phases With Leading Indicators: A Probit Approach

This paper examines the significance of widely used leading indicators of the UK economy for predicting the cyclical pattern of commercial real estate performance. The analysis uses monthly capital value data for UK industrials, offices and retail from the Investment Property Databank (IPD). Prospective economic indicators are drawn from three sources namely, the series used by the US Conference Board to construct their UK leading indicator and the series deployed by two private organisations, Lombard Street Research and NTC Research, to predict UK economic activity. We first identify turning points in the capital value series adopting techniques employed in the classical business cycle literature. We then estimate probit models using the leading economic indicators as independent variables and forecast the probability of different phases of capital values, that is, periods of declining and rising capital values. The forecast performance of the models is tested and found to be satisfactory. The predictability of lasting directional changes in property performance represents a useful tool for real estate investment decision-making.commercial real estate, turning points, leading indicators, probit models

Enhancing the timing of the asset allocation process.

Much of previous research in finance has concentrated on explaining movements of individual securities rather than on explaining movements in the stock market as a whole. Although the available data are more limited than those for individual stocks, the movements in the stock market as a whole are extremely important for movements in individual stocks. Indeed, market events of the past ten years have sparked an interest in tactical asset allocation. The turbulence of October 1987 has only accelerated this interest. This study seeks to develop a methodology that systematically incorporates currently available information into the tactical asset allocation process. The goal of this study is not to predict individual stock prices, or every small movement in the market. Rather we would like to use the currently available data to provide the investor with an estimate of the probabilities associated with the broad measure of either a bullish or bearish market period. Logit analysis is used to determine which of the various timely and readily available data significantly affect the probabilities of bullish and bearish market months. We use the estimated probabilities generated by the logit analysis to suggest the optimal allocation of funds between the risk-free asset and the market portfolio and compare several timing strategies with a buy-and-hold strategy. An Asset allocation strategy based on the probabilities assigned by the logit model outperformed a buy-and-hold strategy by achieving a greater terminal wealth with less variability of returns. We also find that one who used our model would have reduced downside risk and improved average performance over past cycles

Enhancing the Toolbox of Fixed Income Active Portfolio Management

AbstractMany central banks adopt an active investment style for reserve management. This paper discusses various possible enhancements to active management tools and processes to generate extra returns in an increasingly challenging environment. The proposed framework is based on an affine model, which includes macroeconomic and market sentiment indicators among the explanatory variables. Using estimates of expected excess returns drawn from the model, an operational indicator produces input highlighting the portfolio's exposure to duration risk. This indicator is incorporated within a broader framework, in which a scorecard considers a range of qualitative elements, including consensus figures on macroeconomic data, monetary policy and interest rates. These elements are then combined with the model output to produce a comprehensive indication with respect to portfolio deviation from the benchmark. It should be noted that the approach presented in this paper is experimental; it has not yet been used in an active portfolio. Finally, consideration is given to the governance of the central bank investment process in order to assess how the proposed enhancements could strengthen the decision-making process. The analysis suggests that the scorecard with model-based input may address some weaknesses inherent in tactical decision- making.The views expressed herein are solely our own and do not necessarily reflect those of the Bank of Italy or the European System of Central Banks

Investigating emerging market economies Reverse REIT-Bond Yield Gap anomalies: a case for tactical asset allocation under the multivariate Markov regime switching model

Submitted in partial fulfilment of the requirements for the degree of Masters of Management in Finance and Investments In the Faculty of Commerce, Law and Management University of the Witwatersrand, Wits Business School, 2016This paper presents a first time application of a variant of the concepts underpinning the Fed Model, amalgamated with the Bond-Stock Earnings Yield Differential, by applying it to the dividend yields of REIT indices. This modification is termed the yield gap, quantitatively constructed and adapted in this paper as the Reverse REIT-Bond Yield Gap. This metric is then used as the variable of interest in a multivariate Markov regime switching model framework, along with a set of three regressors. The REIT indices trailing dividend yield and associated metrics are the FTSE/EPRA NAREIT series. All data are from Bloomberg Terminals. This paper examines 11 markets, of which the EMEs are classified as Brazil, Mexico, Turkey and South Africa, whereas the advanced market counterparts are Australia, France, Japan, the Netherlands, Singapore, the United Kingdom, and the United States. The time-frame spans the period June 2013 until November 2015 for the EMEs, whilst their advanced market counterparts time-span covers the period November 2009 until November 2015. This paper encompasses a tri-fold research objective, and aims to accomplish them in a scientifically-based, objective and coherent fashion. Specifically, the purpose is in an attempt to gauge the reasons underlying EMEs observed anomalies entailing reverse REIT-Bond yield gaps, whereby their tenyear nominal government bonds out-yield their trailing dividend yields on their associated REIT indices; what drives fluctuations in this metric; and whether or not profitable tactical asset allocation strategies can be formulated to exploit any arbitrage mispricing opportunities. The Markov models were unable to generate clear-cut, definitive reasons regarding why EMEs experience this anomaly. Objectives two and three were achieved, except for France and Mexico. The third objective was also met. The REIT-Bond Yield Gaps static conditions have high probabilities of continuing in the same direction and magnitude into the future. In retrospection, the results suggest that by positioning an investment strategy, taking cognisance of the chain of economic events that are likely to occur following static REIT-Bond Yield Gaps, then investors, portfolio rebalancing and risk management techniques, hedging, targeted, tactical and strategic asset allocation strategies could be formulated to exploit any potential arbitrage profits. The REIT-Bond Yield Gaps are considered highly contentious, yet encompasses the potential for significant reward. The Fed Model insinuates that EME REIT markets are overvalued relative to their respective government bonds, whereas their advanced market counterparts exhibit the opposite phenomenon.XL201

Polls, Coalition Signals, and Strategic Voting: An Experimental Investigation of Perceptions and Effects

The paper investigates how poll information and coalition signals affect strategic voting, defined as casting a vote for a party other than the most preferred party to better influence the election outcome. In particular if the outcome of an election is perceived to be close, voters in multi-party systems with proportional representation and coalition governments should have an incentive to cast a vote for the party that best influences the formation of the next government. The study focuses in particular on voters’ attention to and perception of polls and coalition signals sent by parties before elections. The study used an innovative design that embedded a laboratory experiment in two real election campaigns, allowing the manipulation of poll results and coalition signals in a realistic environment. The findings suggest that political sophistication plays a crucial role for the accurate perception of polls and strategic voting. Coalition signals are found to have a surprisingly strong effect on (apparently) strategic voting.

Resilient Market Timing Strategies For Global Equities

The systemic impact of the global financial crisis of 2008 reveals that there are periods of uncertainty during which most asset classes experience substantial drawdown, rendering diversification an ineffective risk management tool. The desired exposures to risky assets such as stocks, bonds and commodities during these periods of systemic risk should be zero. This paper tests the effectiveness of two market timing strategies that intend to provide early signals for portfolio protection during turbulent times: a filter rule strategy based on the portfolio drawdown (DD) and drawup (DU) thresholds; and an exponential moving average (EMA) strategy based on the crossover of the fast moving average (FMA) and the slow moving average (SMA) of the fund values. The pre-specified market timing strategies are tested on the total return index of the Morgan Stanley Capital International World (MSCI World) Index since the inception of the index in 1997 through 2008. Both the optimal filter rule strategy and the optimal EMA strategy achieve Sharpe ratios that are higher than the Sharpe ratio of the unprotected MSCI World Index. The comparison of the historical risk-return characteristics reveals that the timing of protection is more accurate for the EMA strategy. As is the case for all market timing strategies, the signals provided by the protection mechanism lag the actual economic events. Thus, the market timing strategies tend to be more effective for prolonged economic downturn