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(2019)
Forecast ranked tailored equity portfolios, (with Cord Stern)
Journal of International Financial Markets, Institutions and Money,
63, 101138.
Show Abstract
We use a dynamic model averaging (DMA) approach to construct forecasts of individual
equity returns for a large cross-section of stocks contained in the SP500, FTSE100, DAX30,
CAC40 and SPX30 headline indices, taking value, momentum, and quality factors as predictor
variables. Fixing the set of ‘forgetting factors’ in the DMA prediction framework,
we show that highly significant return forecasts relative to the historic average benchmark
are obtained for 173 (281) individual equities at the 1% (5%) level, from a total of 895 stocks.
These statistical forecast improvements also translate into considerable economic gains,
producing out-of-sample R2 values above 5% (10%) for 283 (166) of the 895 individual stocks.
Equally weighted long only portfolios constructed from a ranking of the best 25% forecasts
in each headline index can generate sizable returns in excess of a passive investment strategy
in that index itself, even when transaction costs and risk taking are accounted for.
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(2019)
Identification and Estimation issues in Exponential Smooth Transition Autoregressive Models,
Oxford Bulletin of Economics and Statistics,
81(3), 667-685.
(Online Appendix, 5.19MB).
Show Abstract
Exponential smooth transition autoregressive (ESTAR) models are widely used in the
international finance literature, particularly for the modelling of real exchange rates. We
show that the exponential function is ill-suited as a regime weighting function because of
two undesirable properties. Firstly, it can be well approximated by a quadratic function
in the threshold variable whenever the transition function parameter γ, which governs
the shape of the function, is ‘small’. This leads to an identification problem with respect
to the transition function parameter and the slope vector, as both enter as a product
into the conditional mean of the model. Secondly, the exponential regime weighting
function can behave like an indicator function (or dummy variable) for very large values
of the transition function parameter γ. This has the effect of ‘spuriously overfitting’ a
small number of observations around the location parameter µ. We show that both of
these effects lead to estimation problems in ESTAR models. We illustrate this by means
of an empirical replication of a widely cited study, as well as a simulation exercise.
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(2017)
The Role of Jumps and Leverage in Forecasting Volatility in International Equity Markets, (with Katja Gisler)
Journal of International Money and Finance,
79(December), 1-19.
(Online Appendix, 1.85MB).
Show Abstract
We analyse the importance of jumps and the leverage effect on forecasts of realized
volatility in a large cross-section of 18 international equity markets, using daily realized
measures data from the Oxford-Man Realized Library, and two widely employed empirical
models for realized volatility that allow for jumps and leverage. Our out-of-sample forecast
evaluation results show that the separation of realized volatility into a continuous and a
discontinuous (jump) component is important for the S&P 500, but of rather limited value for
the remaining 17 international equity markets that we analyse. Only for 6 equity markets
are significant and sizable forecast improvements realized at the one-step-ahead horizon,
which, nevertheless, deteriorate quickly and abruptly as the prediction horizon increases.
The inclusion of the leverage effect, on the other hand, has a much larger impact on all 18
international equity markets. Forecast gains are not only highly significant, but also sizeable,
with gains remaining significant for forecast horizons of up to one month ahead.
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(2017)
Macroeconomic Factors and Equity Premium Predictability, (with Martin Tischhauser)
International Review of Economics and Finance,
51(September), 621-644.
(Data, 1.07MB).
Show Abstract
Neely et al. (2014) have recently demonstrated how to efficiently combine information
from a set of popular technical indicators together with the standard Goyal and Welch (2008)
predictor variables widely used in the equity premium forecasting literature to improve out-
of-sample forecasts of the equity premium using a small number of principal components.
We show that forecasts of the equity premium can be further improved by, first, incorporating
broader macroeconomic data into the information set, second, improving the selection
of the most relevant factors and combining the most relevant factors by means of a forecast
combination regression, and third, imposing theoretically motivated positivity constraints
on the forecasts of the equity premium. Applying standard out-of-sample forecast evaluation
tests, we find that in particular our proposed forecast combination approach, which
combines forecasts of the most relevant Neely et al. (2014) and macroeconomic factors and
further imposes positivity constraints on the equity premium forecasts, generates statistically
significant and economically sizable improvements over the best performing model of
Neely et al. (2014). Out-of-sample R2 values can be as high as 1.75%, with (annualised) gains
in certainty equivalent returns of up to 3.35%, relative to the ALL factors forecasts of Neely
et al. (2014).
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(2017)
Measuring the Output Gap in Switzerland with Linear Opinion Pools, (with Oliver Müller)
Economic Modelling,
64(August), 163-171.
(Data, 100KB).
Show Abstract
We use the recently proposed linear opinion pool methodology of Garratt et
al. (2014) to construct real-time ensemble nowcast densities of the output
gap for Switzerland over an out-of-sample period from 2003:Q1 to 2015:Q4.
The model space consists of a large number of bivariate VAR specifications
for inflation and the output gap, with each specification using a different
estimate of the output gap, lag order in the VAR, and structural break
information. The ensemble nowcast densities for the output gap are
constructed by combining the predictive densities of the individual VAR
specifications, weighted by their ability to provide accurate density
forecasts for inflation. The overall performance of the linear opinion pool
is assessed by its real-time output gap nowcasts and by the size of the ex
post revisions to the output gap nowcasts. We find that the linear opinion
pool does not produce any more accurate density or point forecasts of
inflation than a number of simple univariate benchmark models that condition
on the same structural break information. Further, the linear opinion pool’s
real-time estimate of the output gap is no more robust to ex post re visions
than the real-time estimates of the individual univariate output gaps. The
fact that Swiss GDP price deflator data are subject to large revisions,
complicates the measurement and forecasting of inflation.
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(2016)
The Term Structure of Interest Rates in an estimated New Keynesian Policy Model, (with Philipp Lentner)
Journal of Macroeconomics,
50(December), 126-150.
Show Abstract
We jointly estimate a New Keynesian Policy Model with a Gaussian affine
no-arbitrage specification of the term structure of interest rates, and assess
how important inflation, output and monetary policy shocks are as sources of
fluctuations in interest rates and the term premium. We work with observable
pricing factors and utilize the computationally convenient normalization of
Joslin et al. (2013b). This allows us to estimate the model without needing to
restrict the parameters driving the market prices of risk. Using data for the
U.S. from 1962:Q1 to 2014:Q2, we find that inflation and the output gap account
for around 80% of the unconditional forecast error variance of bond yields at
the short and medium end of the term structure, while monetary policy shocks
account for around 20%. Bond yields respond to macroeconomic shocks only
gradually, peaking after about 4 quarters. This is due to sizable monetary
policy inertia estimates in our model. At the peak of the response, inflation
shocks increase bond yields by more than one-to-one, and output shocks by less
than one-to-one, which is consistent with a Taylor type monetary policy rule.
Our term premium estimate is strongly counter-cyclical and can capture salient
features of the term structure that constitute a puzzle in the expectations
hypothesis.
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(2016)
Global Equity Market Volatility Spillovers: A Broader Role for the United States, (with Katja Gisler)
International Journal of Forecasting,
32(4), 1317–1339.
Show Abstract
Rapach et al. (2013) have recently shown that U.S. equity market returns carry valuable
information to improve return forecasts in global equity markets. In this study, we extend
the work of Rapach et al. (2013) and examine if U.S. based equity market information can be
used to improve realized volatility forecasts in a large cross-section of international equity
markets. We use volatility data for the U.S. and 17 foreign equity markets from the Oxford
Man Institute’s realized library and augment for each foreign equity market our benchmark
HAR model with U.S. equity market volatility information. We show that U.S. equity market
volatility information substantially improves out-of-sample forecasts of realized volatility in
all 17 foreign equity markets that we consider. Forecast gains are not only highly significant,
but produce out-of-sample R2 values between 4.56% and 14.48%, with 12 of these being
greater than 10%. The improvements in out-of-sample forecasts remain statistically significant
for horizons up to 1 month ahead. A substantial part of the predictive gains are driven
by forward looking volatility as captured by the VIX.
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(2016)
Heterogeneous Agents, the Financial Crisis and Exchange Rate Predictability, (with Gion Donat Piras)
Journal of International Money and Finance,
60(February), 313–359.
(Data, 1.71MB).
Show Abstract
We construct an empirical heterogeneous agent model which optimally combines
forecasts from fundamentalist and chartist agents and evaluates its out-of-
sample forecast performance using daily data covering an overall period from
January 1999 to June 2014 for six of the most widely traded currencies. We use
daily financial data such as level, slope and curvature yield curve factors,
equity prices, as well as risk aversion and global trade activity measures in
the fundamentalist agent’s predictor set to obtain a proxy for the market’s view
on the state of the macroeconomy. Chartist agents rely upon standard momentum,
moving average and relative strength index technical indicators in their
predictor set. Individual agent specific forecasts are constructed using a
flexible dynamic model averaging framework and are then aggregated into a model
combined forecast using a forecast combination regression. We show that our
empirical heterogeneous agent model produces statistically significant and
sizable forecast improvements over a random walk benchmark, reaching out-of-
sample R2 values of 1.41, 1.07, 0.99 and 0.74 percent at the daily one-step
ahead horizon for 4 out of the 6 currencies that we consider. Forecast gains
remain significant for horizons up to three-days ahead. The forecast
improvements are largely realised before and around the time of the Lehman
Brothers collapse. We show further that our model combined forecasts produce
economic value to a mean variance investor, yielding annualized Sharpe ratios of
around 0.89 and annualized performance fees in excess of 460 basis points.
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(2015)
Forecasting Copper Prices with Dynamic Averaging and Selection Models, (with Carlo Moretto)
North American Journal of Economics and Finance,
33(1), 1–38.
(Online Appendix, 276KB).
Show Abstract
We use data from the London Metal Exchange (LME) to forecast monthly copper
returns using the recently proposed dynamic model averaging and selection
(DMA/DMS) framework, which incorporates time varying parameters as well as
model averaging and selection into one unifying framework. Using a total of
18 predictor variables that include traditional fundamental indicators such
as excess demand, inventories and the convenience yield, as well as
indicators related to global risk appetite, momentum, the term spread, and
various other financial series, we show that there exists a considerable
predictive component in copper returns. Covering an out-of-sample period
from May 2002 to June 2014 and employing standard statistical evaluation
criteria we show that the out-of-sample R2 (relative to a random walk
benchmark) can be as high as 18.5 percent for the DMA framework. Time series
plots of the cumulative mean squared forecast errors and time varying
coefficients show further that firstly, a large part of the improvement in
the forecasts is realised during the peak of the financial crisis period at
the end of 2008, and secondly that the importance of the most relevant
predictor variables has changed substantially over the out-of-sample period.
The coefficients of the SP500, the VIX, the yield spread, the TED spread,
industrial production and the convenience yield predictors are most heavily
affected, with the TED spread and yield spread coefficients even changing
signs over this period. Our predictability results remain valid for forecast
horizons up to 6 months ahead, but are weaker and smaller than at the one
month horizon.
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(2015)
Measuring Fund Style, Performance and Activity: A New Style Profiling Approach, (with Robert Hill and Jon Eggins)
Accounting and Finance,
55(1), 29–55.
Show Abstract
We construct new measures of fund style, performance and activity from linear combinations
of off-the-shelf stock-market indices. A fund's benchmark portfolio is a linear
combination of two or more reference portfolios that in a least-squares sense most closely
approximates the fund's portfolio. The resulting linear combination scalar is itself a
measure of fund style, and the distance between a fund and its benchmark is a measure
of fund activity. Our approach has a number of advantages over existing characteristic
matching methods. We illustrate our approach using a data set of US institutional
funds.
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(2014)
Equilibrium Credit: The Reference Point for Macroprudential Supervisors, (with Martin Melecky)
Journal of Banking and Finance,
41(4), 135–154.
(Addon Material, 249KB).
Show Abstract
Equilibrium credit is an important concept because it helps to identify excessive credit
provision in an economy. This paper proposes a structural approach to determine equilibrium
credit which is based on the long-run through-the-cycle transaction demand for credit.
Using a panel data set consisting of 49 high and middle-income countries from 1980 2010,
we show that there exists considerable variation in the cross-country estimates of the income
and price elasticities of credit and that the unit elasticity restriction implicitly imposed
by the credit-to-GDP ratio is strongly rejected by the data. This suggests that the credit-to-GDP
ratio is not appropriate to measure equilibrium credit. We show further that the
cross-sectional variation in the income and price elasticities of credit can be related to a
set of relevant economic, financial and institutional development indicators of a country.
The main determinants that explain the cross-sectional variation in the income and price
elasticities are financial depth, access to financial services, use of capital markets, efficiency
and funding of domestic banks, central bank independence, the degree of supervisory integration,
and the experience of a financial crisis. As an empirical illustration, we compute
equilibrium credit and credit gaps for eleven new EU member states using our structural
framework and compare it to credit gaps based on the Basel III approach.
-
(2013)
Macroprudential Stress Testing of Credit Risk: A Practical Approach for Policy Makers, (with Martin Melecky)
Journal of Financial Stability,
9(3), 347–370.
Show Abstract
Drawing on the lessons from the global financial crisis and especially from
its impact on the banking systems of Eastern Europe, the paper proposes a
new practical approach to macroprudential stress testing. The proposed
approach incorporates: (i) macroeconomic stress scenarios generated from
both a country specific statistical model and historical cross-country
crises experience; (ii) indirect credit risk due to foreign currency
exposures of unhedged borrowers; (iii) varying underwriting practices across
banks and their asset classes based on their relative aggressiveness of
lending; (iv) higher correlations between the probability of default and the
loss given default during stress periods; (v) a negative effect of lending
concentration and residual loan maturity on unexpected losses; and (vi) the
use of an economic risk weighted capital adequacy ratio as the relevant
outcome indicator to measure the resilience of banks to materialising credit
risk. We apply the proposed approach to a set of Eastern European banks and
discuss the results.
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(2012)
Understanding forecast failure of ESTAR models of real exchange rates,
Empirical Economics,
34(1), 399-426.
(Data, 56KB).
Show Abstract
The forecast performance of the empirical ESTAR model of Taylor, Peel and Sarno
(2001) is examined for 4 bilateral real exchange rate series over an out-of-sample evaluation
period of nearly 12 years. Point as well as density forecasts are constructed,
considering forecast horizons of 1 to 22 steps head. The study finds that no forecast
gains over a simple AR(1) specification exist at any of the forecast horizons that are
considered, regardless of whether point or density forecasts are utilised in the evaluation.
Non-parametric methods are used in conjunction with simulation techniques
to learn about the models and their forecasts. It is shown graphically that the nonlinearity
in the point forecasts of the ESTAR model decreases as the forecast horizon
increases. The non-parametric methods show also that the multiple steps ahead forecast
densities are normal looking with no signs of bi-modality, skewness or kurtosis.
Overall, there seems little to be gained from using an ESTAR specification over a simple
AR(1) model.
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(2010)
The impact of ECB monetary policy decisions and communication on the yield curve, (with Claus Brand and Jarkko Turunen)
Journal of the European Economic Association,
8(6), 1266–1298.
Show Abstract
We use intraday changes in money market rates to construct indicators of news
about monetary policy stemming separately from policy decisions and from official
communication of the ECB, and study their impact on the yield curve. We show that
communication may lead to substantial revisions in expectations of monetary policy
and at the same time exerts a significant impact on interest rates at longer maturities.
Thereby, the maturity response pattern to communication is hump-shaped, while that
of policy decisions is downward sloping.
-
(2008)
An estimated New Keynesian Policy Model for Australia, (with Martin Melecky)
The Economic Record,
84(264), 1-16.
(Additional Notes, 259KB).
Show Abstract
An open economy New Keynesian policy model for Australia is estimated in this
study. We investigate how important external shocks are as a source of macroeconomic
fluctuations when compared to domestic ones. The results of our analysis suggest that
the Australian business cycle and domestic inflation are most affected by domestic demand
and supply shocks, respectively. However, domestic output also appears to be
strongly affected by foreign demand shocks, and domestic inflation by exchange rate
shocks. Domestic variables do not seem to be significantly affected by foreign supply
and monetary policy shocks.
-
(2006) Bootstrap causality tests of the relationship between the equity markets of the U.S. and
other developed countries: Pre- and post-September 11, (with Eduardo Roca and Abdulnasser Hatemi-J),
Journal of Applied Business Research,
22(3), 65-74.
Show Abstract
We analyse the causal relationship between the equity markets of the US and those of the UK, Japan, Germany,
France, Canada and Australia based on leveraged bootstrap approach developed by Hacker and Hatemi-J (2005).
This method overcomes problems of non normalities and ARCH effects in the data. Using weekly MSCI price indices,
we focus our investigation on the period 1998 to 2005 which we divided into two sub-periods to take into
account the potential structural break arising from September 11. Our results show that before September 11,
there was bi-directional causality between the US and Japan and between the US and Germany. In addition,
there was also a uni-directional causality from the US to Canada and from the US to France. After September
11, the only causality was a unidirectional one from the US to Japan and from the UK to the US. Thus, after
September 11, the US Granger-caused a fewer number of markets. This could imply that after September 11,
the other markets became more efficient in responding to information transmitted from the US market.
-
(2005) The extent and stability of long-run relationships between stock prices: Evidence from the U.S.,
the U.K. and Australia, (with Eduardo Roca),
Investment Management and Financial Innovations,
2(4), 80-94.
Show Abstract
We examine whether a significant long-run relationship between the US, UK and Australian stock market
prices exists and whether this relationship is temporally stable, based on the use of cointegration
methodology as applied to the period of 1984 to 2001. We. find a stationary long-run relationship between
the UK and US, but not between the Australian and US, and Australian and UK, markets. Our results further
reveal that the UK-US relationship was impacted by two structural shocks - the October 1987 stock market
crash and the 1993-1994 US bond market crash. This relationship was stable during the period before the
October 1987 crash and remained to be so after this period until it was disrupted by the 1993-1994 US bond
market crash. During the period starting after 1994 up to 2001, this relationship between the UK and US
markets, however, ceased to exist. Thus, for investors with UK and US stocks in their portfolios, there
was no need for re-balancing of their portfolio during the periods of 1984 to 1993 but this had to be
done after 1994.
-
(2002) Equity market price interdependence between Australia and the Asian Tigers, (with Eduardo Roca),
International Journal of Business Studies,
10(2), 61-74.
Show Abstract
The study investigates the extent and structure of long-term and short-term price interaction between the
equity markets of Australia and the Asian Tigers - Hong Kong, Korea, Singapore and Taiwan, taking into
account the Asian financial crisis. It applies cointegration and generalised variance decomposition and
impulse response analyses using MSCI price index data. No significant long-term relationship between
Australia and the Asian Tigers is found both before and after the Asian crisis. No significant short-term
relationship is also found during the period before the crisis. However, after the crisis, the study finds
Australia to be significantly interdependent with Hong Kong and Singapore.