how to integrate risk appetite information to improve price momentum based strategies

8/8/2019 How to Integrate Risk Appetite Information to Improve Price Momentum Based Strategies

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How to integrate Risk Appetite information toimprove Price momentum based strategies

Philippe Dupuy, Ph.D,

Associate Professor

Accounting, Law and Finance

Grenoble Ecole de Management



Momentum strategies

Positions in MSCI-EMU are fully financed at EUR Libor 3-month and reset every week (no capitalization).

Buying assets that have over performed in therecent past.

Jegadeesh and Titman (1993, 2001). Momentumeffects tend to persist across equity styles (Fama -French factors), across international regionalequities.

Based on autocorrelation properties of financialseries

Usual strategies: rank assets according to factors(Beta, P/B, P/E,«) and buy first n quintile versuslast n quintile (quintile might be overlapping)

Also arbitrages between market indices and cashexhibit autocorrelation. Therefore momentumstrategies should work.



Momentum strategies for market index

Momentum strategies for indices perform

poorly.

The performance of the market (the signal)

might be due to size effects (wi), and/or

idiosyncratic risk pricing (ei) which have few to

do with market or systemic momentum and

create noise in the signal.

We apply a methodology to correct this bias

(see Kumar Persaud 2001, Gai Vause 2006

and Dupuy 2009) and calculate a pure ³risk

appetite´ indicator enabling one to implement

momentum strategies on market indices.

Momentum strategies: the signal is the n-week observed return. Positions in MSCI-EMU arefully financed at EUR Libor 3-month and reset every week (no capitalization).



Risk appetite index (RAI)



The concordance coefficientis independent to the sizeand sign of past marketreturns.

The RAI might send a ³buy´signal even in downwardtrending markets.

Similar to high beta-low betasignals but with bounds andidiosyncratic bias removed.

More efficient.

Market return(momentum signal)

Momentum position Risk appetiteposition

S>0

Risk appetiteposition

S<0

Rt-n > 0 Buy Buy Sell

Rt-n < 0 Sell Buy Sell

Risk appetite index (RAI)



Risk appetite based momentum strategies might sell in bull markets and buy in

bear markets. They embark a discrete ³contrarian´ functionality.

Momentum strategies

Delta = (Mom ± RAI). Delta = 0 same signal.Delta = 2 Mom buys, RAI sells. Delta = -2 Mom Sells, RAI buys.



Momentums strategies: risk statistics

Momentum strategies: the signal is the n-week observed return. Risk appetite momentum strategies:the signal is the n-week observed risk appetite. Position in MSCI-EMU are fully financed at EUR Libor 3-month and reset every week (no capitalization).



Momentums strategies: cumulated returns

Momentum strategies (black line): the signal is the n-week observed return. Risk appetite momentum strategies (red line): the signal is the n-week observed risk appetite. Position in MSCI-EMU are fully financed at EUR Libor 3-monthand reset every week (no capitalization).



1. The concordance coefficient might enable one to discern between market

movements that were due to the reassessment of systemic and idiosyncratic risk.

2. The absolute value of the coefficient of concordance is a measure of the frequencyof cross-sectional market movements that were due to systemic risk pricing. This

magnitude lies in between zero and one.

3. Using the concordance coefficient, we are able to generate a series of returns thatwere only due to systemic risk pricing.

the daily return of the market portfolio, R pt , might be decomposed as follow:

R pt = bt R pt + (1 í bt ) R pt

with bt = | S t | and S t the concordance coefficientbt R pt being the share of the daily return due to systemic risk pricing and by difference

(1 í bt ) R pt being the share of the daily return due to specific risk pricing

Time varying returns and Time varying ³systemiconly´ returns



we decompose the weekly return of the MSCI EMU into two components:i. the performance due to systemic risk pricing (bt R pt )ii. the performance due to idiosyncratic risk pricing (1 í bt ) R pt .

This graph shows the change in the weekly returns of the MSCI EMU (black line) and thechange in the estimation of the return of the index that is due to systemic risk pricing, (bt R pt )(red line). The difference between the two series is the weekly return that is due to specific riskre-pricing (1 í bt ) R pt .

Returns and ³systemic only´ returns



2006

2010

Returns and ³systemic only´

returns: in 2006 & 2010



Volatility Feedback Strategy: signals

V olatility feedback hypothesis, Campbell and Hentschel (1992): changes of an index and changes of volatility are positively related on a long term horizon.

Volatility and ³systemic volatilityare centered

Thresholds might be set to signalonly significant shock of ³systemicvolatility´. Hence red signal is often

nil. Late buyer in 2008 for relatively³normal´ amounts.

Nearly no trade in 2010 so far.



Volatility Feedback Strategy: risk statistics

For short-term horizon a strategy based on volatility or a strategy based on ³systemic volatility´ producesimilar risk statistics. This strategy tends to work for long term horizon, at the 12-week horizon, a strategy based on ³systemic volatility´ exhibit better statistics. At the 24-week horizon, returns are negative but a strategy based on ³systemic volatility´ seems to offer better protection. Further work would be data mining.



Conclusion Risk appetite methodologies enable one to discern between returns due to

idiosyncratic risk pricing and systemic risk pricing.

Only the systemic share of the returns offers momentum opportunities

Both momentum and volatility feedback strategies risk statistics might beimproved using RAI.

These strategies offer usually good diversification properties.



References



Annex: Signals are dependant to the returns

ranking period.

Beta are estimated on an equally weighted market return to avoid size effects.



Annex: Signals are independent to the beta

ranking period.

Beta are estimated on an equally weighted market return to avoid size effects.



Annex: Risk appetite indicator over the long term =

the risk cycle

how to integrate risk appetite information to improve price momentum based strategies

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