Testing for volatility persistence change: The effect of the credit crisis on the Portuguese banks

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Crashes, volatility, and the equity premium: Lessons from S&P 500 options

We use a novel pricing model to imply time series of diffusive volatility and jump intensity from S&P 500 index options. These two measures capture the ex ante risk assessed by investors. Using a simple general equilibrium model, we translate the implied measures of ex ante risk into an ex ante risk premium. The average premium that compensates the investor for the ex ante risks is 70% higher than the premium for realized volatility. The equity premium implied from option prices is shown to significantly predict subsequent stock market returns.

Are one factor logarithmic volatility models useful to fit the features of financial data? An application to microsoft data.

This paper provides empirical evidence that continuous time models with one factor of volatility, in some conditions, are able to fit the main characteristics of financial data. It also reports the importance of the feedback factor in capturing the strong volatility clustering of data, caused by a possible change in the pattern of volatility in the last part of the sample. We use the Efficient Method of Moments (EMM) by Gallant and Tauchen (1996) to estimate logarithmic models with one and two stochastic volatility factors (with and without feedback) and to select among them.

Forecasting volatility using a continuous time model

This paper evaluates the forecasting performance of a continuous stochastic volatility model with two factors of volatility (SV2F) and compares it to those of GARCH and ARFIMA models. The empirical results show that the volatility forecasting ability of the SV2F model is better than that of the GARCH and ARFIMA models, especially when volatility seems to change pattern. We use ex-post volatility as a proxy of the realized volatility obtained from intraday data and the forecasts from the SV2F are calculated using the reprojection technique proposed by Gallant and Tauchen (1998).

Well-posedness and invariant measures for HJM models with deterministic volatility and Lévy noise

We give sufficient conditions for existence, uniqueness and ergodicity of invariant measures for Musiela's stochastic partial differential equation with deterministic volatility and a Hilbert space valued driving Lévy noise. Conditions for the absence of arbitrage and for the existence of mild solutions are also discussed.

Stock market volatility and learning

Introducing bounded rationality in a standard consumption-based asset pricing model with time separable preferences strongly improves empirical performance. Learning causes momentum and mean reversion of returns and thereby excess volatility, persistence of price-dividend ratios, long-horizon return predictability and a risk premium, as in the habit model of Campbell and Cochrane (1999), but for lower risk aversion. This is obtained, even though our learning scheme introduces just one free parameter and we only consider learning schemes that imply small deviations from full rationality. The findings are robust to the learning rule used and other model features. What is key is that agents forecast future stock prices using past information on prices.

Can a Lucas model with habit generate realistic conditional volatility in exchange rate returns?

In this paper, we attempt to give a theoretical underpinning to the well established empirical stylized fact that asset returns in general and the spot FOREX returns in particular display predictable volatility characteristics. Adopting Moore and Roche s habit persistence version of Lucas model we nd that both the innovation in the spot FOREX return and the FOREX return itself follow "ARCH" style processes. Using the impulse response functions (IRFs) we show that the baseline simulated FOREX series has "ARCH" properties in the quarterly frequency that match well the "ARCH" properties of the empirical monthly estimations in that when we scale the x-axis to synchronize the monthly and quarterly responses we find similar impulse responses to one unit shock in variance. The IRFs for the ARCH processes we estimate "look the same" with an approximately monotonic decreasing fashion. The Lucas two-country monetary model with habit can generate realistic conditional volatility in spot FOREX return.

IInflation and Globalisation: A Dynamic Factor Model with Stochastic Volatility

National inflation rates reflect domestic and international (regional and global) influences. The relative importance of these components remains a controversial empirical issue. We extend the literature on inflation co-movement by utilising a dynamic factor model with stochastic volatility to account for shifts in the variance of inflation and endogenously determined regional groupings. We find that most of inflation variability is explained by the country specific disturbance term. Nevertheless, the contribution of the global component in explaining industrialised countries’ inflation rates has increased over time.

Inflation Uncertainty, Exchange Rate Depreciation and Volatility: Evidence from Ghana, Mozambique and Tanzania

While flexible exchange rates facilitate stabilisation, exchange rate fluctuations can cause real volatility. This gives policy importance to the causal relationship between exchange rate depreciation and its volatility. An exchange rate may be expected to become more volatile when the underlying currency loses value. We conjecture that a reverse causation, which further weakens the currency, may be mitigated by price stability. Data from Ghana, Mozambique and Tanzania support this: depreciation makes exchange rate more volatile for all but volatility does not causes depreciation in Tanzania which has enjoyed a more stable inflation despite all countries adopting similar macro-policies since early 1990s.

Volatility of Housing

The aim of the project is to develop a theoretical framework where homelessness arises due to various economic and social factors that vary over time. The ultimate goal is i) to understand whether homelessness spells, entrances and exits could be predicted and if so what information is necessary; and ii) to design and evaluate a homelessness prevention programme in a changing and uncertain environment. Examples of the questions we want to answer are: Should it be made easier for people to borrow money so that they can get out of homelessness, or will such borrowing allow people to over-consume today and so fall into homelessness tomorrow? Should precautionary savings be encouraged so that people have cushions to withstand future shocks, or will savings just delay entry into homelessness? What interventions will affect the probability of becoming homeless and how will they affect behaviour? How will interventions affect incentives to save and to consume before homelessness prevention programmes kick in?

The rise and fall of piecework–timework wage differentials: market volatility, labor heterogeneity, and output pricing

Based on detailed payroll data of blue collar male and female labor in Britain’s engineering and metal working industrial sectors between the mid-1920s and mid-1960s, we provide empirical evidence in respect of several central themes in the piecework-timework wage literature. The period covers part of the heyday of pieceworking as well as the start of its post-war decline. We show the importance of relative piece rate flexibility during the Great Depression as well as during the build up to WWII and during the war itself. We account for the very significant decline in the differentials after the war. Labor market topics include piecework pay in respect of compensating differentials, labor heterogeneity, and the transaction costs of pricing piecework output.

Revisiting Shiller’s excess volatility hypothesis

One of the cornerstone of financial anomalies is that there exists money making opportunities. Shiller’s excess volatility theory is re-investigated from the perspective of a trading strategy where the present value is computed using a series of simple econometric models to forecast the present value. The results show that the excess volatility may not be exploited given the data available until time t. However, when learning is introduced empirically, the simple trading strategy may offer profits, but which are likely to disappear once transaction costs are considered.

Revisiting Shiller’s excess volatility hypothesis

One of the cornerstone of financial anomalies is that there exists money making opportunities. Shiller’s excess volatility theory is re-investigated from the perspective of a trading strategy where the present value is computed using a series of simple econometric models to forecast the present value. The results show that the excess volatility may not be exploited given the data available until time t. However, when learning is introduced empirically, the simple trading strategy may offer profits, but which are likely to disappear once transaction costs are considered.

Volatility smile extrapolation with an artificial neural network

I use a multi-layer feedforward perceptron, with backpropagation learning implemented via stochastic gradient descent, to extrapolate the volatility smile of Euribor derivatives over low-strikes by training the network on parametric prices.