Essays on Risk Modeling. Applications to Portfolio and Risk Management (summary section only)

In this thesis we deal with the concept of risk. The objective is to bring together and conclude on some normative information regarding quantitative portfolio management and risk assessment. The first essay concentrates on return dependency. We propose an algorithm for classifying markets into rising and falling. Given the algorithm, we derive a statistic: the Trend Switch Probability, for detection of long-term return dependency in the first moment. The empirical results suggest that the Trend Switch Probability is robust over various volatility specifications. The serial dependency in bear and bull markets behaves however differently. It is strongly positive in rising market whereas in bear markets it is closer to a random walk. Realized volatility, a technique for estimating volatility from high frequency data, is investigated in essays two and three. In the second essay we find, when measuring realized variance on a set of German stocks, that the second moment dependency structure is highly unstable and changes randomly. Results also suggest that volatility is non-stationary from time to time. In the third essay we examine the impact from market microstructure on the error between estimated realized volatility and the volatility of the underlying process. With simulation-based techniques we show that autocorrelation in returns leads to biased variance estimates and that lower sampling frequency and non-constant volatility increases the error variation between the estimated variance and the variance of the underlying process. From these essays we can conclude that volatility is not easily estimated, even from high frequency data. It is neither very well behaved in terms of stability nor dependency over time. Based on these observations, we would recommend the use of simple, transparent methods that are likely to be more robust over differing volatility regimes than models with a complex parameter universe. In analyzing long-term return dependency in the first moment we find that the Trend Switch Probability is a robust estimator. This is an interesting area for further research, with important implications for active asset allocation.

Unrealized expectations of jumps in volatility: An explanation to the low and time-varying predictive power of implied volatility

The low predictive power of implied volatility in forecasting the subsequently realized volatility is a well-documented empirical puzzle. As suggested by e.g. Feinstein (1989), Jackwerth and Rubinstein (1996), and Bates (1997), we test whether unrealized expectations of jumps in volatility could explain this phenomenon. Our findings show that expectations of infrequently occurring jumps in volatility are indeed priced in implied volatility. This has two important consequences. First, implied volatility is actually expected to exceed realized volatility over long periods of time only to be greatly less than realized volatility during infrequently occurring periods of very high volatility. Second, the slope coefficient in the classic forecasting regression of realized volatility on implied volatility is very sensitive to the discrepancy between ex ante expected and ex post realized jump frequencies. If the in-sample frequency of positive volatility jumps is lower than ex ante assessed by the market, the classic regression test tends to reject the hypothesis of informational efficiency even if markets are informationally effective.

Snow cover models in operational watershed forecasting

Yhteenveto: Lumimallit vesistöjen ennustemalleissa

Analysts' Accuracy of Estimation and the Relative Trading Volume

This study contributes to the neglect effect literature by looking at the relative trading volume in terms of value. The results for the Swedish market show a significant positive relationship between the accuracy of estimation and the relative trading volume. Market capitalisation and analyst coverage have in prior studies been used as proxies for neglect. These measures however, do not take into account the effort analysts put in when estimating corporate pre-tax profits. I also find evidence that the industry of the firm influence the accuracy of estimation. In addition, supporting earlier findings, loss making firms are associated with larger forecasting errors. Further, I find that the average forecast error increased in the year 2000 – in Sweden.

Indian Ocean Dipole: Processes and impacts

Equatorial Indian Ocean is warmer in the east, has a deeper thermocline and mixed layer, and supports a more convective atmosphere than in the west. During certain years, the eastern Indian Ocean becomes unusually cold, anomalous winds blow from east to west along the equator and southeastward off the coast of Sumatra, thermocline and mixed layer lift up and the atmospheric convection gets suppressed. At the same time, western Indian Ocean becomes warmer and enhances atmospheric convection. This coupled ocean-atmospheric phenomenon in which convection, winds, sea surface temperature (SST) and thermocline take part actively is known as the Indian Ocean Dipole (IOD). Propagation of baroclinic Kelvin and Rossby waves excited by anomalous winds, play an important role in the development of SST anomalies associated with the IOD. Since mean thermocline in the Indian Ocean is deep compared to the Pacific, it was believed for a long time that the Indian Ocean is passive and merely responds to the atmospheric forcing. Discovery of the IOD and studies that followed demonstrate that the Indian Ocean can sustain its own intrinsic coupled ocean-atmosphere processes. About 50% percent of the IOD events in the past 100 years have co-occurred with El Nino Southern Oscillation (ENSO) and the other half independently. Coupled models have been able to reproduce IOD events and process experiments by such models – switching ENSO on and off – support the hypothesis based on observations that IOD events develop either in the presence or absence of ENSO. There is a general consensus among different coupled models as well as analysis of data that IOD events co-occurring during the ENSO are forced by a zonal shift in the descending branch of Walker cell over to the eastern Indian Ocean. Processes that initiate the IOD in the absence of ENSO are not clear, although several studies suggest that anomalies of Hadley circulation are the most probable forcing function. Impact of the IOD is felt in the vicinity of Indian Ocean as well as in remote regions. During IOD events, biological productivity of the eastern Indian Ocean increases and this in turn leads to death of corals over a large area.Moreover, the IOD affects rainfall over the maritime continent, Indian subcontinent, Australia and eastern Africa. The maritime continent and Australia suffer from deficit rainfall whereas India and east Africa receive excess. Despite the successful hindcast of the 2006 IOD by a coupled model, forecasting IOD events and their implications to rainfall variability remains a major challenge as understanding reasons behind an increase in frequency of IOD events in recent decades.

Origin of a trend in ECMWF wind analysis and its objective removal

The suitability of the European Centre for Medium Range Weather Forecasting (ECMWF) operational wind analysis for the period 1980-1991 for studying interannual variability is examined. The changes in the model and the analysis procedure are shown to give rise to a systematic and significant trend in the large scale circulation features. A new method of removing the systematic errors at all levels is presented using multivariate EOF analysis. Objectively detrended analysis of the three-dimensional wind field agrees well with independent Florida State University (FSU) wind analysis at the surface. It is shown that the interannual variations in the detrended surface analysis agree well in amplitude as well as spatial patterns with those of the FSU analysis. Therefore, the detrended analyses at other levels as well are expected to be useful for studies of variability and predictability at interannual time scales. It is demonstrated that this trend in the wind field is due to the shift in the climatologies from the period 1980-1985 to the period 1986-1991.

Forecasting rain for groundnut farmers�how good is good enough

: We illustrate how climatological information about adverse weather events and meteorological forecasts (when available) can be used to decide between alternative strategies so as to maximize the long-term average returns for rainfed groundnut in semi-arid parts of Karnataka, We show that until the skill of the forecast, i.e. probability of an adverse event occurring when it is forecast, is above a certain threshold, the forecast has no impact on the optimum strategy, This threshold is determined by the loss in yield due to the adverse weather event and the cost of the mitigatory measures, For the specific case of groundnut, it is found that while for combating some pests/diseases, climatological information is adequate, for others a forecast of sufficient skill would have a significant impact on the productivity.

Vertical thermal structure of the atmosphere during active and weak phases of convection over the north Bay of Bengal: Observation and model results

Owing to the lack of atmospheric vertical profile data with sufficient accuracy and vertical resolution, the response of the deep atmosphere to passage of monsoon systems over the Bay of Bengal. had not been satisfactorily elucidated. Under the Indian Climate Research Programme, a special observational programme called 'Bay of Bengal Monsoon Experiment' (BOBMEX), was conducted during July-August 1999. The present study is based on the high-resolution radiosondes launched during BOBMEX in the north Bay. Clear changes in the vertical thermal structure of the atmosphere between active and weak phases of convection have been observed. The atmosphere cooled below 6 km height and became warmer between 6 and 13 km height. The warmest layer was located between 8 and 10 km height, and the coldest layer was found just below 5 km height. The largest fluctuations in the humidity field occurred in the mid-troposphere. The observed changes between active and weak phases of convection are compared with the results from an atmospheric general circulation model, which is similar to that used at the National Centre for Medium Range Weather Forecasting, New Delhi. The model is not able to capture realistically some important features of the temperature and humidity profiles in the lower troposphere and in the boundary layer during the active and weak spells.