LIMITATIONS OF VALUE-AT-RISK (VAR) FOR BUDGET ANALYSIS

Value-at-risk (VaR) is increasingly being applied to problems in agriculture, especially valuation of crop insurance and agricultural lending risk exposure. VaR conveys the probability that losses exceeding a threshold will likely occur within a specified timeframe. However, it does not provide the expected value of losses, should they happen. When determining risk exposure for budget analysis, this latter amount is of keen interest. Expected tail loss (ETL) methods are developed and compared with VaR.Risk, Value-at-Risk, Expected Tail Loss, crop insurance, loan loss, Agricultural Finance, Risk and Uncertainty,

Empirical studies in corporate credit modelling; liquidity premia, factor portfolios & model uncertainty

Insurers match the cash flows of typically illiquid insurance liabilities, such as in-force annuities, with government and corporate bonds. As they intend to buy corporate bonds and hold them to maturity, they can capture the value attached to liquidity, without running the market liquidity risk that is associated with having to sell bonds in the open market. During the long consultation period dedicated to the mark-to-market valuation of insurance assets and liabilities for the Solvency II regulatory framework, CEIOPS noted the importance of the accurate breakdown of the credit spread into its components, most notably the credit and non-credit (i.e. liquidity) components. In this thesis we review many modelling efforts to isolate the liquidity premium and propose a reduced-form modelling approach that relies on a new, relative liquidity proxy. Challenging the status quo when it comes to active and passive investment strategies, products and funds, Exchange Traded Funds and `smart-beta' products provide investors with straightforward ways to strategically expose a portfolio to risk drivers, raising the bar for traditional investment funds and managers. In this thesis, we investigate how traditional sources of equity outperformance (alpha), such as small caps, low volatility and value, translate to UK corporate bonds. For automated trading strategies in corporate bonds, and those with specific factor exposure requirements in particular, transaction costs, rebalancing and an optimal turnover strategy are crucial; these aspects of building factor portfolios are explored for the UK market. Since the financial crisis, mathematical models used in finance have been subject to a fair amount of criticism. More than ever has this highlighted the need of better risk management of financial models themselves, leading to a surge in `model validation' roles in industry and an increased scrutiny from regulatory bodies. In this thesis we look at stochastic credit models that are commonly used by insurers to project forward credit-risky bond portfolios and the model uncertainty and parameter risk that arises as a result of relying on published credit migration matrices. Specifically, our investigation focuses on two violations of the Markovian process that credit transitions are assumed to follow and statistical uncertainty of the migration matrix

Equity Premium: - Does it exist? Evidence from Germany and United Kingdom

Malkiel and Xu (1997) state that idiosyncratic volatility is highly correlated with size and that it plays a powerful role in explaining expected returns. In this paper we ask (a) whether idiosyncratic volatility is useful in explaining the variation in expected returns; and, (b) whether our findings can be explained by the turn of the year effect. We find that (a) our three-factor model provides a better description of expected returns than the CAPM. That is, we find that firm size and idiosyncratic volatility are related to security returns. In addition, we also find that our findings are robust throughout the sample period. We show that the CAPM beta alone is not sufficient to explain the variation in stock returns.Idiosyncratic Volatility, Size Effect, CAPM, Risk Premia

Personal Taxation, Portfolio Choice and The Effect of the Corporation Income Tax

Extending the traditional treatment of the corporate tax to an economy with a progressive personal tax fundamentally changes the analysis. While the corporate tax system (CTS) does increase the total tax rate on corporate source income for some investors, the exclusion of retained earnings implies that the CTS lowers the tax rate for high-income investors. Analyzing such an economy requires replacing the traditional "equal-yield" equilibrium condition with a more general portfolio balance model. In this model, introducing a CTS can actually increase the corporate share of the capital stock even though the relative tax rate on corporate income rises.

Default Risk Premia and Asset Returns

We identify a common default risk premia (DRP) factor in the risk-adjusted excess returns on pure default-contingent claims. Asset pricing tests using almost 50 corporate bond portfolios sorted on rating, maturity or industry suggest that the DRP factor is priced in the corporate bond market. For index put option portfolios sorted on maturity and moneyness, both average returns and DRP beta estimates become more negative with decreasing time to maturity. There is little to no evidence of the DRP factor being priced in equity markets. Most of the variation in DRP is explained by the portion DRP^{JtD} due to common jump-to-default risk premia. A theoretical framework where DRP^{JtD} is part of the pricing kernel supports our empirical findings.

Towards quantification of condition monitoring benefit for wind turbine generators

Condition monitoring systems are increasingly installed in wind turbine generators with the goal of providing component-specific information to the wind farm operator and hence increase equipment availability through maintenance and operating actions based on this information. In some cases, however, the economic benefits of such systems are unclear. A quantitative measure of these benefits may therefore be of value to utilities and O&M groups involved in planning and operating wind farm installations. The development of a probabilistic model based on discrete-time Markov Chain solved via Monte Carlo methods to meet these requirements is illustrated. Potential value is demonstrated through case study simulations

Credit Risk Models for Managing Bank’s Agricultural Loan Portfolio

In this paper, we have developed a credit scoring model for agricultural loan portfolio of a large Public Sector Bank in India and suggest how such model would help the Bank to mitigate risk in Agricultural lending. The logistic model developed in this study reflects major risk characteristics of Indian agricultural sector, loans and borrowers and designed to be consistent with Basel II, including consideration given to forecasting accuracy and model applicability. In this study, we have shown how agricultural exposures are typically can be managed on a portfolio basis which will not only enable the bank to diversify the risk and optimize the profit in the business, but also will strengthen banker-borrower relationship and enables the bank to expand its reach to farmers because of transparency in loan decision making process.Credit Risk Modelling; Lending; Agriculture

Systematic Property Risk: Quantifying UK Property Betas 1983-2005

The increased frequency in reporting UK property performance figures, coupled with the acceptance of the IPD database as the market standard, has enabled property to be analysed on a comparable level with other more frequently traded assets. The most widely utilised theory for pricing financial assets, the Capital Asset Pricing Model (CAPM), gives market (systematic) risk, beta, centre stage. This paper seeks to measure the level of systematic risk (beta) across various property types, market conditions and investment holding periods. This paper extends the authors’ previous work on investment holding periods and how excess returns (alpha) relate to those holding periods. We draw on the uniquely constructed IPD/Gerald Eve transactions database, containing over 20,000 properties over the period 1983-2005. This research allows us to confirm our initial findings that properties held over longer periods perform in line with overall market performance. One implication of this is that over the long-term performance may be no different from an index tracking approach.Real Estate, Risk, Property, Betas

Credit Risk Models for Managing Bank’s Agricultural Loan Portfolio

In this paper, we have developed a credit scoring model for agricultural loan portfolio of a large Public Sector Bank in India and suggest how such model would help the Bank to mitigate risk in Agricultural lending. The logistic model developed in this study reflects major risk characteristics of Indian agricultural sector, loans and borrowers and designed to be consistent with Basel II, including consideration given to forecasting accuracy and model applicability. In this study, we have shown how agricultural exposures are typically can be managed on a portfolio basis which will not only enable the bank to diversify the risk and optimize the profit in the business, but also will strengthen banker-borrower relationship and enables the bank to expand its reach to farmers because of transparency in loan decision making process.Credit Risk Modelling; Lending; Agriculture

Asset Market Liquidity Risk Management: A Generalized Theoretical Modeling Approach for Trading and Fund Management Portfolios

Asset market liquidity risk is a significant and perplexing subject and though the term market liquidity risk is used quite chronically in academic literature it lacks an unambiguous definition, let alone understanding of the proposed risk measures. To this end, this paper presents a review of contemporary thoughts and attempts vis-à-vis asset market/liquidity risk management. Furthermore, this research focuses on the theoretical aspects of asset liquidity risk and presents critically two reciprocal approaches to measuring market liquidity risk for individual trading securities, and discusses the problems that arise in attempting to quantify asset market liquidity risk at a portfolio level. This paper extends research literature related to the assessment of asset market/liquidity risk by providing a generalized theoretical modeling underpinning that handle, from the same perspective, market and liquidity risks jointly and integrate both risks into a portfolio setting without a commensurate increase of statistical postulations. As such, we argue that market and liquidity risk components are correlated in most cases and can be integrated into one single market/liquidity framework that consists of two interrelated sub-components. The first component is attributed to the impact of adverse price movements, while the second component focuses on the risk of variation in transactions costs due to bid-ask spreads and it attempts to measure the likelihood that it will cost more than expected to liquidate the asset position. We thereafter propose a concrete theoretical foundation and a new modeling framework that attempts to tackle the issue of market/liquidity risk at a portfolio level by combining two asset market/liquidity risk models. The first model is a re-engineered and robust liquidity horizon multiplier that can aid in producing realistic asset market liquidity losses during the unwinding period. The essence of the model is based on the concept of Liquidity-Adjusted Value-at-Risk (L-VaR) framework, and particularly from the perspective of trading portfolios that have both long and short trading positions. Conversely, the second model is related to the transactions cost of liquidation due to bid-ask spreads and includes an improved technique that tackles the issue of bid-ask spread volatility. As such, the model comprises a new approach to contemplating the impact of time-varying volatility of the bid-ask spread and its upshot on the overall asset market/liquidity risk.Economic Capital; Emerging Markets; Financial Engineering; Financial Risk Management; Financial Markets; Liquidity Risk; Portfolio Management; Liquidity Adjusted Value at Risk