New Economics Papers
on Risk Management
Issue of 2007‒08‒27
six papers chosen by



  1. Risk-based cash demand in a firm By Michalski, Grzegorz
  2. Modeling and predicting the CBOE market volatility index By Marcelo Fernandes; Marcelo Cunha Medeiros; MArcelo Scharth
  3. The Profitability of Technical Stock Trading has Moved from Daily to Intraday Data By Stephan Schulmeister
  4. Assets Relative Risk for Long-term Investors By GOLLIER, Christian
  5. Should new or rapidly growing banks have more equity? By Niinimäki , Juha-Pekka
  6. The Interaction Between the Aggregate Behaviour of Technical Trading Systems and Stock Price Dynamics By Stephan Schulmeister

  1. By: Michalski, Grzegorz
    Abstract: Firms hold cash for a variety of different reasons. Generally, cash balances held in a firm can be called considered, precautionary, speculative, transactional and intentional. The first are the result of management anxieties. Managers fear the negative part of the risk and hold cash to hedge against it. Second, cash balances are held to use chances that are created by the positive part of the risk equation. Next, cash balances are the result of the operating needs of the firm. In this article, we analyze the relation between these types of cash balances and risk. This article also contains propositions for marking levels of precautionary cash balances and speculative cash balances. Current models for determining cash management, assign no minimal cash level, or their minimal cash level is based on the manager's intuition. Presented in this article model avoid intuition and is based on calculation. Application of this proposition should help managers to make better decisions to maximize the value of a firm.
    Keywords: Demand for Cash; Cash balances; Risk; Uncertainty; Real Options; Option Value of Money; Short-Term Financial Management; Working Capital Management
    JEL: G39 G32
    Date: 2006–08–15
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:4541&r=rmg
  2. By: Marcelo Fernandes (Queen Mary, University of London); Marcelo Cunha Medeiros (Department of Economics, PUC-Rio); MArcelo Scharth
    Abstract: This paper performs a thorough statistical examination of the time-series properties of the market volatility index (VIX) from the Chicago Board Options Exchange (CBOE). The motivation lies on the widespread consensus that the VIX is a barometer to the overall market sentiment as to what concerns risk appetite. To assess the statistical behavior of the time series, we run a series of preliminary analyses whose results suggest there is some long-range dependence in the VIX index. This is consistent with the strong empirical evidence in the literature supporting long memory in both options-implied and realized volatilities. We thus resort to linear and nonlinear heterogeneous autoregressive (HAR) processes, including smooth transition and threshold HAR-type models, as well as to smooth transition autoregressive trees (START) for modeling and forecasting purposes. The in-sample results for the HAR-type indicate that they cope with the long-range dependence in the VIX time series as well as the more popular ARFIMA model. In addition, the highly nonlinear START specification also does a god job in controlling for the long memory. The out-of-sample analysis evince that the linear ARMA and ARFIMA models perform very well in the short run and very poorly in the long-run, whereas the START model entails by far the best results for the longer horizon despite of failing at shorter horizons. In contrast, the HAR-type models entail reasonable relative performances in most horizons. Finally, we also show how a simple forecast combination brings about great improvements in terms of predictive ability for most horizons.
    Keywords: heterogeneous autoregression, implied volatility, smooth transition, VIX.
    JEL: G12 C22 C53 E44
    Date: 2007–08
    URL: http://d.repec.org/n?u=RePEc:rio:texdis:548&r=rmg
  3. By: Stephan Schulmeister (WIFO)
    Abstract: This paper investigates how technical trading systems exploit the momentum and reversal effects in the S&P 500 spot and futures market. The former is exploited by trend-following models, while the latter by contrarian models. In total, the performance of 2,580 widely used models is analysed. When based on daily data, the profitability of technical stock trading has steadily declined since 1960 and has become unprofitable over the 1990s. However, when based on 30-minutes data the same models produce an average gross return of 8.8 percent per year between 1983 and 2000. These results do not change substantially when trading is simulated over six subperiods. Those 25 models which performed best over the most recent subperiod produce a significantly higher gross return over the subsequent subperiod than all models. Over the out-of-sample period 2001-2006 the 2,580 models perform much worse than between 1983 and 2000. This result could be due to stock markets becoming more efficient or to stock price trends shifting from 30-minutes prices to prices of higher frequencies.
    Keywords: Technical trading, stock price dynamics, momentum effect, reversal effect
    Date: 2007–04–02
    URL: http://d.repec.org/n?u=RePEc:wfo:wpaper:y:2007:i:289&r=rmg
  4. By: GOLLIER, Christian (c.)
    Date: 2007–07–14
    URL: http://d.repec.org/n?u=RePEc:ide:wpaper:7279&r=rmg
  5. By: Niinimäki , Juha-Pekka (Bank of Finland Research)
    Abstract: There is substantial evidence that new banks and rapidly growing banks are risk prone. We study this problem by designing a relationship-lending model in which a bank operates as a financial intermediary and centralised monitor. In the absence of deposit insurance, the bank’s limited liability option creates an incentive problem between the bank and its depositors, the likely outcome of which is a reduction in the amounts of resources allocated to monitoring its borrowers. Hence, the bank must signal its safety to depositors by maintaining the equity ratio held. The optimal equity ratio is dynamic, ie new banks need relatively more equity than established banks, which enjoy profitable old lending relationships – charter value – that reduce the incentive problem. However, if an established bank grows rapidly, its share of old relationships also decreases and the bank will have to raise its equity ratio. With deposit insurance, regulators should set higher equity requirements for new banks and rapidly growing banks than for those in a more established position. The results of the model can be extended to more general inter-firm control of credit institutions.
    Keywords: financial intermediation; relationship banking; financial fragility; bank regulation; deposit insurance; moral hazard; product quality
    JEL: G11 G21 G28
    Date: 2007–09–04
    URL: http://d.repec.org/n?u=RePEc:hhs:bofrdp:2001_016&r=rmg
  6. By: Stephan Schulmeister (WIFO)
    Abstract: This study analyses the interaction between the aggregate trading behaviour of technical models and stock price fluctuations in the S&P 500 futures market. It examines 2,580 widely used trading systems based on 30-minutes prices. The sample comprises trend-following as well as contrarian models. It shows that technical trading exerts an excess demand pressure on the stock market. This is because technical models produce clusters of trading signals that are on the same side of the market, either buying or selling. Initial stock price changes triggered by news are strengthened by a sequence of trading signals produced by trend-following models. Once 90 percent of the models have signalled a particular position, stock prices tend to move in the direction congruent with the position-holding of the models. This phenomenon has to be attributed to the transactions of non-technical traders, perhaps amateurs. Once price movements lose their momentum, contrarian technical models contribute to reversals of the trend.
    Keywords: Technical trading, stock price dynamics, momentum effect, reversal effect
    Date: 2007–04–02
    URL: http://d.repec.org/n?u=RePEc:wfo:wpaper:y:2007:i:290&r=rmg

General information on the NEP project can be found at https://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.