Aggregate dividends and consumption smoothing

We show that net equity payouts from the corporate sector play a crucial role in helping individuals manage their consumption path across the business cycle. In particular, we show that, as investors' desire to smooth consumption increases, optimal aggregate dividends become both more volatile and more counter-cyclical to help counterbalance pro-cyclical labor income. These findings are robust to whether or not agency conflicts exist in the economy.

Low Volatility Options and Numerical Diffusion of Finite Difference Schemes

2000 Mathematics Subject Classification: 65M06, 65M12.

Optimal investment under stochastic volatility and power type utility function

2000 Mathematics Subject Classification: 37F21, 70H20, 37L40, 37C40, 91G80, 93E20.

Hatékonyság növelése tervezéssel - avagy: aggregált tervezés alkalmazása egy magyar vállalatnál = Improving efficiency with production planning - Applying aggregate planning at a Hungarian company

A cikk alapvető kérdése, hogy miképpen használható a tervezés a termelési folyamatok, s ezzel a vállalati m}uködés egészének hatékonyságnövelése érdekében. A termeléstervezés szintjei és eszközei közül a középtávú aggregált tervezésre koncentrálunk. Ennek oka elsősorban az, hogy tapasztalatunk szerinte tervezési szint gyakorlati alkalmazása még nem tekinthető elterjedtnek, s ebből következően az eszköz alaposabb ismerete és alkalmazásának elterjedése jelentős tartalékokat tárhat fel a m}uködési hatékonyság növelése terén. A dolgozat a termeléstervezés klasszikusnak tekinthető modelljét alkalmazza egy hazai vállalat esetében. Az elemzés során vizsgáljuk a modell alkalmazhatóságát és a különböző tervezési alternatívák hatását a hatékonyság növelésére. A modell számítógépes megoldását a Microsoft Excel Solver programjával végeztük. _______ The article demonstrates how production planning, especially aggregate production planning can positively influence the competitiveness of production firms. First the structure of production planning, different, but interconnected levels of it are introduced than the aggregate planning is elaborated in more details. Reason for focusing on aggregate planning lies in the fact that according to our experience aggregate planning is an operation planning method applied least of all production planning methods in Hungary. Due to this we are convinced that demonstrating a real case study in this area can help managers to realize that adopting it can significantly influence e±ciency in operation and represent important source of development. We applied a classic aggregate planning model for a Hungarian producing company. We have tested the adaptability of the model and also the effect of different concrete planning scenarios on efficiency. Solution of the mathematical model is calculated using the program of Microsoft Excel Solver.

Volt-e likviditási válság? Volatilitás és likviditás kapcsolatának vizsgálata (Was there a liquidity crisis? Analysis the relationship between volatility and liquidity)

Széleskörűen alátámasztott, empirikus tény, hogy önmagában a nagyobb volatilitás csökkenti a piac likviditását, vagyis változékonyabb piacokon várhatóan nagyobb lesz egy-egy tranzakció áreltérítő hatása. Kutatásomban azt a kérdést vizsgáltam, hogy a Budapesti Értéktőzsdén az OTP-részvény piacán a 2007/2008-as válságban tapasztalható, átmeneti likviditáscsökkenés betudható volt-e egyszerűen a megnövekedett volatilitásnak, vagy ezen túl abban más tényezők (pl. a szereplők körének és viselkedésének drasztikus megváltozása, általános forráscsökkenés stb.) is szerepet játszhattak-e. A volatilitást a loghozamok szórásával, illetve a tényleges ársávval, míg az illikviditást a Budapesti Likviditási Mértékkel (BLM) reprezentáltam. Egyrészt azt állapítottam meg, hogy az OTP esetében a tényleges ársáv szorosabban korrelál a BLM-mel, mint a szórás. Másrészt az is egyértelmű, hogy a válság előtti kapcsolat a volatilitás és a likviditás között a válságban és azután már jelentősen megváltozott. Válságban az illikviditás jóval nagyobb volt, mint amit a volatilitás növekedése alapján vártunk, a válság lecsengése után azonban megfordult ez a reláció. _________ It is a widely supported empirical fact, that the greater volatility in itself decreases the liquidity of the market, namely more volatile a market is, the higher a transaction’s price impact will be. I have examined in my paper the question, whether the decrease of liquidity during the crisis of 2007/2008 in case of the OTP stock – traded on the Budapest Stock Exchange – was the consequence of the increased volatility, or other factors had an effect on the illiquidity as well (e.g.: the drastic change of market participants’ behaviour; reduction of fi nancing sources; etc.). I have represented volatility with the standard deviation of the logreturns, and with the true range, while the illiquidity with the Budapest Liquidity Measure (BLM). On one hand I have identifi ed, that in case of the OTP, the true range has a stronger relationship with the BLM than the standard deviation has. On the other hand it was clear, that the relationship between volatility and liquidity has changed notably during and after the crisis. During crisis the illiquidity was greater than what I have estimated based on the volatility increase, but after the crisis this relation has changed.

A beruházási projektek aggregált tőkeigénye = The Aggregate Capital Needs of Investment Projects

A tanulmány abból indul ki, hogy a beruházási projektek értékelése során egyidejűleg szükséges figyelembe venni a projektben lekötött tőkét és a lekötési időt mint jövedelemtermelési lehetőséget. Definiálja a projekt aggregált tőkeigényének fogalmát és megszerkeszti a vonatkozó mérőszámot. Az aggregált tőkeigény új vállalatgazdasági kategória, mely a beruházási projektek értékelésének egy új megközelítését teszi lehetővé. A projekt aggregált tőkeigénye azt a tőkeösszeget jelenti, mely a projekt működtetéséhez annak teljes élettartama alatt szükséges. A három meghatározó tényező: a kezdőtőke, a megtérülési idő (illetőleg az élettartam) és a megtérülés gyorsasága. A számszerűsítéshez minden évre vonatkozóan meg kell határozni az adott évben lekötött tőkét, ami az adott évig még meg nem térült tőkerészt jelenti, majd ezek összegzése révén adódik az aggregált tőkeigény. A mértékegység egységnyi tőke egyévi lekötése. A tanulmány az összefüggések modellszerű levezetése mellett gazdag példaanyagot is tartalmaz. Az elemzés bővíti a nettó jelenérték tartalmára vonatkozó ismereteket, rávilágít az aggregált tőkeigény ismeretének fontosságára mind a nettó jelenérték, mind a belső kamatláb esetében. _____ The starting point of this paper is that in the evaluation process of investment projects necessary to take into account simultaneously the tied-up capital and tiedup time as the income-generating potential. For this, it defines a special content of aggregate capital needs of investment projects, and elaborates an index. The aggregate capital needs is a new business economics category, which provides a new aspect to evaluate investment projects. This means the amount of capital needed for the operation of the project during its full duration. Three factors determine the aggregate capital needs for investments projects. These are the amount of initial investment, the payback period (or the duration) and the rapidity of capital payback. The solution is to sum up the yearly tied-up capital, that is, the notreturned parts of the capital for each year. The measurement unit is one unit tied-up capital for one year. The paper formulates the main relationships as models and by way of explanation presents some examples. The analysis highlights the importance of considering the aggregate capital needs furthermore widens knowledge regarding the net present value and internal rate of return.

An autoregressive conditional filtering process to remove intraday seasonal volatility and its application to testing the noisy rational expectations model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

The Food Service Industry Environment: Market Volatility Analysis

In their dialogue entitled - The Food Service Industry Environment: Market Volatility Analysis - by Alex F. De Noble, Assistant Professor of Management, San Diego State University and Michael D. Olsen, Associate Professor and Director, Division of Hotel, Restaurant & Institutional Management at Virginia Polytechnic Institute and State University, De Noble and Olson preface the discussion by saying: “Hospitality executives, as a whole, do not believe they exist in a volatile environment and spend little time or effort in assessing how current and future activity in the environment will affect their success or failure. The authors highlight potential differences that may exist between executives' perceptions and objective indicators of environmental volatility within the hospitality industry and suggest that executives change these perceptions by incorporating the assumption of a much more dynamic environment into their future strategic planning efforts. Objective, empirical evidence of the dynamic nature of the hospitality environment is presented and compared to several studies pertaining to environmental perceptions of the industry.” That weighty thesis statement presumes that hospitality executives/managers do not fully comprehend the environment in which they operate. The authors provide a contrast, which conventional wisdom would seem to support and satisfy. “Broadly speaking, the operating environment of an organization is represented by its task domain,” say the authors. “This task domain consists of such elements as a firm's customers, suppliers, competitors, and regulatory groups.” These are dynamic actors and the underpinnings of change, say the authors by way of citation. “The most difficult aspect for management in this regard tends to be the development of a proper definition of the environment of their particular firm. Being able to precisely define who the customers, competitors, suppliers, and regulatory groups are within the environment of the firm is no easy task, yet is imperative if proper planning is to occur,” De Noble and Olson further contribute to support their thesis statement. The article is bloated, and that’s not necessarily a bad thing, with tables both survey and empirically driven, to illustrate market volatility. One such table is the Bates and Eldredge outline; Table-6 in the article. “This comprehensive outline…should prove to be useful to most executives in expanding their perception of the environment of their firm,” say De Noble and Olson. “It is, however, only a suggested outline,” they advise. “…risk should be incorporated into every investment decision, especially in a volatile environment,” say the authors. De Noble and Olson close with an intriguing formula to gauge volatility in an environment.

Three essays on the microstructure of exchange traded funds

Exchange traded funds (ETFs) have increased significantly in popularity since they were first introduced in 1993. However, there is still much that is unknown about ETFs in the extant literature. This dissertation attempts to fill gaps in the ETF literature by using three related essays. In these three essays, we compare ETFs to closed ended mutual funds (CEFs) by decomposing the bid-ask spread into its three components; we look at the intraday shape of ETFs and compare it to the intraday shape of equities as well as examine the co-integration factor between ETFs on the London Stock Exchange and the New York Stock Exchange; we also examine the differences between leveraged ETFs and unleveraged ETFs by analyzing the impact of liquidity and volatility. These three essays are presented in Chapters 1, 2, and 3, respectively. ^ Chapter one uses the Huang and Stoll (1997) model to decompose the bid-ask spread in CEFs and ETFs for two distinct periods—a normal and a volatile period. We show a higher adverse selection component for CEFs than for ETFs without regard to volatility. However, both ETFs and CEFs increased in magnitude of the adverse selection component in the period of high volatility. Chapter two uses a mix of the Werner and Kleidon (1993) and the Hupperets and Menkveld (2002) methods to get the intraday shape of ETFs and analyze co-integration between London and New York trading. We find two different shapes for New York and London ETFs. There also appears to be evidence of co-integration in the overlapping two-hour trading period but not over the entire trading day for the two locations. The third chapter discusses the new class of ETFs called leveraged ETFs. We examine the liquidity and depth differences between unleveraged and leveraged ETFs at the aggregate level and when the leveraged ETFs are classified by the leveraged multiples of -3, -2, -1, 2, and 3, both for a normal and a volatile period. We find distinct differences between leveraged and unleveraged ETFs at the aggregate level, with leveraged ETFs having larger spreads than unleveraged ETFs. Furthermore, while both leveraged and unleveraged ETFs have larger spreads in high volatility, for the leveraged ETFs the change in magnitude is significantly larger than for the unleveraged ETFs. Among the multiples, the -2 leveraged ETF is the most pronounced in its liquidity characteristics, more so in volatile times. ^

An Autoregressive Conditional Filtering Process to remove Intraday Seasonal Volatility and its Application to Testing the Noisy Rational Expectations Model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

(Table 1, page 171) Thorium and cobalt content of the total aggregate of manganese nodules from various locations

A criterion is suggested for discrimination between ferromanganese oxide minerals, deposited after the introduction of manganese and associated elements in sea water solution at submarine vulcanism, and minerals which are slowly formed from dilute solution, largely of continental origin. The simlultaneous injection of thorium into the ocean by submarine vulcanism is indicated, and its differentiation from continental thorium introduced into the ocean by runoff is discussed.

Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers

The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized covariances that incorporates asymmetry and long memory (hereafter the RMESV-ALM model). The matrix exponential transformation guarantees the positivedefiniteness of the dynamic covariance matrix. The contribution of the paper ties in with Robert Basmann’s seminal work in terms of the estimation of highly non-linear model specifications (“Causality tests and observationally equivalent representations of econometric models”, Journal of Econometrics, 1988, 39(1-2), 69–104), especially for developing tests for leverage and spillover effects in the covariance dynamics. Efficient importance sampling is used to maximize the likelihood function of RMESV-ALM, and the finite sample properties of the quasi-maximum likelihood estimator of the parameters are analysed. Using high frequency data for three US financial assets, the new model is estimated and evaluated. The forecasting performance of the new model is compared with a novel dynamic realized matrix-exponential conditional covariance model. The volatility and co-volatility spillovers are examined via the news impact curves and the impulse response functions from returns to volatility and co-volatility.

Forecasting the term structure of volatility of crude oil price changes

Peer reviewed

Electoral Volatility, Political Sophistication, Trust and Efficacy

In this article we investigate voter volatility and analyze the causes and motives of switching vote intentions. We test two main sets of variables linked to volatility in literature; political sophistication and ‘political (dis)satisfaction’. Results show that voters with low levels of political efficacy tend to switch more often, both within a campaign and between elections. In the analysis we differentiate between campaign volatility and inter-election volatility and by doing so show that the dynamics of a campaign have a profound impact on volatility. The campaign period is when the lowly sophisticated switch their vote intention. Those with higher levels of interest in politics have switched their intention before the campaign has started. The data for this analysis are from the three wave PartiRep Belgian Election Study (2009).