Exploring New Material and Analytical Method for Characterization and Conservation of Artifacts

In this dissertation, we focus on developing new green bio-based gel systems and evaluating both the cleaning efficiency and the release of residues on the treated surface, different micro or no destructive techniques, such as optical microscopy, TGA, FTIR spectroscopy, HS-SPME and micro-Spatially Offset Raman spectroscopy (micro-SORS) were tested, proposing advanced analytical protocols. In the first part, a ternary PHB-DMC/BD gel system composed by biodiesel, dimethyl carbonate and poly-3 hydroxybutyrate was developed for cleaning of wax-based coatings applied on indoor bronze. The evaluation of the cleaning efficacy of the gel was carried out on a standard bronze sample which covered a layer of beeswax by restores of Opificio delle Pietre Dure in Florence, and a real case precious indoor bronze sculpture Pulpito della Passione attributed to Donatello. Results obtained by FTIR analysis showed an efficient removal of the wax coating. In the second part, two new kinds of combined gels based on electrospun tissues (PVA and nylon) and PHB-GVL gel were developed for removal of dammar varnish from painting. The electrospun tissue combined gels exhibited good mechanical property, and showed good efficient in cleaning over normal gel. In the third part, green deep eutectic solvent which consists urea and choline chloride was proposed to produce the rigid gel with agar for the removal of proteinaceous coating from oil painting. Rabbit glue and whole egg decorated oil painting mock-ups were selected for evaluating its cleaning efficiency, results obtained by ATR analysis showed the DES-agar gel has good cleaning performance. Furthermore, we proposed micro-SORS as a valuable alternative non-destructive method to explore the DES diffusion on painting mock-up. As a result, the micro-SORS was successful applied for monitoring the liquid diffusion behavior in painting sub-layer, providing a great and useful instrument for noninvasive residues detection in the conservation field.

Predicting market movement with Artificial Neural Networks

This paper presents an application of an Artificial Neural Network (ANN) to the prediction of stock market direction in the US. Using a multilayer perceptron neural network and a backpropagation algorithm for the training process, the model aims at learning the hidden patterns in the daily movement of the S&P500 to correctly identify if the market will be in a Trend Following or Mean Reversion behavior. The ANN is able to produce a successful investment strategy which outperforms the buy and hold strategy, but presents instability in its overall results which compromises its practical application in real life investment decisions.

Self-Fulfilling Price Cycles

This paper presents a model of a self-fulfilling price cycle in an asset market. Price oscillates deterministically even though the underlying environment is stationary. The mechanism that we uncover is driven by endogenous variation in the investment horizons of the different market participants, informed and uninformed. On even days, the price is high; on odd days it is low. On even days, informed traders are willing to jettison their good assets, knowing that they can buy them back the next day, when the price is low. The anticipated drop in price more than offsets any potential loss in dividend. Because of these asset sales, the informed build up their cash holdings. Understanding that the market is flooded with good assets, the uninformed traders are willing to pay a high price. But their investment horizon is longer than that of the informed traders: their intention is to hold the assets they purchase, not to resell. On odd days, the price is low because the uninformed recognise that the informed are using their cash holdings to cherry-pick good assets from the market. Now the uninformed, like the informed, are investing short-term. Rather than buy-and-hold as they do with assets purchased on even days, on odd days the uninformed are buying to sell. Notice that, at the root of the model, there lies a credit constraint. Although the informed are flush with cash on odd days, they are not deep pockets. On each cherry that they pick out of the market, they earn a high return: buying cheap, selling dear. However they don't have enough cash to strip the market of cherries and thereby bid the price up.

Tuovatko pääomasijoittajat lisäarvoa? Suomessa listattujen osakkeiden tuottovertailu

Tämän tutkimuksen tavoitteena on selvittää listautumisantien suoriutumista Suomen markkinoilla, sekä verrata pääomasijoittajien ja muiden listaamia yrityksiä. Tutkimusperiodina käytetään 36 kuukautta. Lisäksi tutkitaan lyhyen ajanjakson tuottoja näiden välillä. Tutkimuksessa selvitetään myös se, miten kansainvälisellä aineistollahavaitut, listautumisanteihin liittyvät anomaliat toteutuvat Suomessa. Tutkimuksen aineisto koostuu 48 yrityksestä, jotka listautuivat Helsingin pörssiin vuosien 1996 - 2000 välillä. Tutkimusmenetelmänä käytetään tapahtumatutkimusta. Kerätystä aineistosta lasketaan ylituotot kolmea eri menetelmää käyttämällä, eli lasketaan CAR-, BHAR- ja WR-ylituotot. Aineistolle tehdään myösregressio, jossa alisuoriutumista selitetään erilaisilla muuttujilla. Empiiristen tulosten mukaan listautumisannit keskimäärin alisuoriutuvat Suomen markkinoilla vertailukohteina käytettyihin indekseihin verrattuna. Tämän tulos tukee aiempia, kansainvälisiltä markkinoilta saatuja havaintoja. Sitä vastoin tämän tutkimuksen perusteella pääomasijoittajien listaamat yritykset alisuoriutuvat enemmän kuin muut listatut yritykset. Tämä havainto poikkeaa kansainvälisellä aineistolla tehdyistä tutkimuksista. Tutkittaessa portfolioiden ominaisuuksia, havaittiin erityisesti listautumisvuoden selittävän alisuoriutumisen voimakkuutta.

Teknisen analyysin menestyksellisyys suomalaisilla osakemarkkinoilla

Tutkielmassa analysoitiin yhteensä 73:n teknisen analyysin menetelmävariaation ja samalta ajanjaksolta lasketun osta ja pidä -strategian tuottojen eroja aineistolla, joka koostui 43 Helsingin Arvopaperipörssin päälistalla vuodesta 1991 vuoteen 1998 noteeratun yhtiön osakkeiden päivän päätöskursseista. Empiiriset testit toteutettiin tutkielmaa varten laadituilla Pascal-ohjelmilla, joilla simuloitiin eri teknisen analyysin menetelmien mukaista päivittäistä kaupankäyntiä. Tulokset osoittivat, ettei teknisen analyysin menetelmien avulla olisi tarkasteluperiodilla päässyt osta ja pidä -strategian tuottotasolle, sillä ainoastaan yksi strategioista ylitti osta ja pidä -strategian tuottotason. Negatiivinen korrelaatio kunkin teknisen analyysin menetelmän tuottamien kauppojen lukumäärän ja strategian kannattavuuden välillä oli erittäin vahva; mitä suurempi signaaliherkkyys, sitä heikompi oli kyseisen strategian tulos. Tutkimustulokset tukivat siten markkinatehokkuuden heikkojen ehtojen hypoteesia, jonka mukaan mennyt hintainformaatio ei ole monetäärisesti hyödynnettävissä.

Performance characteristic of moving average trading rules in the Finnish stock market

The thesis examines the profitability of DMAC trading rules in the Finnish stock market over the 1996-2012 period. It contributes to the existing technical analysis literature by comparing for the first time the performance of DMAC strategies based on individual stock trading portfolios to the performance of index trading strategies based on the trading on the index (OMX Helsinki 25) that consists of the same stocks. Besides, the market frictions including transaction costs and taxes are taken into account, and the results are reported from both institutional and individual investor’s perspective. Performance characteristic of DMAC rules are evaluated by simulating 19,900 different trading strategies in total for two non- overlapping 8-year sub-periods, and decomposing the full-sample-period performance of DMAC trading strategies into distinct bullish- and bearish-period performances. The results show that the best DMAC rules have predictive power on future price trends, and these rules are able to outperform buy-and-hold strategy. Although the performance of the DMAC strategies is highly dependent on the combination of moving average lengths, the best DMAC rules of the first sub-period have also performed well during the latter sub-period in the case of individual stock trading strategies. According to the results, the outperformance of DMAC trading rules over buy-and-hold strategy is mostly attributed to their superiority during the bearish periods, and particularly, during stock market crashes.

Detecting intraday periodicities with application to high frequency exchange rates

Many recent papers have documented periodicities in returns, return volatility, bid–ask spreads and trading volume, in both equity and foreign exchange markets. We propose and employ a new test for detecting subtle periodicities in time series data based on a signal coherence function. The technique is applied to a set of seven half-hourly exchange rate series. Overall, we find the signal coherence to be maximal at the 8-h and 12-h frequencies. Retaining only the most coherent frequencies for each series, we implement a trading rule that is based on these observed periodicities. Our results demonstrate in all cases except one that, in gross terms, the rules can generate returns that are considerably greater than those of a buy-and-hold strategy, although they cannot retain their profitability net of transactions costs. We conjecture that this methodology could constitute an important tool for financial market researchers which will enable them to detect, quantify and rank the various periodic components in financial data better.

A three-regime model of speculative behaviour: modelling the evolution of the S&P 500 composite index

We examine whether a three-regime model that allows for dormant, explosive and collapsing speculative behaviour can explain the dynamics of the S&P 500. We extend existing models of speculative behaviour by including a third regime that allows a bubble to grow at a steady rate, and propose abnormal volume as an indicator of the probable time of bubble collapse. We also examine the financial usefulness of the three-regime model by studying a trading rule formed using inferences from it, whose use leads to higher Sharpe ratios and end of period wealth than from employing existing models or a buy-and-hold strategy.

A meta analysis of real estate fund performance

This paper provides evidence regarding the risk-adjusted performance of 19 UK real estate funds in the UK, over the period 1991-2001. Using Jensen’s alpha the results are generally favourable towards the hypothesis that real estate fund managers showed superior risk-adjusted performance over this period. However, using three widely known parametric statistical procedures to jointly test for timing and selection ability the results are less conclusive. The paper then utilises the meta-analysis technique to further examine the regression results in an attempt to estimate the proportion of variation in results attributable to sampling error. The meta-analysis results reveal strong evidence, across all models, that the variation in findings is real and may not be attributed to sampling error. Thus, the meta-analysis results provide strong evidence that on average the sample of real estate funds analysed in this study delivered significant risk-adjusted performance over this period. The meta-analysis for the three timing and selection models strongly indicating that this out performance of the benchmark resulted from superior selection ability, while the evidence for the ability of real estate fund managers to time the market is at best weak. Thus, we can say that although real estate fund managers are unable to outperform a passive buy and hold strategy through timing, they are able to improve their risk-adjusted performance through selection ability.

Forecasting real estate returns using financial spreads

This paper examines the predictability of real estate asset returns using a number of time series techniques. A vector autoregressive model, which incorporates financial spreads, is able to improve upon the out of sample forecasting performance of univariate time series models at a short forecasting horizon. However, as the forecasting horizon increases, the explanatory power of such models is reduced, so that returns on real estate assets are best forecast using the long term mean of the series. In the case of indirect property returns, such short-term forecasts can be turned into a trading rule that can generate excess returns over a buy-and-hold strategy gross of transactions costs, although none of the trading rules developed could cover the associated transactions costs. It is therefore concluded that such forecastability is entirely consistent with stock market efficiency.

The blended approach to real estate allocations: performance implications of combining an exposure to German Spezialfonds with Global Listed Real Estate Securities

This paper seeks to increase the understanding of the performance implications for investors who choose to combine an unlisted real estate portfolio (in this case German Spezialfonds) with a (global) listed real estate element. We call this a “blended” approach to real estate allocations. For the avoidance of doubt, in this paper we are dealing purely with real estate equity (listed and unlisted) allocations, and do not incorporate real estate debt (listed or unlisted) or direct property into the process. A previous paper (Moss and Farrelly 2014) showed the benefits of the blended approach as it applied to UK Defined Contribution Pension Schemes. The catalyst for this paper has been the recent attention focused on German pension fund allocations, which have a relatively low (real estate) equity content, and a high bond content. We have used the MSCI Spezialfonds Index as a proxy for domestic German institutional real estate allocations, and the EPRA Global Developed Index as a proxy for a global listed real estate allocation. We also examine whether a rules based trading strategy, in this case Trend Following, can improve the risk adjusted returns above those of a simple buy and hold strategy for our sample period 2004-2015. Our findings are that by blending a 30% global listed portfolio with a 70% allocation (as opposed to a typical 100% weighting) to Spezialfonds, the real estate allocation returns increase from 2.88% p.a. to 5.42% pa. Volatility increases, but only to 6.53%., but there is a noticeable impact on maximum drawdown which increases to 19.4%. By using a Trend Following strategy raw returns are improved from 2.88% to 6.94% p.a. , The Sharpe Ratio increases from 1.05 to 1.49 and the Maximum Drawdown ratio is now only 1.83% compared to 19.4% using a buy and hold strategy . Finally, adding this (9%) real estate allocation to a mixed asset portfolio allocation typical for German pension funds there is an improvement in both the raw return (from 7.66% to 8.28%) and the Sharpe Ratio (from 0.91 to 0.98).

Are price limits on futures markets that cool? evidence from the brazilian merchantile & futures exchange

This paper investigates the impact of price limits on the Brazil- ian future markets using high frequency data. The aim is to identify whether there is a cool-off or a magnet effect. For that purpose, we examine a tick-by-tick data set that includes all contracts on the São Paulo stock index futures traded on the Brazilian Mercantile and Futures Exchange from January 1997 to December 1999. Our main finding is that price limits drive back prices as they approach the lower limit. There is a strong cool-off effect of the lower limit on the conditional mean, whereas the upper limit seems to entail a weak magnet effect on the conditional variance. We then build a trading strategy that accounts for the cool-off effect so as to demonstrate that the latter has not only statistical, but also economic signifi- cance. The resulting Sharpe ratio indeed is way superior to the buy-and-hold benchmarks we consider.

Análise do desempenho de regras da análise técnica aplicada ao mercado intradiário do contrato futuro do índice Ibovespa

Este artigo tem como objetivo verificar a robustez do contéudo preditivo de regras da análise técnica, usando informações intradiárias do mercado futuro do índice de ações da Bolsa de Valores de São Paulo (Ibovespa Futuro). A metodologia sugerida foi a avaliacão em grupos, conforme os resultados de Baptista (2002), tal que as regras são obtidas conforme os resultados em alguns dos subperíodos estudados, sendo testadas em períodos subsequentes. Como resultado, obteve-se robustez ao longo do tempo e à taxa de amostragem dos dados no desempenho das regras acima do benchmark (buy-and-hold), porém considerações realistas acerca do momento de compra, assim como da corretagem (exceto grande investidor), podem reduzir substancialmente os ganhos

Suportes e resistências : uma aplicação ao mercado de moedas por meio da análise comparada de estratégias

A Análise Técnica postula que os preços dos ativos nos mercados financeiros se movem em tendências de alta ou baixa. Ainda, no meio de uma tendência há patamares de preços, suportes e resistências, que quando rompidos indicam uma possível reversão dos preços para a direção contrária à direção vigente. Conseqüentemente, após essa “falha de movimento”, os agentes se beneficiariam dessa informação para tomar suas decisões de investimento e obter lucros. O presente trabalho analisa tal afirmação verificando a ocorrência deste fato no mercado de moedas, FOREX. A análise é feita por meio do teste de médias dos retornos de uma estratégia operacional baseada nas falhas contra a simples estratégia buy-and-hold. Adicionalmente, são feitas análises de sensibilidade para enriquecer o estudo. Por fim, verifica-se que a estratégia proposta não oferece resultados conclusivos a favor das falhas.

O desempenho de longo prazo dos IPOs no Brasil

Desde 2004, o movimento de abertura de capital das empresas brasileiras intensificou-se de forma atípica, sendo que o auge ocorreu em 2007, quando 64 companhias estrearam na bolsa de valores. Por meio da metodologia do buy-and-hold e pautado pela análise de regressão múltipla, o escopo deste trabalho é avaliar o desempenho de longo prazo das ofertas iniciais de ações (IPOs) ocorridos no país entre 2004 e 2007, quando 106 empresas foram listadas no mercado acionário nacional. Para tanto, busca-se verificar a existência de retorno médio anormal num horizonte de 60 meses de negociação, e ainda analisar o impacto de alguns fatores para tal desempenho, como a magnitude do underpricing, o volume da emissão e a busca por liquidez, o tipo de oferta ao mercado (primária e/ou secundária), o perfil do investidor, e o nível de Governança Corporativa na listagem em bolsa. Os principais resultados obtidos mostram que os 78 IPOs selecionados para a amostra final apresentaram rentabilidade média de -4,57% durante os cinco anos de negociação desde a estreia, enquanto o índice Bovespa acumulou retorno médio de 35,31%, o que significa uma underperformance de -39,88%. E a análise dos fatores determinantes apontou que apenas a participação dos investidores estrangeiros é estatisticamente significante para os retornos anormais dos IPOs. Diante dos resultados obtidos, serão abordados os principais aspectos que possam justificar tal dinâmica e ainda sugestões para novos estudos complementares.