Hoje no mercado brasileiro de eletricidade, o preço da energia convencional é composto pela soma do valor do Preço de Liquidação das Diferenças (PLD) divulgado pela Câmara de Comercialização de Energia Elétrica (CCEE) semanalmente com o valor do Spread negociado bilateralmente no mercado à vista (mercado de curto prazo), resultante do equilíbrio entre oferta e demanda. Em alguns momentos, o valor do Spread chega a representar mais de 100% do custo total da energia. Este trabalho faz uma análise do mercado brasileiro, bem como, de alguns mercados no exterior de energia elétrica e destaca os pontos que tem influência direta, na formação do Spread da energia convencional e como isso afeta a decisão de contratação dos agentes. Além disso, o trabalho busca encontrar correlações entre dados divulgados, como carga e oferta de energia, com o ágio negociado no mercado de curto prazo, buscando entender o real impacto de cada um desses fatores e explicar as grandes variações já observadas. Sugere-se também um modelo de regressão linear múltipla para a projeção de valores do ágio. Para tanto, foram utilizadas informações proveniente de um banco de dados de cotações de negócios efetivamente realizados no curto prazo desde janeiro de 2011 até julho de 2014, bem como informações retiradas da CCEE e Operador Nacional do Sistema (ONS). / The Brazilian wholesales energy market price is formed by de sum of the PLD (Market Clearing Price which is released weekly by the Commercial Chamber) and a Spread value, resulting from the negotiation between the market agents. In some cases, the Spread represent more than 100% of the energy total cost. This paper presents an overview about some energy markets, focusing the Brazilian Energy Market, so as to highlight points that affect the Spread value at the spot market and, as consequence, the strategy of the market agents. Additionally, this paper shows the correlation between energy demand and energy offer and energy spread negotiated at the short term market, trying to understand the real impact of each variable trying to get the right explanation regarding the big variations observed. It has been suggested a mathematical model of multiple linear regression to forecast the spread value. In order to accomplish this purpose it was used (i) a historical data of effectively trading situations at the short term market, comprising the period between January 2011 to July 2014, as well as (ii) informations released by the Commercial Chamber (CCEE) and the System Operator (ONS).

Hoje no mercado brasileiro de eletricidade, o preço da energia convencional é composto pela soma do valor do Preço de Liquidação das Diferenças (PLD) divulgado pela Câmara de Comercialização de Energia Elétrica (CCEE) semanalmente com o valor do Spread negociado bilateralmente no mercado à vista (mercado de curto prazo), resultante do equilíbrio entre oferta e demanda. Em alguns momentos, o valor do Spread chega a representar mais de 100% do custo total da energia. Este trabalho faz uma análise do mercado brasileiro, bem como, de alguns mercados no exterior de energia elétrica e destaca os pontos que tem influência direta, na formação do Spread da energia convencional e como isso afeta a decisão de contratação dos agentes. Além disso, o trabalho busca encontrar correlações entre dados divulgados, como carga e oferta de energia, com o ágio negociado no mercado de curto prazo, buscando entender o real impacto de cada um desses fatores e explicar as grandes variações já observadas. Sugere-se também um modelo de regressão linear múltipla para a projeção de valores do ágio. Para tanto, foram utilizadas informações proveniente de um banco de dados de cotações de negócios efetivamente realizados no curto prazo desde janeiro de 2011 até julho de 2014, bem como informações retiradas da CCEE e Operador Nacional do Sistema (ONS). / The Brazilian wholesales energy market price is formed by de sum of the PLD (Market Clearing Price which is released weekly by the Commercial Chamber) and a Spread value, resulting from the negotiation between the market agents. In some cases, the Spread represent more than 100% of the energy total cost. This paper presents an overview about some energy markets, focusing the Brazilian Energy Market, so as to highlight points that affect the Spread value at the spot market and, as consequence, the strategy of the market agents. Additionally, this paper shows the correlation between energy demand and energy offer and energy spread negotiated at the short term market, trying to understand the real impact of each variable trying to get the right explanation regarding the big variations observed. It has been suggested a mathematical model of multiple linear regression to forecast the spread value. In order to accomplish this purpose it was used (i) a historical data of effectively trading situations at the short term market, comprising the period between January 2011 to July 2014, as well as (ii) informations released by the Commercial Chamber (CCEE) and the System Operator (ONS).

This thesis extends the 52-week high momentum literature, which was first published by George and Hwang in 2004, by stressing the parameters of the trading strategy to investigate its robustness. George and Hwang, in their seminal paper, find that the ratio of a stock’s close price to its 52-week high price is a good predictor of future returns. The thesis stresses various parameters of the strategy - such as the percent of total stocks bought and sold each period – and applies the strategy over different time periods – such as bull and bear markets. The study finds that the strategy is more profitable over the later half of the data set due to underperformance in bear markets such as the 1929 market crash and subsequent Great Depression. The results also show a significant difference in profitability between bull and bear market periods. The second half of the thesis looks at a new area in momentum, the absolute 52-week high. The strategy buys stocks whose price has increased over the previous six months, and who also close to their 52-week high price. Stocks are only bought (sold) if their price has increased (decreased) over the past six months and is close to (far from) the 52-week high price. The aim is to cut out stocks that are considered to be underperforming in the 52-week high momentum strategy, leaving only true winner and loser stocks. This strategy was found to increase the strength of the 52-week high momentum strategy, and the results show that there is no longer a significant difference between bull and bear market returns.

Submitted by Kesley Leandro da Silva (kesley.leandro@gmail.com) on 2016-03-10T17:32:09Z No. of bitstreams: 1 Dissertação v02.docx: 272937 bytes, checksum: 8b3b51152e65026481b1ba2a1541fcde (MD5) / Rejected by Renata de Souza Nascimento (renata.souza@fgv.br), reason: Kesley, Segue abaixo as alterações que deverão ser realizadas em seu trabalho: - O arquivo deve estar em pdf. - Nome e Título em Letra maiúscula. - Retirar a sigla SP que consta ao lado de SÃO PAULO. - A ficha catalográfica deve estar na parte inferior da pagina - Centralizar os títulos Resumo e Abstract - As páginas anteriores da Introdução não podem estar numeradas. Em seguida, submeter novamente o trabalho. Att on 2016-03-10T21:57:30Z (GMT) / Submitted by Kesley Leandro da Silva (kesley.leandro@gmail.com) on 2016-03-11T15:24:37Z No. of bitstreams: 1 Dissertação v03.pdf: 1405923 bytes, checksum: 28d2a1fb855d75506c6f1f010f4ff5a5 (MD5) / Approved for entry into archive by Renata de Souza Nascimento (renata.souza@fgv.br) on 2016-03-11T15:42:19Z (GMT) No. of bitstreams: 1 Dissertação v03.pdf: 1405923 bytes, checksum: 28d2a1fb855d75506c6f1f010f4ff5a5 (MD5) / Made available in DSpace on 2016-03-11T16:00:12Z (GMT). No. of bitstreams: 1 Dissertação v03.pdf: 1405923 bytes, checksum: 28d2a1fb855d75506c6f1f010f4ff5a5 (MD5) Previous issue date: 2016-02-15 / Utilizo dados semanais para investigar a lucratividade de estratégias de momentum no mercado de câmbio baseadas em dois diferentes métodos de extração da tendência, possivelmente não linear. Comparo a performance com as tradicionais regras de médias móveis, método linear bastante utilizado pelos profissionais do mercado. Eu encontro que o desempenho de todas as estratégias é extremamente sensível à escolha da moeda, às defasagens utilizadas e ao critério de avaliação escolhido. A despeito disso, as moedas dos países do G10 apresentam resultados médios melhores com a utilização dos métodos não lineares, enquanto as moedas dos países emergentes apresentam resultados mistos. Adoto também uma metodologia para o gerenciamento do risco das estratégias de momentum, visando minimizar as 'grandes perdas'. Ela tem êxito em diminuir as perdas máximas semanais, o desvio-padrão, a assimetria e curtose para a maior parte das moedas em ambas as estratégias. Quanto ao desempenho, as operações baseadas no filtro HP com gestão do risco apresentam retornos e índices de Sharpe maiores para cerca de 70% das estratégias, enquanto as baseadas na regressão não paramétrica apresentam resultados melhores para cerca de 60% das estratégias. / I use weekly data to investigate the profitability of momentum strategies in the currency market based on two different methods of trending extraction, possibly nonlinear. I compare the performance with the traditional moving averages rules, linear method of trading broadly used by market professionals. I find that the performance of all strategies is extremely sensitive to the choice of currency, lags parameters and the evaluation criteria. Nevertheless, the G10 currencies show better average results with the nonlinear methods, while the emerging market currencies show mixed results. I also adopt a methodology for managing the risk of momentum strategies to minimize the “worst crashes”. It works to lower the maximum weekly losses, the standard deviation, the skewness and the kurtosis for most currencies in both strategies. In terms of performance, HP filter with risk-managed momentum shows higher return and Sharpe ratio for about 70% the observations, while those based on nonparametric regression show higher numbers for about 60% the observations.

Submitted by Camilo de Léllis Cavalcanti Júnior (camilojr@gmail.com) on 2013-09-20T14:38:32Z No. of bitstreams: 1 Dissertação - Estratégia de Trading Utilizando o Modelo Dinâmico de Nelson-Siegel Final.pdf: 1310470 bytes, checksum: f90849f3305d9519f30ddd197d650214 (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2013-09-20T14:43:47Z (GMT) No. of bitstreams: 1 Dissertação - Estratégia de Trading Utilizando o Modelo Dinâmico de Nelson-Siegel Final.pdf: 1310470 bytes, checksum: f90849f3305d9519f30ddd197d650214 (MD5) / Made available in DSpace on 2013-09-20T14:49:57Z (GMT). No. of bitstreams: 1 Dissertação - Estratégia de Trading Utilizando o Modelo Dinâmico de Nelson-Siegel Final.pdf: 1310470 bytes, checksum: f90849f3305d9519f30ddd197d650214 (MD5) Previous issue date: 2013-08-21 / Esta pesquisa busca testar a eficácia de uma estratégia de arbitragem de taxas de juros no Brasil baseada na utilização do modelo de Nelson-Siegel dinâmico aplicada à curva de contratos futuros de taxa de juros de 1 dia da BM&FBovespa para o período compreendido entre 02 de janeiro de 2008 e 03 de dezembro de 2012. O trabalho adapta para o mercado brasileiro o modelo original proposto por Nelson e Siegel (1987), e algumas de suas extensões e interpretações, chegando a um dos modelos propostos por Diebold, Rudebusch e Aruoba (2006), no qual estimam os parâmetros do modelo de Nelson-Siegel em uma única etapa, colocando-o em formato de espaço de estados e utilizando o Filtro de Kalman para realizar a previsão dos fatores, assumindo que o comportamento dos mesmos é um VAR de ordem 1. Desta maneira, o modelo possui a vantagem de que todos os parâmetros são estimados simultaneamente, e os autores mostraram que este modelo possui bom poder preditivo. Os resultados da estratégia adotada foram animadores quando considerados para negociação apenas os 7 primeiros vencimentos abertos para negociação na BM&FBovespa, que possuem maturidade máxima próxima a 1 ano. / This research tries to test the effectiveness of an interest rate arbitrage strategy in Brazil based on a Dynamic Nelson-Siegel model applied to the term structure of future contracts of 1 day of interest rates traded at BM&FBovespa for the time between January, 2nd of 2008, and December, 3rd, 2012. The work adapts to the Brazilian market the mode originally proposed by Nelson and Siegel (1987), and some of its extensions and interpretations, reaching one of the models proposed by Diebold, Rudebusch and Aruoba (2006), in which they estimate the parameters of Nelson-Siegel Model in one only step, putting it in a state-space form and using the Kalman Filter to make the factors’ forecast, assuming that their behavior is an order 1 VAR. The model has the advantage that all the parameters are estimated simultaneously, and the authors showed that it has a good forecast power. The results of the adopted strategy were encouraging when considered for negotiation only the 7 first available maturities at BM&FBovespa, which have maturity of around 1 year.

This master’s thesis is focused on the development, optimization and testing automated trading systems (ATS) using technical analysis. The first part, which describes mainly theoretical background, is followed by the practical part. This section deals with designing workflow for the development of ATS. Outcome of this thesis is portfolio of strategies that can be traded on e-mini markets. Some systems have been designed in Adaptrade Builder using genetic algorithms, while all testing was performed in TradeStation platform.

The world is right now in a global transition from a fossil fuel dependency towards an electrified society based on green and renewable energy. Investments in power grid capacity are therefore needed to meet the increased future demand which this transition implicates. One part of this is the expansion of intermittent energy sources, such as wind and solar power. Even though these sources have benefits in form of cheap and green energy, they have other characteristics that need to be addressed. Per definition, intermittent power sources cannot produce energy on demand since they are dependent on weather conditions such as wind and sun. This induces a second problem which is that it can be hard to predict the production from intermittent power sources, especially wind, which increases the volatility in the power market. Because of these characteristics, the expansion of wind power has increased the volume traded on the intraday power market. The intermittent energy surge, emphasizes the need of a good trading strategy for balance responsible parties to handle the increased trading volume and volatility. The prupose of this report is to introduce the elements which affect intraday power trading, formulate the fundamentals of a power trading strategy and thereafter explore how predictive models can be used in such a strategy. This includes predicting regulating and intraday market prices using linear regression models, neural networks and LSTM-models. Furthermore, the report highlights underlying properties which affects the predictive power of a prediction model used to forecast wind power production. Regulating prices can be predicted well using both linear regression models and more complex deep learning models based on weather and market data. Both approaches are better than using a simple model based on the latest regulating and market price, since the simple model tends to fall short in a volatile market. Overall, the deep learning models performs the best.  The difference in result when predicting the volume weighted average price on the intraday market, using linear regression and machine learning, are not as substantial. In fact, the linear models tends to outperform the machine learning models in some instaces. The conclusion when analyzing how underlying properties affect wind power prediction models is that how far ahead the model predicts is not the key factor affecting predictive power. Instead, the production volume predicted has a larger effect.

This thesis aims to investigate the feasibility of using a Markovian approach toforecast short-term stock market movements. To assist traders in making soundtrading decisions, this study proposes a Markovian model using a selection ofthe latest closing prices. Assuming that each time step in the one-minute timeframe of the stock market is stochastically independent, the model eliminates theimpact of fundamental analysis and creates a feasible Markov model. The modeltreats the stock price’s movement as entirely randomly generated, which allowsfor a more simplified model that can be implemented with ease. The modelis intended to serve as a starting ground for more advanced technical tradingstrategies and act as useful guidance for a short-term trader when combinedwith other resources. The creation of the model involves Laplace smoothing toensure there are no zero-probabilities and calculating the steady-state probabilityvector of the smoothed matrix to determine the predicted direction of the nexttime step. The model will reset daily, reducing the impact of fundamental factorsoccurring outside trading hours and reducing the risk of carrying over bias fromprevious trading day. Any open positions will hence be closed at the end of theday. The study’s purpose is to research and test if a simple forecasting modelbased on Markov chains can serve as a useful tool for forecasting stock prices atshort time intervals. The result of the study shows that a Markov-based tradingstrategy is more profitable than a simple buy-and-hold strategy and that theprediction accuracy of the Markov model is relatively high. / Denna avhandling syftar till att undersöka möjligheten att använda en markoviskmetod för att förutsäga kortsiktiga rörelser på aktiemarknaden. För att hjälpaaktörer på aktiemarknaden att fatta välgrundade handelsbeslut föreslår dennastudie en markovisk modell för att förutsäga nästa stängningspris baserat påde senaste stängningspriserna. Modellen antar att varje tidssteg i ett en-minuts intervall på aktiemarknaden är stokastiskt oberoende, vilket eliminerarpåverkan från fundamental analys och skapar förutsättningen för en genomförbarmarkov-modell. Modellen behandlar aktieprisets rörelse som helt slumpmässigtgenererat, vilket möjliggör en mer förenklad modell som kan implementeraspå marknaden. Modellen är avsedd att tjäna som en utgångspunkt förmer avancerade tekniska handelsalgoritmer och fungera som en användbarvägledning för en akitehandlare med kort tidshorisont i kombination med andraresurser. Skapandet av modellen inkluderar använding av Laplace-jämning föratt säkerställa att det inte finns nollsannolikheter samt beräknandet av denstationära sannolikhetsvektorn för den jämnade matrisen i syfte att bestämmaden förutsedda riktningen för nästa tidssteg. Modellen kommer att återställasdagligen, vilket minskar påverkan från de fundamentala faktorer som inträffarutanför handelstiderna och ser till att bias inte överförs till nästa börsdag. Dettainnebär att alla öppna positioner stängs vid dagens slut. Studiens syfte är attforska och testa om en enkel prognosmodell baserad på Markovkedjor kan varaanvändbar som ett verktyg för att förutsäga aktiepriser vid korta tidsintervall.Resultatet från studien visar på att en markov-baserad trading strategi är merlönsam än en enkel köp-och-behåll strategi och att prediktionernas träffsäkerhetfrån en markov modell är relativt höga.

本文考量波動度不對稱效果(Volatility Asymmetric Effect)與均數回歸(Mean Reverting)兩個特性，並考量台股市場特性，嘗試建立一個適合台灣市場的波動度交易策略。利用GARCH(1,1)波動度與VIX指標建構第一個交易訊號，並建立當日沖銷部位。以賺取日內行情為出發點，利用時間序列模型捕捉波動度的高估或低估且搭配純跨式(Pure Straddle)策略或根據Delta調整後的跨式(Adjusted Straddle)策略。第二個交易訊號則是利用市場敏感指標，觀察外資與自營商在交易部位與未平倉部位的變化，找出對於波動度的影響。建立由選擇權與期貨組成的Delta-Hedged部位，藉由觀察市場上主力籌碼的變化，動態調整部位契約，尋找波段之間的獲利機會。 實証部分以期交所公布的每日交易資料與VIX日資料，利用2007至2008兩年的歷史資料，估計參數與測試交易訊號。樣本外期間為2009年1月開始至3月結束共55個交易日。考量交易成本後，兩個不同型態的交易訊號，仍然能夠藉由本研究的策略，獲得正的報酬。本文認為台灣為一個淺碟市場，過度反應資訊的特性，讓波動度策略出現獲利的機會。藉由這個波動度交易系統的研究，除了讓資金豐沛的機構投資人使用外，也能夠讓一般投資大眾建立自己的波動度交易策略 關鍵字:波動度交易，選擇權交易策略，GARCH(1,1)，VIX，市場情緒指標 / Trying to apply a preliminary study of volatility trading strategies in Taiwan derivative market is the topic of this dissertation. Capturing the market movement or even the dynamic of underlying asset is a Pandora’s Box for academic researchers and industry participants. Mean-reverting and asymmetrical effects are the two special characteristics of volatility for us to design our trading system according to the previous empirical studies. In our study, we use different type of volatility signal to capture the trading opportunities. Use the new released information form TAIFEX including VIX and Position Structure of Institutional Traders to design our signal. We apply the idea to use pure option position and delta-hedged position as our trading tools in this volatility trading system and look for the opportunities between realized volatility and implied volatility. An over-reaction may rises the uncertainty and also lead the market volatility change coherently. We use history data from 2007 to 2008 test our trading signal and parameters. The out sample period is from 2009 January to 2009 March which has 55 trading days to simulate our strategies. In the end, we see a positive result in both trading signals which earns positive return after considering the trading cost. Key words: Volatility Trading, Market Sentiment Indices, Option Strategies, VIX, GARCH(1,1)

The introduction of contracts for difference, CFDs, in the Nordic market has meant a tremendous freedom for both large investors and small investors. CFDs, like many other financial derivatives, allow speculation on price movements in virtually all global markets with easy access to leverage, which is the same as borrowed capital. CFDs carry high risk and hence should only be used by qualified traders.  Swedish CFD providers have been criticized for mass marketing their services with lack of regard for the industry's sustainability. The legal requirements placed on CFD providers for customer's creditworthiness and knowledge are also said to be weak, given the products complexity and high risk. Thus, the purpose with this research is to respond to the criticism by examining the level of risk management, and the level of strategic awareness among CFD traders. The epistemological orientation of this research conforms to the philosophy of positivism, and the research approach is consistent with the deductive approach. The research is based on a quantitative data collection method were a survey was carried out with CMC Markets’ customers with 233 respondents.After examining the usage of risk management tools, position sizing and monitoring; the results suggest that the level of risk management among CFD traders is moderately high. For a trading strategy to function, and hence be successful, it is important that traders are consistent with the various components that a trading strategy consists of. After examining to what extent the CFD traders positions are based on rules and signals as well as loyalty to them, to what extent they optimize their trading strategy, and lastly to what extent they use available strategy methods I came to the conclusion that there is a relatively low level of strategic awareness.Keywords: CMC Markets, Finance, CFDs, Investment, Derivative, Securities Trading, CFD Trading, Stocks, Risk management, Strategic awareness, Trading strategy, Technical analysis, Fundamental analysis