Browsing by Author "Suominen, Matti"

Now showing 1 - 20 of 61
  • No Thumbnail Available
    Item
    Alternative behavioral explanations for the MAX effect: Evidence from Finland
    (2024) Raussi, Aku; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
    The MAX effect refers to the tendency of stocks with high single-day returns during the prior month to produce weak returns in the subsequent month. Initially attributed to investor preference for lottery-like assets, more recent literature proposes alternative behavioral explanations for the phenomenon such as overreaction to new information and anchoring bias. This thesis explores these explanations in Finland, focusing on the impact of earnings announcements and the nearness of price to the 52-week high on the MAX effect. The study finds that the MAX effect disappears when only considering returns stemming from earnings announcements, and when stocks are priced near 52-week highs. Furthermore, the research reveals that idiosyncratic volatility almost entirely explains the MAX effect in Finland. Controlling for idiosyncratic volatility reduces the four-factor alpha of the MAX effect by 96.1%. Also, unlike MAX, idiosyncratic volatility can predict returns beyond the subsequent month. These findings challenge previous conclusions about the MAX effect in Finland and provide strong evidence against the lottery preference explanation.
  • Thumbnail Image
    Item
    Arbitrage capital and currency carry trade returns
    (Helsinki: Helsinki School of Economics, 2008) Jylhä, Petri; Suominen, Matti; Lyytinen, Jussi-Pekka; School of Business; Kauppakorkeakoulu
  • Thumbnail Image
    Item
    Asset allocation versus momentum strategies: findings from cross-asset allocation in equity markets
    (2021) Bouyahia, Alex; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
    Mean-variance-based asset allocation and momentum are common strategies in the investment industry. These strategies are generally based on the assets’ past returns that are used to form expectations on the assets’ future movements. Thus, the mean-variance and momentum strategies are related through the used past returns in portfolio formation. Due to this connection, this thesis examines whether allocation strategies use past returns more effectively than time series momentum strategies and answer the question: Do asset allocation strategies outperform time series momentum strategies? The implemented asset allocation methods in this study are the mean-variance with robust estimates and the Black-Litterman approach. I evaluate the allocation and momentum strategies’ performance in an empirical test with an international sample of 20 leading developed countries’ equity index returns. Moreover, from prior literature, I apply the documented bond-equity cross-asset phenomenon illustrated in the context of time series momentum to construct cross-asset allocation strategies. Thus, allocation strategies are built based on past equity and bond market returns. This thesis contributes to the existing literature in three ways. First, I show that the equity-based allocation strategies produce larger Sharpe ratios than the momentum strategies with the cost of obtaining higher risk exposures. Second, the equity-based allocation strategies’ returns are mainly explained by the time series momentum when the portfolio formation windows are 12-months. Finally, I find that the bond-based cross-asset allocation strategies obtain low risk-levels and generate positive and significant multifactor alpha over common risk factors and momentum strategies. The results imply that these cross-asset allocation strategies find information from past bond market returns that generate abnormal returns in the equity market.
  • Thumbnail Image
    Item
    Attention-related predictability in the stock market
    (2024) Ketonen, Saku; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
    The attention of investors has profound implications on their investment decisions and the aggregate movements of the markets. It underlies the learning of new economic information as well as the decisions to act. The prior body of academic literature has detailed the nature of attention both theoretically and empirically. Theoretical models consider attention to be a limited resource, which is allocated to reduce the uncertainty in portfolios and to generate higher economic gains. Empirical studies have validated these notions and provided further insights by employing investor attention proxies to measure it indirectly. Notably, the absence of attention has been associated with the prominence of post-earnings-announcement price drifts, in which the stock prices tend to continue drifting in the direction of the earnings surprise. The present study aims to determine whether the price drifts are influenced by the ownership structures of the companies, with a focus on the implications of institutional attention for the price efficiencies and the predictability of these drifts. In addition, the utility of investor attention proxies in combination with modern machine learning methods for predicting the price drifts is evaluated. The research methods employed are primarily based on regression analyses and the application of neural networks. Stocks classified as being institutionally owned displayed more efficient prices than the stocks with a more retail-oriented investor base. Conversely, the price drifts of retail-owned stocks appeared to be more predictable. Additionally, the combination of modern machine learning methods and investor attention proxies turned out to provide substantial practical utility in predicting the post-earnings-announcement price drifts and generating economic gains. In particular, it was found that the price drifts following negative earnings surprises were more predictable and greater in magnitude than those following positive earnings surprises, yielding information ratios twice as large in comparison. Overall, the conducted analyses provided further insights into the progressions of post-earnings-announcement price drifts and demonstrated the viability of using machine learning methods combined with investor attention proxies in forecasting them. Although the results of this study were compelling, numerous areas for improvement and further exploration were identified.
  • No Thumbnail Available
    Item
    Beta bubbles
    (2018-06) Jylhä, Petri; Suominen, Matti; Tomunen, Tuomas; Department of Finance; Columbia University
    We show that an increase in a stock’s breadth of institutional ownership or turnover is followed by a significant, but temporary, increase in its CAPM beta estimate and a decrease in its CAPM alpha. The increasing effect of breadth of ownership on beta estimates is mainly driven by short-term investors. These transitory trading-activity-driven components of beta estimates contribute to the empirical failure of the CAPM and the large returns to long-short portfolios that bet against beta. Relations between ownership breadth, turnover, and betas, which we document, help explain the puzzling fact that, on average, betas increase after seasoned equity offerings and stock splits and decrease after stock repurchases.
  • No Thumbnail Available
    Item
    Brave New World of Strategic Asset Allocation: Theory and Evidence from The Norwegian Government Pension Fund Global
    (2018) Hurskainen, Jere; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
  • No Thumbnail Available
    Item
    CAE system in The Structural Design of a Composite Aircraft
    (1988) Suominen, Matti; Ahopelto, Erkki; Konetekniikan osasto; Teknillinen korkeakoulu; Helsinki University of Technology; Saarela, Olli
  • No Thumbnail Available
    Item
    Characteristics of Bitcoin Volatility at High Frequency
    (2018) Mankinen, Harri; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
    This thesis models and examines the realized bitcoin volatility calculated from five-minute intraday squared returns and its unconditional distribution. The study also explores the intraday periodicity and volatility persistence in bitcoin markets. In addition, the thesis tests if there are day-of-the-week effects for bitcoin returns and volatility. Lastly, the study compares model-free realized volatility measures to linear and nonlinear GARCH-models and tests their prediction power to find the most efficient model for bitcoin volatility. I use all transactions for BTCUSD between January 2014 and February 2018, using data from four cryptocurrency markets which CME uses to calculate their bitcoin price index, which represent currently the closest thing to an official BTCUSD price. This amounts to a total of 67,600,230 trades. After the descriptive analysis of the data, I calculate five-minute interval logarithmic returns from the aggregate dataset. I use kernel density functions to create the volatility distributions, and I employ various tests and regressions to research the intraday periodicity and persistence of bitcoin volatility. I construct 10 different GARCH specifications and compare their fit in-sample and out-of-sample by using four different information criteria, two robust loss functions and adjusted coefficient of determination as the comparison measures. The robustness of the results is confirmed using different intraday sampling intervals, namely 1-minute and 30-minute intervals The main findings of this thesis are that the distribution for realized bitcoin volatility are extremely fat tailed, or leptokurtic. Furthermore, the volatility has a long lasting and high persistence, and the autocorrelations are statistically significant for long periods. The findings for unconditional distributions, and volatility persistence are consistent and similar with prior research on currencies and equities. Interestingly and on the contrary to currencies and equities, bitcoin intraday periodicity does not show the typical U-shaped pattern, which is likely due to absence of institutional traders and market makers, and the possibility to trade 24 hours a day. In addition, nonlinear GARCH-models, especially CGARCH gives the best in-sample model fit for bitcoin, which also performs best with out-of-sample forecasts, suggesting the importance of having both short-run and long-run components of conditional variance when modeling bitcoin volatility using intraday data. This study adds to the existing literature by suggesting a transfer of academic interest from the traditional asset classes to cryptocurrencies and how to model and estimate their unconditional distributions and volatility. According to my best knowledge, this is the first study to model the unconditional distribution of the realized volatility for bitcoin, and the first to compare RV and GARCH models for bitcoin using intraday data.
  • No Thumbnail Available
    Item
    Circuit breakers and market crashes: Evidence from China
    (2016) Kahelin, Antti; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
    Purpose of the study Circuit breaker is a market mechanism intended to curb excessive volatility by halting continuous trading after a significant intraday price deviation. Existing literature identifies four key problems with circuit breakers: magnet pull effect, delayed price discovery, trading interference and volatility spillover. The empirical literature on market wide circuit breakers is limited due to lack of observations. This thesis contributes to existing literature by bridging the gap between empirical research on price limits affecting individual securities and theoretical literature on market wide circuit breakers by being the first to empirically test the four aforementioned hypotheses using the case of China’s circuit breaker implemented between 4.1.-7.1.2016. Data and methodology The data consists of A shares of Shanghai listed CSI300 index constituents, and their Hong Kong traded H shares for the dual listed companies. In addition to the event window, the data for control samples extends from 1.1.2011 to 31.3.2016. The hypotheses are tested by comparing the circuit breaker sample to two control samples: 1) A ”matched” control sample, where an observation with the closest corresponding intraday return is matched with a circuit breaker day observation. 2) Hong Kong control sample, where the dual listed A shares are compared to their corresponding Hong Kong listed H-shares. This approach is novel to this branch of literature, and is more robust in the sense that both A- and H-shares react simultaneously to same information regarding the underlying cash flows. Findings I find, that shares with low market capitalization, high market correlation, high turnover and tight bid-ask spreads perform the worst during the circuit breaker. I also find strong evidence of magnet pull hypothesis in the form of increased selling pressure in the close proximity to the circuit breaker trigger level. I find no significant evidence of delayed price discovery or trading interference. Furthermore, I find evidence of volatility spillover caused by increased uncertainty as proxied by relative bid-ask spread. I show that in anticipation to circuit breaker’s implementation, sophisticated investors prefer to trade in Hong Kong markets that are unaffected by the policy. Furthermore, by analyzing the dual listed shares I show that in a market affected by circuit breaker this ’migration of trading volume’ magnifies the feedback loop behavior that is driving magnet pull, but mitigates the same problems in the absence of one. Findings are mostly consistent with empirical literature on price limits, and differ in ways that would be expected based on theoretical framework. The results imply that circuit breaker caused the problems it is intended to solve.
  • Thumbnail Image
    Item
    Contrast effects in reactions to earnings announcements
    (2022) Haavisto, Arttu; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
    Contrast effect is a behavioral error, where a related prior observation has an inverse effect on the perception of the following one. New evidence in financial literature shows that the effect has potential to induce short-term mispricing when investors contrast consecutive pieces of earnings announcement news on one another. The purpose of this paper is to revisit the topic and to study the effect by employing a new set of data consisting of large publicly listed U.S. companies in the 21st century. The results presented in this paper are inconclusive and to an extent contradicting with prior literature. The results of the full-sample OLS regressions show no evidence of a contrast effect between any proxy for a salient earnings surprise and the short term returns of firms announcing their earnings the following day. However, splitting the sample into subsamples based on business cycles shows that, during the longest continuous economic expansion period from 2009 to 2020, the contrast effect is economically and statistically significant, albeit not robust to the inclusion of year-month fixed effects. During this period, the mispricing persists for up to five trading days, and is driven by consecutive announcements by firms in the top NYSE size decile.
  • Thumbnail Image
    Item
    Dash for Cash: Monthly Market Impact of Institutional Liquidity Needs
    (Oxford University Press, 2020-01) Etula, Erkko; Rinne, Kalle; Suominen, Matti; Vaittinen, Lauri; Department of Finance; Goldman Sachs Group; Mandatum Life
    We present broad-based evidence that the monthly payment cycle induces systematic patterns in liquid markets around the globe. First, we document temporary increases in the costs of debt and equity capital that coincide with key dates associated with month-end cash needs. Second, we present direct and indirect evidence on the role of institutions in the genesis of these patterns and derive estimates of the associated costs borne by market participants. Third, and finally, we investigate the limits to arbitrage that prevent markets from functioning efficiently. Our results indicate that many investors and their agents, including mutual funds, suffer from liquidity-related trading.
  • No Thumbnail Available
    Item
    Decomposing and Reconstructing Time-Series Momentum with Discrete Wavelet Transform
    (2016) Akrenius, Patrik; Jokivuolle, Esa; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
    OBJECTIVES OF THE STUDY: The momentum phenomenon is one of the most studied phenomena in finance, covered by research within various geographical markets, time frames, and asset types. The methodologies used for portfolio creation in these research studies are very diverse. This thesis contributes to the research gap by examining time-series momentum using wavelet decomposition in momentum portfolio creation. Wavelet methodologies fit research within time series in finance and economics particularly well, as decomposition into wavelet coefficients allows analyzing processes that occur naturally at different time scales. Traders make decisions at various time intervals ranging from minutes to years, and wavelet decomposition allows examining these intervals closer. DATA AND METHODOLOGY: My sample consists of monthly S&P 500 returns over the period of January 1965 to December 2015. This study replicates time series momentum portfolios of Moskowitz et al. (2012) and supplements the initial portfolio creation strategies with wavelet decomposition with the aim of finding main constituents to momentum and denoising the data used as a basis to form the portfolios. FINDINGS OF THE STUDY: The analysis shows strong evidence that wavelet decomposition improves portfolio creation and provides almost seven times higher returns than the literature standard time-series momentum strategy over the in-sample period. However, the higher returns occur through a higher portfolio turnover rate. The findings suggest that the decomposed trading signal is more sensitive to changes in momentum in the S&P 500 Index, and due to the higher number of transactions required compared to the classic strategy, a proper real-world implementation requires filtering further the statistical significance of the trading signal in order to avoid unnecessary transactions.
  • No Thumbnail Available
    Item
    Design of the high speed box beam suitable for mass production
    (1991) Anttila, Esa; Suominen, Matti; Konetekniikan osasto; Teknillinen korkeakoulu; Helsinki University of Technology; Saarela, Olli
  • No Thumbnail Available
    Item
    Developing a mobile application for collecting multimodal electrocardiography and motion sensor data
    (2018-05-14) Suominen, Matti; Palva, Lauri; Suotsalo, Kimmo; Sähkötekniikan korkeakoulu; Särkkä, Simo
    Electrocardiography (ECG) measures the electrical activity of the heart. Being able to obtain accurate information from the heart is important for reliable diagnosis. Accurately measuring ECG can be difficult if the patient is moving, because movement causes artifacts in the ECG. This thesis describes a measurement system that simultaneously records ECG and the movement of a patient. The measurement system consists of a mobile phone, multiple inertial measurement units (IMU), and a portable ECG device. The devices communicate with Bluetooth. Combining data from multiple different sources, especially synchronizing the data, can be difficult. This thesis presents solutions for the challenges. For the data collection, two different methods were compared: streaming the data to a mobile phone, or storing the data to sensor memory and retrieving it later. Out of these methods, the internal memory method was more reliable, so it was deemed better for the purpose of the measurement system. A functional measurement system was developed, and data was collected with the system. The quality of data is good, and the system can be used for data collection from test subjects. However, the system still has some problems. Reliability of the system is an issue especially with the streaming method, and the lack of real-time data collection and the limited size of the internal memory are issues with the internal memory method.
  • No Thumbnail Available
    Item
    Dividend Month Premium in the United Kingdom
    (2019) Kumral, Kadir; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
  • No Thumbnail Available
    Item
    Does Corporate Social Responsibility Still Pay Off? Positive and Best-in-Class Screening Portfolios by Using MSCI ESG Ratings in 1992-2017
    (2020) Kokljuschkin, Anton; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
    ESG Investing, i.e. investing based on Environmental, Social, and Governance considerations, is an increasingly more important topic amid investors. Previous research has found positive and statistically significant excess return in positive and best-in-class screening methods especially when applying the Community and Employee Relations category portfolios. In the late 2010s, controversial results have appeared in ESG literature. However, risk-adjusted research on ESG ratings and future returns has not been conducted after 2012. This thesis examines the fundamental question of ESG investing: whether stocks with high MSCI ESG ratings exhibit excess return. The thesis studies whether ESG ratings exhibit the excess return when using the positive screening method in the previously examined period of 1992–2004 and the best-in- class screening method in the time period of 1992– 2007. More interestingly, the thesis examines the periods after the initial studies: 2005–2017 for the positive screens and 2008–2017 for the best-in-class screens. Furthermore, the whole sample of 1992–2017 is examined for both screening methods. The thesis contributes to the existing literature in the following three different ways. First, the thesis mostly confirms the results of previous research by Kempf and Osthoff (2007), and Statman and Glushkov (2009) about the statistically significant relation between the financial performance and MSCI ESG rating of companies. The Community screen portfolio resulted in positive and statistically significant returns when employing the best-in-class screen. Further, Employee Relations yields statistically significant results when positive screening is used. Furthermore, this thesis finds that the Diversity category exhibited positive and statistically significant 3.97% annualized excess return while in the previous studies the result remained barely statistically insignificant. Second, the thesis finds that the positive and statistically significant results disappear after initial time period in 2005–2017 and 2008–2017. The Community and Employee Relations screen portfolios turn mostly negative yet statistically insignificant. More interestingly, the Diversity category exhibits statistically significant annualized excess return of -4.72%. Furthermore, the Environmental screen portfolio yields statistically significant 3.40% annualized excess return. Third, the thesis measures the whole sample time period of 1992–2017. Nearly all the results from the prior time periods disappear when using the entire time period. Only when using positive screening, the Products category results in a negative and statistically significant return of -2.51%.
  • No Thumbnail Available
    Item
    Does unusually low trading volume signal negative information?
    (2016) Poikela, Satu; van Bommel, Jos; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
  • Thumbnail Image
    Item
    Dynamics of corporate and sovereign credit spreads in Europe – Changes during and after the debt crisis
    (2018) Nummela, Elina; Suominen, Matti; Jokivuolle, Esa; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
    Purpose of the study The objective of this thesis is to study whether changes in European sovereigns’ credit spreads affect credit spreads of local banks and firms, and the other way around. European banks and sovereigns have been proven to be interconnected through spillovers of credit risk during crisis periods (Acharya et al., 2014). The aim of this study is to test whether recently introduced regulation and the European Banking Union have been able to break the link that is harmful for the stability of the financial sector and to European economies. In addition, I study whether a similar connection of credit spreads exists between non-financial firms and sovereigns as well, a relation that is scarcely discussed in existing literature. Data and methodology The sample consists of a panel dataset of credit default swap spreads of 14 European sovereigns, 31 banks and 113 non-financial companies between January 2009 and June 2017. Historical CDS data is fetched from Datastream and control variables from several sources. Changes in the relation between sovereign and corporate credit spreads is studied with linear panel regressions on daily changes in CDS spreads, controlling for market movements and day and firm fixed effects. The sample is divided into four sub-periods to test whether regulatory improvements have decreased the co-movement between credit spreads. In addition, several interaction variables are added to the regression models to test for the existence of different channels of credit risk transfer. Findings The results show a two-way dynamic between sovereign and corporate credit risk in Eurozone countries. Changes in sovereign CDS spreads significantly affect firm CDS spreads over and above market movements and firms’ own equity returns, while sovereign spreads are also meaningfully affected by changes in the private sector’s credit risk. The findings differ meaningfully between studied sub-periods, and the two-way relation between financial sector and sovereign spreads diminishes after 2014. Effects for the non-financial sector are more persistent, but economically smaller. In addition, I find that banks and firms are more affected by sovereign credit risk if they are likely to receive government support, or have a credit rating close to the sovereign rating. Banks holding large amounts of domestic bonds and firms that are more dependent on bank financing are also more vulnerable to sovereign risk.
  • No Thumbnail Available
    Item
    Economic momentum and equity returns
    (2022) Nurmi, Julius; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
    In this thesis, I take inspiration from Dahlquist and Hasseltoft (2020), who find that investing in the currency market according to past trends in macroeconomic indicators generates significant excess returns not explained by conventional risk factors and currency trading strategies. I expand their approach to the universe of equity indices by creating a trading strategy that invests in international equity indices according to past trends in economic momentum, attempting to take advantage of equity return predictability, which has been vastly studied and documented in academia. I show that equity return predictability can be harnessed into a profitable investment strategy by investing in indices of countries with negative macroeconomic trends, while short-selling indices of countries with positive macroeconomic trends. Although some of the performance has eroded over time, using an investment signal consisting of a combination of industrial production, retail sales, and the inverse of unemployment, proves robust also in subsamples split by timeframe or geography. No conventional risk factors are able to explain these returns, however it should be noted that I have not accounted for transaction costs when running the strategies in historical data.
  • Thumbnail Image
    Item
    The effect of ECB's pandemic emergency purchase program to European corporate bond yields
    (2021) Koho, Anton; Suominen, Matti; Rahoituksen laitos; Kauppakorkeakoulu; School of Business
    I assess the effect of European Central Bank’s Pandemic Emergency Purchase Program (PEPP) to the European corporate bond yields in the secondary market during the year 2020. I find evidence suggesting that bonds eligible to the program experienced significantly larger decrease in yield spreads (swap spreads) after the initial announcement of the purchase program (announcement effect) as well as after the start of the ECB’s purchases (direct effect). The announcement effect after the third PEPP announcement in December 2020 is completely different as eligible bonds increased more in yield spread.