Hong Kong does not sell land but instead only offers lease contracts, while creating artificial land scarcity, yet the country ranks number one on the economic freedom index. My research is questioning how such alternative housing and land regulations affect economic freedom and indirectly foreign direct investment. Is this model an exemplary solution to improve economic freedom in densely populated areas? Alternatively, is the regulation perhaps not fully understood and not taken into account when creating the economic freedom index? Or is the local regulation rather an intended tool to improve the ranking and attract investments? To find out, the aim is to research the policies' effect on public perception of the housing market, the degree to which financial models in the real estate market take these limitations into account, and the effect on foreign direct investments. These three research focuses will clarify the policies' effect on ordinary citizens and incentives for policymakers and investors.

To analyse the situation I'm taking a journalistic approach in reaching out to policymakers, real estate experts and investors to understand their different perspectives and relate them to the mathematic models which are applied in the financial sector. This research is made possible with the Warwick, Hong Kong exchange programme.

The amount of available cryptocurrency news data is constantly growing, posing the question of whether this can be exploited to create profitable automated cryptocurrency trading systems. This research explores the viability of using deep learning models to forecast changes in cryptocurrency prices using a vast data set of news articles and social media posts. A robust sentiment analysis model is used to extract sentiment scores, converting the news data into a quantitative data set. Three different models are built with corresponding trading strategies to test their profitability using a large 7-month test period of unseen data. All three models perform very well, especially during volatile periods, with the best model achieving an overall return on trades of 287.9%, as well as 91.3% profitable trades during the test period. One of the key findings is that models incorporating news data greatly outperform those that do not, suggesting that the Efficient Markets Hypothesis may not be applicable to cryptocurrency trading. Additionally, incorporating technical analysis indicators into the data set seems to make a small impact on the profitability of the models, bringing into question their widespread popularity.

Historians have offered different interpretations of the origins of the Pacific War. Interventionists have collided with revisionists over the ultimate cause of the Japanese attack on Pearl Harbor. According to the Interventionists, the Pacific War started with a handful of Japanese militarists displaying such extreme aggression that the United States had to resist. Revisionists assert that the Axis powers did not endanger American security; Roosevelt knew that his policies would result in war.

There were numerous milestones that led to the Pacific War. My research provides an in-depth analysis of two: first, the freezing of Japanese assets and placing an oil embargo on Japan in August 1941 and, second, the US final requirements to Japan to reopen trade in November 1941. These two milestones are important because they highlight two pivotal elements for Japan - its dependence on foreign oil and its historic interest in China.

The first part of the research analyzes the oil embargo, while the second part of the research reviews the US requirements to Japan to restart trade. Both parts start with a factual overview, referencing sources by such historians as Basil Rausch, Wayne S. Cole, and Minoru Nomura. Next, the oil embargo and the ultimate demands are presented through the lenses of revisionists (Harry E. Barnes and William H. Chamberlain) and interventionists (Basil Rauch, Forrest Davis, and Herbert Feis). Finally, it is explained why the revisionist perspective is more persuasive: the US provoked Japan for the US to enter WWII through the "Asiatic Back Door.�

Following the 2008 global financial crisis, investors have increasingly turned to emerging market investments to seek higher returns. However, lack of liquidity in such economies has been a source of barrier to foreign investment. In the next few years, 70% of global economic growth is expected to come from these emerging economies (IMF, 2019). Therefore, my presentation will examine how liquidity can be improved in these countries and the impact this will have on the global economy.

This work intends to develop understanding of liquidity in emerging markets, through comparative research of India, Colombia, South Africa and Brazil, to identify – (1) the causes of illiquidity in emerging economies. (2) the problems faced by foreign investors and (3) how improved financial infrastructure in these countries will improve future liquidity. By conducting this research, I hope to understand what companies and investors can do to improve liquidity.

Emerging markets provide investors with high risk and high returns, an alternative to the much lower interest rates found in developed countries. Accessing these markets can be tricky for investors due the lack of liquidity and this has had a large impact on foreign investment. However, as these countries grow and their financial infrastructure (i.e. Stock Market) develops, their markets will become increasingly accessible to foreigners.