Automated Algorithmic Trading for Cryptocurrencies

The proposed project work is totally supported and easy yet effective strategy named as Martingale. An automatic system which only requires only some pre-coded instructions to execute trades on variety of market variables starting from asset price to trading volume. The strategy along with each cryptocurrency, the benchmark against which the algorithm is tested is that the market’s performance. Returns are compared with the buying and so multiplying the trade volume at each loss and different scenarios are analysed to work out the chance related to the buying compared with an algorithmic strategy. Results are going to be in love with the market’s actual trends and also with some alternate possible trends to check all market scenarios. An internet interface will accompany the presentation allowing the users to check the strategies by entering their parameters and instantly seeing the results

Exchange Rate Transaction of International Trade Goods Based on Fuzzy Granulation and Deep Learning

The change of international trade goods exchange rate transaction has an impact on economic operations and economic stability. Therefore, an international trade goods exchange rate transaction based on fuzzy granulation and in-depth learning is proposed. Based on fuzzy information granulation and BP neural network, this paper analyzes the interest rate evaluation theory. For the future expectation of currency exchange rate, portfolio equilibrium determines the proportional relationship of each component in the portfolio and analyzes the impact of asset price and exchange rate change according to this relationship. Then, it points out the risk evaluation index system, calculates the risk degree of exchange rate transaction of international trade goods, and then evaluates the risk of exchange rate transaction of international trade goods. It completes the research on exchange rate transactions of international trade goods based on fuzzy granulation and in-depth learning. The experimental results show that excessive exchange rate fluctuation will bring the same proportion fluctuation to the asset price in the financial market, and the coordination between exchange rates and the coordination of exchange rate and asset price can promote the steady growth of national economy.

Banks and Economic Growth: A Basic Disequilibrium Model with Five Rationing Regimes

In this paper, an inductive research methodology and the principle of parsimony are applied to reconsider a central issue in economics and macro-finance, namely the determinants of economic growth and the role of the financial sector. A simple framework is derived, characterised by information imperfections and the absence of market clearing. The literature on rationing has identified the need to consider differing rationing regimes but has not included a banking sector. Such a set-up is presented in this paper, which identifies the link between credit and economic growth under differing rationing regimes, with varying consequences for inflation. The familiar case of money creation resulting in inflation features as a special case within the general framework. Others are the possibility of asset price bubbles and collapses, non-inflationary growth despite full employment, and instability in banking systems. The model is consistent with empirical evidence that has been difficult to reconcile with conventional equilibrium models. It is found that within this simple rationing framework, banks, left to their own devices, do not necessarily deliver stable, non-inflationary growth, and there is no reason to expect their behaviour to optimise social welfare. Some implications for research and policy are discussed.

Asset Prices Under Knightian Uncertainty

We extend Lucas’s classic asset-price model by opening the stochastic process driving dividends to Knightian uncertainty arising from unforeseeable change. Implementing Muth’s hypothesis, we represent participants’ expectations as being consistent with our model’s predictions and formalize their ambiguity-averse decisions with maximization of intertemporal multiple-priors utility. We characterize the asset-price function with a stochastic Euler equation and derive a novel prediction that the relationship between prices and dividends undergoes unforeseeable change. Our approach accords participants’ expectations, driven by both fundamental and psychological factors, an autonomous role in driving the asset price over time, without presuming that participants are irrational.

Leaning against the Bubble: Central Bank Intervention in Walrasian Asset Markets

The paper presents a two-period Walrasian financial market model composed of informed and uninformed rational investors, and noise traders. The rational investors maximize second period consumption utility from the payoffs of trading risk-free holdings to risky assets in the first period. The central bank reacts directly to asset price movements by selling or buying assets to stabilize the market price. It is found that the intervention makes the risky asset’s market price per share less sensitive to information shocks, which presses the market price towards its average price thus reducing price variance. The informed investors’ prediction coefficient remains unaffected, but that of the uninformed investors is magnified, which cancels out the negative effect on shock sensitivity thus keeping the expected value of the risky asset’s dividend constant. Finally, the introduction of the policy rule does not affect rational investors’ risk per share. A general conclusion is that the central bank’s policy can be regarded as an effective automatic stabilizer of financial markets.