Stock Market Volatility, Risk Attitude and the Demand for Money in the UK

Is stock market volatility an important determinant of money demand in the UK? If yes, what is the driving force behind that effect? In a cointegration framework, we find that volatility in share prices is an important positive determinant of money demand, alongside standard variables and the stock price level. By studying different stock market indexes effects, we find that the risk aversion of investors is an important force behind the effect, implying that the effect is due to investors’ flight to safer assets in times of volatile stock prices

Dynamics in systematic liquidity

We develop the principal component analysis (PCA) approach to systematic liquidity measurement by introducing moving and expanding estimation windows. We evaluate these methods along with traditional estimation techniques (full sample PCA and market average) in terms of ability to explain (1) cross-sectional stock liquidity and (2) cross-sectional stock returns. For several traditional liquidity measures our results suggest an expanding window specification for systematic liquidity estimation. However, for price impact liquidity measures we find support for a moving window specification. The market average proxy of systematic liquidity produces the same degree of commonality, but does not have the same ability to explain stock returns as the PCA-based estimates.Liquidity (Economics)

Forecasting Inflation: the Relevance of Higher Moments

We provide evidence that higher moments of the relative price distribution improve out-of-sample forecasts of inflation. Further, we show how theoretically consistent higher moments can be calculated by expanding the seminal work by Theil (1967). Results presented here are of direct relevance to monetary authorities, policy analysts and academic economistsrelative price distribution, higher moments, out-of-sample inflation forecasting

Analyzing Divisia Rules Extracted from a Feedforward Neural Network

This paper introduces a mechanism for generating a series of rules that characterize the money-price relationship, defined as the relationship between the rate of growth of the money supply and inflation. Division component data is used to train a selection of candidate feedforward neural networks. The selected network is mined for rules, expressed in human-readable and machine-executable form. The rule and network accuracy are compared, and expert commentary is made on the readability and reliability of the extracted rule set. The ultimate goal of this research is to produce rules that meaningfully and accurately describe inflation in terms of Divisia component dataset

Does money matter in inflation forecasting?

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two non-linear techniques, namely, recurrent neural networks and kernel recursive least squares regression - techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation.Forecasting ; Inflation (Finance) ; Monetary theory

Meet and Run

A defense for Gia Binner’s MFA Thesis, Meet and Run, argues that accessible art, known in this paper as commercial dance, is a meaningful vehicle for social change and that it has the ability to dismantle the outdated, European concert dance dominance by modeling the interdependency of both worlds

Scotland as an optimal currency area

The June 2016 UK referendum on continued EU membership where the people of Scotland voted to remain, while the rest of the United Kingdom voted to leave, once again makes the issue of whether Scotland is an optimal currency area very topical. England voted strongly to leave Europe while Scotland backed remain by 62% to 38%. The Scottish government published its draft bill on a second independence referendum in October 2016. The move does not mean another referendum will definitely be held, but this does raise the possibility that Scotland might choose independence and staying in the EU without the rest of the United Kingdom. If Scotland charts a course of independence from the rest of the United Kingdom, then they would likely either issue their own currency or join or form another currency area. In this paper, we test the microeconomic foundations of a common currency area for Scotland, United Kingdom, and the rest of the United Kingdom without Scotland. We find that the United Kingdom, Scotland, and the United Kingdom without Scotland all meet the microeconomic criteria for a common currency area. In contrast, banking data suggest that lending in Scotland is different from lending in the rest of the United Kingdom, adding some doubt to the issue of whether or not Scotland is a common currency area with the United Kingdom.</p

Does commonality in illiquidity matter to investors?

This paper investigates whether investors are compensated for taking on commonality risk in equity portfolios. A large literature documents the existence and the causes of commonality in illiquidity, but the implications for investors are less well understood. In a more than fifty year long sample of NYSE stocks, we find that commonality risk carries a return premium of around 2.6 per cent annually. The commonality risk premium is statistically and economically significant, and substantially higher than what is found in previous studies. It is robust when controlling for illiquidity level effects, different investment horizons, as well as variations in illiquidity measurement and systematic illiquidity estimation

“Risky” monetary aggregates for the UK and US

We extend the scope of monetary aggregation beyond capital certain assets that make up central bank data sets and identify groups of assets that form monetary aggregates composed of both capital certain and risky, capital uncertain, assets. We construct monetary aggregates for the US and UK using a superlative index and relax a key assumption of the Consumption Capital Asset Pricing Model (CCAPM), a one year planning horizon, by using forecasted returns on risky assets. Our new risky monetary aggregates perform well in VAR tests. We recommended exploring risky assets as providers of liquidity services in future research on this topic