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The crisis of 2008 started with asset price bubbles which spread to other sectors, thus driving a recession. Turmoil in the housing sector can directly harm the domestic economy and financial stability. The research aims to analyze macroeconomic variables that can affect asset prices in Indonesia and how the inflation-targeting framework directly affects asset prices. This study contributes to the current research, such as the early warning system for the asset sector that the crisis of 2008 started with asset price bubbles. The Inflation Targeting Framework (ITF) policy used by the Central Bank has shown its effectiveness in the property sector. It can be seen that a negative response is shown from property prices when there are inflationary shocks. The response of interest rates to fluctuations in housing prices is stronger than the response of housing prices to fluctuations in interest rates. It indicates that the interest rate stimulus is more reactive to changes in housing prices as an accommodation of housing price volatility. GDP and money supply will respond negatively to property price fluctuations, which can lead to a crisis because GDP responds negatively. The strengthening of fiscal and monetary policy can soften the volatility of asset prices.

In this study, we investigate the impact of industry‐based tail dependence risk on the cross‐section of stock returns. To this end, we propose a novel tail risk dependence measure (industrial tail exposure risk [ITER]), which captures the tail risk exposure of individual stocks to multiple industries. Using US equity real estate investment trusts (REITs) data from 1993 to 2020, we document that stocks in the highest ITER portfolio outperform stocks in the lowest ITER portfolio by 8.40% per annum. This positive return spread is significant even after controlling for well‐known firm characteristics. The return premium of ITER is stronger for small, value, and highly levered stocks and is substantially high during recession periods. Finally, the effects of ITER are cross‐sectionally more associated with REITs that have greater degrees of the following factors: bivariate tail exposure risks of major industries, exposure to local industry tail risk, geographical concentration, and ownership of home‐biased investors. Overall, our results suggest that REIT investors are indeed averse to tail risks that are associated with various sectors. [ABSTRACT FROM AUTHOR]

In the first half of 2022, China issued a package of policies to stabilize the economy, which proposed to expand credit supply and promote the steady decline of real loan interest rates. However, at the beginning of COVID-19, the policy of interest rate reduction in major economies such as the US and Britain failed to effectively stimulate economic recovery, even led to increased pressure on economic stagflation risk and the rising of asset prices, which should be taken as a warning by China. This paper uses data from Wind database, the Peoples's Bank of China and CIEnet statistics database. It constructs a mixed-frequency and markov-switching dynamic factor(MF-MS-DFM)model to measure the business cycle of China's economy, then examines the impact of interest rate cuts on macroeconomic and asset prices and the role of financial credit channel during different periods of economic cycle by constructing a counterfactual structural vector auto-regressive(CSVAR)model. The results show that during the economic expansion period, the interest rate reduction will accelerate the expansion of financial credit, and the financial credit channel can amplify the stimulating effect of the interest rate reduction on the macro-economy, but during the economic contraction period, the interest rate reduction will slow down the expansion of financial credit, and the financial credit channel will weaken the boosting effect of the interest rate reduction on the macroeconomy. During the period of economic expansion, the financial credit channel will magnify the devaluation effect of interest rate reduction on RMB, strengthen the role of interest rate reduction in pushing up house prices and stock prices, and mitigate the rise in bond prices caused by interest rate reduction. This paper proves that 1)the financial credit channel is an important factor in the effect of interest rate reduction on macroeconomic boost, and financial credit channel in the economic contraction period may cause the interest rate reduction to be unable to effectively stimulate the economic recovery; 2)during the economic expansion period, the housing price and the stock price rise after the interest rate reduction exist credit driven factor. Compared with the existing literature of the same kind, this paper makes the following three extensions: first, this paper takes into account the pro-cyclical nature of financial credit in the empirical research design. To accomplish this objective, it conducts a regional study on the sample data in the economic expansion period and the economic contraction period to make the research results more accurate and targeted. Secondly, in the view of data which are applicated, a single frequency of data is not used, but mixed frequency data is used to measure the economic cycle and construct macroeconomic indicators, retaining complete data information to make the measurement results of the economic cycle and the measurement of macroeconomic development level more reliable; Thirdly, in the view of model methodology, a counterfactual approach was used to strip away the impact of financial credit channel interference in the policy effect of interest rate cuts. By comparing the estimated results of benchmark models, the role of financial credit channel in the transmission mechanism of interest rate cuts can be accurately and intuitively demonstrated. The research in this article proves that financial credit channel is an important reason for the differences in the effects of interest rate reduction policies in different economic cycle stages. It provides references for the central bank to pay attention to the direction of interest rate policy formulation in different economic cycle stages, helps the central bank process interest rate policies more finely, and guides the central bank to enhance the macroeconomic boosting effect of interest rate reduction through financial credit management. [ABSTRACT FROM AUTHOR]

Purpose. The author targets the creation of an analytical investment framework by merging existing statistical techniques. The paper aims to introduce a framework constructed for the Georgian economy that can assist investors in analyzing the medium-term implications of different macro scenarios. For this, a tactical and strategic asset allocation decision-making framework was developed to optimize portfolios by employing a Balanced Portfolio approach, with the help of forecasted macroeconomic variables using econometric techniques (VECM – Vector Error Correction Model; Taylor rule estimation with OLS – Ordinary Least Squares). The author also intends to lay the foundations for future research regarding the investment characteristics of the emerging market. Design/methodology/approach. The first forecasts of inflation and policy rate are obtained with the Vector Error Correction and Taylor rule models. Macroeconomic forecasts/ projections are then applied to link asset price developments derived from Monte Carlo simulations. Finally, the Balanced Portfolio approach is utilized to optimize asset weights given different scenarios. Findings. The results show that this approach lowers risk in all assumed scenarios and obtains better returns compared to plain vanilla efficient-frontier optimization. Portfolios have better risk-return profiles than before optimization with this approach. These results were obtained by using the macro model described in the paper. Originality. The paper aims to introduce a framework that is a combination of multiple well-established macroeconomic and investment models in the academic community, which is tailored for a developing economy such as Georgia. Thus, the originality of the research rests in the method of choosing specific techniques, variables, and connections between different models to best estimate the optimal portfolio given the objective of the investment. [ABSTRACT FROM AUTHOR]

In models of financial frictions, stock market booms tend to follow adverse liquidity shocks. This finding is clearly at odds with the data. We demonstrate that this counterfactual result is specific to real business cycle models with exogenous growth. Once we allow for both endogenous productivity and growth, this puzzling price dynamic easily disappears. Intuitively, the gloomy economic‐growth outlook following an adverse liquidity shock generates a predictable and negative long‐run component in dividend growth, leading to the collapse of equity prices. [ABSTRACT FROM AUTHOR]

This paper studies a two‐country version of the standard banking model with financial markets to investigate the effects of financial market globalization on financial stability. In autarky, two types of banks arise endogenously: some always remain solvent and others can default. When the financial markets are integrated, three types of banks can arise endogenously, and some banks go bankrupt because of the liquidity shock of another country. I show that financial market globalization can cause financial contagion and reduce welfare. In addition, the endogenous heterogeneous risk profile of the two countries can be observed. [ABSTRACT FROM AUTHOR]

We develop several innovations to bring the best practices of traditional investment funds to the blockchain landscape. Specifically, we illustrate how: (1) fund prices can be updated regularly like mutual funds; (2) performance fees can be charged like hedge funds; (3) mutually hedged blockchain investment funds can operate with investor protection schemes, such as high water marks; and (4) measures to offset trading related slippage costs when redemptions happen. Using our concepts – and blockchain technology – traditional funds can calculate performance fees in a simplified manner and alleviate several operational issues. Blockchain can solve many problems for traditional finance, while tried and tested wealth management techniques can benefit decentralization, speeding its adoption. We provide detailed steps – including mathematical formulations and instructive pointers – to implement these ideas and discuss how our designs overcome several blockchain bottlenecks, making smart contracts smarter. We provide numerical illustrations of several scenarios related to our mechanisms. • Innovations to bring the best practices of traditional funds to blockchain. • Update fund prices, charge performance fees and incorporate investor protection. • Detailed steps to implement these ideas as blockchain smart contracts. • Highlight main issues with the operation of mutual funds and hedge funds. • Discussion of how blockchain technology can alleviate those concerns. [ABSTRACT FROM AUTHOR]

This paper first, investigates the responsiveness of stock prices to changes in interest rates in Malawi, a low-income country in sub-Saharan Africa. Secondly, determines whether Gross Domestic Product of such economies respond significantly to changes in stock prices. Time series data from January 2001 to December 2019 are utilised. Unit root tests indicate that each variable is integrated of order one and the Johansen test for cointegration reveal that the variables are cointegrated, with one cointegrating equation. Therefore, a vector error correction model has been adopted to investigate the short and long-run dynamic relationship among the variables. Results of Granger causality tests and impulse response analysis indicate that stock prices do respond to changes in interest rates. Moreover, Gross Domestic Product also responds to changes in stock prices. Thus, contrary to previous studies, this paper finds that an asset price channel operating through stock prices exists in Malawi. More specifically, this study finds that variations in interest rates cause significant changes in stock prices which in turn cause changes in Gross Domestic Product. Among others, the study recommends that the monetary authorities should raise public awareness on investment opportunities available in stock markets.

This paper introduces one unique price motion process with fractional Brownian motion. We introduce the imaginary number into the agent’s subjective probability for the reason of convergence; further, the result similar to Ito Lemma is proved. As an application, this result is applied to Merton’s dynamic asset pricing framework. We find that the four order moment of fractional Brownian motion is entered into the agent’s decision-making. The decomposition of variance of economic indexes supports the possibility of the complex number in price movement.

Using a rare disaster risk database from almost the last one hundred years, we examine the differences in the reaction of asset prices to rare disaster risk between commodity and financial assets. We first employ time-varying parameter VAR (TVP-VAR) models to investigate the role of rare disaster risk in the price dynamics of major asset markets. The results indicate that disaster risk generally has a more intense and persistent impact on crude oil and stock markets when compared to gold and bond markets. However, the role of rare disaster risk differs substantially between commodity and financial assets, as well as between the short and long term. Moreover, when using a nonparametric causality-in-quantiles method to detect causal relationships, we provide evidence of the nonlinear causality effect of rare disaster risks on asset volatilities, and not their returns, except for crude oil. In addition, we demonstrate that augmenting a diversified portfolio of stock or bonds with gold can significantly increase its risk-adjusted performance. The findings have important implications for investors as well as policymakers.

The purpose of this study was to analyze factors affecting the housing market by setting household loans and M2, which are liquidity indicators, and the industrial production index reflecting economic fluctuations, as variables, and to determine the effect of expected housing prices. An empirical analysis was conducted based on the data from January 2005 to May 2020, and the HP filter was applied to the real house price as the expected house price variable. As a result of the analysis, it was found that real household loans, real M2, and so on, had an effect on house prices, and expectations for past house prices and house prices increased the house prices in the present period. These results show that even though the liquidity expansion is aimed at revitalizing the economy, it can affect housing prices as well. [ABSTRACT FROM AUTHOR]

Based on the three functions of currency internationalization, including exchange medium, pricing currency and foreign reserve, this paper explores how the degree of currency internationalization affects the impact of the exchange rate and the asset price on valuation effects. Using samples of 161 countries or regions from 2001 to 2016 and the threshold regression method, we find that, firstly, there is a threshold effect of the exchange rate on valuation effects due to currency internationalization. The higher the comprehensive level of currency internationalization is, the greater the positive impact of the exchange rate on valuation effects will be. Secondly, the threshold effect of the asset price on valuation effects due to currency internationalization is not significant because of the high stickiness of asset price. Besides, compared with developed countries, currency internationalization is more important to increase valuation effects through exchange rate channel and asset price channel in developing countries or regions. Finally, there are some differences in the three types of currency internationalization functions. The promotion of exchange medium function will lead to a greater positive impact of the exchange rate on valuation effects, as well as pricing currency function. However, the foreign reserve function has no such effect. [ABSTRACT FROM AUTHOR]

The ARIMA model is widely adopted by the financial industry as the standard statistical instrument for forecasting asset returns. Numerous studies have compared the accuracy of the ARIMA model with other competing models. However, there are no studies that cover a broad range of equities and their time series. Furthermore, there is no clear guideline on the time series window selected to fit the ARIMA model. In addition, there are no firm conclusions on whether older information in the sample should be abandoned. This makes it impossible to draw a definitive conclusion about the predictive power of the ARIMA model. This study sets out to address this gap in the literature. It summarizes more than two million ARIMA forecasts of future daily returns, using data from January 3, 1996 to May 12, 2017. The forecasts are run with different model parameter settings. We find that the five-year sliding fixed-width window fits US equity market asset prices to the highest degree, with an annual over-optimistic error of 2.6561%. However, when environments with positive and negative returns are separated, the ARIMA models generate forecasting errors of − 0.0009% and 0.011%, and both underestimate gain and loss. These errors are lower for low volatility equities. We conclude that the lack of nonlinearity of the ARIMA model is not a major concern, and that the ARIMA models do not lose their validity if the data windows are carefully selected. Our conclusions are not in conflict with the weak form market efficiency hypothesis and are robust in an environment with transaction cost. [ABSTRACT FROM AUTHOR]

This paper examines the effect of monetary policy on the market value of the liquidity services that financial assets provide, known as the liquidity premium. The theory predicts that money supply and nominal interest rates have positive effects on the liquidity premium, but asset supply has a negative effect. The empirical analysis with U.S. data confirms the theoretical predictions. The theory also proposes that the liquidity properties of assets can cause negative nominal yields when the money holding cost is low and liquid assets are scarce. The suggestive empirical findings in Switzerland to support this theoretical result are presented. [ABSTRACT FROM AUTHOR]

We analyze in this paper the problem of choosing the optimal portfolio for investors under uncertain exit random time. We consider the portfolio choice with fixed assets in the presence of information costs and short sales constraints. This context allows us to focus on the optimal portfolio choice with fixed assets. Investors aim to maximize the ratio between the wealth and the value of the fixed assets. We obtain the optimal portfolio choice strategy with fixed assets when the time horizon is a random exit time. Our results are new in the literature. We illustrate the main findings through some simulation results. [ABSTRACT FROM AUTHOR]