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Even though commodity pricing models have been successful in fitting the term structure of futures prices and its dynamics, they do not generate accurate true distributions of spot prices. This paper develops a new approach to calibrate these models using not only observations of oil futures prices, but also analysts' forecasts of oil spot prices. We conclude that to obtain reasonable expected spot curves, analysts' forecasts should be used, either alone, or jointly with futures data. The use of both futures and forecasts, instead of using only forecasts, generates expected spot curves that do not differ considerably in the short/medium term, but long term estimations are significantly different. The inclusion of analysts' forecasts, in addition to futures, instead of only futures prices, does not alter significantly the short/medium part of the futures curve, but does have a significant effect on long-term futures estimations.

Contingent Pricing • Futures Pricing --- Financial Forecasting and Simulation

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Accounting often is referred to as the language of business; unfortunately, many business professionals lack the fluency in this unique language required to perform basic financial analysis, prepare budgetary forecasts, or compare competing capital investment alternatives. And while there is no shortage of financial-related textbooks or reference manuals, most assume that readers have educational backgrounds - and/or have had years of professional experience - in accounting, financial analysis, or corporate finance. This book targets professionals with limited exposure to - or formal training in - accounting or related finance disciplines. These individuals often include - but certainly are not limited to - engineers, information technology specialists, retail managers, entrepreneurs, marketing directors, construction contractors, attorneys, and even bankers who are making career transitions from consumer lending positions to become commercial loan officers. The primary purpose of this book is to help managers and business owners from diverse professional and educational backgrounds to: (1) converse more effectively with their accounting and finance colleagues; (2) understand the structure and the elements of general-purpose financial statements, (3) identify both the usefulness and the limitations of accounting information; (4) prepare basic financial forecasts; and (5) make sense of commonly used decision-making models.

Accounting. --- Financial statements. --- Accruals --- accounting --- financial statements --- balance sheet --- income statement --- statement of cash flows --- assets --- deferrals --- liabilities --- equity --- revenue --- expenses --- cash flow --- financial analysis --- financial management --- profitability --- solvency --- liquidity --- budgeting --- decision-making --- financial forecasting --- pro forma financial statements --- cost-volume-profit analysis --- breakeven --- capital budgeting --- payback period --- discounted present-value --- internal rate of return --- net present value --- time-value of money

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This paper presents a rule for foreign exchange interventions (FXI), designed to preserve financial stability in floating exchange rate arrangements. The FXI rule addresses a market failure: the absence of hedging solution for tail exchange rate risk in the market (i.e. high volatility). Market impairment or overshoot of exchange rate between two equilibria could generate high volatility and threaten financial stability due to unhedged exposure to exchange rate risk in the economy. The rule uses the concept of Value at Risk (VaR) to define FXI triggers. While it provides to the market a hedge against tail risk, the rule allows the exchange rate to smoothly adjust to new equilibria. In addition, the rule is budget neutral over the medium term, encourages a prudent risk management in the market, and is more resilient to speculative attacks than other rules, such as fixed-volatility rules. The empirical methodology is backtested on Banco Mexico’s FXIs data between 2008 and 2016.

Banks and Banking --- Econometrics --- Finance: General --- Foreign Exchange --- Central Banks and Their Policies --- Financial Forecasting and Simulation --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- Financing Policy --- Financial Risk and Risk Management --- Capital and Ownership Structure --- Value of Firms --- Goodwill --- International Financial Markets --- Currency --- Foreign exchange --- Econometrics & economic statistics --- Financial services law & regulation --- Finance --- Exchange rates --- Vector autoregression --- Exchange rate risk --- Currency markets --- Financial risk management --- Foreign exchange market --- Mexico

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Inflation has been below the Federal Reserve’s target for much of the past 20 years, creating worries that inflation may be deanchoring from the FOMC’s target. This paper uses a factor model that incorporates information from professional forecasters, household and business surveys, and the market for Treasury inflation protected securities (TIPS) to estimate long-run inflation expectations. These have fallen notably in the past few years (to roughly 1.9 percent for CPI inflation, well below the FOMC’s target). It appears that, even before the covid recession, the private sector viewed the economy as likely to suffer from persistent headwinds to inflation.

Business and Economics --- Finance: General --- Inflation --- Investments: General --- Macroeconomics --- Money and Monetary Policy --- Price Level --- Deflation --- Interest Rates: Determination, Term Structure, and Effects --- Financial Markets and the Macroeconomy --- General Financial Markets: General (includes Measurement and Data) --- Financial Forecasting and Simulation --- Investment --- Capital --- Intangible Capital --- Capacity --- Energy: Demand and Supply --- Prices --- Portfolio Choice --- Investment Decisions --- Monetary Policy --- Finance --- Monetary economics --- Return on investment --- Oil prices --- Liquidity --- Inflation targeting --- National accounts --- Asset and liability management --- Monetary policy --- Saving and investment --- Economics --- United States

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We propose a framework to link empirical models of systemic risk to theoretical network/ general equilibrium models used to understand the channels of transmission of systemic risk. The theoretical model allows for systemic risk due to interbank counterparty risk, common asset exposures/fire sales, and a “Minsky" cycle of optimism. The empirical model uses stock market and CDS spreads data to estimate a multivariate density of equity returns and to compute the expected equity return for each bank, conditional on a bad macro-outcome. Theses “cross-sectional" moments are used to re-calibrate the theoretical model and estimate the importance of the Minsky cycle of optimism in driving systemic risk.

Banks and Banking --- Finance: General --- Industries: Financial Services --- Semiparametric and Nonparametric Methods --- Financial Forecasting and Simulation --- Banks --- Depository Institutions --- Micro Finance Institutions --- Mortgages --- Financing Policy --- Financial Risk and Risk Management --- Capital and Ownership Structure --- Value of Firms --- Goodwill --- General Financial Markets: Government Policy and Regulation --- General Financial Markets: General (includes Measurement and Data) --- Banking --- Finance --- Systemic risk --- Interbank markets --- Consumer loans --- Loans --- Banks and banking --- Financial risk management --- International finance