Money Market Calculations
The money market is the market for short-term debt instruments. Short-term debt is traditionally defined as having original maturities of one year or less. Some of these instruments are interest bearing while others are discount instruments. Moreover, many of these securities calculate interest based on a 360-day year while others use a 365-day year. There are some essential money market calculations including day count conventions and basic formulas of price/yield one needs to know to understand how the money market works. 
 
 
Keywords: 
 
day count convention; 
day count basis; 
actual/actual; 
actual/360; 
30/360; 
yield on a bank discount basis; 
CD equivalent yield; 
bond-equivalent yield; 
effective annual yield
State Taxes and Reserve Requirements as Major Determinants of Yield Spreads among Money Market Instruments
Abstract Empirical studies and much marketplace opinion have it that the spread between private money market rates and the U.S. Treasury bill rate of comparable maturity is due to differential default risk, liquidity risk, and relative supplies. This paper presents an argument and empirical evidence that the bulk of the systematic and medium-term differential between privates rates—in this case, domestic CDs, commercial paper, bankers' acceptances, and Eurodollar CDs—and the T-bill rate is due to the exemption of interest on Treasury securities from state and local taxation. In the case of Eurodollar CDs, the additional and major systematic factor explaining the spread (vis a vis T-bills) is the exemption of Eurodollar CDs from the Federal Reserve's “tax” via reserve requirements. An empirical section confirms the role of standard default risk, liquidity risk, and market “absorption” variables in determining short-term deviations from tax-adjusted parity. The taxadjusted parity condition, however, remains the major systematic and medium-term determinant—certainly more important than has been suggested previously in the literature.
Complexity, Network-Decisions And Alternative Risk Premia: Some New Theories Of Structural Change And Portfolio Decisions.
Structural Change is the basis for many decisions such as government fiscal and monetary policies, government interventions, corporate-expenditure decisions, corporate strategic decisions, portfolio management decisions in finance; household allocation decisions, etc.. Structural change in industries and national economies is increasingly more difficult to detect partly because of the growth and dominance of Complex Systems and “Networks” in modern industries and economies – such Networks and Complex Systems include GVCs (global value chains), retail store networks; franchising networks; internet networks; services networks; credit-chains in industries; online social networks; etc.. The relationship between Complexity and Structural Change is well established in the physics, applied math and economic dynamics literatures. Traditional definitions and modeling of structural change have erroneously focused on changes in labor, technological progress, market share, and or capital – which are grossly inadequate in the new economy and post- global financial crisis (as confirmed by changes in the global retailing and housing industries and other industries). Also the modeling of structural change seems to be constrained by the availability of data, and often omits the relationship between structural change on one hand, and globalization, financial stability and international financial contagion. This article: i) introduces the Operations Strategy Model of structural change, explains how it differs from the Lewis Model of Structural Change; and explains the often omitted relationship between operations strategy (of companies and government agencies) and structural change; ii) introduces other new Complexity-based models/theories of Structural Change in industries; iii) reviews the relationships among Operations Research, Complexity and Structural Change; iv) explains the symbiotic relationship between structural change on one hand, and economic growth, financial stability, financial contagion and globalization; v) discusses the significant gap between academic research and practice and explains some issues and factors that should be considered in the development and testing of structural change models; vi) explains how alternative risk premia can be generated from new models of Structural Change.