Optimal Investment Under Transaction Costs: A Threshold Rebalanced Portfolio Approach

We study optimal investment in a financial market having a finite number of assets from a signal processing perspective. We investigate how an investor should distribute capital over these assets and when he should reallocate the distribution of the funds over these assets to maximize the cumulative wealth over any investment period. In particular, we introduce a portfolio selection algorithm that maximizes the expected cumulative wealth in i.i.d. two-asset discrete-time markets where the market levies proportional transaction costs in buying and selling stocks. We achieve this using "threshold rebalanced portfolios", where trading occurs only if the portfolio breaches certain thresholds. Under the assumption that the relative price sequences have log-normal distribution from the Black-Scholes model, we evaluate the expected wealth under proportional transaction costs and find the threshold rebalanced portfolio that achieves the maximal expected cumulative wealth over any investment period. Our derivations can be readily extended to markets having more than two stocks, where these extensions are pointed out in the paper. As predicted from our derivations, we significantly improve the achieved wealth over portfolio selection algorithms from the literature on historical data sets.Comment: Submitted to IEEE Transactions on Signal Processin

Tracking the best level set in a level-crossing analog-to-digital converter

Cataloged from PDF version of article.In this paper, we investigate level-crossing (LC) analog-to-digital converters (ADC)s in a competitive algorithm framework. In particular, we study how the level sets of an LC ADC should be selected in order to track the dynamical changes in the analog signal for effective sampling. We introduce a sequential LC sampling algorithm asymptotically achieving the performance of the best LC sampling method which can choose both its LC sampling levels (from a large class of possible level sets) and the intervals (from the continuum of all possible intervals) that these levels are used based on observing the whole analog signal in hindsight. The results we introduce are guaranteed to hold in an individual signal manner without any stochastic assumptions on the underlying signal. © 2012 Published by Elsevier Inc

Growth optimal investment with threshold rebalancing portfolios under transaction costs

We study how to invest optimally in a stock market having a finite number of assets from a signal processing perspective. In particular, we introduce a portfolio selection algorithm that maximizes the expected cumulative wealth in i.i.d. two-asset discrete-time markets where the market levies proportional transaction costs in buying and selling stocks. This is achieved by using 'threshold rebalanced portfolios', where trading occurs only if the portfolio breaches certain thresholds. Under the assumption that the relative price sequences have log-normal distribution from the Black-Scholes model, we evaluate the expected wealth under proportional transaction costs and find the threshold rebalanced portfolio that achieves the maximal expected cumulative wealth over any investment period. © 2013 IEEE

Multiagent Cooperative Search for Portfolio Selection

We present a new multiagent model for the multiperiod portfolio selection problem. A system of cooperative agents divide initial wealth and follow individual worst-case optimal investment strategies from random portfolios, sharing their final profits and losses. The multiagent system achieves better average-case performance than a single agent with the same initial wealth in a simple stochastic market. A further increase in performance is achieved through communication of hints between agents and probabilistic strategy-switching. However, this explicit cooperation is redundant in a market that approximates the Capital Asset Pricing Model, a model of equilibrium stock price dynamics. Journal of Economic Literature Classification Numbers: C63, C73, D83, G11.Engineering and Applied Science

Managerial risk in information technology investments : effects of framing, narrow framing and time inconsistent preferences on real options exercise decisions

Real options theory has been advocated as a solution to risky IT investment decisions. IT investments decisions are risky due to uncertainty around future outcomes and the inability of traditional financial measures (like NPV, IRR) to account for inherent managerial flexibility. On the one hand, it is argued that real options analysis captures and formalizes managers' intuition, hence creating a disciplined decision making process. On the other hand, the intuitive valuation of the options is criticized due to the prevalent effects of various judgmental biases. In this dissertation, we explore three potential biases that can affect the real option exercise decisions in terms of either suboptimal option exercise choice due to framing and narrow framing effects, or suboptimal exercise time due to time inconsistent preferences of IT managers. We test for framing effects in individual IT project decisions and narrow framing effects in IT portfolio decisions, by conducting an online experiment among top and mid-level IT professionals. The results show that IT professionals are prone to framing real options at exercise time and simplifying complicated real option exercise decisions by isolating them in IT portfolios. Further, their decisions are influenced by their personal risk preferences. We analyze the effect of time-inconsistent preferences of present-biased managers on the exercise time of real growth and abandonment options and the realized values using a discrete time option valuation model. The results show that present-biased managers are more likely to exercise growth options early when the net payoffs are low, the growth option payoffs have high volatility, and the risk free discount rate is small. Also, present-biased managers are more likely to exercise abandonment option late when the net payoffs from continuing the project are high, salvage value of the project is low, and the rate of change in the salvage value over the period of time is low. In addition, present biased managers are more likely to exercise a growth option early in its life when the project is performing well. We provide implications for practice and IT governance

Online portfolio selection: A survey

Ministry of Education, Singapore under its Academic Research Funding Tier

An analysis of spending behaviour under liquidity constraints with an application to financial hedging

Imperial Users onl