Dynamic Investment Strategy with Factor Models Under Regime Switches

Komatsu, Takahiro; Makimoto, Naoki

doi:10.1007/s10690-015-9200-8

Cited by 3 publications

(6 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The idea of LRS is to overcome these difficulties by restricting the strategy space to the set of strategies represented by a linear combination of factors up to the time of investment. Although LRS is not exactly optimal in all possible dynamic strategies, judging not only from our experiments where we confirm that LRS provides solutions close to optimal but from its theoretical basis that LRS is optimal for an infinite horizon problem without constraints as solved in Gârleanu and Pedersen [9] and Komatsu and Makimoto [12], we conclude that LRS is potentially applicable to a wide class of complex dynamic portfolio optimizations under practical investment conditions.…”

Section: Discussionmentioning

confidence: 62%

“…Dombrovskii and Obyedko [6] investigates a problem to minimize deviations from a benchmark subject to a borrowing constraint under regime switches. Komatsu and Makimoto [12] extends Gârleanu and Pedersen [9] to regime switching factors and return processes. Yao, Li and Li [22] studies a dynamic optimal multi-period asset allocation associated with uncontrollable liability where a stochastic interest rate is governed by the discrete time Vasicek model, showing a prospective of the model extensions into regime dependent space.…”

Section: Introductionmentioning

confidence: 88%

“…Under the regime switching circumstance, Komatsu and Makimoto [12] extends Gârleanu and Pedersen [9] in such a way that the optimal investment is shown to be…”

Section: Linear Rebalancing Strategy Under Regime Switchesmentioning

confidence: 99%

“…The portfolio optimization model considered in this paper is similar to that in Komatsu and Makimoto [12] which introduced regime switches into Gârleanu and Pedersen [9]. We consider an economy with N assets traded at t = 1, 2, .…”

Section: Portfolio Optimization Problem Under Regime Switchesmentioning

confidence: 99%

“…In this paper, we extend the linear rebalancing rule to regime switching models. For an infinite horizon problem under regime switches without constraints, Komatsu and Makimoto [12] proves that an optimal portfolio has a same form as Gârleanu and Pedersen [9] while weight matrices between the current portfolio and factors are regime dependent. This leads to a dynamic investment strategy comprised of a linear combination of past and current factors with regime dependent coefficient matrices.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Linear Rebalancing Strategy for Multi-Period Dynamic Portfolio Optimization Under Regime Switches

Komatsu

Makimoto

2018

JORSJ

Self Cite

View full text Add to dashboard Cite

Although there is a growing interest of applying regime switching models to portfolio optimization, it has never been quite easy as yet to obtain analytical solutions under practical conditions such as self-financing constraints and short sales constraints. In this paper, we extend the linear rebalancing rule proposed in Moallemi and Saglam [17] to regime switching models and provide a multi-period dynamic investment strategy that is comprised of a linear combination of factors with regime dependent coefficients. Under plausible mathematical assumptions, the problem to determine optimal coefficients maximizing a mean-variance utility penalized for transaction costs subject to self-financing and short sales constraints can be formulated as a quadratic programming which is easily solved numerically. To suppress an exponential increase of a number of optimization variables caused by regime switches, we propose a sample space reduction method. From numerical experiments under a practical setting, we confirm that our approach achieves sufficiently reasonable performances, even when sample space reduction is applied for longer investment horizon. The results also show superior performance of our approach to that of the optimal strategy without concerning transaction costs.

show abstract

Section: Discussionmentioning

confidence: 62%

Section: Introductionmentioning

confidence: 88%

“…Under the regime switching circumstance, Komatsu and Makimoto [12] extends Gârleanu and Pedersen [9] in such a way that the optimal investment is shown to be…”

Section: Linear Rebalancing Strategy Under Regime Switchesmentioning

confidence: 99%

Section: Portfolio Optimization Problem Under Regime Switchesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Linear Rebalancing Strategy for Multi-Period Dynamic Portfolio Optimization Under Regime Switches

Komatsu

Makimoto

2018

JORSJ

Self Cite

View full text Add to dashboard Cite

show abstract

Time Series Prediction with LSTM Networks and Its Application to Equity Investment

Matsumoto¹,

Makimoto

2020

Advanced Studies of Financial Technologies and Cryptocurrency Markets

View full text Add to dashboard Cite

Constructing Sentiment Signal-Based Asset Allocation Method with Causality Information

Taguchi,

Sakaji,

Izumi

et al. 2023

New Gener. Comput.

View full text Add to dashboard Cite

This study demonstrates whether financial text is useful for the tactical asset allocation method using stocks. This can be achieved using natural language processing to create polarity indexes in financial news. We perform clustering of the created polarity indexes using the change point detection algorithm. In addition, we construct a stock portfolio and rebalanced it at each change point using an optimization algorithm. Consequently, the proposed asset allocation method outperforms the comparative approach. This result suggests that the polarity index is useful for constructing the equity asset allocation method.

show abstract

Dynamic Investment Strategy with Factor Models Under Regime Switches

Cited by 3 publications

References 17 publications

Linear Rebalancing Strategy for Multi-Period Dynamic Portfolio Optimization Under Regime Switches

Linear Rebalancing Strategy for Multi-Period Dynamic Portfolio Optimization Under Regime Switches

Time Series Prediction with LSTM Networks and Its Application to Equity Investment

Constructing Sentiment Signal-Based Asset Allocation Method with Causality Information

Contact Info

Product

Resources

About